T INDIAN JOURNALHE
OF COMMERCE(A Quarterly Refereed Journal Published by the Indian Commerce Association)
Vol.69 No.1 January-March 2016
Prof. H.K. Singh - Managing Editor
With Secretariat at : Faculty of Commerce, Banaras Hindu University,Varanasi, (U.P.) - 221005Visit : www.icaindia.info, www.ijoc.inEmail : [email protected], [email protected]
Print : : 19-512X | Online : : 2454-6801ISSN ISSN
Gnyana Ranjan Bal, Hemant Kumar Majhi andMalabika Deo
Raju G andDeepika Krishnan
Parimal H. Vyas, Parag S. Shukla andMadhusudan N. Pandya
Chandana Kashyap andAshima Sharma Borah
K.Kanaka Raju
Mohammad Azmat Ali and Patrick Anthony
R.Ramachandran
Sudhir Chandra Das andShalakha Rao
K. Kanaka Raju
Kripa Shankar Jaiswal
Sanket Vij, Narender Garg andH J Ghosh Roy
M Muniraju, Swaminath S andGanesh S R
Implications of Human Capital in Asset Pricingand Behavioral Finance: Evidence from India
Behavioural Impact of Traders in the Indian OptionMarket
An Empirical Exploration of In�uences of RetailStore Atmosphere on Shoppers’ Satisfaction in theBaroda City of Gujarat State
Opportunities and Challenges of E-Retailing inAssam: A Study with Special Reference to NalbariDistrict, Assam
Integration of Tools of Social Media forEnrichment of Human Resources in MultivariateOrganizations
Social Media-Marketing, Recruitment and CyberCrime – A Case Study of Hyderabad City
Skilled Based Learning System for Employability –With Reference to B-Schools from EmpiricalPerspective
Capabilities in Employability Skills (Self Perceived)among Under-Graduate Commerce Students: ACross –Sectional Study
Growth Driver of an Indian Economy-Make-in-India
Make in India vs. Teach in India: A Case study ofHigher Education in India
Nuclear Power Generation for Industrializationvis-a-vis Impact on Environment and Community :A Case Study of India
Role of Green Credit and its Impact onIndustrialization – An Empirical Study withSpecial reference to Select Industries in Bangalore
MANAGING EDITORProf. H.K. Singh
Faculty of CommerceBanaras Hindu University, Varanasi, Uttar Pradesh, India
JOINT MANAGING EDITORSDr. Subhash Garg Dr. Ajay Kr. Singh Dr. Sanket VijProfessor, Dean & Director Associate Professor ProfessorCentre for Research, Innovation & Faculty of Commerce and Business Department of ManagementTraining, The University Delhi School of Economics, Mahila Vishwavidyalaya, KhanpurIIS BPSJaipur, Rajasthan University of Delhi, Delhi (Sonepat), Haryana
ASSOCIATE EDITORSDr. S.B. Lall Dr. Meera Singh Dr. Shweta Kastiya Sapan AsthanaVanijya Mahavidyalaya Autonomous College The UniversityUP PG IIS MUITPatna University, Patna Varanasi Jaipur Lucknow
EDITORIAL CONSULTANTS
Membership to Indian Commerce AssociationIndividual Institutional
Annual Members 1,000 N.A.`
Life Members 5,000 25,000` `
Subscriptions/ Membership fee is to be paid in the form of Demand Draft, drawn in favour of 'Indian Commerce Association', payable at Amritsar. Feecan also be directly deposited in Indian Commerce Association Account No: 14572191054283 in Oriental Bank of Commerce (Branch: ,MAJITHAAMRITSAR IFSC ORBC- code: 0101457) www.icaindia.info/index.php/membership. Every member will have to register online on before sending thefee to Dr. Balwinder Singh, Secretary, Indian Commerce Association, Associate Professor, Department of Commerce, Guru Nanak Dev University,Amritsar-143001, Punjab, India.Advertisements : Limited space is available for advertisement on the following rates :
Back Cover page Full 10,000 Inside Cover page Full 5,000` `
Full Page 3,000 Half Page 2,000` `
Correspondence: All manuscripts and correspondence regarding publications and advertisement should be addressed to : Prof. H.K. Singh, ManagingEditor, Indian Journal of Commerce, Faculty of Commerce, Baranas Hindu University, Varanasi 221005, Email : [email protected], Web :www.ijoc.inThe views expressed in the articles and other material published in do not re�ect the opinions of the .The Indian Journal of Commerce ICA
The Indian Journal of CommerceA Quarterly Refereed Journal
Aims and Objectives : Indian Journal of Commerce, started in 1947, is the quarterly publication of the Indian Commerce Association todisseminate knowledge and information in the area of trade, commerce, business and management practices. The Journal focusses ontheoretical, applied and disciplinary research in commerce, business studies and management. It provides a forum for debate and deliberationsof academics, industrialists and practitioners.
Prof. David RossUniversity of Southern Queensland, AustraliaCurrently in University, MalaysiaHELPProf. Suneel MaheshwariIndiana University of Pennsylvania, Pennsylvania, USAProf. Ing. Elena HorskaProfessor of MarketingSlovak University of Agriculture in Nitra, Slovak RepublicProf. Walter Terry ParrishICE Academy, Smethwick (Birmingham) Campus, United KingdomProf. Doc. Ing. Petr SauerUniversity of Economics, Prague, Czech RepublicProf. M. SaeedMinot State University, North Dakota, USAProf. Andras NabradiUniversity of Debrecen, Debrecen, HungaryProf. Syed Ahsan JamilDhofar University, OmanProf. S.P. BansalVice-Chancellor, IGU, RewariProf. B. RameshEx Dean of Commerce, Goa UniversityDr. Subodh KesharwaniSMS IGNOU, , New DelhiProf. Coskun Can AktanDokuz Eylül University, Izmir, TurkeyProf. R.K. JenaUtkal University, Bhubaneswar, OdishaDr. R.U. SinghMagadh University, BiharProf. Popp JozsefDeputy Director, , Budapest, HungaryAERIProf. Hamid SaremiVice-Chancellor, Islamic Azad University, Quchan, IranDr. Rakesh GuptaGrif�th University, Australia
Prof. B.P. SinghChairman, Delhi School of Professional Studies & Research (GGSIPUniversity), Rohini, DelhiProf. L.N. DahiyaMD University Rohtak, HaryanaProf. Arvind KumarUniversity of Lucknow, Lucknow, Uttar PradeshProf. O.P. RaiBanaras Hindu University ( ), Varanasi, Uttar PradeshBHUProf. D.P.S. VermaEx Professor, Faculty of Commerce & BusinessDelhi School of Economics, University of Delhi, DelhiProf. P. Purushottam RaoFormerly Professor, Osmania University, HyderabadProf. P.R. AgrawalVice- Chancellor, V.B.S. Purvanchal University, Jaunpur, U.P.Dr. Babban TaywadeDhanwate National College, Nagpur, MaharashtraDr. T.A. ShiwareKPB Hinduja College, Mumbai, MaharashtraProf. R. VinayakFormerly Professor, M.D. University, Rohtak, HaryanaProf. K. EresiBangalore University, Bengaluru, KarnatakaProf. K.S. JaiswalMG Kashi Vidyapeeth, Varanasi, Uttar PradeshProf. Sanjay BaijalDDU Gorakhpur University, Gorakhpur, Uttar PradeshProf. Sandip K. BhattSardar Patel University, Nagar, Anand, GujaratVVProf. Umesh HolaniEx Dean of Commerce, Jiwaji University, Gwalior, M.P.Prof. Debabrata MitraNorth Bengal University, Bardwan, West BengalProf. Bhagwan DasFM University, Balasore, Odisha
T INDIAN JOURNALHE
OF COMMERCE
Vol. 69 No.1 January-March 2016
CONTENTS� Editorial 3-4
Prof. H.K. Singh� Presidential Address 5-9
Prof. Jayanta Kumar Parida� Dr. C.D. Memorial Lecture 10-16
Prof. B.P. Singh
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India 17-26Gnyana Ranjan Bal, Hemant Kumar Majhi and Malabika Deo
Behavioural Impact of Traders in the Indian Option Market 27-32Raju G and Deepika Krishnan
An Empirical Exploration of In�uences of Retail Store Atmosphere on Shoppers’ Satisfaction 33-53in the Baroda City of Gujarat StateParimal H. Vyas, Parag S. Shukla and Madhusudan N. Pandya
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference 54-66to Nalbari District, AssamChandana Kashyap and Ashima Sharma Borah
Integration of Tools of Social Media for Enrichment of Human Resources in 67-75Multivariate OrganizationsK.Kanaka Raju
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City 76-93Mohammad Azmat Ali and Patrick Anthony
Skilled Based Learning System for Employability – With Reference to B-Schools from 94-109Empirical PerspectiveR.Ramachandran
Capabilities in Employability Skills (Self Perceived) among Under-Graduate 110-122Commerce Students: A Cross –Sectional StudySudhir Chandra Das and Shalakha Rao
Growth Driver of an Indian Economy-Make-in-India 123-131K. Kanaka Raju
Make in India vs. Teach in India: A Case study of Higher Education in India 132-137Kripa Shankar Jaiswal
Nuclear Power Generation for Industrialization vis-a-vis Impact on Environment 138-147and Community : A Case Study of IndiaSanket Vij, Narender Garg and H J Ghosh Roy
Role of Green Credit and its Impact on Industrialization – An Empirical Study with 148-154Special reference to Select Industries in BangaloreM Muniraju, Swaminath S and Ganesh S R
( 1 )
(A Quarterly Refereed Journal Published by the Indian Commerce Association)
� Secretary’s Report, 2015 155-157� Minutes of the Executive Committee 158-159� Minutes Of The Annual General Body Meeting 160-161� Saurabh Shiware Memorial Young Researcher Award 162-163� Prof. Manubhai M. Shah Memorial Award 164-165� Book Review 167
Our global and political environment is bubbling with great hopes and aspirations of pink health and rising graphof Trade, Industry and Commerce all around. As such, it becomes my humble and honest duty, belonging to theworld of academics, to interact and share with some instrumental guidelines for the contributors and participantsin the forthcoming issues of the Indian Journal of Commerce.
Research along with its practical implications and usage and utility in the �eld of business studies has greatrelevance today. It is therefore, suggested that Papers based on application oriented research are more welcome;especially in the �elds of industry, commerce, business studies and management areas. The papers must includetables, diagrams, illustrations and such other tools to support the different and divergent viewpoints. As such, thelength of a paper including all these has to be cautiously controlled and should not exceed 20 double space pages.Short communications relating to review articles, report of various conferences, summary/views on severalgovernments' reports, database issues etc. should also not exceed more than 5 double spaced pages and are invitedto be published. We also welcome book-reviews and summary of Ph. D. dissertations but not in more than twodouble spaced pages. Care should be taken that whatever manuscripts are sent for publication in this journalshould not have been published elsewhere any time before.
As is the common practice, two copies of the manuscripts typed in double space on A4 size bond paper should besubmitted and the electronic version of the paper must accompany 3.5 inch high density �oppy diskette in PCcompatible 7.0 document format.Papers without �oppy/ will not be accepted. It is informed that all theWORD CDpapers/contributions submitted for publication in the journal will be subjected to peer reviews and the decision ofthe Editorial Committee will be �nal.
First page of the Paper should consist of the title of the paper, name(s), of the author(s) along with all the otherrequired details and the abstract should not exceed more than150 words. Second page should start with the title ofthe paper again to be followed by the text. In the captions for the tables, �gures and column headings in the tables,the �rst letter of the �rst word should be capitalised and all other words should be in lower case, except the propernouns. Footnotes in the text should be numbered consecutively in plain Arabic superscripts. All the footnotes, ifany, should be typed under the heading 'Footnotes' at the end of the paper immediately after Conclusion.
Follow the Author -date (Harvard) System in-text reference: e.g. Saurabh (2014) observed that….A Study(Shantanu et. L. 2015) found that…..When it is necessary to refer to a speci�c page(s), cite it in the text as: Saurabh(2014 P. 105) observed that…A study Saurabh 2014a, Saurabh 2014b, Saurabh 2014c, so on and so forth.
It is to be noted that only cited works should be included in the 'References' which should appear alphabetically atthe end of the paper. Follow the reference citation strictly in accordance with the following examples.
Book : Singh, H. K. 2015. Mutual Funds Market. New Delhi: Kanishka publishers.
Journal Article : Singh, Meera 2015. Journal of Indian School of Political Economy. Jan-March,2015, Vol-22, Nos 1,pp 34-48.
Government Publication : Government of India, Ministry of Communications, Department ofTelecommunications 2015. Annual report. New Delhi.
Chapter in a Book : Gilberto Mendoza, 2015, A Premier on Marketing Channels and Margins. Pages 257-276 inPrices, Products and People (Gregory J. Scott, ed.) London. Lynne Rienner Publishers.
All copyrights are with the Indian Commerce Association and the authors. The authors are responsible forcopyright clearance for any part of the content of their articles. The opinions expressed in the articles of this journalare those of the authors, and do not re�ect the objectives or opinion of the Association.
All the manuscripts should be sent to Prof. H.K.Singh, Managing Editor, The Indian Journal of Commerce,
Banaras Hindu University, Faculty of Commerce, Banaras Hindu University, Varanasi 221005, Mobile:09415264509, E-mail: [email protected] • [email protected]
Published by Prof. H. K. Singh on behalf of the Indian Commerce Association
NOTES FOR CONTRIBUTORS
( 2 )
FROM THE DESK OF THE MANAGING EDITOR
I am most delighted to present before you, the volume 69 (January-March 2016 issue) of thereputed Indian Journal of Commerce. Business is a process for signi�cant changes in thecontext, emphases and boundaries due to the intense competition and customerexpectations. A paradigm shift that characterizes in the business of the twenty �rst century isshaping up to a knowledge driven society in which the basic economic factor is not thematerial, labour, and capital but the value based knowledge. Existence and acceleratedgrowth in a knowledge driven society implies vertical excellence through networking andboosting the core competencies. Human resources have to ensure the continuous learning,persistence, con�dence collaboration and commitment by one and all across theorganization.
69th All India Commerce Conference organized under the guidance of dynamic conferencesecretary Prof. Arvind Kumar, Dean Faculty of Commerce, Lucknow University is dedicatedto ef�cacious, substantial and signi�cant topics such as- (a) , (b)Startup India Indian
Financial System, Globalization of Markets, ourism and Hospitality, Women(c) (d) T (e)Empowerment, Empirical Researches The Startup Indiaand (f) . campaign was �rstannounced on 15 August 2014 by our Hon'ble Prime Minister Sri Narendra Modi, whoseaction plan aimed at promoting bank �nancing for startup ventures to boostentrepreneurship and encourage startups with job creation. is a set ofFinancial System
institutional arrangements such as conditions and mechanism governing the production,distribution, exchange, etc. through which �nancial surpluses in the economy are mobilizedfrom surplus units and transferred to de�cit spenders. refer to theGlobal Marketing
combination of promotion and selling of goods and services with an increasinglyindependent and integrated global economy. is the third largest foreign exchangeTourism
earner in India. Tourism and hospitality has shown a signi�cant contribution to employmentand economic growth, better infrastructure, focused marketing and promotion efforts, thegrowth of intra-regional cooperation, etc. shows women's versatileWomen Empowerment
participation in decision-making process of the nation, both politically and economically. Ithas become a signi�cant topic of discussion in regards to development and economics.Empirical researches on relevant topics related with main theme of Accounting and Financeare also the part of the reputed 69th AICC which will provide diversi�ed solutions andguidelines to the problems related to the business world. The EC of ICA has decided to start
( 3 )
Prof. H.K. SinghFaculty of Commerce
Managing Editor, Indian Journal of CommerceBanaras Hindu University, Varanasi
Ex Vice Chancellor, Maharishi University of IT, LucknowPresident, Indian Association for Management Development
E-mail: [email protected] • Mobile: 09415264509
one speci�c session exclusively for research scholars in the name of ICA Research ScholarAward so that they must get proper chance for deliberation.
The present issue comprises the papers nominated for Best Business Academic of theYear (BBAY) awards for all the six sessions held at 68th AICC, namely: Behavioural
Finance, E- Relationship, Social Media, Skill Development, Make in India andEmpirical Researches. I have an ardent hope that you all will be bene�ted with theseresearch papers of the current issue and will revert with your valuable comments.
I express my appreciation to our readers and community at large for the warm welcomeand resounding support to the journal and ICA. We are working hard to betterunderstand our readers and to deliver a valuable product to you on a regular basis. I hopeall of you will continue to reach out to us any time through e-mail and mobile withfeedback and suggestions for bringing out appropriate amendments in this reputedjournal. As you all are aware, now our journal is completely a on-line journal, so you arerequested to browse it through networks. I conclude by quoting few lines from BhagwadGeeta,
Uddharedaatmanaatmaana, naatmaanamavasaadayeth!aatmaiva hyaatmana, bandhuraatmaiva ripuraatmanah!!
(Let a man raise himself by his own efforts. Let him not degrade himself. Because aperson's best friend or his worst enemy is none other than his ownself.)
Last but not the least I would like to quote a doha by Rahim,
Dheere Dheere Re Mana , Dheere Sub Kutch HoyeMali Seenche So Ghara , Ritu Aaye Phal Hoye.
(Slowly slowly O mind, everything in own pace happens. The gardener may water with ahundred buckets, fruits arrives only in its season)
Prof. H.K. Singh
( 4 )
Galaxy of Commerce Intelligentsia drawn from far and near of the country.
Ladies and Gentlemen present over here on this grand occasion of the 68th
AICC being hosted by this University.
It is my great pleasure and privilege to welcome you all to this historic 68th
All India Commerce Conference in this alluring and beautiful campus of
Vinoba Bhave University, Hazaribag, Jharkhand. On behalf of the association
and on my behalf, I would like to thank the authorities of the Vinoba Bhave
University for making this event happen in this Sacred Land of Vinoba
Bhavejee- a great son of the soil who dedicated his life to the cause and
concern of the poor and landless people of the country through Bhoodan
Movement.
Friends, our visionary Prime Minister who graciously accepted our invitation
to inaugurate this conference to-day could not make himself available due to
his pressing engagement and busy schedule. We all will miss his aid and
advice. Sir, the entire Commerce fraternity of the country not only have great
faith but also committed to your ideology, “Sabka Saath, Sabka Vikas”. Sir, in
your absence, we promise and affirm you that we all will sincerely work in unison to make your dream a reality.
Friends, let me quote our PM in America “India was known as land of science, art and technocrats is no more valid as
on date. We have developed a lot since then. Today we talk of management of science or arts or technocrats”. All of them
come from our fraternity.
India is one of the largest reservoirs of youth population. More than 40 per cent of population is in the age group of 16-
30 years which indeed can change India’s destiny. A new image of India is being visualized across the world. Investors
ranked India as No.1 destination due to the availability of professionals, effective governance and low cost production.
This has created an atmosphere of optimism and hope amongst us to move forward in the midst of crises of varied
nature in other parts of world. Indians are now determined to bring a significant change in the economic front of the
country by creating a stronger social system leading to a mass revolution. We have the talents; we have the technology
and the best technocrats; what best we need at this juncture, is to awaken them and demonstrate others that we Indians
can build, produce, export, import and trade with the rest of the world in much more competitive and effective manner
than others. I strongly believe that our association can play a very crucial role in this regard.
Friends, I would like to remind the members of our association that a country is said to be developed when it is
industrially developed. But today the concept of trade and commerce everywhere, be it local, national or international
have gone into a Paradigm shift. The rapid change in technology is reshaping the world. It is the technology that
empowers everything and has been acting as a tool to bridge the gap between hope and opportunity. Development in
information and communication technology, have revolutionalized every activity be it teaching, research, banking,
investment, international trade or anything else. This is so as in globally competitive market, knowledge constantly
makes itself obsolete with the result that today’s advanced knowledge is tomorrow’s ignorance. One has to be on the
learning curve and continuously move up, if at all, to see the pace of development.
Friends, we all wish to change India’s destiny to a developed nation. But at the same time, we should not forget that we
have experienced a long history of deprivation, which was sufficient enough to keep the economic activity at a crawl.
But gone are those days. The country has been marking a dramatic turnaround in prosperity with the new era of
opportunities even for the lowest cadre of the society. This we could be able to experience because of the creation of
awareness,intelligence, education, initiatives, perseverance and above all the united efforts of the community as a
PRESIDENTIAL ADDRESS
68th ALL INDIA COMMERCE CONFERENCEOF INDIANCOMMERCE ASSOCIATION
( 5 )
whole. Keeping that in view I specifically opted this topic of “University- Industry Interface for Economic Prosperity”
as my presidential address. In my opinion there is an urgent need for a convergence between the Universities of our
country and the productive sector of the nation for a sustainable growth and to harness the demographic dividend that
the country posses.
The University education system in India, though highly structured, is intensely stratified and predominately public
controlled and funded. It has been done with an intention to preserve and enrich the societal value. However, vast
changes have taken place the world over in recent years. Globalisation and economic liberalisation have put the
University at a cross road which forces us to tune the educational system in pace with the changing market requirement.
This has been changing the entire culture including values, norms, ideals, beliefs, customs, skills and techniques. All
these require qualitative and quantitative improvement for the dissemination of knowledge so that large numbers of
skilled manpower can be created who can increase the competitive advantage of the organization they join. This in turn
will benefit the industry at large to a greater extent. And it is but natural justice that industries must come forward with
proactive measures to extend their helping hands with the university and decide the process of qualitative changes
required by them. The process can, not only change the value of industry, but also can maximise the national wealth
Benefits of University Industry Interface
A University is a place not merely for courses of varied disciplines but one for imparting need based education. A
University student should not only be well read but also well bred. His mind should be directed toward development.
For this purpose, the experience and knowledge of professors and students should be exchanged with the skill,
requirements and practicability of the industry. The convergence would usurp in the following benefits.
Students
• The students in the university system face the problem of scholastic achievement but no job.
• There will be more scholarships and aids for students. The poor but meritorious students will be able to find
necessary sponsorship and achieve his goal to concentrate only on research and development.
• In addition to the job, the students can have infield experience which will go a long way in building their career.
• Interpersonal skill of the students will develop as they will gain practical experience while pursuing their study
and interacting with practitioners in the industry.
Professors
• The professor will get first hand information from the industry which will help them in designing their course
curriculum, field of research and preparation of case studies for students.
• The theoretical knowledge of professors will be reinforced with the practical orientation.
• They can have their own consultancy.
Industry
• The industry will get qualified trained human resources.
• The existing workers can be trained and retrained on a regular basis in the university to refresh their mind set
and knowledge.
• Many industry experts are poor communicators while many University professors are poor consultants. If both
of them combine they can make a great job for the society.
• The hitherto research projects of the professors can be commercially exploited by industry with back ward or
forward linkages.
• The industry will find solutions to many of their managerial and technological problems.
University
• The University will not have to depend entirely on Government funding rather industrial houses will take lead
in sharing the burden as part of their R &D.
( 6 )
• There will be improvement of infrastructure facilities needed by students and professors – the major constraint
for research.
• Professionalism will be inculcated in the academic management.
• More number of patents, copyrights can come up with due encouragement and motivation.
• The university will become true cosmopolitan in nature.
Besides these direct beneficiaries, the whole society and state will also make a lot of gain out of this interface as their
resources can be utilized at optimum level.
The Big Question
If the synergy between University and Industry makes a win-win situation where everybody will make gain, why is it
not happening? This is a matter of thousand dollar question. The reasons are to be traced out at the earliest and efforts
must be evolved to eradicate the problems for the betterment of the society and the economy at large.
Barriers to University Industry Interface
A deep factual analysis of the problems of the two sides reveals the following barriers.
• Non-availability of link point for the interaction between the university and the industry. This problem is further
aggravated by (i) lack of Co-ordination (ii) confusion as to individual responsibility (iii) inefficient organization
(iv) indifferent public relations, and (v) duplication of control.
• Industry differs sharply from university in the following aspects such as (i) a relatively monolithic business
target (ii) inherently dedicated to making profit (iii) concerned more with short term goals. These are just the
opposite of the traditional interests and concerns of universities.
• Many of the university faculties are reluctant to work with the industry for the following reasons (i) not worth the
trouble and bother action (ii) need and possible benefits not recognized (iii) feeling of incompetence in a new
environment, not knowing where to start (iv) university does not have provision of incentives or facilities to
encourage faculty involvement with industry problems.
• Industry-university interaction and knowledge dissemination is not regarded as core or mainstream activity.
• The irregular commitment and availability of university professors sometimes frustrate the industry.
• There is a clash of ego between industry and university fraternity. Very often there is the mutual underestimation
of each other’s strength and capability.
• Besides all these, the lack of administrative interest, absence of development funding, promotional activities also
stand as barrier to an effective university-industry interface.
How to overcome the Barriers
There is no second opinion on the fact that the productivity and profitability of the industry will remarkably be
changed if they are able to get quality human resources from Universities. It is also true that the academic activities and
research will have more relevance if they are utilized in industry. Thus, clear cut strategy must be developed for
overcoming all sorts of barriers between university and industry. In this regard the following points may be taken note
of by the concerned authorities.
• There is a need to convince the business and industry that direct support to manpower and technology
development is at least as important as marketing and advertising for which they allocate very little resources.
( 7 )
• Industry and university must consider the education and training of young graduates as their shared
responsibility, while designing the course curriculum.
• Structural mechanisms must be evolved for continuous bilateral flow of useful information, equipment, manpower,
funds etc. to have continuous linkage.
• University should encourage faculty to direct their research and development efforts to local industry needs so
also the industry concerned by selecting proper faculty based on their specialisation.
• Industry must give its staff the time to learn from university as a part of their induction and training programmes
from time to time.
• Industry must be given a chance to have its own say in the design of university curriculum as and when required.
• The rules and regulations of industry and university interface must be designed to promote interaction between
them. Government intermediary role is found to be very significant in this regard.
• Interface cells must be set up in both places manned by motivated and committed persons duly framed by the
Government machineries.
Friends, I see you all as knowledge soldiers of our economy. You have to keep on moving for a leverage intellectual
capital growth; creative destruction of the old unproductive structures, keep on researching and innovating, otherwise
some other warring economy may capture us.
I convey my sincere thanks to the learned members of the association for selecting such nice topics for the different
technical Sessions and seminars which are not only of current relevance in the field of commerce and business but also
very much close to the dream vision of our beloved prime ministers. Briefly, these topics are on
i) Behavioural Finance
ii) E-Retailing
iii) Social media
iv) Skill Development
v) The road ahead for make in India and
vi) Environmental Issues vis-à-vis Industrialisation
The behavioral finance deals with the influence of psychology on the behavior of financial practitioners and its subsequent
impact on them. The herding mentality of most of our small investors in stock market, the aftermath shock of the chit
fund depositors especially in the eastern region of our country, the attachment of Indians towards gold investment are
really interesting and important areas to be researched upon by our members. The knowledge of these behaviors would
be an eye opener for not only the investors but also for the economic planners as well.
Today, the e-retailers are reshaping the consumer market in India. Their business and market share is growing rapidly.
They are increasingly becoming a threat to the brick and mortar retail business. These people are providing consumer
with a 24x7 market place with loads of choices to look for. The consumers are actually able to compare the products,
look for availability of the product, get detail information about the product check the prices at various online websites
selling the specific product and also look for attractive offers. However, this business is not without its own cup of
problem which includes low margin, e-security, logistics, supply constraints, mood of customers and many others
which needs an indepth research.
Social Media have already brought in so many revolutions throughout the world. These sites have taken over our lives
so much so that it is even hard to imagine that a few years ago there was no Face book or Twitter. These Medias are also
powerful tools to help companies reach their HR goals, Social Medias can help companies to engage with a wider
audience, build brand awareness, expand the talent pool, target top candidates for recruitment and improve on their
effectiveness of their selection process without significant increase in costs. I hope a lot more analytical research are
required in this field.
A skilled work force is an essential requirement for economic transformation of the individual and the nation as a
whole. As in a dynamic economy like India, where a large number of agrarian labour force are shifting to manufacturing
and service sectors, there is a mismatch between existing skill and the skill requirement of the economy. The traditional
( 8 )
education system does not produce skills that are relevant for industry needs; however, planning for skill development
is complex and involves large investment. Unless these are planned in greater detail, they can be counterproductive.
An active interface between academia and industry executives is of paramount importance now to study these aspects
of industry requirements and to develop necessary skills.
If India can make a Mangalyaan at a cost of less than a Hollywood movie, we have the talent to produce anything and
compete with anybody on the world. The ‘make in India’ is concept envisioned by the Prime Minister Narendra Modi
to transform India into a global manufacturing hub. For this to happen, we have to reach three mile stones –
1. Reviving the manufacturing sector
2. Gain global competitiveness
3. Claim global leadership.
However, the road is not easy and many hurdles are on the way such as:
1. Land Acquisition
2. Labour Reforms
3. Tax Reforms
4. Project Clearance
5. Infrastructure
6. Capacity Building
7. Skill Development and many more
All these things pose challenging questions before the policy makers such as (a) How to define ‘Brand India’ and the
“India Difference” in manufacturing in relation to the global standards? (b) Can we make sustained effort to market the
brand? (c) Do we have the necessary R&D investments and quality improvements ? (d) Will we be able to attract
sufficient FDI’s in the present political environment ? I hope this conference will exhaustively deliberate on the issues
and evolve suitable answers.
Friends, India have put the right step in the envisioned growth trajectory of becoming the Economic Super Power by
2020. To achieve this dream, concerted efforts and actions have to be chalked out and sustained at every level. This can
be only facilitated by the committed Commerce and management fraternity of the country provided we walk together,
we move together, we think together, we resolve together as opined by our Hon’ble Prime minister
I am obliged to all the esteemed members of pour association and the office bearers for their continued and unstinted
support in furthering the objectives of the association during my tenure. I wish all of us together can put the association
in a place of pride in the society. I conclude my views by quoting Thomas Jefferson that “Commerce with all nations,
Alliance with none should be our motto”.
In the end I would like to quote from our Upanishad
“Sarve Bhabantu Sukhinah; Sarve Santu Niramaya
Sarve Bhadrani Pashyantu Ma Kaschid Dhukha Bhag Bhavet”
“Let all be happy,
Let all be free from diseases
Let everyone be well off
Let there be no sorrow any time.”
Long live our Association
Jai Hind. JAI JAGANNATH
Prof. Jayanta Kumar Parida
( 9 )
Dr. Chandra Dev Singh, popularly known as Dr. C. D.
Singh was born on 14th January, 1927 in a middle class
Zamindar family in a village called Pakauli situated 5
kms. South-east of Punpun Railway Station which is on
the main Patna-Gaya rail line at a distance of about 15
kms. from Patna Junction Railway Station.
His entire education upto graduation level was completed
in the capital city of Bihar, i.e. Patna. He graduated in
Commerce discipline in 1948 from Patna University, Patna,
and earned his Master’s degree in commerce from Banaras
Hindu University, Banaras in 1950. All through his
academic career, he was a first class student having
passed all his public examinations in first division. He
earned his Ph.D. Degree in Business Administration
from Cornell University, USA in 1964. The title of his
doctoral thesis was “Graduate Education in Commerce
in India”.
Dr. C. D. Singh began his academic career as Lecturer in
HD Jain College, Ara (Bihar), way back in 1950 and
remained there for about a year. Thereafter, he moved to
join Patna University as a Lecturer where he served from
1951-1954.
In 1954, Dr. C. D. Singh moved to join as Reader & Head,
Department of Commerce of P.G. Campus, Bhagalpur of
Bihar University, Muzzafarpur. In 1965 he joined
Bhagalpur University as its founder, Professor, Head &
Dean, Faculty of Commerce after getting duly selected by
Bihar Public Service Commission, Patna, the position
which he occupied until the date of his superannuation in
1989.
He was one of those rare species of Professors of Commerce
who were leading the discipline all over India as there
were hardly half a dozen university professors in the
country in commerce , a situation which remained so up
Professor Chandra Deo Singh (Dr. C. D. Singh) Memorial Lecture68th All India Commerce Conference
of Indian Commerce Association (ICA)
Delivered byProfessor B. P. Singh
to late 70s and early 80s. During those days the selection
of university faculty in Bihar used to be done by Bihar
Public Service Commission, Patna.
He was elevated to the position of Pro-Vice Chancellor of
Magadh University, Bodhgaya, District - Gaya, Bihar, the
position which he held during 1975-77, repressive years
of emergency imposed in the country, and became the
acting Vice-Chancellor of the same university during 1977-
1978, the years following the lifting of emergency in India
in 1977, and the installation of late Shri Morarji Desai led
government at the centre.
Later on, he became the full-fledged Vice-Chancellor of
Lalit Narayan Mithla University, Darbhanga, from 1983-
1985, the university located in Mithla region of Bihar where
he served with distinction.
During his active academic career, he published dozens of
research papers in leading journals of India and abroad
along with a number of books which endeared him to the
academic community not only in Bihar but in the whole of
India.
He guided more than 30 Ph.D. scholars who obtained their
doctorate degree under his able supervision. He had the
distinction of being a member of the various Board of
Studies including Research Boards, and a member of a
number of Academic and Executive councils of various
universities in India. Besides, he had also served as an
expert member of the various selection committees of
different universities, and of Public Service Commission
including Union Public Service Commission, New Delhi.
He had the distinction of presiding over the 1981 Annual
Conference of the Indian Commerce Association as its
President hosted by the Department of Commerce,
University of Burdwan, West Bengal.
( 10 )
I feel extremely honoured and privileged for having been
invited by the Indian Commerce Association to deliver
late Professor CD Singh Memorial Lecture a renowned
academic personality and thoroughly humanitarian
persona without any qualms of position or status during
the 68th Annual Conference of ICA being hosted by the
Faculty of Commerce and Business Management, Vinoba
Bhave University, Hazaribagh, which remained a part of
Bihar as long as he was in active University service till the
time of his death on 12th May, 1994.
Keeping in view the personality, academic status, stature,
and the subject affiliation of Late Prof. C.D. Singh, I have
chosen to deliver the memorial lecture in his honour on a
subject, viz., “A journey from Millennium Development
Goals To Sustainable Development Goals: The Road
Ahead” a subject of great relevance and concern for the
whole world.
The Sustainable Development Goals (SDGs) are a new,
universal set of goals, built on the Millennium
Development Goals (MDGs), eight anti-poverty goals that
the world committed to achieve by 2015. The MDGs,
adopted in 2000 by the U.N., aimed at an array of burning
issues and problems that included:
GOAL 1: ERADICATE EXTREME POVERTY AND
HUNGER
• Extreme poverty has declined significantly over the
last two decades. In 1990, nearly half of the
population in the developing world lived on less
than $1.25 a day; that proportion dropped to 14 per
cent in 2015.
• The number of people in the working middle class—
living on more than $4 a day—has almost tripled
between 1991 and 2015. This group now makes up
half the workforce in the developing regions, up from
just 18 per cent in 1991.
• The proportion of undernourished people in the
developing regions has fallen by almost half since
1990, from 23.3 per cent in 1990–1991 to 12.9 per
cent in 2014–2015.
GOAL 2: ACHIEVE UNIVERSAL PRIMARY
EDUCATION
• The primary school net enrolment rate in the
developing regions has reached 91 percent in 2015,
up from 83 per cent in 2000.
• The literacy rate among youth aged 15 to 24 has
increased globally from 83 percent to 91 per cent
between 1990 and 2015. The gap between women
and men has narrowed.
GOAL 3: PROMOTE GENDER EQUALITY AND
EMPOWER WOMEN
• Many more girls are now in school compared to 15
years ago. The developing regions as a whole have
achieved the target to eliminate gender disparity in
primary, secondary and tertiary education.
• In Southern Asia, only 74 girls were enrolled in
primary school for every 100 boys in 1990. Today,
103 girls are enrolled for every 100 boys.
• Women now make up 41 per cent of paid workers
outside the agricultural sector, an increase from 35
per cent in 1990.
GOAL 4: REDUCE CHILD MORTALITY
• The global under-five mortality rate has declined by
more than half, dropping from 90 to 43 deaths per
1,000 live births between 1990 and 2015.
• Since the early 1990s, the rate of reduction of under-
five mortality has more than tripled globally.
• Measles vaccination helped prevent nearly 15.6
million deaths between 2000 and 2013. The number
of globally reported measles cases declined by 67
per cent for the same period.
GOAL 5: IMPROVE MATERNAL HEALTH
• Since 1990, the maternal mortality ratio has declined
by 45 per cent worldwide, and most of the reduction
has occurred since 2000.
• In Southern Asia, the maternal mortality ratio
declined by 64 per cent between1990 and 2013, and
in sub-Saharan Africa it fell by 49 per cent.
GOAL 6: COMBAT HIV/AIDS, MALARIA AND OTHER
DISEASES
• New HIV infections fell by approximately 40 per
cent between 2000 and 2013, from an estimated 3.5
million cases to 2.1 million.
( 11 )
• Over 6.2 million malaria deaths have been averted
between 2000 and 2015, primarily of children under
five years of age in sub-Saharan Africa. The global
malaria incidence rate has fallen by an estimated 37
per cent and the mortality rate by 58 per cent.
• More than 900 million insecticide-treated mosquito
nets were delivered to malaria-endemic countries
in sub-Saharan Africa between 2004 and 2014.
• Between 2000 and 2013, tuberculosis prevention,
diagnosis and treatment interventions saved an
estimated 37 million lives. The tuberculosis mortality
rate fell by 45 per cent and the prevalence rate by 41
per cent between 1990 and 2013.
GOAL 7: ENSURE ENVIRONMENTAL
SUSTAINABILITY
• Ozone-depleting substances have been virtually
eliminated since 1990, and the ozone layer is
expected to recover by the middle of this century.
• In 2015, 91 per cent of the global population is using
an improved drinking water source, compared to
76 per cent in 1990.
• Globally, 147 countries have met the drinking water
target, 95 countries have met the sanitation target
and 77 countries have met both.
• Worldwide, 2.1 billion people have gained access to
improved sanitation. The proportion of people
practicing open defecation has fallen almost by half
since 1990.
• The proportion of urban population living in slums
in the developing regions fell from approximately
39.4 per cent in 2000 to 29.7 per cent in 2014.
GOAL 8: DEVELOP A GLOBAL PARTNERSHIP FOR
DEVELOPMENT
• Official development assistance from developed
countries increased by 66 per cent in real terms
between 2000 and 2014, reaching $135.2 billion.
• In 2014, 79 per cent of imports from developing to
developed countries were admitted duty free, up
from 65 per cent in 2000.
• The proportion of external debt service to export
revenue in developing countries fell from 12 per cent
in 2000 to 3 per cent in 2013.
• As of 2015, 95 per cent of the world’s population is
covered by a mobile-cellular signal.
• Internet penetration has grown from just over 6 per
cent of the world’s population in 2000 to 43 per cent
in 2015. As a result, 3.2 billion people are linked to a
global network of content and applications.
However, the MDGs failed to consider the root causes of
poverty and overlooked gender inequality as well as the
holistic nature of development.
The goals made no mention of human rights and did not
specifically address economic development. While the
MDGs, in theory, applied to all countries, in reality they
were considered targets for poor countries to achieve, with
finance from wealthy states. Conversely, every country will
be expected to work towards achieving the SDGs.
As the MDG deadline approaches, about 1 billion people
still live on less than $1.25 a day – the World Bank
measure on poverty – and more than 800 million people
do not have enough food to eat. Women are still fighting
hard for their rights, and millions of women still die during
giving birth to a child.
The proposed 17 goals of SDGs:
1. End poverty in all its forms everywhere.
2. End hunger, achieve food security and improved
nutrition, and promote sustainable agriculture.
3. Ensure healthy lives and promote wellbeing for all
at all ages.
4. Ensure inclusive and equitable quality education,
and promote lifelong learning opportunities for all.
5. Achieve gender equality, and empower all women
and girls.
6. Ensure availability and sustainable management
of water, and sanitation for all.
7. Ensure access to affordable, reliable, sustainable and
modern energy for all.
8. Promote sustained, inclusive and sustainable
economic growth, full and productive employment,
and decent work for all.
9. Build resilient infrastructure, promote inclusive and
sustainable industrialization, and foster innovation.
( 12 )
10. Reduce inequality within and among countries
11. Make cities and human settlements inclusive, safe,
resilient and sustainable
12. Ensure sustainable consumption and production
patterns
13. Take urgent action to combat climate change and its
impacts
14. Conserve and sustainably use the oceans, seas and
marine resources for sustainable development
15. Protect, restore and promote sustainable use of
terrestrial ecosystems, sustainably manage forests,
combat desertification, halt and reverse land
degradation, and prevent biodiversity loss
16. Promote peaceful and inclusive societies for
sustainable development, provide access to justice
for all, and build effective, accountable and inclusive
institutions at all levels
17. Strengthen the means of implementation and
revitalise the global partnership for sustainable
development
The SDGs have been officially adopted by the General
Assembly of UN, and will become applicable from January
2016. The deadline for the SDGS is 2030.
Although significant achievements have been made on
many of the MDG goals worldwide, progress has been
uneven across regions and countries, leaving significant
gaps. Millions of people are being left behind, especially
the poorest and those disadvantaged because of their
sex, age, disability, ethnicity or geographic location.
Targeted efforts will be needed to reach the most
vulnerable people.
Millions of poor people still live in poverty and hunger,
without access to basic services
Despite enormous progress, even today, about 800 million
people still live in extreme poverty and suffer from hunger.
Over 160 million children under age five have inadequate
height for their age due to insufficient food. Currently, 57
million children of primary school age are not in school.
Almost half of global workers are still working in
vulnerable conditions, rarely enjoying the benefits
associated with decent work. About 16,000 children die
each day before celebrating their fifth birthday, mostly from
preventable causes. The maternal mortality ratio in the
developing regions is 14 times higher than in the developed
regions.
In 2015, one in three people (2.4 billion) still use
unimproved sanitation facilities, including 946 million
people who still practice open defecation. Today over 880
million people are estimated to be living in slum-like
conditions in the developing world’s cities. With global
action, these numbers can be turned around.
Globally big gaps exist between the poorest and richest
households, and between rural and urban areas
In the developing regions, children from the poorest 20
per cent of households are more than twice as likely to be
stunted as those from the wealthiest 20 per cent. Children
in the poor households are four times as likely to be out of
school as those in the richer households. Under-five
mortality rates are almost twice as high for children in the
poor households as for children in the richer ones. In rural
areas, only 56 per cent of births are attended by skilled
health personnel, compared with 87 per cent in urban
areas. About 16 per cent of the rural population do not use
improved drinking water sources, compared to 4 per cent
of the urban population. About 50 per cent of people living
in rural areas lack improved sanitation facilities, compared
to only 18 per cent of people in urban areas.
Gender inequality persists
Women continue to face discrimination in access to work,
economic assets, and participation in private and public
decision-making. Women living in poverty are far more
than men. In Latin America and the Caribbean, the ratio of
women to men in poor households increased from 108
women for every 100 men in 1997 to 117 women for every
100 men in 2012, despite declining poverty rates for the
whole region.
Women remain at a disadvantage in the labour market.
Globally, about three quarters of working-age men
participate in the labour force, compared to only half of
working-age women. Women earn 24 per cent less than
men globally. In 85 per cent of the 92 countries with data
on unemployment rates by level of education for the years
2012–2013, women with advanced education have higher
rates of unemployment than men with similar levels of
education. Despite continuous progress, today the world
has to go still far towards equal gender representation in
private and public decision-making.
( 13 )
Conflicts remain the biggest threat to human
development
By the end of 2014, conflicts had forced almost 60 million
people to abandon their homes—the highest level recorded
since the Second World War. If these people were a nation,
they would make up the twenty fourth largest country in
the world. Every day, 42,000 people on average are forcibly
displaced and compelled to seek protection due to
conflicts, almost four times the 2010 number of 11,000.
Children accounted for half of the global refugee
population under the responsibility of the United Nations
High Commissioner for Refugees in 2014. In countries
affected by conflict, the proportion of out-of-school children
increased from 30 per cent in 1999 to 36 per cent in 2012.
Fragile and conflict-affected countries typically have the
highest poverty rates.
Climate change and environmental degradation
undermine progress achieved, and poor people suffer
the most
Global emissions of carbon dioxide have increased by over
50 per cent since 1990. Addressing the unabated rise in
greenhouse gas emissions and the resulting likely
impacts of climate change, such as, altered ecosystems,
weather extremes and risks to society, remains an urgent,
critical challenge for the global community.
An estimated 5.2 million hectares of forest were lost in
2010, an area about the size of Costa Rica. Overexploitation
of marine fish stocks led to declines in the percentage of
stocks within safe biological limits, down from 90 per cent
in 1974 to 71 per cent in 2011. Species are declining overall
in numbers and distribution. This means they are
increasingly threatened with extinction.
Water scarcity affects 40 per cent of people in the world
and is projected to increase. Poor people’s livelihoods are
more directly tied to natural resources, and as they often
live in the most vulnerable areas, they suffer the most from
environmental degradation.
Having a vivid scenario of the global realities prevailing
and impacting economies and the people of the world, it
would be quite in the fitness of this paper to briefly sketch
out what is the situation in India on the parameters which
have been listed in the foregoing pages of this paper.
As per the United Nations Report, the largest number of
poor people live in India, the salient features of which are
given here below:
• About 17% of the poor people in the world live in
India.
• Poor People living in India account for 36 crs and
30 lakhs, out of which 52% poor people live in five
states of Uttar Pradesh, Bihar, Madhya Pradesh,
Jharkhand, and Chhatisgarh.
• About 33 percent of the world hungry people live in
India.
• According to Global Hunger Report about 7,000
people die of hunger every day in India out of which
3,000 are children, i.e, about 25 lakh Indians die of
hunger each year.
• As per the Global Monitoring Report, 2014 the
maximum number of illiterates live in India, the
details of which are given here below:
• Thirty Seven (37%) per cent of uneducated
people in the world live in India, which in terms
of absolute numbers it comes out to be 28 crores
and 70 lakhs.
• According to UNICEF Report on School
Dropouts Study about 8 crores children in India
dropout before passing out class 8th standard.
• In rural India only 28% people have passed out
their 8th class standard.
• As per the Socio- Economic Caste Census 2011,
only 3.45 % people possess graduate or higher
University degree(s).
• India is put to a loss of 1.2 % per annum to its
G.D.P. because of the uneducated people in the
country.
• India in terms of corruption has been ranked at
85th rank out of 175 countries rated by the
Transparency International which results into a
loss of 1.5% p.a. to the G.D.P. of the country.
The Most Pressing Evils which stare Into The Eyes of India Like
Demons have been briefly listed here below:
( 14 )
I. Rising Population is a Big Challenge To India
which Dilutes Most of The Economic and Social
Gains which India Registers Through The Process
of Economic and Social Development, To Tackle
which none of The Political Parties or Political
Leaders Talk or Is willing to Discuss
At present India’s population has reached 127 crores
at an annual rate of 1.6% per annum. According to
the U.N. Report India will take on China as the
largest populous country of the world in the year
2022.
As a result of this numerical expansion in
population in India, water availability for Indians
will be just 50% of the total requirement for water by
the year 2030 as per the Report of the International
Water Management Institute.
II. The Demon of Filth, Garbage, and open
Defecation Also Pose A Big Problem & Challenge
For India
As of now, half of India’s population does not have access
to toilet in their home, hence have to go for defection
in the open, This huge number of people going for
open defection constitutes 59% of the world
population who have been indulging into open
defection. In rural India 69% and in urban India
18% people indulge into open defection which is
responsible for the death of 160 people every day on
account diarrhea caused by infection through flies?
This awful deficiency of basic sanitation results into
a loss of Rs. 3, 50,000 crores to GDP every year.
III. Another great threat in India is from Pollution. Out
of 20 most polluted cities in the world, 13 are from
India which includes Delhi & Mumbai.
According to Global Burden of Disease Report about
one lakh people die each year on account of Air
Pollution in India, and about 3 crores of india’s
population is suffering from asthma. Indian
economy incurres a loss of Rs. 5, 82,000 crores each
year to it’s GDP on account of this pollution.
IV. There is a staggering number of 3 crores pending
cases in different courts in India, and it will take
years and decades before one can expect to get justice
in India. According to Law Commission India
should have 50 judges on every 10 lakhs people,
whereas in actual practice, we have only 15 judges.
India has in all 19,000 judges according to National
Court Management System, the number of pending
cases in India would shoot up to 15 crores by 2040,
and the number of judges would just be 75,000 up
from 19,000 at present.
V. There is ever frightening number of rape cases in
India. In 2014 there were 36,735 cases of rape
reported in police records in India out of which 4427
rape cases were reported in respect of girls who were
14 years of age or less. This startling number of
reported cases of rape does not include another 50%
of rape cases which go unreported. The conviction
rate in the trial court of reported cases of rape is just
24%.
VI. There are alarming numbers of riots most of which
take communal colour. From 2009 to June 2015 there
were 4561 cases of riots (which involving 2371 days,
thus there are two cases of riots each day). According
to the report of the Ministry of Home Affairs, there
were 287 communal riots on India during 2015 up
to May.
The Sustainable Development Goals should have four
pillars. The first should be to carry on the crucial work of
the MDGs in order to end extreme poverty by 2030. The
developing countries have successfully cut the overall
poverty rate by half comparing 1990 and 2010, from around
44% to 22%. The biggest gains have come in China, while
Africa has lagged behind, though Africa too is now on a
path of poverty reduction. Nolater than 2030 the remaining
extreme poverty and hunger should be eradicated.
Happiness in the poorest countries would be strongly
boosted by such an historic breakthrough.
The second pillar of the SDGs should be environmental
sustainability. Without that, no gains against poverty,
hunger, or disease can endure long. The environmental
pillar of the SDGs may be guided by the concept of
“planetary boundaries,” the notion that humanity must
avoid specific thresholds of environmental damage to
avoid creating irreparable harms to the Earth and to future
generations.
( 15 )
The third pillar should be social inclusion, the
commitment of every society that the benefits of technology,
economic progress, and good governance should be
accessible to everybody, women as well as men, minority
groups as well as the majority. Happiness must not be the
preserve of a dominant group. The goal should be
happiness for all.
The fourth pillar should be good governance, the ability
of society to act collectively through truly participatory
political institutions. Good governance is not only a means
to an end, but also an end in itself, since good governance
signifies the ability of people to help shape their own lives
and to reap the happiness that comes with political
participation and freedom.
Yet how shall we measure success, to know that our society
is on track? Here is where new metrics of happiness can
play a crucial role. To assess the four pillars of sustainable
development, we need a new set of indicators that extend
well beyond the traditional GNP.
I pray to the Almighty to let the departed soul of Professor
C. D. Singh remain in eternal peace, and let the surviving
members of the family of Professor Singh, and his
professional fraternity follow into his foot-steps of
Greatness, Humility, and Sacrifice to be the guiding lamp-
post for all of us in our life.
Om Shanti Om Shanti Om Shanti
( 16 )
( 17 )
INTRODUCTION
In the present dynamic competitive capital market, the prediction of stock returns is
becoming more and more complex. The prediction starts with development of capital
asset pricing model (CAPM) Sharpe (1964), Linter (1965) and Mossin (1966). But in
later period it has been criticized in many ways due to its assumptions are becoming
invalid. Fama and French (1992) found a flat relationship between expected return and
systematic risk. Jaganathan and Wang (1996) disagrees the beta of the market remains
constant over the period of time. And also several studies are there which have considered
some other factors like book to debt ratio, market value and size of firm (Fama and
French (1992), Campbell (1996) etc.) to predict stock return. There are many factors
which affect the stock return. Basically as per assumptions of CAPM (Sharpe, 1964) the
systematic risk and unsystematic risk both affect the stock returns. Here systematic risk
is measured through computation of â which denotes the market risk and unsystematic
Key words
Behavioral Finance, Asset
pricing, Human capital,
VAR, Granger causality.
Implications of Human Capital in Asset Pricingand Behavioral Finance: Evidence from India
Gnyana Ranjan Bal, Hemant Kumar Majhi and Malabika Deo
ABSTRACT
Recently the area of behavioral finance has received a significant attention of many academicians and
researchers all over the world. Asset pricing model, in explaining cross sections of expected returns, is
one of most burning and debatable issue in behavioral finance. The most prestigious noble Prize has been
awarded two times in this area for its significant contribution. Recently in 2013 Eugene Fama, Lars
Peter Hansen, and Robert Shiller for their contributions to asset pricing and earlier Harry M. Markowitz,
Merton H. Miller and William F. Sharpe has been awarded the coveted prize in the year 1990.The break
through research by Sharpe (1964) explained risk-return trade off through proposition of capital asset
pricing model.Capital asset pricing model (CAPM) explains the risk factors with help of á and â. á
indicate the unsystematic risk and â indicates the systematic risk. Many studies in different market
reject the assumptions and validation of CAPM. After failure of CAPM many factors like book to debt
ratio, size effect and value effect have considered to explain cross section of risk return relationship
attempts (Fama and French, 1992). Along with many marketable factors studies have also considered
non marketable factors like human capital for better explanation of risk return trade off (Campbell, 1996).
The present study tests the validity of discrete time asset pricing model in Indian market. This present
paper has attempted to analyses the role of human capital in prediction of share prices in emerging capital
market of India. We have employed Vector Auto Regression to explain the dynamic interrelationship of
different factors affecting security prices like human capital, dividend etc. Also the Granger Causality
has been applied to show the causal relationship between security returns and human capital including
other factors. Impulse response function has also been employed to find out the impact of shock of one
variable on another. This paper contribute towards the literature of asset pricing models. Specifically in
area of dynamic asset pricing with non-tradable factors like human capital etc. by investigating the
hypothesis that human capital is a significant factor affecting stock prices. The findings of the paper
conclude that risk-return relationship can be better explained with the help of human capital. There
exists a causal relationship between human capital and asset prices, thus it should be taken as proxy in
empirical asset pricing model.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 18 )
risk is measured through á which denotes firm specific
risk. As the company specific risk can be hedged through
selection of optimal portfolio so only systematic risk has
been used in asset pricing models. After the failure of
CAPM, many attempts (Fama and French, 1992, Campbell,
1996) have been made towards development of a better
model. Some have become successful to develop a model
and some are still opposing it. Due to such critiques the
studies tries to consider other factors to provide a better
explanation for cross section of expected returns like
Jaganathan and Campbell (1996), Wang (1996) includes
human capital as proxy in asset pricing, some other factors
like book to debt ratio, market value and size of firm (Fama
and French, 1992 etc.Some important and most cited study
literatures on this topic are summarized here under:
Table 1: Findings of major studies on CAPM model
Author Year Finding
Black, Jensen, and Scholes
(1972) Support CAPM
model
Black (1972, 1993)
Support CAPM model
Fama and MacBeth (1973) Support CAPM
model
Terregrossa (2001) Support CAPM
model
Fama and French (1992), Reject CAPM
model
Campbell (1993, 1996)
Reject CAPM Model
Jaganathan and Wang 1996 Reject CAPM
Model
Roll 1977 Reject CAPM
Model
In Indian context there are also a number of studies have
been taken place in this context; however very few have
attempted to test new proxies in asset pricing. In Indian
context among various studies, CAPM has been supported
by Yalwar (1988), Varma (1988) and Srinivasan (1988).
While Studies like Gupta and Sehgal (1993),
Madhusoodanan (1997), Sehgal (1997), Ansari (2000), and
Manjunatha et al. (2007) doubts the efficiency and validity
of CAPM in Indian market. In another study factors models
were supported by Connon and Sehgal (2003) than CAPM.
While in study of Five factor models like Beta, Size Book to
market equity ratio, EPS to Price ratio, Manjunatha and
Mallikarjunappa (2006) concludes none of the factor
significantly explains variation in security returns, but
they found exception in case of Beta and (Rm-Rf) in certain
cases. In the study made by Shijin, Gopalswamy and
Acharya(2012) it was found that there is dynamic
interrelationship between human capital and security
price, so human capital should be considered as a proxy
in asset pricing model.
So from the above literature it is clearly observed that the
existing proxies are not able to explain the cross sections
of share prices in India. So there is a need arises to take
care of these limitations with some new factors. In our
study we have employed the discrete time asset pricing
model(Campbell, 1996) to see whether human capital does
have any impact on stock returns. In order to analyze this,
we have employed Vector Auto Regression estimates.
Granger causality is used to see causal relationship
between variables and impulse response to see the shock
of one variable to other as suggested by (Shijin,
Gopalswamy and Acharya 2012). As indicated by
previous study only human capital may not explain
significantly the cross section of returns, so along with
human capital other factors like dividend, GDP (as an
alternative proxy), treasury bill rate and Yield spread
between short and long term bonds has been taken for
study. Our results support the conclusion of Shijin,
Gopalswamy and Acharya (2012) that human capital has
a greater role in share price prediction. Especially in Indian
market this cannot be ignored in asset pricing, as Indian
market has become central attraction of investors because
of its pool of skilled and cheaper labour since 1991.
BEHAVIORAL FINANCE, ASSET PRICING, HUMAN
CAPITAL AND OTHER FACTORS
The area of market efficiency, cross section of expected
returns etc. arethe most debatable topic in behavioral
finance. How investors predict the stock prices? What are
the factors affecting risk aversion behavior of a consumer?
How cross sections of expected returns can be explained
with proxy of different variables? These are some
unanswered questions till now.The literature shows a
numerous number of studies for different asset pricing
model in this context.
Sharpe-Linter-Mossin Static CAPM Model
CAPM measures the risk of an asset by co-variance of asset
return with return on all invested wealth known as market
return. But this has been challenged by Roll(1977) and
Merton (1973). As per Merton(1973) risk should be
measured by its co-variance with marginal utility of
investors, because the change in marginal utility can
derived by change in expectation of future return. Also
Roll(1977) argues market return cannot be measured
accurately enough to test the CAPM.But econometrician
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India
( 19 )
ignores the fact that beta and risk premium vary over the
time period will mistakenly conclude that CAPM does not
hold. Also some time specific economic events affect the
asset prices.
The basic propositions of CAPM model (Equation-1) can
be explained in the following equation:
( )it f m f tR R R Rβ= + − + ∈ (1)
Here itR indicates the Security return, fR indicates risk
free rate of return, mR indicates Market return, β indicates
systematic return and t∈ denotes error terms. The CAPM
estimates the risk by covariance of iR to market, so it can
be written as follows Equation (2):
0 1( ) ,i iE R γ γ β= − (2)
If ( )iE R is expected return of any asset, then iβ will be the
co-variance of iR to mR , then can be explained as follows
equation (3):
β = ( , )/ ( )i i m mCov R R Var R (3)
Here Cov means Co-variance and Var means variance, βi
is the magnitude of the changes.
Human Capital, Behavioral Finance and Asset Pricing
The failure of CAPM model and criticism of CAPM model
encouraged the researchers to find new proxies which can
explain risk-return tradeoff in a better manner. The first
ever study by Mayer (1972) theoretically includes a major
of return on human capital. As per Jaganathan and Wang
(1996) Return on value weighted portfolio of all stocks or
market return is proxy for return on aggregate wealth. The
aggregate wealth of any economy may be aggregate of
financial wealth and labour component (proxy for human
capital). As per Campbell (1996) the labour component
holds up to two third of total wealth of economy (GNP). So
avoiding human capital in asset pricing may be a major
issue.
Human capital mobility is the ability to reallocate the
economic resources across the economy maximizes the
aggregate output and mitigates asymmetric shock and
increase total welfare.The human capital(wage component
of labour, labour mobility) affects the operating leverage of
company and so on the return on asset prices. As mobility
of labour will change the cash flows of the company, so
the aggregate of risk will changed and affect the equity
premium. Aggregate wealth in the portfolio is aggregate of
dividend and wage component, so dividend has also been
tested as a proxy. Study has also proved that return on
human capital included in return in aggregate wealth
outperforms the static CAPM model (Jaganathan and
Wang, 1996).
Human capital as factor in asset pricing was first used by
Campbell (1993, 1996). The study uses human capital in
single period asset pricing to make human capital tradable.
The human capital mainly used in pricing model without
using consumption data. It replaces the consumption data,
where the wealth in the economy represented by ( )1tW + ,
which represents human capital, savings and the income
returns on the wealth in t+1 period. Thus the future return
on investment can be calculated by wealth invested after
consumption multiplied by market rate of return ( ), 1m tR + .
If Ctis consumption of an investor and W
t is his total
wealth, then investment will be (Wt –C
t), the derived
equation of future return is as follow Equation (4).
+ += −1 , 1( )( )t m t t tW R W C (4)
This above non-linear equation can be linearized by
dividing above equation by Wt,taking log. The resultant
equation will be showing the present value of future
returns in terms of future expectation (Campbell, 1993).
The increase or decrease in wealth or return can change in
consumption pattern of an investor.If therewill be increase
in return ( ), 1m tR + or total wealth this will lead to increase
in consumption to bring equilibrium between present and
future consumption. The following equation shows
tradeoff between current and future consumption as shown
below equation (5):
+ + +− = −1 1 1( )t tct t tC E E E ( )∞
+ + +=ρ − −∑ , 1 10
jm t j t tj
E E
∞
+ +=ρ ∆∑ 10
,jt jj
C (5)
With the combination of log linear equation and budget
constraint, risk return trade off with presence of human
capital can be arrived without using consumption data in
cross sectional asset pricing given as below Equation (6):
+ α + += − +, 1 , 1 , 1(1 )m t t t t y tR v R v R (6)
Gnyana Ranjan Bal, Hemant Kumar Majhi, Malabika Deo
( 20 )
The variables of the model are:
tv : Represents the ratio of human wealth to total wealth
α +, 1tR : Represents the return on financial wealth
+, 1y tR : Represents return on human wealth
+, 1m tR : Represents market return
And α refers to financial asset and y refers to stream of
labor wealth. This relationship helps to establish a role of
human capital in explaining market return along with
other financial asset. But when, v = 0 that means absence
of human capital, this model will be fail.
OBJECTIVE OF THE STUDY
The paper aims to analyse the role of human capital in the
behavioral finance and asset pricing prediction models.
By using discrete time asset pricing (which empirically
includes non-tradable factors like human capital) this
paper attempts to validate the requirement of human capital
as one of the proxy for empirical asset pricing model. Also
using the VAR estimates the paper establishes dynamic
relationship among the variables and causal relationship
has been analysed with the help Granger Causality test.
This paper will significantly contribute to previous
literature how including of human capital to cross sections
can better explain the risk-return relationship.
DATA AND METHODOLOGY
As daily returns of many macro economic variables are
not available, so monthly data has been taken for the study
from 1st April 2008 to 31st march 2012 as per availability of
data. The monthly stock prices have been obtained from
NSE website and other variables used in the study have
been collected from CMIE databases and RBI website. For
the purpose of analysis two variables have been taken
named as real value weighted index return termed as RVW
(S&P CNX Nifty) and labor income termed as LBRW. Wage
component of companies listed in S&P CNX Nifty have
taken as labor component. Along with LBRW Gross
domestic product (GDP) has also been tested as proxy of
labor component. The other variables used in the study
are dividend(DIV) of companies listed in S&P CNX Nifty,
“relative treasury bill rate” (RTB) and yield spread
between long and short term government bonds (TRM).
One year moving average of DIV and TRM has been
calculated for study.
In order to examine discrete time asset pricing model
(Campbell, 1996) Vector Auto Regression (VAR) estimates
has been employed.In order to estimate the dynamic
interrelationship of Asset prices, human capital and other
factors the following VAR has been applied. If lag variables
yt-1,
yt-p,
affect yt then a VAR can be written as:
t 1 t-1 p t-p ty = A y + ...+ A y + ε
In this case with three endogenous variables and p lags
where y1 and its lagged values, and tε are k + 1 vectors
and A1,..., A
p are matrices of constants to be estimated
(Maddala, 2007). In our case by taking lag of Rt and
Human capital (HC) the following VAR equation has been
derived:
1 1
M N
t i t i i t j t
t i
R R HC− −= =
= + + +∑ ∑α β γ ε
VAR Lag Order Selection Criteria
Lag length on the basis of Schwarz information criterion
(SC) and Hannan-Quinn information criterion (HQ) is
being chosen for the study. Lag length is most important
factor as high lag length indicates more standard error as
it consumes more degree of freedom and lower indicates
biasness in result.
Granger Causality
The granger causality shows causal relationship between
variable. In granger causality we are taking null hypothesis
that there is no casual relation exists between the variables.
Here it will show whether the variables used above are
unidirectional or bidirectional causing each other.
Impulse response function
In impulse response we come to know the whether one
variable is affected by the shock of another and when? It
will show the direction of changing of variables. Here we
can analyze whether there is upward or downward
movement.
RESULTS AND ANALYSIS
Table 2 : Unit Root Test
Variable ADF PP
DIV -6.494410*** -6.497420***
RVW -4.548204*** -4.591277***
RTB -8.772261*** --8.619271***
TRM --8.289141*** -8.132904***
LBRW -6.964513*** -7.026142***
GDPLR -7.033924*** -7.127906***
***indicates significance at 1% level.
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India
( 21 )
Interpretation
We know before estimating VAR, variables should be
stationary. To test the Stationary of data, we have done
unit root test on the basis of Phillips Perron and Augmented
Dickey Fuller. Stationary data means, the mean and
variance of the series are constant and any increase/
decrease does not affect the mean and variance. Here our
null hypothesis was variable has unit root problem. In all
cases on basis of both ADF and Phillips Perron the null
hypothesis has been rejected. It has been seen that at first
difference, that is RTB, TRM, LBRW, GDPLR all variables
are stationary except DIV, RVW stationary at level. As p
value is 0 which reflects Adj t stat is significant irrespective
of sign. P value and Type I error are directly related. As p
value is 0, so no chance of type I error, so all the variables
are stationary.
VAR Lag Order Selection Criteria:
We have selected lag length on the basis of Schwarz
information criterion (SC) and Hannan-Quinn information
criterion (HQ). As at 1 lag the both value are lower, so lag
length 1 is chosen for final estimate. Lag length is most
important factor as high lag length indicates more standard
error as it consumes more degree of freedom and lower
indicates biasness in result. The above implies at 1 lag
length the estimation will be adequate.
Table 3 : VAR Lag Order Selection Criteria
Endogenous variables: RVW RTB TRM LBRW GDPLR DIV
Lag LogL LR FPE AIC SC HQ
0 -1349.695 NA 2.33e+19 61.62250 61.86580 61.71273 1 -1187.104 273.4490* 7.51e+16* 55.86835* 57.57145* 56.49994*
2 -1152.455 48.82392 8.76e+16 55.92975 59.09263 57.10270
3 -1117.314 39.93266 1.18e+17 55.96881 60.59148 57.68312
* indicates lag order selected by the criterion
LR: sequential modified LR test statistic (each test at 5% level)
FPE: Final prediction error
AIC: Akaike information criterion
SC: Schwarz information criterion
HQ: Hannan-Quinn information criterion
Granger Causality
Table 4:Causality between Share price and Human Capital
Null hypothesis Test
statistics Decision
H01=Human Capital does not
granger cause share price 11.43350*** Reject H01
H02=Share price does not granger cause human capital
3.572359 Accept H02
*** Significant at 1% level
The above table shows the causality between share prices
and human capital. As for H01, test statistics is more than
critical value so null hypothesis has been rejected, there
causality between share price and human capital. While
in case H02, test statistics is less than critical value, so
accept the null hypothesis. Here the evidence shows the
unidirectional granger causality between share price and
human capital.
Table 51 : Summary of Granger causality between different variables
ENDOGENOUS VARIABLE (Dependent)
LAGGED ENDOGENOUS VARIABLE
RVW LBRW GDPLR RTB DIV TRM ALL
RVW 11.43350*** 10.82411*** 8.086269** 0.625390 3.386991 26.14202***
LBRW 3.572359 1.753395 0.560052 9.611634*** 1.192029 13.07852
GDPLR 5.540440* 1.109685 1.149785 9.282197*** 1.062470 14.12406
RTB 1.390108 1.802988 1.993686 1.134488 2.621047 10.13388
DIV 0.502792 0.216092 0.027256 0.704632 0.141242 4.913611
TRM 0.736359 0.127002 0.100831 12.16914*** 1.623244 37.81504***
***, ** and * represent the significance at 1%, 5% and 10% level respectively.
Interpretation
The granger causality shows the causing of one variable
to another. That indicates how much one variable explains
the other. In granger causality we are taking null hypothesis
that there is no casual relation exists between the variables.
When the p value is less than á, null hypothesis is rejected
and there is a casual relation among the variables. At first
we have taken RVW(stock return) as dependent variable,
we can there is a causal relationship between RVW and
LBRW (human capital, GDPLR and RTB. And in overall
the null hypothesis of non-causality is also been rejected.
Again we can see when LBRW is dependent variable; DIV
alone is significantly causes LBRW. In case of dependent
variable GDPLR, RVW and DIV cause GDPLR. When the
Gnyana Ranjan Bal, Hemant Kumar Majhi, Malabika Deo
( 22 )
RTB becomes the dependent variable; all the variables DIV,
GDPLR, LBRW, RTB, and TRM have not influenced. The
variable TRM is influenced by RTB, which is very much
significant.
The above observation shows that there is causal
relationship between share prices and human capital. So
the role of labor income as a return on human capital
cannot be ignored in prediction of market return. So the
along with financial wealth and other factors including
human capital also influences the cross section returns.
Impulse Response Function
In impulse response, we came to know whether one
variable is affected by the shock of another and when.
Here it traces the impact of one SD shock to one innovation
on other variables. This will show the impact of show
both in present period and its transmission in future period.
This dynamic response of share price to human capital
indicates the human has a significant role in asset pricing.
The following figures show the impulse response among
different variables.
Impulse response of Share price to Human capital
- 2
- 1
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 1 0
R e s p o n s e o f S h a r e P r i c e t o H u m a n C a p i ta l
Figure 1: Response of share price to human capital
The Figure 1 shows the response of share prices to human
capital. We can see that starting from month1 to month3
human capital has a significant impact on share prices.
While the shock has been absorbed in later period.
Impulse response of share price to other variables
Figure 2 shows the response of share price to RTB, in initial
month 1 and 2 there is a negative trend, while in later
period it shows a positive trend. Similarly in figure.3, it
can be observed that share price responds negatively to
shock of TRM up to month 6 and absorbs the shock in later
period. The shock is more significant in month 3. The
figure.4. shows the response of share price GDPLR(
alternative proxy for labour component). There is a positive
response of share prices to shock of GDPLR from month 1
to month 5. While the figure 5. Response to shock of
dividend shows a dynamic trend, initially positive and
negative in period 5 and again positive in later period.
-2
-1
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
R esp on se o f S ha re P ric e to RTB
Figure 2 : Response of share price to RTB
-2
-1
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
Re sponse of Share P rice to TR M
Figure.3. Response of share price to TRM
-2
-1
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
Response of Share Price to GDPLR
Figure 4 : Response of share price to GDPLR
-2
-1
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10
Response of Share Price to Dividend
Figure 5 : Response of share price to dividend
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India
( 23 )
Impulse response among of other variables
The figure.6 traces the impact of one SD shock to one
innovation on other variables. The response of GDPLR to
RTB is significant at initial period but later on it shows a
little impact. It reveals positive trend up to month 5 and
negative later on. We can see there is a significant effect on
DIV to the shock of RTB. Also the response of dividend to
LBRW is significant in initial period. Similarly other
response does not seem to be significant. Also the same
has been revealed in Granger causality.
-0.4
0.0
0.4
0.8
1.2
2 4 6 8 10
Response of RTB to RVW
-0.4
0.0
0.4
0.8
1.2
2 4 6 8 10
Response of RTB to TRM
-0.4
0.0
0.4
0.8
1.2
2 4 6 8 10
Response of RTB to LBRW
-0.4
0.0
0.4
0.8
1.2
2 4 6 8 10
Response of RTB to GDPLR
-0.4
0.0
0.4
0.8
1.2
2 4 6 8 10
Response of RTB to DIV
-.4
-.2
.0
.2
.4
2 4 6 8 10
Response of TRM to RVW
-.4
-.2
.0
.2
.4
2 4 6 8 10
Response of TRM to RTB
-.4
-.2
.0
.2
.4
2 4 6 8 10
Response of TRM to LBRW
-.4
-.2
.0
.2
.4
2 4 6 8 10
Response of TRM to GDPLR
-.4
-.2
.0
.2
.4
2 4 6 8 10
Response of TRM to DIV
-2,000
-1,000
0
1,000
2,000
3,000
2 4 6 8 10
Response of LBRW to RVW
-2,000
-1,000
0
1,000
2,000
3,000
2 4 6 8 10
Response of LBRW to RTB
-2,000
-1,000
0
1,000
2,000
3,000
2 4 6 8 10
Response of LBRW to TRM
-2,000
-1,000
0
1,000
2,000
3,000
2 4 6 8 10
Response of LBRW to GDPLR
-2,000
-1,000
0
1,000
2,000
3,000
2 4 6 8 10
Response of LBRW to DIV
-10,000
0
10,000
20,000
2 4 6 8 10
Response of GDPLR to RVW
-10,000
0
10,000
20,000
2 4 6 8 10
Response of GDPLR to RTB
-10,000
0
10,000
20,000
2 4 6 8 10
Response of GDPLR to TRM
-10,000
0
10,000
20,000
2 4 6 8 10
Response of GDPLR to LBRW
-10,000
0
10,000
20,000
2 4 6 8 10
Response of GDPLR to DIV
-4
0
4
8
2 4 6 8 10
Response of DIV to RVW
-4
0
4
8
2 4 6 8 10
Response of DIV to RTB
-4
0
4
8
2 4 6 8 10
Response of DIV to TRM
-4
0
4
8
2 4 6 8 10
Response of DIV to LBRW
-4
0
4
8
2 4 6 8 10
Response of DIV to GDPLR
Response to Cholesky One S.D. Innovations
Figure 6 : Impulse response between different variables
Gnyana Ranjan Bal, Hemant Kumar Majhi, Malabika Deo
( 24 )
CONCLUSION
In this study we have employed the discrete time asset
pricing model (Campbell, 1996) to study the role of human
capital in explaining cross section returns in India.
Employing VAR estimates we studied the dynamic
interrelationship between DIV, RVW, RTB, TRM, LBRW
and GDPLR.The study analyzes the influence of both labor
component and GDP as human capital on share prices.
Granger causality and IRFs performed to analyze causal
relation and directional change among the variables.
The results shows that there is causal relationship exist
between human capital and security prices. Human capital
should not be ignored in asset pricing model. Human
capital as proxy in asset pricing can better explain the risk
return tradeoff. India as an emerging economy is attracted
hub for its human capital, so there is need arises for better
treatment and reporting of human capital by the
companies. As prior literature finds weak evidence of
CAPM and other model in explain the expected returns,
so new proxies may be taken into consideration for better
explanation. Our study reveals a significant role of human
capital in asset pricing model. Ignoring of human capital
will become a serious issue in case of emerging economies
especially in India. Further study can be made to test this
in different portfolios to provide a better explanation. Also
study may consider data from different countries to explain
this dynamic relation and make it generalized one. Methods
like Variance decomposition can be also made for better
understanding of the results.
REFERENCES
Banz, R.W. (1981). The relationship between return and
market value of common stock. Journal of Financial
Economics, 9 (1), 3-18.
Basu, S. (1983).The relationships between earnings yield,
market value, and return for NYSE common stocks:
further evidence. Journal of Financial Econometrics, 12,
51-74.
Bhandari, L.C. (1988). Debt/equity ratio and expected
common stock returns: empirical evidence. Journal
of Finance, 43, 507-28.
Bhattacharya, B.B., Bhanumurthy, N.R., Chakravarty, S.
and Rai, K. (2003).A short-term time series
forecasting model for Indian economy.IEG Working
Paper Series No. 72/2003.
Black, F.; Jensen, M. C. and Scholes, M. (1972). Studies in
Theory of Capital Markets, New York: Praeger.
Black, F. (1972). Capital Market Equilibrium and Restricted
Borrowing, Journal of Business, 48(3), 444-445.
Black, F. (1993). Beta and Return, Journal of Portfolio
Management, 20(1), 8-18.
Breeden, D.T. (1979). An intertemporal asset pricing model
with stochastic consumption and investment
opportunities. Journal of Financial Economics, 7, 265-
96.
Brooks, C. (2008).Introductory Econometrics for Finance.
Cambridge university press
Campbell, J.Y. (1993). Intertemporalasset pricing without
consumption data, The American Economic Review,
83, 487-512.
Campbell, J.Y. (1996). Understanding risk and return.Journal
of Political Economy, 104, 298-345.
Chen, Roll and Ross (1986).Economic Forces and the Stock
Market.Journal of Business, 59, 383-403.
Connon, G. and Sehgal, S. (2003). Tests of Fama and French
Model in India, Decision, 30(2), 1-20.
Enders, W. (2008).Applied Econometric Time Series.Wiley,
New Delhi.
Epstein, L.G. and Zin, S.E. (1989).Substitution, risk
aversion, and the temporal behavior ofconsumption
and asset returns: a theoretical framework.
Econometrica, Vol. 57,pp. 937-69.
Epstein, L.G. and Zin, S.E. (1991).Substitution, risk
aversion, and the temporal behavior ofconsumption
and asset returns: an empirical analysis.Journal of
Political Economy, 99, 263-86.
Fama, E.F. and French, K.R. (1996). The CAPM is Wanted,
Dead or Alive, Journal of Finance, 51(5), 1947-1958.
Fama, E.F. and French, K.R. (1998). Value versus Growth:
The International Evidence, Journal of Finance, 50(6),
55-84.
Fama, E.F. and French, K.R. (2002). The Equity Premium,
Journal of Finance, 57(2), 637-659.
Fama, E.F. and MacBeth, J.D. (1973). Risk, Return, and
Equilibrium: Empirical Tests, Journal of Political
Economy, 81(3), 607-636.
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India
( 25 )
Fama, E.F. and French, K.R. (1992).The cross-section of
expected stock returns. Journal ofFinance, 47, 427-65.
Fama, E.F. and French, K.R. (1993).Common risk factors in
the returns on stocks and bonds. Journal of Financial
Economics, 33, 3-56.
Fama, E.F. and Schwert, W.G. (1977).Human capital and
capital market equilibrium.Journal ofFinancial
Economics, 4, 95-125.
Friend, I. and Blume, M.E. (1975).The demand for risky
assets.American Economic Review, 65, 900-22.
Gibbons, M.R. (1982). Multivariate tests of financial
models: a new approach. Journal of Financial
Econometrics, 10, 3-27.
Jagannathan, R. and Wang, Z. (1996).The conditional
CAPM and the cross-section of expected
Returns.Journal of Finance, 51, 3-53.
Jagannathan, R., Kubota, K. and Takehara, H.
(1998).Relationship between labor income risk and
average return: empirical evidence from the Japanese
stock market. Journal of Business, 71, 319-47.
Kothari, S. P. and Shanken, J. (1995). In Defense of Beta,
Journal of Applied Corporate Finance, 8(1), 53-58.
Lintner, J. (1965). The valuation of risk assets and the
selection of risky investments in stock portfolios and
capital budgets. Review of Economics and Statistics,
47, 13-37.
Lu¨tkepohl, H. (1991).Introduction to Multiple Time Series
Analysis.Springer, New York, NY.
Madhusoodanan, T. .P (1997). Risk and Return: A New
Look at the Indian Stock Market, Finance India, 11(2),
285-304.
Manjunatha, T. and Mallikarjunappa, T. (2006). An
Empirical Testing of Risk Factors in the Returns on
Indian Capital Market, Decision, 33(2), 93-110.
Manjunatha, T. and Mallikarjunappa, T. (2009).Bivariate
Analysis of Capital Asset Pricing Model in Indian
Capital Market, Vikalpa, 34(1), 47-59.
Manjunatha, T.,Mallikarjunappa, T. and Begum, M. (2006).
Does Capital Asset Pricing Model Hold in the Indian
Market?,Indian Journal of Commerce, April-June, 59(2),
73-83.
Manjunatha, T.,Mallikurjunappa, T. and Begum, M.,
(2007).Capital Asset Pricing Model: Beta and Size
Tests, AIMS International Journal of Management, 1(1),
71-87.
Mankiw, G. and Shapiro, M.D. (1986). Risk and return:
consumption beta versus market beta. Review of
Economics and Statistics, 68 No. 3, 452-9.
Merton, R.C. (1973). An intertemporal asset pricing
model.Econometrica, 41, 867-87.
Mohanty, P., (2002). Evidence of Size Effect on Indian Stock
Returns, Vikalpa, 27(2), 27-37.
Mossin, J. (1966).Equilibrium in a capital asset pricing
market.Econometrica, 34, 768-83.
Pesaran, M.H. and Shin, Y. (1998).Generalised impulse
response analysis in linear multivariate Models.
Economics Letters, 58, 17-29.
Polk, C. (1999). The market as a hedge. working paper series.
Qin, J. (2002). Human-capital-adjusted capital asset pricing
model.Japanese Economic Review, 53 (2), 182-98.
Reinganum, M.R. (1981). A new empirical perspective on
the CAPM.Journal of Financial andQuantitative
Analysis, 16, 439-62.
Roll, R.R. (1977). A critique of the asset pricing theory’s
tests: part 1: on past and potential testability of the
theory.Journal of Financial Economics, 4, 129-76.
Roll, R.R. and Ross, S.A. (1980). An empirical investigation
of the arbitrage pricing theory.Journal of Finance, 35,
1073-103.
Rosett, J.G. (2001). Equity risk and the labor stock: the case
of union contracts. Journal of Accounting Research,
39, 337-64.
Santos, T. and Veronesi, P. (2000).Labor income and
predictability of stock returns.unpublished Working
Paper No. 520, The Center for Research in Security
Prices, University of Chicago, Chicago, IL.
Sehgal, S. (1997). An Empirical Testing of Three parameter
Capital Asset Pricing Model in India, Finance India,
11(4), 424-442.
Sehgal, S. (2003). Common Factors in Stock Returns: The
Indian Evidence, The ICFAI Journal of Applied Finance,
9(1), 5-16.
Gnyana Ranjan Bal, Hemant Kumar Majhi, Malabika Deo
( 26 )
Shanken, J. (1985). Multi-beta CAPM or equilibrium APT?A
reply.Journal of Finance, 40, 1189-96.
Sharpe, W.F. (1964). Capital asset prices: a theory of market
equilibrium under conditions of Risk.Journal of
Finance, 19(3), 425-42.
Shijin, S., Gopalaswamy, A.K. and Acharya, D.
(2012).Dynamic risk-return relation with human
capital: a study on Indian markets. International
Journal of Emerging Market, 7(2), 146-159.
Sims, C.A. (1980). Macroeconomics and
reality.Econometrica, 48, 1-48.
Srinivasan, S. (1988).Testing of Capital Asset Pricing
Model in Indian Environment, Decision, 15(1), 51-
59.
Terregrossa, S.J. (2001). Robust International Tests on the
CAPM, Applied Economics, 8(2), 121-124.
Yalwar, Y.B. (1988). Bombay Stock Exchanges: Rate of
Return and Efficiency, Indian Economics Journal, 35(4),
68-121.
Zellner, A. (1962). An efficient method of estimating
seemingly unrelated relations and tests for
aggregation bias.Journal of the American Statistical
Association, 57, 348-67.
Gnyana Ranjan Bal
Assistant Professor
Dept. of Commerce
Guru GhasidasVishwavidyalaya, C.G.
Hemant Kumar Majhi
Ph.D. Scholar, Dept. of Banking and Technology
Pondicherry University, Pondicherry
E-mail : [email protected]
Dr. Malabika Deo
Professor and Head, Dept. of Commerce
Pondicherry University, Pondicherry
E-mail : [email protected]
Implications of Human Capital in Asset Pricing and Behavioral Finance: Evidence from India
( 27 )
INTRODUCTION
In financial terms, derivatives is a designation for financial instruments whose value
derives from an underlying asset, e.g. shares, bonds or share indices. Over the past
several years derivatives have become an important element of the financial world and
these instruments are now traded on exchanges worldwide. The main reason is that
they have attracted many different types of traders and have a great deal of liquidity.
The attractiveness of option market can be proved by looking into the increasing trend
in the total traded value in the option market over a period of time in a developing
economy like India. Options can be used both for hedging as well as for speculation.
Options contract is a type of derivatives contract which gives the buyer or holder of the
contract the right but not the obligation to buy or sell the underlying asset at a
predetermined price within or at end of a specified period. There are two types of
options namely call option and put option. An option to buy is called call option and
option to sell is called put option. Trading in options involves high risk. The buyer will
lose the premium if he does not exercise his option; while the seller has unlimited loss
potential if the buyer decides to exercise his right. To ensure a certain level of profits, a
trader (whether buyer or seller) must use strategies that act as a hedging device to either
minimize losses or lock a certain minimum profit level. Generally people have two
goals: security and return. Risk averse investors aims security while risk takers want to
maximize their return. Each investor has his own needs and behaviour based on the
different shapes of utility functions which measures the investors risk aversion degree.
Key words
Option, Option market,
Traders, Open interest and
Volume
Behavioural Impact of Traders in the IndianOption Market
Raju G and Deepika Krishnan
ABSTRACT
The behaviour of traders in the derivative market differs with variations in the quantity of private
information, their expectation and the liquidity available. Most academics argue that equity investors are
more likely to behave rationally than equity derivatives traders. Since derivatives are new segment of
secondary market operation in India, investors need to understand the complexity of this trade. This
paper investigates the behaviour of option market trader using a unique and detailed dataset of open
interest and volume of CNX Nifty index option listed on the National Stock Exchange from April 2014
to March 2015. Empirical and statistical analyses are conducted to evaluate the movement of open
interest and the volume of contracts to determine the rational and irrational behaviour of traders in
option market. The analyses documents major stylized facts about the option market activity over these
time period and also investigate how their trading changed during the stock market fluctuations. The
empirical evidence shows that traders purchases more calls to open brand new positions when the
volume of stocks are higher over horizons ranging from one week to two years. Moreover, the least
sophisticated group of traders substantially increased their purchases of calls on growth but not value
stocks during the stock market volatility during the five year period and none of the investor groups
significantly increased their purchases of puts during the volatility period in order to overcome short
sales constraints in the stock market.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 28 )
Since the risk and volatility of derivatives are increasing,
the protection against these has become integral part of
market. The liquidity provided by option market makes
the market more viable. They also play an important role
in financial markets by facilitating day trading. That is,
option market provides both liquidity and smooth prices.
Thus, their trading behaviour tends to stabilize asset
prices. However, once many traders makes profit during a
period of time, they tend to trade more aggressively,
increasing price movement and generating more volatile
return series. In this situation, their trading behaviour may
also destabilize asset prices. It is well documented that
not only the option prices, but also the non-price variables,
such as open interest, trading volume etc., from the option
market can also affect the prices in the underlying equity
market. Open interest means the number of outstanding
contracts in a particular class or series existing in the option
market; while, the trading volume refers to the total value
of all the contracts traded in that particular class. This
paper investigates the behaviour of traders in the equity
option market using a unique and detailed dataset of open
interest and trading volume from CNX Nifty index option
listed in the National Stock Exchange. By applying the
statistical method on open interest and volume based call
and put options, this study empirically analyse the
performance of traders in option market.
The remainder of this paper is organized as follows.
Section 2 discusses a brief review of the past literature
relevant with this study and pointed out the efforts trying
to achieve through this study. A brief description of the
method and the tests applied in the study along with the
empirical findings in section 3. Lastly, concluding remarks
have been given in section 4.
REVIEW OF LITERATURE
Various researchers in the past have tried to study the
investor behaviours and their preference towards
derivative markets in India. Some studies have also
attempted to document the volume effect of option market
on stock price, stock market volume and bid-ask spread.
An attempt to survey the literature on this subject however;
some of the studies may not have been included due to
constraints in terms of their availability. Hayes and
Tennenbaum (1979) investigate the impact of option listing
on the volume of underlying shares traded in the cash
market. They conclude that listing of options does result
in increase in the volume of trading in underlying shares.
According to them, this effect is caused by the variety in
option trading strategies and linkage between cash market
and option market as it results in continuous feedback to
each of these markets. Manaster and Rendleman (1982)
document the evidence in support of option market leading
the stock market. They contend that an option trader is
likely to be more informed than the average stock investor,
and option prices may reflect additional information not
captured by observed stock prices. The closing prices of
listed call options contain information about the
equilibrium stock prices that is not contained in the closing
prices of underlying stocks. Anthony (1988) empirically
investigates the relation between common stock and call
option trading volumes using Granger-Newbold Causality
test and Multivariate Causality tests. The study concludes
that option trading volume “leads” stock volume with a
one-day lag. However, the results support the dependence
between the two series though the leading role for option
volume was less strongly supported, i.e. 48 per cent of
cases based on both the tests. Vijh (1988) examines the
potential biases from trade prices and concludes that more
trades in the option market occur at ask than at bid. He
observes that it may lead to option trade prices to be
upward biased estimates of the corresponding true prices.
He, further, adds that this bias and non-synchronous
trading may create an impression that option prices contain
information not reflected in the contemporaneous stock
prices even during times when the two prices are in
equilibrium. Conard (1989) investigates the effect of option
introduction from 1974 to 1980 and concludes that it has
positive permanent price effect on the underlying security
beginning slightly before the introduction date. She
suggested that timing of price effect just before the
introduction of options (not announcement) may be due
to the traders building inventory for hedging purposes in
anticipation of trading volumes in options. She also
concludes that the variance of average excess return has
also declined after the introduction of options while the
systematic risk has remained the same.
Though most of the studies have been conducted in context
of USA, some research studies have also been carried out
in Canada, UK and Finland. Elfakhani and Chaudhury
(1995) examine the effects of the Canadian option listings
on the volatility of underlying stocks. They conclude that
option listing had a stabilizing effect on the underlying
stocks in total risk as well as non-diversifiable risk sense
during 1970s. However, there has been an increase in non-
diversifiable risk surrounding the market crash of 1987.
As opposed to the outcome of several other studies like
Conard (1989) and Kim and Young (1991), they note that
Behavioural Impact of Traders in the Indian Option Market
( 29 )
the put option listings tend to reduce the total as well as
the non-diversifiable risk. In a study that was focused on
listing effect of put options, Chaudhury and Elfakhani
(1997) conclude that listing of put options have ‘stabilizing
effect’ as the systematic risk (beta) of underlying stocks
has declined in post listing period in Canada. They, further,
analyse the cross sectional variations in the volatility effect
of put options listing and found indirect support for the
hypothesis that option listing enhances liquidity and thus
has a stabilizing influence on the stock variance. They
attribute regulatory environment in Canada for beta
stabilization effect as Canada restricts institutional
investors from speculative trading in derivatives. In context
of Finland, Sahlstorm (2001) examines the stock option
listing effects and concludes that it benefits the efficiency
and operation of stock market in Helsinki Stock Exchange.
More specifically, this study documents the impact of stock
option listing on underlying stocks’ volatility, bid-ask
spread, and autocorrelation structure of return series. It
finds the evidence of decrease in volatility and bid-ask
spread levels, and smaller positive first-order
autocorrelation after option initiation and thus concludes
increase in efficiency of underlying asset market. Some
studies have also been conducted in UK. Watt, Yadav and
Draper (1992) report increase in efficiency of underlying
asset market caused by option listing as a result of
temporary price increase immediately prior to listing, lower
unsystematic and total risk, better price adjustment to new
information, and significant decline in skewness of
returns. Later on, Hamill, Opong and McGregor (2002)
analyse the stock option listing effect in UK using a number
of market based research methodologies. They find that
the impact of option listing event has diminished over
time and thus support the market completion hypothesis.
According to this study, option listings no longer affect
the underlying equity market.
METHODOLOGY AND DATA ANALYSIS
The Securities and Exchange Board of India (SEBI)
introduced index options in July 2001. The trading interest
in these contracts has been consistently increasing since
the introduction of derivatives in National Stock
Exchange. It provides all the market information on call
and put options traded on different indices during the
day that include option premium (open, high, low and
close), trading volume and open interest at each strike
price. The main data for this paper were obtained from the
CNX Nifty Index Option which covers index option
contracts for one year from the April 2014 to March 2015.
As the present study attempts to decipher the open interest-
volume relationship, the liquidity of index options becomes
an important issue. Keeping this in view, monthly average
daily open interest and volume each from Call European
(CE) and Put European (PE) is taken because they are
considered to most liquid over the volatility market. The
option contracts available in Indian market are for one,
two, three and six- month maturity. Further, the expiration
day data has been excluded from the study to avoid the
biasness due to expiration effect.
Table 1 : Summary Statistics of Open Interest and
Contract Volume of European Call and Put Option
from April 2014 to March 2015
Variable Mean Std. Dev.
C.V. Skew-ness
Ex Kurtosis
Call Open Interest
1.29556 0.5308 0.4097 1.3906 0.4908
Call Volume
3.2592 1.5007 0.4604 0.8584 0.1294
Put Open
Interest 2.9097 2.0381 0.7004 0.7595 -0.6638
Put Volume
3.4372 1.2981 0.3776 0.2328 -1.3929
As mentioned earlier, this study investigates the
significance of net open interest and trading volume in
index option market to analyse the trader behaviour over
entire data period from 2010 to 2015. Hence, Table 1
presents the statistical summary of open interest and
contract volume of call and put option contract taken from
CNX Nifty index option. The table narrates that the
standard deviation of call open interest is lower but the
coefficient of variance show higher figure in the put open
interest. This shows an irregularity and diverse nature of
option market in Indian context. Many economic and
financial time series exhibit trending behaviour or non
stationarity in the mean. If the data are trending, then some
form of trend removal is required. Therefore, a relevant
stationarity or unit root test is required to avoid the trending
behaviour.
UNIT ROOT TEST
An important econometric task is determining the most
appropriate form of the trend in the data. Two common
trend removal or de-trending procedures are first
differencing and time- trend regression. First differencing
is appropriate for I (1) time series and time- trend regression
Raju G and Deepika Krishnan
( 30 )
is appropriate for trend stationary I (0) time series. Unit
root test suggest a relevant technique for analysing the
trending behaviour. Hence, the variable under study has
been tested to check the stationarity of the series.
Step 1: Testing for a unit root in Call Open Interest
Augmented Dickey-Fuller test for Call open interest
including one lag of (1-L), sample size 12, unit-root null
hypothesis: a = 1 with constant model: (1-L)y = b0 + (a-
1)*y(-1) + ... + e., 1st-order autocorrelation coeff. for e: -
0.238, estimated value of (a - 1): -1.1064, test statistic:
tau_c(1) = -2.26864, asymptotic p-value 0.1823
Step 2: Testing for a unit root in Call Volume
Augmented Dickey-Fuller test for Call volume including
one lag of (1-L), sample size 12, unit-root null hypothesis:
a = 1 with constant model: (1-L)y = b0 + (a-1)*y(-1) + ... + e,
1st-order autocorrelation coeff. for e: 0.265, estimated value
of (a - 1): -1.25624, test statistic: tau_c (1) = -2.82856,
asymptotic p-value 0.05427
Step 3: Testing for a unit root in Put Open Interest
Augmented Dickey-Fuller test for Put open interest
including one lag of (1-L), sample size 12, unit-root null
hypothesis: a = 1 with constant model: (1-L)y = b0 + (a-
1)*y(-1) + ... + e, 1st-order autocorrelation coeff. for e: -0.092,
estimated value of (a - 1): -0.389145, test statistic: tau_c (1)
= -1.91959, asymptotic p-value 0.3235
Step 4: Testing for a unit root in Put Volume
Augmented Dickey-Fuller test for Put volume including
one lag of (1-L), sample size 12, unit-root null hypothesis:
a = 1 with constant model: (1-L)y = b0 + (a-1)*y(-1) + ... + e,
1st-order autocorrelation coeff. for e: -0.169, estimated value
of (a - 1): -0.718169, test statistic: tau_c (1) = -1.6808,
asymptotic p-value 0.4411.
The first difference autocorrelation under ADF test shows
negative figures which strongly reject the hypothesis that
there is a unit root at 1 per cent significance level. Hence,
an cointegration regression test is undertaken considering
the dependent variable as call open interest on one side
and put open interest on another.
COINTEGRATING REGRESSION
If two or more series are individually integrated (in the
time series sense) but some linear combination of them
has a lower order of integration, then the series are said to
be co integrated. Call open interest and the contract volume
of its associated with the put option move through time.
Testing the hypothesis that there is a statistically
significant connection between the call option and the put
option is done by testing for the existence of a co integrated
combination of the two series.
Table 2 : Cointegrating Regression - OLS, using
observations 2014:04-2015:03 (T = 12) Dependent
variable: Call Open Interest
Coefficient std.
error t-ratio p-value
Const −8783.55 62216.3 −0.1412 0.8912
Call
volume 19.2661 9.38306 2.053 0.0741 *
Put open int
−0.0467705 0.15307 −0.3056 0.7677
Put volume
25.9381 24.0036 1.081 0.3114
* 1 per cent significance level
Mean dependent var
129556 S.D. dependent var
53084.3
Sum squared resid
1.62 S.E. of regression
44992.9
R-squared 0.477 Adjusted R-squared
0.281
Log-likelihood −143.16 Akaike criterion 294.33
Schwarz criterion
296.27 Hannan-Quinn 293.61
rho −0.2159 Durbin-Watson 2.277
An examination of the results of statistical analysis reveals
that both the open interest and volume based predictors
are significant explanatory variables for estimating the
behaviour of trader in the option contract. From the table 2
it is clear that p value is greater for the variable put open
interest. Moreover, the adjusted r- square is lower
comparing to the r- square which indicates lower
correlation effect in the market. Such incidence cause a
dramatic effect on the call option market, moreover
influence the nature of trading.
Table 3 : Cointegrating regression - OLS, using
observations 2014:04-2015:03 (T = 12)
Dependent variable: Put Open Interest
coefficient std.
error t-ratio p-value
Const -246045 113564 -2.167 0.0621*
Call Open -0.246645 0.807209 -0.3056 0.7677
Call Volume
20.7054 25.6004 0.8088 0.4420
Put volume
145.899 28.6553 5.092 0.0009***
*95 per cent significance level *** 1 per cent significance level
Behavioural Impact of Traders in the Indian Option Market
( 31 )
Mean dependent var
290976.5 S.D. dependent var
203814.0
Sum squared resid
8.5410 S.E. of regression
103322.3
R-squared 0.813097 Adjusted R-squared
0.743008
Log-likelihood −153.1418 Akaike criterion
314.2835
Schwarz criterion
316.2232 Hannan-Quinn 313.5654
rho 0.101888 Durbin-Watson 1.626753
Here, the p- value is greater for the variable call open
interest while taking put open interest as dependent
variable. But the put option traders behave in the opposite
direction, when the market shows an implied volatility. In
the put option contract, the open interest and trading
volume shows a parallel variation. Here comes the role of
protective put option contract. A protective put strategy is
usually employed when the options trader is still bullish
on a stock they already own but vary of uncertainties in
the near term. It is used as a means to protect unrealized
gains on shares from a previous purchase. There is
likelihood that the open interest based predictors may
increase even when the net open interest declines. This is
due to the fact that trader may be dealing in the call or put
options at higher trading volume that leads to increase in
these predictors. The reverse would happen in case of
increase in net open interest but the options are entered at
lower trading volume.
CONCLUSION
This paper takes advantage of a unique and detailed data
set of open interest and volume from CNX Nifty index
option listed on National Stock Exchange (NSE) to
investigate the option market behaviour of traders. The
changes in the behaviour of the traders are significantly
analysed from April 2014 to March 2015 in order to study
recent fluctuation in the derivative market. The evidence
summarizes that traders usually buy more calls to open
new positions after positive returns on underlying stocks
at horizons from one month to five years. Furthermore,
traders display trend-chasing behaviour in their purchases
of calls to open new positions. That is, all types of traders
purchase more calls to open new positions when the past
volume on the underlying stocks are higher. This fact
suggests that investor sentiment about stocks is established
over long horizons. For the most part, a similar relation
also holds between past volume and the selling of new
calls and the buying and selling of new puts.
Finally, the option trading volume is analysed to test the
co integration with open interest. It was found that the
volume of calls purchased to open new positions by least
sophisticated traders’ increases substantially during the
option market fluctuation from 2014 beginning onwards.
In fact, these traders increased their option volume on
growth stocks by a factor of four at the height of the
volatility but did not increase their activity in value stocks
at all. In addition, during the volatility period some traders
became much more sensitive to past volume changes and
thus exhibited much stronger trend-chasing behaviour
than in other periods. The more sophisticated type of
traders, on the other hand, did not increase their overall
activity in options during the volatility period, although
they did moderately increase their activity in call options
on growth companies and decrease their activity on value
companies. Despite the fact that the volatility had little
impact on the overall level of traders in the option activity,
it did significantly alter the trend chasing behaviour of
these traders. Specifically, their appetite for buying calls
on strongly performing stocks increased substantially. In
contrast to the other investors, the volatility was a non-
event for the firm proprietary traders in terms of their option
market activity. Finally, it is quite interesting that none of
the trader groups showed any substantial increase in put
purchases during the volatility period. Such purchases
would have been expected if short sales constraints in the
stock market were preventing investors from betting
against stocks which they viewed as overvalued. It appears
that even when appropriate securities are available,
investors have a hard time mustering the courage to bet
against stock market volatility.
REFERENCES
Anthony, J. (1988). The interrelation of stock and option
market trading volume data. Journal of Finance, 43,
949-964.
Conrad, J. (1989). The price effect of option introduction.
Journal of Finance, 44, 487-498.
Elfakhani, Said and Chaudhury, M. (1995). The Volatility
effect of option listing: Some Canadian evidence.
Quarterly Review of Economics and Finance, 35, 97 –
116.
Hamill, Philip A., Opong, K. and McGregor, P. (2002).
Equity option listing in the UK: A comparison of
market-based research methodologies. Journal of
Empirical Finance, 9, 91 – 108.
Raju G and Deepika Krishnan
( 32 )
Hayes, Samuel L. and Tannenbaum, M. E. (1979). The
impact of listed options on underlying shares.
Financial Management, Winter, 72 – 76.
Kim, Wi Saeng and Young, Colin M. (1991). The effect of
traded option introduction on shareholder wealth.
Journal of Financial Research, 14, 141 – 151.
Manaster, Steven and Rendleman, Richard J. (1982).
Option prices as predictors of equilibrium stock
prices. Journal of Finance, 37, 1043 – 1057.
Sahlstorm, P. (2001). Impact of option listings on risk and
return characteristics in Finland. International Review
of Financial Analysis, 10, 19 – 36.
Watt, W.H., Yadav, P. and Draper, P. (1992). The impact of
option listing on underlying stock returns: The UK
evidence. Journal of Business Finance and Accounting,
19, 485 – 503.
Vijh, Anand M. (1988). Potential biases from using only
trade prices of related securities on different
exchanges. Journal of Finance, 43, 1049-1055.
Vijh, Anand M. (1990). Liquidity of the CBOE equity
options. Journal of Finance, 45, 1157-1179.
Dr. Raju G
Associate Professor
Department of Commerce
Govt. College for Women
Thiruvananthapuram, Kerala
Email : [email protected]
Deepika Krishnan
Research Scholar
Faculty of Management Studies
University of Kerala, Thiruvananthapuram
Kerala
Email : [email protected]
Behavioural Impact of Traders in the Indian Option Market
( 33 )
PROLOGUE
India’s retail sector is also emerging as retail destination as evidenced by the size of US
$ 350 Billion positively influenced by factors viz., market size; Gross Domestic Product
(GDP); growth rate; personal income and rising number of aspirational consumers of
the middle class respectively. By the year 2030, the middle class of India is estimated to
reach figure of 91 Million households and by the year 2030, total number of 570 Million
Indians are expected to live in cities, nearly twice the current population of the USA.
India’s consumption level is estimated to reach figure of US $ 1.5 Trillion from the
current level of US $ 750 Billion by the year 2020 (Lynch, 2005). India is considered as
the youngest nation in the whole world and the global Indian households are expected
to reach level of 9.5 Million with their spending power of 14.1 Trillion rupees by the year
2025. This dramatic rise in spending power shall come mainly from young graduates
of India’s top colleges to command large earnings from Indian and foreign
multinationals and are emerging as ‘Ferociously Upwardly Mobile’ clearly evident of
showing importance of Indian youth in terms of its sheer size and market with unique
characteristics (Farrell and Beinhocker, 2007).
Key words:
Store Atmosphere,
Shopper, Patronage
Intention, Customer
Experience,
Customer Satisfaction
An Empirical Exploration of Influences of RetailStore Atmosphere on Shoppers’ Satisfaction in theBaroda City of Gujarat State
Parimal H. Vyas, Parag S. Shukla and Madhusudan N. Pandya
ABSTRACT
The consumer market of India has witnessed an unprecedented growth poised to emerge as one of the
fastest growing economies of the world economy due to demographic profile and rising income levels of
Indian consumers. The Indian retail market is expected to grow at a Cumulative Annual Growth Rate
[CAGR] of 12 per cent to reach a figure of US $ 900 Billion by the year 2017. The organized retail market
estimated currently at US $ 35 Billion is expected to reach a figure of US $ 90 Billion growing at CAGR
of 21 percent by the year 2025. India is expected to be ranked among the top 5 economies of the world from
the current 12th rank in terms of consumption by the year 2025. In such a competitive era the good and
interesting retail store atmosphere is certainly expected to act as a differentiator so as to influence
customer experiences resultant into a positive behavioural intention. The key objective of the empirical
research study was to study and examine the relationship between the selected factors of the store
atmosphere vis-a-vis customer satisfaction and its influences on customers or shoppers’ intention and
patronage behaviour for which 110 shoppers were conveniently selected from amongst different shopping
malls located in the Baroda City of the Gujarat State. The selected factors comprising of the store
atmosphere factors were viz., Display and Layout; Music; Lighting; Cleanliness; Visual Merchandising,
and Sales Staff respectively. The researchers have applied descriptive statistics, factor analysis, regression
analysis and the Structural Equation Model was also developed to explain and demonstrate the relationship
between selected factors of the store atmosphere and its influences on customers’ or shoppers’ satisfaction
to offer useful implications concerning formulation of retail strategies to enhance value driven offerings
to them by shopping malls in near future.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 34 )
REVIEW OF LITERATURE
An attempt has been made in this research paper to study
the satisfaction of the shoppers as the dependent variable
to be measured from shoppers which were drawn from
different shopping malls located in the Baroda city of the
State of Gujarat. The researchers have also outlined in brief
key findings of the earlier research studies concerning viz.,
retail sectors of India; factors comprising of the store
atmosphere; store patronage intentions and retail shoppers
patronage behaviour as follows.
Retail Sector of India
Organized retailing in most economies have typically
passed through four distinct phases viz., new retail entrant
driving growth; consumer demand organized formats;
retailer strengthening backend system, and retailers going
global. India is currently passing through the second phase
of evolution referred herewith as consumer demand
organized formats. India’s retail market shall reach figure
of US $ 850 Billion to be sub-divided into US $ 650 Billion
for traditional retail, and US$ 200 Billion for organized
retail by the year 2020. By the year 2015, more than 300
Million shoppers are likely to patronize organized retail
chains. Gupta (2007) had reflected on socio-demographic
characteristics of the retail sector of India. Mishra (2008)
had depicted that the economic growth, demographics,
increasing income, purchasing power and changing
Indian consumers are the various factors behind growth
of organized retail market in India.
Store Atmosphere and Shoppers’ Experience in Retailing
A pleasant store atmosphere is one of those elements which
are highly demanded as retailers find it difficult to gain
advantages on the basis of product, price, promotion and
place (Baker, Levy, & Grewal, 1992).Turley and Milliman
(2000) had argued that store atmosphere contributes to a
success or failure of business. Levy and Weitz (2009) had
stated that store atmosphere is an attribute that aims to
intensify the store environment with the combination of
different cues such as lighting, colour, music, and scent.
Milliman (1982) had categorized store atmosphere as a
term that is used to explain shoppers’ feeling towards the
shopping experience which cannot always be seen. Kotler
(1973-1974) had described the term atmospherics as the
design of store environment that stimulates shoppers’
emotions and ultimately affects their purchase behaviour.
Consumers will act emotionally and go along with
functional features through enjoying a pleasant store
atmosphere (Schmitt, 1999). The store atmosphere and the
services provided by retailers are two different variables
to cause the customer patronage intention (Baker et al.,
2002). Wakefield and Baker (1998) too had proved that
atmospheric stimuli have impact on the probability of
shoppers to stay in the store. Store atmosphere influences
shoppers’ perception towards the services provided to
them (Bitner, 1992). Store atmosphere creates
a fantastic and entertaining shopper experience that
directly affects their shopping behaviour (Kozinets et al.,
2002).
The empirical research for the influence of store
atmosphere on consumer behaviour is still limited (Areni
& Kim, 1994; Bitner, 1992; Turley & Milliman, 2000; Zeynep
& Nilgun, 2011). Areni and Kim (1994); Eroglu, Ellen, and
Machleit (1991) had identified that the scope of customers’
responses investigated in past studies is quite narrow.
Turley and Milliman (2000); Zeynep and Nilgun (2011)
had found that past researches have mainly focused to
study impact of one atmospheric cue at a time, and hence
ignored the joint consequence of other stimuli.
The investigation on the influence of various sensory cues
on consumers’ behaviour is still limited (Zeynep & Nilgun,
2011). Burnkrant et al (1982) had defined consumer
patronage intention as the combination of attitude,
normative beliefs and motivation towards the purchasing
behaviour. According to Donovan and Rossiter (1982),
retailers should possess the knowledge of customer
patronage intention to help them in building an
appropriate store atmosphere.
A well-defined store atmosphere will help to entice and
retain new customers and to create positive impact on the
customer patronage intention by minimizing cost, time,
and effort (Ishwar, Ruchi, & Zillur, 2010).
Macintosh and Lockshin (1997) had stated that patronage
intention gets reflected in shoppers’ willingness to shop
longer in store; reveal positive word-of-mouth for the store,
shop more and continue to repurchase in the future.
A brief review of selected factors of the store atmosphere
viz., display and layout, background music, cleanliness,
lighting, visual merchandising and sales staff has been
offered as follows.
Display and Layout
Store display and layout include fixtures, product
groupings, traffic flow, department locations, allocation
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 35 )
of floor space and allocations within department (Turley
& Milliman, 2000). The product display helps to highlight
the particular products and create a mood and message
that will positively affect shoppers’ behaviour (Kotler,
1974). It guides visual attention of customers on desirable
presented merchandise (Cahan & Robinson, 1984). The
design of store display and layout contributes to one fourth
of retail sales for a store (Mills, Paul, & Moorman, 1995).
Many shoppers also like to shop in the store which allows
them move easily (Titus & Everett, 1995).
Background Music
Genre, rhythm, or volume of music is manipulated mostly
by retailers to attract customers to their stores (Milliman,
1982, 1986; Smith, Patricia, & Ross, 1966; Yalch &
Spangenberg, 1993). According to Bruner (1990),
customers’ emotion can be well controlled by the
background music. Having suitable background music in
the store is able to reduce negative effect towards waiting
for services because it distracts the customers in the sense
that the length of waiting time becomes shorter (Hui, Dube,
& Chebat, 1997). Playing a familiar music will capture
consumers’ attention on the products or services in the
store because customers are emotionally connected with
the music played (Yalch & Spangenberg, 2000).
Lighting
According to James and Mehrabian (1976), lighting is the
main factor of store atmosphere that has greater impact on
consumer behaviour. According to Vaccaro, Yucetepe,
Baumgarten, and Lee (2008), brighter level of lighting is
considered as an important issue in retail atmosphere
because it enhances positive customer perception. When
the store is brighter, customers are more likely to observe
and touch the products in the store. Furthermore,
customers tend to be more active in asking detail
information of a product under a brighter lighting condition
rather than a dim condition (Vaccaro et al., 2008).
Cleanliness
Cleanliness improve store atmosphere (Akinyele, 2010).
Cleanliness of a store creates positive impression among
customers to make them stay longer and prefer to revisit
the store in the future (Gajanayake, Gajanayake, &
Surangi, 2011).
Carpenter and Moore (2006) had showed that cleanliness
is the most important store atmospheric cue that affects
customers to shop longer or visit. He had also described
that cleanliness is the appearance of the store because it
affects the store image and creates positive or negative
feeling among customers towards the store.
Visual Merchandising
Visual merchandising refers to the creative use of the
combination of products, atmosphere and spaces into a
motivating and engaging displays and arranging goods
and merchandise assortments within a store to improve
the layout and store appearance. Visual merchandising is
strategic arrangement that includes the activity of
enhancing the products presentation, support brands,
increase store traffic and sales and adds visual excitement
(Kouchekian & Gharibpoor, 2012). In order to have a good
visual merchandising, the retailer must establish a
different strategy such as create an enjoyment store
atmosphere and organize the merchandise in the store
effectively (Kim, 2013).
Sales Staff [Participating Factors]
Fournier (1998) had studied the relationship between
customers’ and salespersons’ as both are mysterious
unless customers clarify their needs to salespersons.
Customers form different expectations towards
salespersons based on the store atmosphere. In different
types of retail stores, salesperson will provide different
intentions and responsibilities towards their target
customers (Harris, Harris, & Baron, 2001). Appearance,
attitude and behaviour of the employees affect customers’
expectation towards the store (Winsted, 2000). Customers’
feel satisfied when the employees are able to provide
extraordinary services experience to them (Jones,
Beattyand, & Mothersbaugh, 2002).
Figure 1: The Conceptual Framework showing
Influence of Retail Atmosphere Variables on
Shoppers’
Store Atmosphere
Variables
-Display & Layout
-Cleanliness
-Lighting
-Background Music
- Visual Merchandising
- Sales Staff
Shoppers’
Cognitive
Responses
Perceived
Retail Store
Image
Customer Value Positive Word of
Mouth
Shopping Intentions
Patronage Intentions
Shoppers’
Satisfaction
Source: Adopted from the Model developed by Baker, 1987.
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 36 )
Baker (1987) had identified those environmental cues in a
store which are Ambient Factors (Temperature, Humidity,
Background Music, Scent and Cleanliness), Design Factors
(Colour, Decor, Texture, Style, Pattern, Layout, and
Accessories And Signage) and Social Factors in form of
influence of human presence in the store area.
RESEARCH METHODOLGY
It mainly included following.
A brief about the research study
The researchers had decided to undertake an empirical
research study based on descriptive research design to
study and examine the influences of selected factors of
store atmosphere on shoppers’ overall satisfaction using
structured-non disguised questionnaire to gather
responses of conveniently drawn 110 shoppers from
amongst different shopping malls located in the Baroda
city of the Gujarat State.
Objectives of the research study
The key objectives of the research study were as follows.
(i) To study and examine influence of selected factors
of store atmosphere on shoppers’ overall
satisfaction;
(ii) To assess influence of selected factors of store
atmosphere viz., display and layout; music; lighting;
cleanliness; visual merchandising and Sales Staff
Participation in delivery of overall satisfaction to
shoppers from the selected retail store, and
(iii) To evaluate influence of selected factors of store
atmosphere on shoppers’ purchase Intention,
purchase decision and patronage behaviour of
selected shoppers.
Key terms of the research study
The key terms of the research study has been described as
follows:
Store Atmosphere
According Kotler (1973), “The atmosphere of a place is
more influential than the product itself in the purchase
decision”. When a store features a panoramic atmosphere
plus with beautiful decoration, design, colour, lighting,
and also having convenient background music, it will
create a different experience to the customer.
Shopper
A shopper is an individual who is buying or shopping
things from a shop or a number of shops. It is the dynamic
interaction of affect and cognition, behaviour and
environmental events by which human beings conduct
the exchange aspects of their lives. (Loudon and Della
Bitta, 2002).
Satisfaction
Kotler (2000) defined satisfaction as “a person’s feelings
of pleasure or disappointment resulting from comparing
a product’s perceived performance or outcome in relation
to his or her expectations”.
Patronage Intention
Patronage Behaviour has been defined as how individuals
choose an outlet for shopping. Store choice and patronage
patterns are based on consumer’s perceptions, images,
and attitudes formed from experiences, information, and
need (Haynes, Pipkin, Black, and Cloud, 1994).
Pre-Testing of a Structured Non-Disguised
Questionnaire
The structured-non disguised questionnaire was drafted
based on the review of literature. In the first phase, a
preliminary questionnaire was developed using multi-
item scales to measure impact of retail store atmosphere
on shoppers’ satisfaction. The structured questionnaire
was pre-tested by personally interviewing 20 shoppers.
Finally, during editing exercise, the problems that were
identified during the pre-testing were rectified. The
components in the structured questionnaire were fine-
tuned keeping in view the experiences gained while
interacting with shoppers and retailers.
Reliability of the Structured Non-disguised
Questionnaire
Reliability test was applied to know the strength of
relationship between the opinions of shoppers’ pertaining
to selected factor of store atmosphere and also to compare
its composite score. The Cronbach’s Alpha score of 0.604
to 0.847 had shown internal reliability of the scale and
reflected the degree of cohesiveness among the selected
items (Naresh K. Malhotra, 2007 and Jum C. Nunnally,
1981).
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 37 )
Table 1: Summary of Indicators and Reliability Alpha
Score
Sr. No.
Grouped Indicator Factors of Store Atmosphere
Cronbach’s Alpha Coefficient
01 Display and Layout in the retail store
0.847
02 Background Music being played in the retail store
0.771
03 Cleanliness in the retail store 0.779
04 Lighting in the retail store 0.604
05 Visual Merchandising in the retail store
0.672
06 Participant factors (Employees/Sales Staff) in the retail store.
0.811
Overall Reliability 0.716
DATA ANALYSIS AND INTERPRETATION
The collected primary data were tabulated, and analyzed
using SPSS 15.0.The researchers have used descriptive
statistics and applied correlation, multiple regression,
factor analysis to test selected formulated hypotheses and
developed Structural Equation Model (Using AMOS 18.0)
to offer findings and implications of this research study.
Profile of the Shoppers
The selected demographic profile of selected shoppers was
prepared which revealed that the male shoppers
constituted 39.1 percent (43) whereas the female shoppers
were 60.9 percent (67) in terms of gender. In case of age-
groups, it was found that 41 per cent of the shoppers were
found as belonging to the age group of Up to 25 Years,
followed by 40 percent in the age group of 40 and above.
However, the shoppers visiting the shopping mall were
found less in the age group of 26 to 40 years (18.2 per cent).
). The analysis of the educational qualifications revealed
that 39 percent shoppers were found as below graduation
followed by 34 percent were above graduation and 27
percent were found to be graduates. Considering the
Occupation of the selected shoppers, 36 percent of them
was students followed by 30 percent belonging to the
service class, and 19 percent were found as homemakers.
From the total number of shoppers, 50 Percent were found
as having a monthly income of Rs. 10,001 to 20,000
followed by 32 percent who were having a monthly income
of Below Rs. 10,000.
Table 2 : Profile of the Selected Shoppers
Sr. No.
Selected Background Variables of Selected
Shoppers
Number and Percentages of
Selected Shoppers
01 Gender Males 43 (39.1)
Females 67 (60.9) 02 Age Group Up to 25
Year 46 (41.8)
26 to 40 20 (18.2)
40 & Above 44 (40.0)
03 Educational Qualification
Below Graduation
43 (39.1)
Graduation 29 (26.4)
Above Graduation
38 (34.5)
04 Occupation Student 40 (36.4)
Service 34 (30.9)
Business 15 (13.6)
Homemaker 21 (19.1)
05 Monthly Family Income
Below Rs. 10,000
36 (32.7)
Rs. 10,001 to 20,000
50 (45.5)
Above 20,001
24 (21.8)
Shoppers preferred retail store in the Baroda City
The most preferred shopping destination of the shoppers’
in the city of Baroda is Hyper city [In-Orbit] having the
highest mean of 4.81 followed by Spencer’s having mean
score of 3.88; Big-Bazaar was found as having mean score
of 3.61; At-Home had received the mean score of 3.48 and
D-mart was having mean score of 3.37 respectively.
Table 3 : Selected Shoppers’ Preferred Retail Store in
the Baroda City
Name of the Preferred Retail Store
Mean Score
Name of the Preferred Retail Store
Mean Score
Hyper City [In-Orbit] 4.81
Reliance Market 3.28
Spencer's 3.88 Reliance Fresh 3.20
Big-Bazaar 3.61 Croma 3.15
At Home 3.48 Aditya Birla More Stores 3.02
D-Mart 3.37 Baroda Central 2.91
Bansal Stores 3.33 Centre Square Mall 2.34
Vishal Mega Mart 3.29
Seven Seas Mall 2.31
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 38 )
Shoppers Frequency of Visits to their Preferred Retail
Store for Shopping:
The total 110 shoppers were administered through the
questionnaires who had visited the retail store for
shooping. 44 percent of the shoppers’ preferred to visit
retail store at least once in a week for shopping to their
preferred shopping destination, 12 percent of the
shoppers’ visited once in a month, and 12 percent in once
in two months. The remaining 32 percent of shoppers were
found as visiting retail store so often.
Table 4 : Selected Shoppers’ Frequency of Visits to
their Preferred Retail Store for Shopping in the Baroda
City
Frequency of Visit to the Retail Store
No. of Shoppers Percentages
At least Once in a Week
49 44.5
At least Once in a Month
13 11.8
At least Once in Two Months
13 11.8
Undecided 35 31.8
Total 110 100.0
Overall Satisfaction as reported by selected shoppers
68 percent of selected shoppers were found as highly
satisfied, 22 percent were found as satisfied and 10 percent
of them were found as highly dissatisfied. It means that
overall the selected shoppers were found to be happy with
the store atmosphere of their most preferred retail store.
The focus can be made to identify the causes of
dissatisfaction amongst those 10 percent shoppers to
suggest the necessary changes to be made to better
formulate appropriate promotional and marketing
strategies to provide a better shopping experience to them.
Table 5 : Selected Shoppers’ Overall Satisfaction
Selected Criteria No. of Shoppers Percentages
Highly Dissatisfied 11 10.0
Satisfied 24 21.8
Highly Satisfied 75 68.2
Total 110 100.0
The results of application of factor analysis
The factor analysis was applied to identify the underlying
dimensions within each selected criteria related to store
atmosphere. The researchers had considered six factors of
store atmosphere viz., display and layout, background
music, Cleanliness, lighting, visual merchandising and
sales staff of the retail store to study and measure overall
satisfaction o selected shoppers in the Baroda City of the
Gujarat State. The factor loadings were used to measure
correlation between criteria and the factors. A factor
loading close to 1 indicates a strong correlation between a
criteria and factor, while a loading closer to zero indicated
weak correlation. The factors were rotated with the used
of Varimax with Kaiser Normalization Rotation Method.
Principal Component Analysis (PCA) method was used
for factor extraction and considered only those factors for
interpretation purpose whose values were greater than
0.7.
The results of the findings of the factor analysis are
presented as follows.
Result of KMO and Bartlett’s Test and Communalities
Score
To measure the suitability of the data for factor analysis
the adequacy of the data was evaluated on the basis of the
results of Kaiser-Meyaer-Oklin (KMO) measures of
sampling adequacy and Bartlett’s Test of Spehericity
(Homogeneity of Variance). The results showed that the
KMO measure of sampling adequacy was between the
ranges of 0.592 to 0.758 so the data was fit for conducting
the factor analysis.
Similarly, Bartlett’s Test of Spehericity (0.00) was significant
(p<.05) which too revealed that sufficient correlation
existed between the criteria to proceed with the application
of factor analysis
Table 6 : KMO and Bartlett’s Test of Sphericity And
Sampling Adequacy
Sr. No.
Selected Factor of the Store
Atmosphere
Kaiser-Meyer-Olkin Measure of
Sampling Adequacy
Bartlett's Test of
Sphericity
01 Display and Layout
0.592 0.000
02 Background Music
0.719 0.000
03 Cleanliness 0.659 0.000
04 Lighting 0.642 0.000
05 Visual Merchandising
0.659 0.000
06 Sales Staff [Participating Factors]
0.758 0.000
Considering the results of factor Analysis it was observed
that all the extracted communalities were acceptable for
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 39 )
Table 7 : Total Variance Explained for the Factor of Display and Layout in the Retail Store
Component
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared
Loadings
Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% Total % of
Variance Cumulative
%
1 3.471 57.851 57.851 3.471 57.851 57.851 3.015 50.251 50.251
2 1.364 22.726 80.577 1.364 22.726 80.577 1.820 30.326 80.577
Extraction Method: Principal Component Analysis
Table 8: Communalities and Rotated Component Matrix of Display and Layout in the Retail Store
Selected Factor of the Store Atmosphere and Items
Communalities Extraction
Component
1 2
Display and Layout - There is sufficient space to move around in the retail store
0.920 0.956 0.080
Display and Layout - The information displayed on the shelves in the store is clear and makes me comfortable to shop in the retail store
0.859 0.925 0.052
Display and Layout - The display and layout of the store helps me in taking quick buying decisions
0.740 0.823 0.251
Display and Layout - The well organized display of the products allows me to easily identify the location of products for shopping
0.592 0.683 0.354
Display and Layout - The store layout is attractive and eye-catching. 0.920 0.031 0.959
Display and Layout - The merchandise presentation in the store is good
0.803 0.316 0.839
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.
Table 9: Total Variance Explained for the Factor of Background Music played in the Retail Store
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total % of Variance
Cumulative % Total
% of Variance
Cumulative % Total
% of Variance
Cumulative %
1 3.036 60.722 60.722 3.036 60.722 60.722 2.738 54.764 54.764
2 1.236 24.713 85.436 1.236 24.713 85.436 1.534 30.672 85.436
Extraction Method: Principal Component Analysis
Table 10 : Communalities and Rotated Component Matrix of Background Music Played in the Retail Store
Selected Factor of the Store Atmosphere and Items
Communalities Extraction
Component
1 2
Background Music - The background music played in the store creates a pleasing environment for shopping in the retail store
0.842 0.911 0.114
Background Music - The background music being played in the retail store increases my interest for shopping in the retail store
0.735 0.265 0.816
Background - The volume of the background music is sufficient enough
0.800 0.031 0.894
Background Music - The background music being played in the retail store makes me stay longer in the store
0.941 0.953 0.179
Background Music - The background music being played in the retail store makes my shopping experience pleasant and enjoyable
0.953 0.964 0.156
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization
a Rotation converged in 3 iterations
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 40 )
all the six selected factors and all criteria are fit for the
factor solution as their extraction values are large enough.
Factor loadings were used to measure correlation between
criteria and the factors (Please refer Table 08, 10, 12, 14,
16 and 18).
Results of Display and Layout Factor
Total Variance Explained for the Factor of Display and
Layout
The total variance of display and layout factor, the first
two components (factor) in the initial solution have an
Eigen values over 1, and it accounted for about 80 per cent
of the observed variations considering the opinion on
display and layout criteria for evaluating the store
atmosphere of the store preferred by the shoppers [Please
Refer Table 7].
Rotated Component Matrix of Display and Layout in the
Retail Store
It became clear that in the factor of Display and Layout
where the three construct statements viz., There is
sufficient space to move around in the retail store; the
information displayed on the shelves in the store is clear
and makes me comfortable to shop in the retail store, and
The display and layout of the store helps me in taking
quick buying decisions were found as more correlated with
component 1. In the factor of Display and layout where
two construct statements viz., The store layout is attractive
and eye-catching and The merchandise presentation in
the store is good were found as more correlated with
component 2 [Please refer Table 8].
Results of Background Music Factor
Total Variance Explained for the Factor of Background
Music played:
In case of the total variance of selected factor in case of the
background music played in the retail store, it was found
that the first two components (factor) in the initial solution
have an Eigen values over 1, and it accounted for about 85
per cent of the observed variations considering the opinion
of shoppers’ on the criteria of background music played
in the retail store for evaluating the store atmosphere of
the store preferred by the shoppers [Please refer Table 9].
Rotated Component Matrix of Background Music played
in the Retail Store
In case of the factor of background Music played in the
retail store where the three construct statements viz., The
background music played in the store creates a pleasing
environment for shopping in the retail store; The
background music being played in the retail store makes
me stay longer in the store, and The background music
being played in the retail store makes my shopping
experience pleasant and enjoyable were found as more
correlated with component 1.
In case of Component 2 in the factor of Background music
where two construct statements viz., The background
music being played in the retail store increases my interest
for shopping in the retail store, and the volume of the
background music is sufficient enough were found as more
correlated with component 2 [Please refer Table 10].
Results of Cleanliness Factor
Total Variance Explained for the Factor of Cleanliness in
the Retail Store:
In case of this factor, the total variance of selected factor in
case of the cleanliness in the retail store, it was found that
the first two components (factor) in the initial solution
have an Eigen values over 1, and it accounted for about 79
per cent of the observed variations considering the opinion
of shoppers’ on the factor of cleanliness maintained in the
retail store for evaluating the store atmosphere of the store
preferred by the shoppers [Please refer Table 11].
Rotated Component Matrix of the Factor for Cleanliness
in the Retail Store
In case of this factor of cleanliness in the retail store where
the three construct statements viz. The neatness of the retail
store makes me feel comfortable to shop in the retail store;
The products sold in the retail store are tidy and without
any damage, and The shelves in the retail store are neat
and arranged properly were found as more correlated with
component 1. In case of Component 2 in the factor of
cleanliness where one construct statement that is the floor
of the retail store is clean and tidy which makes me feel
better was found as more correlated with component 2
[Please refer Table 12].
Results of Lighting Factor
Total Variance Explained for the Factor of Lighting in
the Retail Store:
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 41 )
Table 11: Total Variance Explained for the Factor of Cleanliness in the Retail Store
Component Initial Eigenvalues
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total % of
Variance Cumulativ
e % Total % of
Variance Cumulative % Total
% of Variance
Cumulative %
1 2.904 58.087 58.087 2.904 58.087 58.087 2.873 57.460 57.460
2 1.053 21.052 79.139 1.053 21.052 79.139 1.084 21.678 79.139
Extraction Method: Principal Component Analysis
Table 12: Communalities and Rotated Component Matrix of the Factor for Cleanliness in the Retail Store
Selected Factor of the Store Atmosphere and Items
Communalities Extraction
Component
1 2
Cleanliness - The neatness of the retail store makes me feel comfortable to shop in the retail store
0.953 0.975 0.051
Cleanliness - The products sold in the retail store are tidy and without any damage
0.944
0.968 0.080
Cleanliness - The shelves in the retail store are neat and arranged properly
0.910 0.953 0.039
Cleanliness - The floor of the retail store is clean and tidy which makes me feel better
0.730
0.023 0.854
Cleanliness - The cleanliness of the retail store motivates me to visit the retail store again and again
0.420 0.328 -0.559
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.
Table 13: Total Variance Explained for the Factor of Lighting in the Retail Store
Component
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared
Loadings
Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% 1 2.153 43.067 43.067 2.153 43.067 43.067 1.870 37.402 37.402
2 1.010 20.206 63.273 1.010 20.206 63.273 1.294 25.872 63.273
Extraction Method: Principal Component Analysis.
Table 14: Communalities and Rotated Component Matrix for the Factor of Lighting in the Retail Store
Selected Factor of the Store Atmosphere and Items Communalities
Extraction Component
1 2
Lighting - The combination of lighting used is matching with the layout of the Store makes me feel good and comfortable to shop in the retail store
0.879 0.442 0.827
Lighting - The lighting of the store is sufficient to check the products
0.662 0.773 0.254
Lighting - The lighting used in the store adds to its attractiveness 0.745 0.831 -0.232
Lighting - The intensity of lighting creates a comfortable shopping environment in the store
0.638 0.682 -0.415
Lighting - The lighting of the store positively affects my mood for shopping
0.240 0.452 -0.190
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 42 )
Table 15: Total Variance Explained for the Factor of Visual Merchandising
Component
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared
Loadings
Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% 1 2.437 48.736 48.736 2.437 48.736 48.736 2.045 40.894 40.894
2 1.017 20.337 69.073 1.017 20.337 69.073 1.409 28.179 69.073
Extraction Method: Principal Component Analysis.
Table 16: Communalities and Rotated Component Matrix for the Factor of Visual Merchandising in the Retail Store
Selected Factor of the Store Atmosphere and Items
Communalities Extraction
Component
1 2
Visual Merchandising - The Eye-Catching Window Displays in the retail store influence me to buy more
0.677 0.646 0.509
Visual Merchandising - The In-store communications and the Mannequin Displays influence my Buying Decisions in the retail store
0.779 0.868 -0.163
Visual Merchandising - The striking promotional signage attracts and motivates me to visit a particular segment in the retail store
0.840 0.901 -0.171
Visual Merchandising - The attractive decor of the store attracts me and makes comfortable to from the retail store
0.574 0.555 -0.516
Visual Merchandising - The Visual Merchandising in the retail store creates excitement and makes me comfortable to shop in the retail store
0.583 0.384 0.660
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations
Table 17: Total Variance Explained for the Factor of Sales Staff in the Retail Store
Component
Initial Eigenvalues Extraction Sums of Squared
Loadings Rotation Sums of Squared
Loadings
Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% Total % of
Variance Cumulative
% 1 3.302 55.025 55.025 3.302 55.025 55.025 2.470 41.172 41.172
2 1.090 18.165 73.191 1.090 18.165 73.191 1.921 32.018 73.191
Extraction Method: Principal Component Analysis
Table 18: Communalities and Rotated Component Matrix for the Factor of Sales Staff in the Retail Store
Selected Factor of the Store Atmosphere and Items
Communalities Extraction
Component
1 2
Sales Staff - The Appearance of the sales staff in the retail store creates a pleasing environment in the store
0.853 0.179 0.906
Sales Staff - The Politeness of the sales staff in the retail store creates an influential environment
0.788 0.195 0.866
Sales Staff - The friendly approach of the sales staff in the retail store creates a positive social environment
0.361 0.395 0.452
Sales Staff - The Reasonable number of shoppers in the retail store creates a cordial and a comfortable environment for me to shop
0.784 0.868 0.173
Sales Staff - The billing counter is not over-crowded 0.792 0.851 0.261
Sales Staff - The Supportive participation of the retail store staff makes me comfortable to shop in the retail store again and again
0.814 0.876 0.217
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 43 )
The first two components (factor) in the initial solution
have an Eigen values over 1, and it accounted for about 63
per cent of the observed variations in the opinion of
shoppers’ on the factor of Lighting in the retail store for
evaluating the store atmosphere of the store preferred by
the shoppers [Please refer Table 13].
Rotated Component Matrix for the criteria of Lighting in
the Retail Store
In the factor of lighting in the retail store where the three
construct statements viz.,The lighting of the store is
sufficient to check the products; The lighting used in the
store adds to its attractiveness, and The intensity of lighting
creates a comfortable shopping environment in the store
were found as more correlated with component 1. In case
of Component 2 in the factor of lighting where one construct
statement that is the combination of lighting used was
found as matching suiting with the layout of the Store
makes me feel good and comfortable to shop in the retail
store was found as more correlated with component 2
[Please refer Table 14].
Results of Visual Merchandising Factor
Total Variance Explained for the Factor of Visual
Merchandising:
The first two components (factor) in the initial solution
have an Eigen values over 1, and it accounted for about 69
per cent of the observed variations considering the opinion
of shoppers’ on the factor of visual merchandising
techniques used in the retail store for evaluating the store
atmosphere of the store preferred by the shoppers [Please
refer Table 15].
Rotated Component Matrix for the Factor of Visual
Merchandising in the Retail Store:
In case of the factor of visual merchandising techniques
used in the retail store where the three construct statements
viz., The striking promotional signage attracts and
motivates me to visit a particular segment in the retail store;
The In-store communications and the Mannequin
Displays influence my Buying Decisions in the retail store,
and The Eye-Catching Window Displays in the retail store
influence me to buy more were found as more correlated
with component 1. In case of Component 2 in the factor of
visual merchandising where construct statements viz., The
Visual Merchandising in the retail store creates excitement
and makes me comfortable to shop in the retail store and
The Visual Merchandising in the retail store creates
excitement and makes me comfortable to shop in the retail
store was found as more correlated with component 2
[Please refer Table 16].
Results of Sales Staff Participation Factor
Total Variance Explained for the Factor of Sales Staff in
the Retail Store:
The first two components (factor) in the initial solution
have an Eigen values over 1, and it accounted for about 73
per cent of the observed variations considering the opinion
of shoppers’ on the factor of sales staff and the
participating factors in the retail store for evaluating the
store atmosphere of the store preferred by the shoppers
[Please refer Table 17].
Rotated Component Matrix for the Factor of Sales Staff
in the Retail Store
In the factor of sales staff in the retail store where the three
construct statements viz., The reasonable number of
shoppers in the retail store creates a cordial and a
comfortable environment for me to shop; The Supportive
participation of the retail store staff makes me comfortable
to shop in the retail store again and again, and The billing
counter is not over-crowded were found as more correlated
with component 1. In case of Component 2 in the factor of
sales staff where construct statements viz.,The appearance
of the sales staff in the retail store creates a pleasing
environment in the store and The Politeness of the sales
staff in the retail store creates an influential environment
was found as more correlated with component 2 [Please
refer Table 18].
CORRELATION AND MULTIPLE REGRESSION
ANALYSIS
The results of the application of correlation and multiple
regressions are given as follows.
Key Hypothesis of the Research Study
There exist a significant relationship between selected factors of
store atmosphere viz., display and layout; music; lighting;
cleanliness; visual merchandising, and sales staff participant
factors vis-à-vis overall satisfaction of shoppers from the retail
store.
Pearson Correlation Analysis
In case of selected factor that is ‘Sales Staff Participant
Factors’ was found as having the strongest positive
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 44 )
Table 19: Pearson Correlation Analysis
Selected Factors The Overall Satisfaction
Pearson Correlation Sig. (1-tailed)
Display and Layout -0.126 0.094
Background Music -0.160(*) 0.048
Lighting 0.037 0.352
Cleanliness 0.071 0.230
Visual Merchandising 0.341(**) 0.000
Sales Staff 0.848(**) 0.000
Overall Satisfaction of Shoppers
1
* Correlation is significant at the 0.05 level (1-tailed). ** Correlation is significant at the 0.01 level (1-tailed).
Table 20: Summary of Partial Correlation
Control Variables
Background Music
Cleanliness
Visual Merchandisin
g Lightin
g
Sales
Staff
Display and
Layout
The Overall Satisfaction of Shoppers
Background Music
Correlation
1.000
Significance (2-tailed)
Cleanliness Correlation
0.017 1.000
Significance (2-tailed)
0.859
Visual Merchandising
Correlation -0.076 0.214 1.000
Significance (2-tailed)
0.433 0.025 .
Lighting Correlation
0.202 0.489 0.040 1.000
Significance (2-tailed)
0.035 0.000 0.676 .
Sales Staff Correlation
0.130 -0.324 0.034 -0.082 1.00
0
Significance (2-tailed)
0.178 0.001 0.726 0.396 .
Display and Layout
Correlation
0.284 -0.086 0.060 -0.048 0.13
3 1.000
Significance (2-tailed)
0.003 0.375 0.537 0.622 0.16
9 .
Table 21: Model Summary of Regression Analysis
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .873(a) .762 .748 .604
a Predictors: (Constant), Display and Layout, Visual Merchandising, Lighting, Sales Staff, Background Music, Cleanliness
b Dependent Variable: The Overall Satisfaction.
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 45 )
Table 22: Analysis of Variance (ANOVA) of Regression Model
Model Sum of Squares df Mean Square F Sig.
1 Regression 120.346 6 20.058 54.919 0.000(a)
Residual 37.618 103 .365
Total 157.964 109
a Predictors: (Constant), Display and Layout, Visual Merchandising, Lighting, Sales Staff, Background Music, Cleanliness
b Dependent Variable: The Overall Satisfaction
Table 23: Summary of Regression Coefficients
Model Unstandardized
Coefficients Standardized Coefficients t Sig.
B Std. Error Beta B Std. Error
1 (Constant) 4.745 1.267 3.746 0.000
Background Music (M) -0.236 0.161 -0.077 -1.472 0.144
Cleanliness (C) 0.204 0.073 0.163 2.795 0.006
Visual Merchandising (VM) 0.119 0.170 0.037 0.702 0.484
Lighting (L) -0.072 0.179 -0.023 -0.401 0.689
Sales Staff (SS) 2.099 0.128 0.847 16.366 0.000
Display and Layout (DL) -0.112 .098 -.058 -1.137 .258
A Dependent Variable: The Overall Satisfaction.
Table 24: Summary of Standardized Regression Weights based on SEM
Sr. No.
Purchase Intention / Decision
Satisfaction Store Patronage Post-Purchase Behaviour / Recommend Store to Others
The Selected Criteria which Reflects the Behavioural Intentions of Shoppers [Standardized Regression Weights based on SEM]
01 Sales Staff 0.72 Sales Staff 0.85 Sales Staff 0.74 Sales Staff 0.80
02 Cleanliness 0.50 Cleanliness 0.16 Cleanliness 0.12 Cleanliness 0.14
03 Background Music
0.35 Background Music
0.08 Background Music
0.08 Background Music
0.09
04 Display and Layout
0.19 Display and Layout
0.06 Lighting 0.07 Display and Layout
0.06
association with overall satisfaction of shoppers from the
retail store (r = 0.848), followed by the positive correlation
between Visual Merchandising and overall satisfaction of
shoppers (r = 0.341), cleanliness and overall satisfaction
of shoppers (r = 0.071), as well as Lighting and overall
satisfaction of shoppers (r = 0.71). In case of selected factors
that is ‘Background Music’ (r = -0.160) and ‘Display and
Layout’(r = -0.126) was found as having the negative
association with overall satisfaction of shoppers.
The p-values of three independent factors viz., Sales Staff
Participation, Visual Merchandising, a Background Music
were less than 0.05 indicated a significant relationship
with overall satisfaction of selected shoppers whereas p-
values of three independent factors viz., Cleanliness,
Lighting And Display and Layout were found as more
than 0.05 which indicated non-significant relationship
with overall satisfaction of selected shoppers [Please refer
Table 19].
Partial Correlation Between Selected Criteria
(Multicollinearity)
Interco relations among all independent factors of this
study were found as low because their coefficient values
were lower than 0.70. This means that none of the
independent factor can be removed from this analysis. As
such, all these factors can be used for further analysis in
multiple regression method [Please refer Table 20].
Multiple Regression Analysis
In order to determine the statistical significance of each
independent factor on the dependent variable an equation
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 46 )
was formed based on Multiple Regression Analysis as
follows.
Equation: Y = a + bX1 + cX2 + dX3 + eX4 + fX5 + h
[Where Y = the Value of the Shopper satisfaction; a = fixed-
equals the value of Y when the value X1, X2, X3, X4, X5 =
0; b, c, d, e, f = slope of regression line; X1= the value of
sales staff (SS) participation; X2 = the value of cleanliness;
X3 = the value of visual merchandising (VM); X4 = the
value of lighting; X5 = the value of display and layout; X6
= the value of music; and h = a random term associated
with each observation].
Regression Model Summary
R2 for this model was found as 0.762 which meant that
means that 76.2 per cent of the variation in the dependent
factor that is overall satisfaction of shoppers can be
explained by six independent factors viz., Sales Staff
Participant Factors, Music, Visual Merchandising, Display
and Layout, Lighting and Cleanliness respectively [Please
refer Table 21].
Analysis of Variance (ANOVA) of Regression Model
F value for this model was 54.919 with 0.000 significance
level. Thus, the overall regression model with these six
predictors (Sales Staff Participant Factors, Music, Visual
Merchandising, Display and Layout, Lighting and
Cleanliness) had worked well in explaining the variation
in overall satisfaction of selected shoppers with store
atmosphere [Please refer Table 22].
Summary of Regression Coefficients
An equation can be formed to determine the statistical
significance of each independent factor on the dependent
variable [Please refer Table 23].
R2 for this study was 0.762 which meant that 76.2 per cent
of the variation in the dependent variable can be explained
by five independent factors. The F value of this model was
54.919 with 0.000 significance level.
An equation was formed for this study as follows:
Equation:
CPI = 4.745 + 2.099 (SS) + 0.204(C) + 0.119 (VM) + -0.072
(L) + -0.112 (DL) -0.236 (M)
According to the linear equation of this study, Sales Staff
Participant Factors, Cleanliness, And Visual
Merchandising revealed a significant positive relationship
with overall satisfaction of selected shoppers with store
atmosphere whereas Lighting, Display and Layout and
the Background Music had significant negative
relationship with overall satisfaction of selected shoppers
with store atmosphere. Sales Staff Participant factor had
the highest impact on overall satisfaction of selected
shoppers with store atmosphere because every one unit
increases in Sales Staff participant Factors will increase
2.099 units of overall satisfaction of selected shoppers by
holding other independent factors constant. Then, it is
followed by Cleanliness (R = 0.204) and Visual
Merchandising (R = 0.119). Lighting with value of r = -
0.072, Display and Layout with a value of r = -0.112, and
Background Music with value of r = -0.236 had shown the
lowest impact on shoppers’ patronage intention because
every one unit increases in this will decrease 0.07, 0.011
and 0.23 units of overall satisfaction of selected shoppers
by holding other independent factors constant.Based on
this equation, Sales Staff Participant Factors, Cleanliness,
and Visual Merchandising were found as having a
significant positive relationship with overall satisfaction
of selected shoppers; whereas Lighting, Display and
Layout and Background Music were found as having
significant negative relationship with shoppers’ patronage
intention.
Figure 2 : SEM Showing Relationship Between
Selected Store Atmosphere Attributes and Shoppers’
Overall Reported Satisfaction as Experienced in
Shopping Mall
In figure 02, a simple regression model is presented where
one observed factor, the overall satisfaction from the
shopping experience in shopping mall is predicted as a
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 47 )
linear combination of the other six observed factors, viz.,
Display and Layout, Background Music, cleanliness,
Visual Merchandising, Lighting and Sales Staff. As with
nearly all empirical data, the prediction will not be perfect.
There are some other factors other than selected six factors
that also assumed to have an effect on overall satisfaction
of selected shoppers with factors of store atmosphere in
retail store for which the model assumes ‘1’ as
standardized regression weights which specifies that other
factors must have a weight of 1 in the prediction of overall
satisfaction with factors of store atmosphere in the retail
store. Each single-headed arrow represents regression
weight. The value shown against two sided arrows (0.22,
0.11, 0.91, 0.97, -0.19, 0.93, 0.28, -0.12, 0.27, 0.14, 0.10, 0.9
and 0.8) is the correlation between selected observed
factors. The values shown with single sided arrow (-0.02,
-0.10, 0.06, 0.07, 0.23, and 0.97) are standardized regression
weights. It means the overall satisfaction with factors of
store atmosphere in the retail store is influenced by Sales
staff participation (0.97) followed by Lighting (0.23), Visual
Merchandising (0.07) and Cleanliness in the Retail Store
(0.06).
Figure 03 : SEM Showing Relationship Between
Selected Store Atmospheres Attributes and Shoppers’
Positive Word of Mouth [Recommend the Store to
Others for Shoppping]
In figure 3, a simple regression model is presented where
one observed variable, the shoppers’ intention to
recommend the retail store to others for shopping [Positive
Word of Mouth] is predicted as a linear combination of the
other six observed factors, viz., Display and Layout,
Background Music, Cleanliness, Visual Merchandising,
Lighting and Sales Staff. The value shown against two
sided arrows (0.30, 0.01, 0.22, 0.05, -0.01, 0.31, 0.49, 0.11,
0.07, 0.19, 0.05, 0.04, 0.12, 0.01 and 0.09) is the correlation
between selected observed factors. The values shown with
single sided arrow (-0.06, -0.09, -0.14, 0.03, -0.05, and 0.80)
are standardized regression weights. It means the
shoppers’ intention to recommend the retail store for
shopping to others that is positive word-of-mouth is
influenced by Sales Staff (0.80) followed by Visual
Merchandising (0.03), Cleanliness (-0.14) and Background
Music (-0.09).
Figure 4 : SEM Showing Relationship Between
Selected Store Atmosphere Attributes and Shoppers’
Patronage Intention to shop from the same Retail Store
In figure 4, a simple regression model is presented where
one observed factor, the shoppers’ patronage Intention is
predicted as a linear combination of the other six observed
factors, viz., Display and Layout, Background Music,
Cleanliness, Visual Merchandising, Lighting and Sales
Staff. The value shown against two sided arrows (0.30,
0.01, 0.22, 0.05, -0.01, 0.31, 0.11, 0.49, 0.07, 0.19, 0.04, 0.05,
0.12, 0.01 and 0.09) is the correlation between selected
observed factors. The values shown with single sided
arrow (-0.06, -0.08, -0.12, 0.01, -0.07, and 0.74) are
standardized regression weights. It means the shoppers’
patronage intentions is influenced by Sales staff (0.80)
followed by Cleanliness (-0.12), Background Music (-0.08)
and Display and Layout (-0.06).
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 48 )
Figure 5 : SEM Showing Relationship Between
Selected Store Atmosphere Attributes and Shoppers’
Puchase Intentions/ Decision to shop.
In figure 5, a simple regression model is presented where
one observed factor, the shoppers’ purchase Intention/
decision is predicted as a linear combination of the other
six observed factors, viz., Display and Layout, Music,
Cleanliness, Visual Merchandising, Lighting and Sales
Staff. The value shown against two sided arrows (0.33, -
0.01, 0.22, 0.05, -0.12, 0.36, 0.24, 0.49, 0.09, 0.03, 0.19, 0.02,
0.12, 0.01, and 0.09) is the correlation between selected
observed factors.
The values shown with single sided arrow (0.19, 0.35, 0.50,
-0.06, 0.04, and 0.72) are standardized regression weights.
It means the shoppers’ purchase intentions/ decisons are
influenced by Sales Staff (0.72) followed by Cleanliness
(0.50), Background Music (0.35) and Display and Layout
(0.19).
Summary of Standardized Regression Weights based
on SEM
It becomes very clear from the finding of the research study
that the behavioural intensions of shoppers in Baroda City
considering shoppers’ purchase decision or overall
satisfaction from the retail store or store patronage or post
purchase behaviour is influenced by Sales Staff
Participation followed by Cleanliness as well as
Background Music in the store. The purchase decision of
the shoppers’ is also to some extent was found as
influenced by Display and Layout of the retail store. The
factor of Lighting in the retail store was found to exert less
influence on the decision of the selected shoppers’ to
purchase products from the retail stores.
DISCUSSIONS AND MANAGERIAL IMPLICATIONS
The key objective of this empirical research study was to
examine the influences of identified and selected factors
of the store atmosphere of the retail store on shoppers’
overall satisfaction, shopping decision, and store patronage
behaviour. Stores are offering their services in all the
countries in the world not specifically focusing on all the
products available in the market and different types of
retail stores provide different combination of various
stimuli of store atmosphere to support the overall business
of those stores. Hence, this study had focused on the retail
stores based in Baroda City of the Gujarat State considering
06 selected factors of store atmosphere to study and
examine its influence on shoppers’ overall satisfaction from
the retail stores in Baroda City of Gujarat State. The
Shoppers were found as having different expectations
on the selected factors of the store atmosphere which are
helpful in generating the practical implications discussed
as follows:
This research study is helpful in providing understanding
to the retailer about how far the current store atmosphere
is capable of providing a better shopping experience to
their shoppers. The study has yielded that the most
important factor of store atmosphere is the participation
of the sales staff in the retail store followed with the
cleanliness in the store, display and layout of the store,
lighting in the store, visual merchandising, and
background music. These factors of the retail store
atmosphere play a dominating role in determining the
overall satisfaction of shoppers, their shopping decision,
and store patronage behaviour respectively.
Considering the factor analysis in terms of the display
and layout of the store, the most important factor that plays
a vital role is the availability of sufficient space to move
around and browse the products, clear and visible
arrangement of products and services and display of
related information helps the shoppers to take purchase
decision very easily.
The existence of such a nicely designed store layout and
attractive visible display will not only provide good
experience to shoppers but also evoke and strengthen the
repurchase intention of the shoppers. The retailers will be
able to occupy a unique and distinct position in the mind
of the shoppers in competitive market conditions. The
display and layout of the store adds to the functional value
that motivates to shop from the particular store. The
information provided through sensible display not only
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 49 )
motivates the shopper but also enhances the perceived
experience and leads to the favourable behaviour towards
the retail store. So the addition to the functional value
through proper layout and display leads to a long term
effect on consumers’ perceptions. The background music
played in the retail store holds a lot of value for the
shoppers.
One important observation that was made during data
collection is that many shoppers’ were of the opinion that
at times the music played in the retail store sometime
cannot be heard due to the noise and low volume and thus
adds to the clutter in the retail store which creates an
unpleasant and noisy environment. Thus, we can infer
that the background music played in the retail store creates
a lighter environment that adds to the positive experience
of shoppers.
The retailers’ should focus on an appropriate amplification
of the music that can maintain a pleasing store atmosphere
on the shopper while s/he is in the retail store. It can also
be inferred that the background music can also result into
an increased footfalls in the retail store.
The retailers can create their own radio station and use it
as a most powerful marketing tool as the monotonous and
the clichéd background music result into loss of interest
on the part of shoppers’ which affects adversely to the
shoppers patronage intention.. Having own radio station
can creates a live environment for customer through more
entertaining latest music trends which support in
engaging the shopper during their store visit. Further,
having own radio station, retailers can promote their new
products and fresh arrivals, service packages, seasonal
promotion, events, and sponsorships.
We can infer that the criteria of cleanliness as maintained
in the retail store are very vital as it relates with creating
an ambient environment which strengthens the intention
of the shoppers by uplifting their mood to shop in the
retail store. In a cluttered store environment where the
product are shabby and not in good condition, the shopper
will evoke negative emotions. The neatness in the product
display on the shelves, clear and tidy arrangement of
products in the retail store shall not only increase the
feeling of comfort and well-being in the minds of the
shopper, but it will also help the retailers to maintain
shopper’s patronage by enhancing the perceived positive
store image.
One can understand that the good lighting combination
in the store neither too bright nor too dull influences the
shoppers’ interest for browsing and shopping as well as
create a comfortable atmosphere in shoppers’ mind. The
lighting can be used by the retailer to create an aesthetic
appeal and to induce attractiveness of the retail store.
The appropriate and adequate use of lighting proves to be
enhancing and illuminating as it creates the desired
appealing effects and highlight the arrangement of
products, displays, signages etc. in various situations. In
order to maintain the appropriate the adequate flow of
lighting the retailers can make use of different forms of
light such as lamps and light fixtures as well as natural
illumination by capturing light from the sun. The retailer
needs to understand that the Lighting in the store helps
the shoppers’ in the process of identifying the product,
provides comfort to shoppers, and improves the overall
visual quality of a retail store. The retailers who operate
with the specialty store formats; the lighting design reflects
the store’s image and possesses the potential to prove as
the most powerful tool and enhancing the overall image of
the store and a unique selling strategy [USP].
The modern day retailers’ should focus on lighting factor
as it has the potentiality and probability to dramatically
affect sales since lighting can increase the floor traffic, create
visual interest, bring effect to the colour of merchandise
and able to direct the customer for moving around and
create an interest in order to stay longer. The retailers can
use the different combinations of lighting strategy to attract
customer attention for achieving the specific target of
specific products as well as to reach to sell more number of
weaker brands.
Though the occasional use of different combination of
lighting the retailer can hide some portion of product
display to create a kind of curiosity so that the shoppers’
interest can be sought which further support in creating
and maintaining a distinctive store image. Thus, the
lighting as tool for creating store atmosphere is capable to
influence the shoppers’ perception, emotion, cosiness and
sustaining shopping experience and store image. Besides,
lighting has an impact on consumer’s cognition, value
orientation as well as purchase decision. It became evident
from the results of the factor analysis that the factor of
Visual merchandising too plays an important role in the
retail store through eye catching window displays,
mannequin display and attractive promotional signages
so as to enhance the product presentation which supports
and stimulates the store traffic and sales.
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 50 )
In order to create visual excitement among the shoppers’the retailers’ should focus on the visual merchandisingaspects through the better products presentation whichsupport weaker brands and increase store traffic. Effectiveuse of visual merchandising not only attracts customersbut arouses interest and compels the customers to staylonger in the retail store to search and identify moresuitable product which fulfil their needs. The retailers’should strategically use the Visual merchandisingtechniques to get pleasure from competitive edge and createimage of store’s personality in a ferociously competitiveretail setting.
It can be very easily inferred from the data analysis thatthe factors staff participant has the strongest positiveassociation with customer patronage intention. Thismeans that the shoppers’ in the city of Baroda considerparticipant factors/sales staff as the most importantdeterminant of their patronage intention. Hence, retailershave to focus more on providing training to staff for theiractive participation in order to build up sympatheticatmosphere in retail stores. It is very clear that the salesstaff and the various participating factors in the retail storeplay a very crucial role in determining the service qualityof the store. It also helps the retailer to not only occupy aunique position in the minds of the shoppers but also itcan work as a key differentiator in a competitive retailscenario. The retailers should ensure the availability ofdesired number of trained staff personnel in the retail storewhich creates a cordial and a comfortable environmentfor shopping.
The positive staff participation in selling processencourages the shoppers to visit the same retail store againand again as the better treatment of the staff membersenhances the credibility and reliability of the particularstore. Further, the good clientele group that is good crowdin the retail store also acts as a motivating factor for othershoppers to visit that particular retail store again andagain.
The adequate number of staff at the billing counter helpsin the fast checkout for the shopper which also adds to thespatial convenience of the store. The behaviour of the salesstaff and pleasing appearance facilitates the retail store tocreate long lasting, pleasant and memorable customerdelivery experience.
Based on correlation and multiple regression analysis, itcan be stated that there exist a negative relationshipbetween display and layout and overall shoppersatisfaction. It implies that every one unit increases indisplay and layout will affect adversely in terms of 0.11units of shopper satisfaction with the condition of otherindependent factors remain constant. It means that theretailer needs to do a detailed analysis considering the
attributes of display and layout.
Identification of those attributes which create a positiveatmosphere in the retail store viz., product organization,location of each department, store display window andshelves information is highly essential. The shoppers ofBaroda city have realized that a sufficient level of eachattribute for display and layout will provide themsatisfaction. But whenever display and layout in the storeis exceeding the level of acceptance among shoppers, theywill feel uncomfortable and it might adversely affect theirstore experience. To illustrate, too much shelvesinformation in the retail store for particular productcategory will confuse shoppers and may createuncomfortable store atmosphere when they visit the retailstore for shopping. In every retail store nowadays,predetermined type of the background music is beingplayed to take hold of shoppers’ attention using suitablerhythm, volume to build up a pleasant atmosphere in theretail stores. The research study conducted in Baroda cityhad showed that background music increases comfort andwillingness of shoppers to stay and or shop longer in thestore.
The retailers need to undertake an in depth research toidentify the most popular up to date trend of the type ofmusic that shoppers prefer as the type of music played inthe store has the potential to fetch different groups ofshoppers to the retail store.
Lighting in the retail store also affects customer experience,purchase decision, store patronage and patronagebehaviour of shoppers. In order to create a comfortableatmosphere for shoppers to shop in the retail store, thesufficient level of lighting in all the areas where productsare displayed as well as at all the corners of the retail storeis highly essential. The attention of shoppers can be luredusing different level and type of lighting so that the discountor any other promotional offer can be highlighted forspecific product or to make the display more unique usingspot light to grab shoppers’ attention on those products.Lighting provides better tangibility in the retail store andwould increase shoppers’ comfort and convenience in theretail store.
The proper use of visual merchandising techniques by theretailer will enable him for attractive presentation of thestore and its merchandise to the shoppers.
The retailer can do this by seamless yet discreet integrationof the store’s advertising, display, decoration, merchandisearrangement, special events by tie-ups, showroomcoordination, and merchandising departments in order tosell the goods and services offered by the store.
The retailers’ in the city of Baroda should also use visualmerchandising in appropraite proportion so as to remain
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 51 )
presentable and convincing to shoppers’ visiting theirretail stores. By maintaining a consistency in the use ofvisual merchandising tools the retailers can achieve thegoal of orderly arrangement of goods and able to winimpulse purchase behaviour from shoppers.
The cleanliness also plays important role in creating betterstore atmosphere along with other variables as clean andtidy atmosphere will add to shoppers’ comfort. Floor ofthe retail stores, product orderliness in respective shelvesare those obvious areas that are often considered byshoppers under the stores cleanliness. Hence, retailers mustalways ensure that their stores are in a cleaned regularlyand kept in tidy condition. Thus, cleanliness inhousekeeping in the retail store will satisfy the desire ofshoppers who have the quest for Search of hygienicenvironment for shopping.
The sales staff participation has the strongest positiveassociation with shoppers’ purchase decision, overallsatisfaction, store patronage and word of mouth. Hence,retailers have to put continual efforts in improving theparticipation of staff in order to build up favourable storeatmosphere through appearance and politeness ofemployees, ability of communication with shoppers andthe level of service quality offered in retail store consideringstore traffic. The retailers should constantly focus onmonitoring and control the employees’ behaviour in theretail store as it will positively influence shoppers’ buyingemotion and resulting satisfaction.
Appearance of sales staff includes clean, tidy uniformsand specifically with standardized uniforms createscredible and reliable outlooks for shoppers and should bea routine practice among store employees. The servingshopper in polite way will create higher shopper storepatronage and positive word of mouth. The retailers needto train their employees in the way they communicate withshoppers in order to attract and retain them.
FUTURE SCOPE OF THE RESEARCH STUDY
The shoppers’ shopping behaviour is found as powerfullyrelated to emotional reactions and behaviour despite ofthe possible fact that it might have been more likelyinfluenced by external factors, a blend of quantitative andqualitative research methods can be deployed by otherresearchers in future to validate the results and findingsof this research study. The researchers interested inconducting research in the area of store atmosphere canmake the use of the research methods used under suchresearch studies for other types of store formats andgenerate and generalise the different perceptions basedon the results of their study. To illustrate, the differentretail stores such as fashion retailing, electronic, luxuryretailing, and pharmaceutical retailing needs differentformats of retailing and can make the use of research forimprovement of store atmosphere. The research study can
also be undertaken considering type of retail store, type ofproduct category and type of retail shoppers to examinetheir overall satisfaction, customer experience, shoppingintention and patronage behaviour.
LIMITATIONS OF THE RESEARCH STUDY
This research study was restricted to selected stores locatedin Baroda city of Gujarat State and its results might not beapplicable in different places and findings of the researchstudy cannot be generalized as shoppers might carrydifferent set of perceptions for different retail stores owingto the different formats that they might visit for buyingdifferent products. The sample size of this survey wasrestricted to 110 shoppers could be small one and limitedand might fail to produce a highly reliable result.Furthermore, a few of open-ended type of questions shouldbe put into the questionnaire which is also the limitingfactor in this research study since it can provide morespecific and detail responses from the respondents and alot of remarkable findings can be discovered in the research.The inclusion of the open ended questions in thequestionnaire with the use of projective techniques wouldlead to originality in data analysis as it covers differentperspectives of shoppers’.
REFERENCES
Akinyele, S. T. (2010). Customer satisfaction and service
quality: customers re-patronage perspectives. Global
Journal of Management and Business Research, 10(6).
Areni, C. S., & Kim, D. (1994). The influence of in-store
lighting on consumers examination of merchandise
in a wine store. International Journal of Research in
Marketing, 11, PP.117-125.
Baker, J. (1987). Excitement at the mall: determinants and
effects on shopping response. Journal of Retailing,
74(4), PP. 515-539.
Baker, J., Parasuraman, A., Grewal, D., & Voss, G. B. (2002).
The influence of multiple store environment cues
on perceived merchandise value and patronage
intention. Journal of Marketing, 66(2), P. 120.
Bitner, M. J. (1992). Servicescapes: the impact of physical
surroundings on customers and employees. Journal
of Marketing, 56, PP.57-71.
Bolton & Drew. (1991), “Integrating Consumer Involvement
and Product Perceptions with Market Segmentation
and Positioning Strategies in retail,” The Journal of
Consumer Marketing, Vol.5, No.2, PP.49-58.
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 52 )
Bruner, G. C. (1990). Music, mood, and marketing. The
Journal of Marketing, 54(4), 94-104.
Burnkrant, R. E., & Page, J. T. J. (1982). An examination of
the convergent, discriminant and predictive validity
of Fishbeinsbehavioral intention model. Journal of
Marketing Research, 19(4), PP.550-561.
Cahan, L., & Robinson, J. (1984). A practical guide to visual
merchandising. New York: John Wiley and Sons, Inc.
Carpenter, J. M., & Moore, M. (2006). Consumer
demographics, store attributes, and retail format
choice in the US grocery market. International Journal
of Retail and Distribution Management, 34 (6), PP.434-
447.
Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere:
an experimental psychology approach. Journal of
Retailing, 58(1), PP.34-57.
Eroglu, S. A., Ellen, P. S., & Machleit, K. A. (1991).
Environmental cues in retailing: suggestions for a
research agenda. Presentation made at the
Symposium on Patronage Behaviour and Retail
Strategic Planning: Cutting Edge II, 1991, in press.
Farrell and Beinhocker (2010),Next big spenders: India
middle class http://www.mckinsey.com/insights/
m g i / i n _ t h e _ n e w s /
next_big_spenders_indian_middle_class
Fournier, S. (1998). Consumers and their brands: developing
relationship theory in consumer research. Journal of
Consumer Research, 24, PP.343-73.
Gajanayake, R., Gajanayake, S., & Surangi, H. A. K. N. S.
(2011). The impact of selected visual merchandising
techniques on patronage intentions in supermarkets.
Unpublished thesis, University of Kelaniya, Sri
Lanka.
Gupta, M. (2007). Brand Position of General Store from
Consumer’s Perspective- A Comparative Study on
Departmental Store and Traditional Shop. In the
Proceedings of the 2004 IPR Conference, Thapar
University, Patiala, PP.25-26.
Harris, K., Harris, R., & Baron, S. (2001). Customer
participation in retail service: lessons from Brecht.
International Journal of Retail & Distribution
Management, 29(8), 359-369.
Haynes, J. L., Pipkin, A. L., Black, W. C., & Cloud, R. M.
(1994). Application of a choice sets model to assess
patronage decision styles of high involvement
consumers. Clothing and Textiles Research Journal,
12(3), PP.22-31.
http://retail.about.com/od/glossary/g/atmosphere.htm,
accessed on 22/08/2015.
Hui, M. K., Dube, L., & Chebat, J. C. (1997). The impact of
music on consumers’ reactions to waiting for
services. Journal of Retailing, 73(1), PP. 87-104.
Ishwar, K., Ruchi, G., & Zillur, R. (2010). Influence of retail
atmospherics on customer value in an emerging
market condition. Journal of Customer Value, 4(1).
Jones, M. A., Beatty, S. E., & Mothersbaugh, D. V. (2002).
Why customers stay: measuring the underlining
dimensions of services switching costs and
managing their differential strategic outcomes.
Journal of Business Research, 55, PP.441-50.
Jum C. Nunnally (1981); “Psychometric Theory”; Tata
McGraw-Hill Publishing Ltd. New Delhi, 1981.
Kim, J. (2013). A Study on the Effect that Visual
Merchandising Design (V.M.D) in Store has on
Purchasing Products. International Journal of Smart
Home. 7(4). PP. 217-223
Kotler, P. (1973-1974). Atmospherics as a marketing tool.
Journal of Retailing, 49(4).
Kotler, P. (2000), Marketing Management. 10th edn. New
Jersey, Prentice-Hall.
Kouchekian, M., Gharibpoor, M. (2013). Investigation the
Relationship between Visual Merchandising and
Customer Buying Decision Case Study: Isfahan
Hypermarkets. International Journal of Academic
Research in Economics and Management Sciences. 1(2).
PP.268-279
Kozinets, R. V., Sherry, J. F., DeBerry-Spence, B., Duhachek,
A., Nuttavuthisit, K., & Storm, D. (2002). The med
flagship brand stores in the new millennium: theory,
practice, prospects. Journal of Retailing, 78(1), PP. 17-
19.
Levy, M., & Weitz, B. A. (2009). Retailing Management
(7th Ed.). New York: McGraw-Hill.
Loudon, David L. and Albert J. Della Bitta (1993), Consumer
Behaviour, Fourth edition, McGraw-Hill, P.341.
Lynch (2005), The Global Indian Shopper”, Journal of
Retailing, May/June PP. 15-23.
An Empirical Exploration of Influences of Retail Store Atmosphere on Shoppers’ Satisfaction in the Baroda City of Gujarat State
( 53 )
Macintosh, G., & Lockshin, L. S. (1997). Retail relationships
and store loyalty: a multi level perspective.
International Journal of Research in Marketing, 14(5),
PP. 487-97.
Malhotra, Naresh K., 2007. Marketing Research: An
Applied Orientation, New Jersey: Pearson
Education, Inc.
Mehrabian, A., & Russell, J. A. (1976). Environmental
variables in consumer research. Journal of Consumer
Research, 3, PP.62-63.
Milliman, R. E. (1982). Using background music to affect
the behaviour of supermarket shoppers. Journal of
Marketing, 46, PP.86-91.
Milliman, R. E. (1986). The influence of background music
on the behaviour of restaurant patrons. The Journal
of Consumer Research, 13(2), PP.286-289.
Mills, K. H., Paul, J. E., & Moorman, K. B. (1995). Apparel
visual merchandising (3rd ed.). Englewood Cliffs,
NJ: Prentice-Hall.
Mishra, S. (2008). New Retail Models in India: Strategic
Perspective Analysis. Journal of Marketing &
Communication, 4 (2), PP. 39-47.
Schmitt, B. (1999). Experiential marketing. Journal of
Marketing Management, 15, 53-67.
Smith, Patricia, & Ross, C. (1966). Arousal hypothesis and
the effect of music on Purchasing Behaviour. Journal
of Applied Psychology, 50, PP. 255-56.
Titus, P. A., & Everett, P. B. (1995). The consumer retail
search process: a conceptual model and research
agenda. Journal of the Academy of Marketing Science,
23(2), 106-119.
Turley, L. W., & Milliman, R. E. (2000). Atmospheric effects
on shopping behaviour a review of the experimental.
Journal of Business Research, 49, 193-211.
Vaccaro, V. L., Yucetepe, V., Torres-Baumgarten, G., & Lee,
M. (2008). The relationship of music-retail
consistency and atmospheric lighting on consumer
responses. Review of Business Research, 8 (5),
PP.214-221.
Wakefield, K. L., & Baker, J. (1998). Excitement at the mall:
determinants and effects on shopping response.
Journal of Retailing, 74(4), PP.515-539.
Winsted, K., F. (2000). Service behaviours that lead to
satisfied customers. European Journal of Marketing,
PP. 399-417.
Yalch, R. F., & Spangenberg, E. R. (1988). An environmental
psychological study of foreground and background
music as retail atmospheric factors. In: Walle A. W.,
editor. AMA Educators Conference Proceedings.
Chicago, IL: American Marketing Association,
PP.106-110.
Zeynep, E., & Nilgun, G. (2011). Congruence between
atmospheric cues and store image in fashion
retailing. Turkey: Izmir University of Economics.
Professor (Dr.) Parimal H. Vyas
Acting Vice Chancellor and Pro-vice Chancellor
The Maharaja Sayajirao University of Baroda &
Joint Professor Of Management Studies, Baroda
E-mail: [email protected]
Shri Parag Sunil Shukla
Assistant Professor of Commerce & Business Management
[Ces] and Research Scholar
Department Of Commerce & Business Management,
Faculty Of Commerce, Baroda
Email : [email protected]
Dr. Madhusudan N. Pandya
Assistant Professor Of Commerce & Business Management
Department Of Commerce & Business Management,
Faculty Of Commerce
Baroda, The M.s. University Of Baroda, Baroda
Email : [email protected]
Parimal H. Vyas, Parag S. Shukla, Madhusudan N. Pandya
( 54 )
INTRODUCTION
Meaning of E-Retailing
Retail is the process of selling the consumer goods and/or services to customers from a
permanent location i.e. a retail store in small quantities directly to the consumers to
earn a profit. When retailing takes place through internet that is the essence of Electronic
Retailing (e-retailing) or Internet Retailing (i-retailing).
Retailing may be distinguished as the sale of goods and services from producers/
manufacturers or businesses to the end-users. Retailing in simple term can be understood
as, selling of goods to consumers, usually in small quantities and not for resale. It is one
of the mainstays of economy of any country and in India, it accounts for approximate
10% of the GDP. Thus, the growth of the Indian economy is quiet dependent on the
growth of its retail sector. Organised online retail is a new prodigy in India and the
market is growing exponentially. With economic growth, resulting in rising per capita
income, bringing Indian masses into the consuming classes. The organised retail sector,
especially online retail is enticing more and more existing shoppers into its realm.
Compared to traditional retailing, organised online retail in India is highly irregular,
out of order and is at a budding stage.1
Internet has brought nearly the entire world just a click away from us. The number of
nuclear families is increasing and both husband and wife are working, as they have
less time to go to the market for purchasing every now and then. Some other reasons
like- shortage of time, traffic jams, late working hours, versatility of plastic money and
above all the approach of internet at the door step of whosoever desires it. Online
Key words
E-Retailing, Internet,
Online Shopping, India,
Assam
Opportunities and Challenges of E-Retailing inAssam: A Study with Special Reference to NalbariDistrict, Assam
Chandana Kashyap and Ashima Sharma Borah
ABSTRACT
In this era of Globalisation, Liberalisation and sophisticated technological and managerial measures, e-
retailing has emerged as the most convenient method of transaction for both the manufacturers/marketers
and consumers. E-retailing has taken the world into storm with its business advantages that has also
created threats for the physical retail stores. But the developing and underdeveloped countries of the
world like India is not being able to keep equal pace with the global velocity of acceptance and adoption of
e-retailing practice. And being one of the economically, technologically and industrially backward states
of the country as compared to other states, the researchers’ home state Assam lags far behind in this
aspect. This empirical study is conducted to find out the extent of acceptance of e-retailing by people of
various age groups and backgrounds in Assam; the general reasons behind acceptance of e-retailing by
the people of Assam and the important factors behind people’s lack of confidence on e-retailing in Assam.
The study has been conducted with special reference to Nalbari district of Assam. Questionnaires and
schedules were used in primary data collection. The results of the study revealed that e-retailing practice
is lagging far behind in the state and there are a number of serious reasons to it that needs attention.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 55 )
retailers have improved their service and are providing
more and more convenience to the customers. From
advance payment options they moved on to payment on
delivery. From fixed delivery timings they have moved on
to convenient delivery timings at the choice of the customer.
India has opened the doors for foreign direct investment
in retail. Still, the phenomena that world is fast shrinking
into a Global Village because of internet and other
communication mediums is not completely reflective in
the Indian context. While developed and fast developing
countries have understood the power of Internet, India
still has a long way to catch up. Some of the reasons behind
this lag are- slow change in the buying behaviour of
Indians, inability of on-line retail players to bend Indian
customers from offline mode to online retail channel, not
up to the mark online portals, lack of seriousness, issues
concerning security and transaction frauds, visitors’
probability of disappear in 15 seconds or less if they don’t
immediately find what they are looking for, multistep
process of shopping, increased time between initial visit
and purchase, customers wait for merchants’ best offer,
etc.2
Information technology has transformed the way
companies conduct business. Technology allows
businesses to automate manual operations and process
information much faster. Another major technological
advancement in the field of business is the Internet, which
has created new communication forms and other business
methods that companies use when processing financial
and business information. Internet has penetrated into
almost every field of modern business. The internet has
created an entire business function commonly referred to
as e-business or e-commerce. E-business represents the
use of internet and business technology in a company’s
operations. Most companies in the business environment
have implemented some form of Internet or business
technology into their business operations.3
The right internet strategy can play a significant part in
the successful marketing and sales of products. The internet
provides a platform to place advertisements with the
potential to reach millions of consumers around the world.
Several advertising options are available on the Web. A
marketer can place banner and text ads on popular
websites that are relevant to his/her particular business.
The internet also gives retailers an additional channel to
sell products. The application of internet in retail selling
is called E-Retailing. Some decades ago, a retail store
without a physical storefront was all but unheard of.
Today, one can buy almost anything one wants on the
internet by visiting a company’s website. This lets a
marketer sell more products without the cost of having to
rent out and stock additional retail floor space. The ability
to sell goods without the cost of a physical storefront is
especially helpful for entrepreneurs who want to keep start-
up costs low.4
E-retailing offers great advantages to both the consumers
and business organisations in the form of convenience,
time saving, better information, competitive pricing,
customisation of product, ease of searching through merely
a search engine instead of roaming around physical
markets, better customer service through electronic
interchange of messages, lowered capital cost to the retailer,
more value-added service, newer specialisation and niche
marketing, global reach of consumers, etc. However, despite
so much benefits e-retailing is offering to the world, e-
retailing practice faces some serious disadvantages too.
Those are- lack of knowledge, awareness and interest in e-
retailing practice; remoteness of some areas that are costly
and difficult to access by the e-retailers; cost of
warehousing goods, dealing with returns and staffing for
these tasks; increase of cyber crimes while e-retailing; cost
of planning, designing, creating, hosting, securing and
maintaining a professional e-commerce website; difficulty
to establish a trusted brand name, especially without a
tangible store; etc.
OBJECTIVES OF THE STUDY
• To find out the extent of acceptance of e-retailing by
people of various age groups and backgrounds in
Assam;
• To find out the reasons behind acceptance of e-
retailing by the people of Assam;
• To find out the prime factors behind people’s lack of
confidence on e-retailing in Assam.
Rationale of the study
Indian economy was liberalised on 24th July, 1991 as part
of bailout deal with the International Monetary Fund to
overcome the severe Balance of Payment crisis faced by
India at that time. As soon as the country border was
opened for trade, foreign direct investment and portfolio
investment as a result of liberalisation, the retail sector in
Chandana Kashyap, Ashima Sharma Borah
( 56 )
the country got a boost. Application of internet in the
marketing and selling process further added to the growing
trend in the country. Yet, as compared to the global
scenario, India is lagging behind in adopting and
practicing e-retailing. There are many factors responsible
for this backwardness. And Assam, being economically-
technologically not so developed as compared to other
parts in India, is perceived to have little idea about e-
retailing. But, here is the twist that in reality, the youth
section of Assam and in fact, the entire North-East India
has been emerging as a tremendous and highly promising
market for e-retailing- as reported by the CEOs of many
online retail marketers. Even then, a greater share of
population in Assam is still hesitant to adopt the e-retailing
practice. Here, in this empirical research, we are trying to
find out the extent of acceptance of e-retailing by people of
various age groups and backgrounds in Assam, the factors
behind acceptance of e-retailing by the people of Assam
and also factors behind people’s lack of confidence on e-
retailing in Assam. The study is conducted with special
reference to Nalbari district.
PROFILE OF NALBARI DISTRICT IN ASSAM:
Assam is a state of India situated in its North-East part.
Located at south of the eastern Himalayas, Assam
comprises the Brahmaputra Valley and the Barak Valley
with an area of 30,285 square miles (78,440 km2). Assam is
one of the eight states comprising the North-East India-
popularly called as the ‘Eight Sisters’ that include- Assam,
Arunachal Pradesh, Manipur, Mizoram, Nagaland,
Tripura, Meghalaya and Recently added- Sikkim.
Geographically Assam and these states are connected to
the rest of India via a 22 km strip of land in West Bengal
called the ‘Siliguri Corridor’ or ‘Chicken’s Neck’. Assam
shares international border with Bhutan and Bangladesh;
and culture, people and climate here is similar to that of
South-East Asia. Assam became a part of British India
after the British East India Company occupied the region
following the First Anglo-Burmese War of 1824–1826.
Before that period, our state was a sovereign country.
According to 2011 census, literacy rate of Assam is 73.18%,
where male literacy rate is 78.81% and that of female is
67.27%. The economy of Assam represents a unique
example of poverty amidst plenty. In spite of being richly
endowed with natural resources, the state lags behind the
rest of India in many aspects.
Nalbari is an administrative district in the state of Assam
in India, created on 14 August, 1985 when it was split
from former undivided Kamrup district. The district
headquarter is located at Nalbari. Nalbari district occupies
an area of 2,257 square kilometres (871 sq mi). It shares its
district boundaries with Kamrup District on the East, Baksa
District on the North, Barpeta District on the West and the
Mighty Brahmaputra River on its South. Nalbari is a
district where people from different religions, mainly
Hindus, Muslim, Christians, Jains and Animistic (tribal
religion). According to the 2011 census Nalbari district
has a population of 7,69,919. Nalbari has a sex ratio of 945
females for every 1000 males, and a literacy rate of 79.89%
with rural literacy rate 78.44% and urban rate 91.46%.
Male literacy is 85.58% consisting of Rural 84.38% and
Urban 95.24%. Female literacy is 73.85% consisting of
Rural 72.14% and Urban 87.48%. The occupational
distribution of the people in the district is not even. The
economy of the district is mainly agriculture-based. About
62.99% of the rural populations are cultivators and about
75.26% of the rural people depend on agriculture. A
relatively smaller share of the total population is
government and private sector employee and self
employed. From this statistics, the economic condition of
the district can be highlighted.
PRESENT TREND OF E-RETAILING IN INDIA
The developing countries like India are going through a
huge shift from old cultural and social era to 21st century
new edge where the developed countries have already
started taking the benefits of e-retailing for their routine
businesses. The citizens of developed countries have also
accepted this transformation. But India is still far from
this transformation.
In India, the accelerated growth in modern retail is
expected to continue for next few years. With consumer
demand and business potential, there is a rapid growth in
online retail outlets. India’s copious ‘Young’ population
and high domestic consumption have manifested
favourably to the growth of the sector. According to Schultz,
D.E. (1996) and others, the market of 21st century will be
dominated by multimedia and multi-channel, with
customers having a wide range of media and channel
options to obtain goods and services. The factors
responsible for the development of online retail sector in
India can be broadly summarized as:-
a) Liberalisation of the Indian economy has led to
opening up of online market for consumer goods
and has helped the Multinational Corporation like
e-bay.com and Amazon.com etc. to make significant
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 57 )
inroads into this vast consumer market by offering
a wide range of choices to the Indian consumers.
b) The Internet Revolution is making the Indian
consumer more accessible to growing influences of
domestic and foreign retail chains. As India
continues to get strongly integrated with the world
economy, riding the waves of globalisation, the
online retail sector is bound to take big leaps in years
to come.
c) There is a shift in Consumer Demand for foreign
brands.
d) Rising in Income and improvements in easy
accessibility are enlarging consumer markets and
accelerating the convergence of consumer tastes.
e) Availability of low-priced smart phones and 2G/
3G/4G networks has enabled internet access
everywhere, even in the rural areas.
f) Rise of the middle-class people who have less time
and are more prone to do everything on their smart
phones, even shopping, is enhancing e-retailing.
g) Free home delivery, deals, discounts, and offers of
such have given a boost to this industry.7
In 2014, nearly 75% (2.1 billion) of all internet users in the
world (2.8 billion) live in the top 20 countries. The
remaining 25% (0.7 billion) is distributed among the other
178 countries, each representing less than 1% of total
internet users. China, the country with largest share of
world internet users (642 million in 2014), represents
nearly 21.97% of total, and has more internet users than
the next three countries combined (United States, India,
and Japan) while India shares only 8.33% of world internet
users which is depicted in Annexure 4. Among the top 10
countries, India is the one with the highest yearly growth
rate of internet users (14%) but also with the lowest
penetration rate of 19.19%. China has internet penetration
rate of 46.03%. At the opposite end of the range, United
States, Germany, France, U.K., and Canada have the highest
penetration rate, over 80% of population in these countries
has an internet connection.
Scenario of E-retailing in India is depicted through the
following figure-
Figure 1: Total retail sales and retail e-commerce sales
in india 2013-2018
[Source: http://dazeinfo.com/wp-content/uploads/2015/01/
retail-Ecommerce-sales-in-India-2013-2018-e1420623335856.png]
In the above figure, we see that till 2015 the share of retail
e-commerce sales has not touched even 1% of the total
retail sales in the country, hence indicating the slow rate
of increase of e-commerce retailing or e-retailing in India.
But the rate is anticipated to increase continuously.
Retailing in India is one of the pillars of its economy and
accounts for about 22% of its GDP. The Indian retail market
is estimated to be US$ 500 billion and one of the top five
retail markets in the world by economic value. India is one
of the fastest growing retail markets in the world, with 1.2
billion people. With the increase in computer literacy rate,
vast availability of cheap smart phones, internet
penetration into the Indian retail market and change in
socio-economic-demographic conditions in the various
segments of Indian society, Indian retail industry is moving
into a new direction. This can be depicted through the
following figure-
Figure 2: Internet User Base in India 2003-2019
[Source: http://blog.ibsindia.org/wp-content/uploads/2015/
04/ecommerce-india.png]
Chandana Kashyap, Ashima Sharma Borah
( 58 )
The commodities that internet users in India buy online
are mainly- clothes, shoes, books, mobile phone, other
electrical and electronic equipments, films, music, ticket/
hotel booking, personal accessories, etc.
Figure 3: E-commerce Market Share of India 2010
[Source: Ankita Pahuja. E-commerce in India and the potential
competition issues with special reference to credit cards market in
India]
The internet has made it possible to conduct business-to-
consumer (B2C) transactions across an open network (Ford,
1998). Although the open network has many benefits, like
low investment costs, it also raises many concerns.
Currently the most important concerns of people with
respect to e-commerce and e-retailing are security, privacy
and consumer protection issues. These concerns have
resulted in the fact that the existing dimensions of e-
commerce and e-retailing are still smaller than expected.
(IDC Research, 2000)
Research has found that the formerly mentioned concerns
- privacy, security and consumer protection - can all be
reduced to consumers’ lack of trust in e-retailing (Dontje
and Olthof, 1999). Trust is central to any commercial
transaction, whether conducted in the conventional way
(i.e. in a retail outlet) or over the Internet (i.e. by means of a
web-site). This is because trust increases the probability of
(re)purchase.
E-RETAILING IN ASSAM
As per the news report published in Firstpost (2014, March
23), India’s North-East is quietly becoming one of the
fastest-growing markets for online retailers with an
increasing number of youngsters from the region logging
on to buy mobiles, accessories and much more. Portals
such as Myntra, Jabong and Snapdeal are finding good
traction for orders from the region as the number of
customers looking to buy the best brands at affordable
prices is on the rise.
The North Eastern states — Arunachal Pradesh, Assam,
Manipur, Meghalaya, Mizoram, Nagaland and Tripura
— generate about 8 percent of traffic and business for
Myntra and the company expects further growth in the
coming quarters, Lawania said, without disclosing
absolute numbers.
Jabong co-founder Praveen Sinha said that North-East is
doing really well in terms of acceptance (of online retail)
and the market potential is also very big. The taste for
fashion is very refined there and customers are trendy,
experimental and are ready to try out fresh arrivals.
For Myntra, Guwahati in Assam and Aizawl in Mizoram
are the two key markets, while there has been a steady
increase in the number of online shoppers from Dibrugarh,
Jorhat, Sibsagar and Tinsukia — all in Assam — in the
past few months. Electronic items such as mobile phones
and cameras are the biggest draws for Snapdeal from the
region, with robust demand for fashion and lifestyle items.
Flipkart generally gets demand for books, mobiles,
computers and accessories and footwear from non-metros.
Although customers find the online space good for value-
for-money purchases, the time taken for deliveries to the
North East remains a challenge. Despite the challenges,
online retailers are unanimous that their business in the
North East India will only grow, given the rising trend in
orders from the region. Even eyewear online shopping
portal Lenskart has seen good traction for its products
from the region. About 20 percent of their overall business
is reported to come from the North East plus West Bengal.
Besides offering a growing market for national or
international e-retailers, a growing number of local
entrepreneurs in Assam are stepping through the e-
commerce route to not only earn profit but also to promote
art, craft and literature of the Northeast. The trend has
become apparent in the past couple of years, with online
portals becoming an important medium for people to buy
and sell items such as traditional paintings, jewelry, home
décor, fabrics including T-shirts with fancy prints and
even regional language books. For last some years, the
indigenous entrepreneurs of Assam producing local
handicraft items of the region have started the practice of
e-retailing for efficient marketing and selling of their
products. These indigenous handicraft industries include
the bamboo industry, silk industry, bell and brass metal
industry, traditional and ethnic dresses, traditional
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 59 )
jewelry, Muga bags, pickles, handloom and handicrafts
products of Assam and lots more. North-East also
developed its first regional language e-book store in 2012.
Although literacy rate in Nalbari district is almost 80% as
stated in the profile, yet this educated population remains
considerably backward in computer literacy. The people
of middle age and beyond are generally seen not to be
much interested in learning and applying computer
technology for their day-to-day activities. Internet
penetration is experienced to be low in the district. Due to
very low internet access and usage, people often are
deprived of almost all the benefits of internet. The practice
of internet in acquiring knowledge regarding school/
college curriculum, monetary transactions, bill payments,
online shopping, etc. is slightly high in the town areas
only and very low in village areas. Lack of or slow network
facility, lack of e-retail delivery facility to the district, lack
of awareness, knowledge and interest are marked as the
main factors behind this. Hardly two or three e-retailing
marketers offer delivery service to the district headquarter,
that too with some days delay. Besides, it is seen that the
youngsters who have access to internet, use internet
primarily for social networking sites, songs download,
etc. But in recent years, a growing trend of internet usage
for knowledge acquiring and e-retailing too has been
noticed. But the e-retail product delivery service is not
satisfactory into the district. This may be due to the
remoteness of the places and distance from Guwahati city.
Dimensions for analysing e-retailing in Assam under
study:
The dimensions on the basis of which E-Retailing in Assam
is measured and analysed in the present study, are
mentioned below-
• Convenience and Time factor
• Better pricing
• Wider selection due to variety
• Ease of comparison
• Avoidance of crowd in physical retail shops
• Shopping related other expenses
• Delivery
• Payment Security
• Price
• Quality
• Own taste and preference
• Easy return
• Product Presentation
These dimensions are studied under different titles through
the questionnaires/schedules.
REVIEW OF LITERATURE
In their study, Steve Burt and Leigh Sparks (2003) drew
three conclusions. First, the largest retailers are now
pursuing internet-enabled advantages and cost reductions
in operations, which could translate to an enhanced
competitive position in process, structure and relationship
terms. Secondly, consumer reactions to the new real and
virtual offers will be fundamental to their success and
failure, but yet consumer reactions are not fully
understood. Thirdly, existing retail floor space will need
enhancement in quality and presentation if it is to continue
to provide retail functions.
Khalid W. Alrawi and Khaled A. Sabry (2009) of UAE
reviews and examines some of the problems that e-
commerce faces through looking at internal and external
factors. The review shows that there is great potential for
e-commerce in the Gulf region that needs attention from
different disciplines and sectors. The study concluded with
a discussion on the possible factors that may contribute to
e-commerce success in the region, including but not limited
to government support, trust-related issues, Information
and Communications Technology (ICT) infrastructure and
Information Technology (IT) skills development.
In their study, Neil F. Doherty and Fiona Ellis-Chadwick
(2010) attempted to present a holistic and critical review
of the early predictions, with regard to the uptake and
impact of Internet retailing; critically reappraise these
claims in light of current trends in Internet retailing; and
explore where e-tailing may be heading in the coming
years. However, it was found that many of the original
predictions, made at the dawn of the Internet era, have not
become a reality: retailers aren’t cannibalising their own
custom, virtual merchants aren’t dominating the market-
place, and the high-street hasn’t, as yet, been put out of
business.
B. Kusuma, N. Durga Prasad, M. Srinivasa Rao (2013)
conducted a study with the objectives of checking the
growth and development of organised retail industry in
India, knowing the major players of organised retailers
and customer services provided by the retailers, knowing
the challenges faced by the organised retail sector in India
and making some suggestions to overcome the challenges
of organised retail sector. They found that Retail in India
is most dynamic industry and represents a huge
Chandana Kashyap, Ashima Sharma Borah
( 60 )
opportunity for domestic and international retailers.
Modern retailing is not a problem to traditional stores as
most of the consumers said that they never stopped visiting
kirana stores. They strongly agreed that coexistence of both
is required. But their frequency of going to kirana store is
reduced.
In his study, Bhavya Malhotra (2014) found that low
internet penetration in India; Indian customers’ high rate
of product return after online purchase; Cash on Delivery
as the preferred payment mode; high failure rate of payment
gateways and fewer use of smart phones- are the major
challenges to be faced by e-retailers in India. Since majority
of the online buyers in India are first time users of this
service, so the rate of product return by online shoppers
after purchase is higher here. Product returns become
expensive for e-business companies, as reverse logistics
presents unique challenges. This becomes all the more
complex in cross border e-business. Besides, people in
India in general, have low trust on online transactions.
But unlike electronic payments, manual cash collection is
painstaking, risky, and expensive for the e-marketers.
Again, e-business companies using Indian payment
gateways are losing out on business, as several customers
do not attempt making payment again after a transaction
fails. Also, due to fact that though the total number of
mobile phone users in India is very high, yet a significant
majority still use low-tech feature phones, and not smart
phones. As a result this consumer group is unable to make
e-business purchases on the move.
In their research work, Monami Banerjee and Dr.
Neelotpaul Banerjee (2012) found that in India, consumers
who purchase online are mostly young people comprising
of students and people in services within the age group of
21-40 years. The study also indicates that most of the
consumers who shop online have a graduate or post
graduate degree and financially well off. The majority of
the consumers use internet every day, and spent around
1-2 hours per internet session. The main purpose of using
the internet is for communication followed by retrieving
information. The revealed that marketer’s integrity is
considered to be the most important factor influencing
consumers’ online trust. The marketers in the virtual world
can gain the consumers’ confidence and faith by delivering
the products on time, undamaged and according to the
specifications mentioned by the customers, and sending
error free bill. Online merchants can enhance their integrity
by providing the consumers’ the option of tracking their
shipments, easy and quick ways of placing orders, and
multiple ways of payment. Marketer’s transparency in
terms of clear return policy, providing shipment cost
details and chat room to interact with other customers,
posting users’ testimonials, giving opportunity to lodge
grievance and feedback online, and having link to other
useful sites; security and privacy, and useful information
content in the web site; convenience in using the web site,
the web design, and word of mouth promotion; etc. play
very crucial roles in building consumers’ trust in e-tailers,
as evidenced in India.
RESEARCH METHODOLOGY
This research work is an empirical research and data were
collected from both primary and secondary sources. But
the study is mainly based on primary data.
The primary data were collected through questionnaires
and schedules consisting of exactly the same set of
questions. The questions included were primarily multiple
choice- respondents needing to tick the correct and proper
response. Some responses were collected in terms of Likert
5 Point Scale as follows—
1-Strongly Disagree, 2- Disagree to some extent, 3-
Neutral (Neither agree nor disagree), 4- Agree to some
extent, 5- Strongly Agree.
Besides, other related information was collected through
informal oral interview of the respondents.
Simple Random Sampling technique was adopted for
collecting primary data. The sample size was fixed at 50.
Besides primary data, some amount of secondary data
were collected from secondary sources viz. books on
Marketing Management, Retail Trade, Research
Methodology and Internet.
Limitations of the study
(i) The study is limited to the area of Nalbari district
only. And the findings of a district cannot represent
the findings of the entire state exactly. The position
and viewpoints of people in the city area definitely
vary from that of rural and backward regions.
Making a generalisation is tough.
(ii) The study is affected by time constraint.
(iii) The respondents already had some neutral or
negative perception about e-retailing.
(iv) The responses obtained from the respondents may
suffer from their personal biasness.
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 61 )
DATA ANALYSIS AND INTERPRETATION
The data collected through the questionnaire/schedule
and the secondary data as well, are analysed here and
firmly represented through various figures. The responses
to the Likert Scale questions were processed further by
calculating mean value of the responses to each item under
various titles and are depicted through figure 7 to figure 9.
Figure 4: Trust on Online Transaction in Assam
Figure 5: Frequency of Online Transaction in Assam
Figure 6: Preference Between Traditional and Online
Shopping in Assam
Figure 7: Factors Influencing Online Shopping in Assam
Figure 8: Importance of Following Criteria in Online
Transaction in Assam
Figure 9: Prime Factors Behind People’s Lack Of
Confidence On E-retailing In Assam
From the above nine figures, we can draw out the following
findings
• The retail e-commerce sales is till now much lower
that the total retail sales in India. The retail e-
commerce sales have not yet touched even 1% of the
total retail sales. But obviously, the percentage of
total retail sales is increasing significantly. (Figure 1)
• Internet penetration rate is increasing significantly
in India and it is increasing in a rising rate since
2009. (Figure 2)
Chandana Kashyap, Ashima Sharma Borah
( 62 )
People in Assam generally trust on online
transaction to some extent only and in case of some
products only. Besides, a significant share of people
here (32%) has never tried online transaction and
therefore do not have knowledge and strong
opinions about it. (Figure 4). It was also found that
the people who had never tried online transaction
in their life and who do not trust it at all were mainly
either under 18 years age group or above 60 years
age groups.
• It was seen that people here purchase products
online mainly on specific occasions. And no
respondent here was found to practice online
shopping more than once a week. This may be due
to significant product delivery problems to the area.
(Figure 5)
• People here generally do not prefer online shopping
forever. They mainly prefer traditional shopping.
(Figure 6)
• ‘Better pricing facilities’ influences the online
shopping in Assam which may be attributed to the
price conscious nature of the people in the middle
income group. Besides, ‘ease of comparison’ of items
online is found to be the least influencing factor,
which may be due to people’s lack of much expertise
in handling online shopping process, in general.
(Figure 7)
• People in Assam generally give most importance to
‘price’ followed by ‘quality’. (Figure 8)
• Inability to touch or see the product to be ordered i.e.
the intangibility factor and hence, lack of surety
about quality of an item online and problem of access
due to the distance from the prime places from where
the products are dispatched, stand as the main
challenges on the way of e-retailing with the people
of Nalbari district. The other factors as depicted in
the figure also play almost equal role. (Figure 9)
• The non-earning students who are of the age group
below 18 years, generally do not have strong
personal opinions and choices regarding
purchasing of items- be it traditional or online
purchase. Their purchasing decisions and ways are
more influenced by parents. Majority of them are
also seen giving importance to ‘show off’ factor
through online purchasing, rather than some solid
reasoning.
• Some of the house wives of 19-30 and 31-45 years
age groups and with medium or low level formal
education are seen to be interested in e-retailing
practice for shopping convenience and availability
of time, avoidance of chaos in physical retail stores
and some sort of prestige issue.
• Elderly persons are generally seen to be not at all
interested in e-retailing. Rather, they are found to
have negative attitude and perceptions towards the
concept. They strongly prefer the traditional
retailing mode.
• Most of the people are not seen to have enough
knowledge about how E-Retailing works. This
finding is irrespective of the persons’ level of
education or socio-economic background.
• Product delivery problem is found to be serious in
the region. Many e-retailers do not deliver products
to remote areas and in case of e-marketers who
deliver too, delay in product delivery is regular
problem here. Therefore people of this district are
often needed to order products to be delivered to the
address based on Guwahati- the nearest city or to
some office addresses in the district.
• Generally the elderly persons while pursuing e-
retailing service needs assistance in the entire
process of e-retailing from other persons, generally
some young person. They seldom can proceed on
their own.
SUGGESTION AND CONCLUSION
The empirical results clearly show that the e-retailing
practice is suffering from many challenges in Assam,
especially in the socio-culturally traditional cum reserved
and economically backward districts of the state.
Computer literacy rate and internet penetration rate is low
or medium here as compared to other states of the country.
Within the state too, the said rate is lower in rural and
semi-urban areas than the city and urban areas. In such a
state where literacy rate is only 73.18% i.e. not satisfactory
and people in mass are being deprived of primary
education opportunity, to attain a significant computer
literacy and internet penetration rate will take some time.
Now Assam and its seven neighbour states in the North-
East India are serving as emerging markets for e-retailing
and mainly the youth section of the society is adopting the
e-retailing practice. There is much to do by the e-marketers
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 63 )
to attract the other demographic and social segments
equally into e-retailing. The prime challenges that the e-
retailers face while conducting business in this region are-
low internet penetration, lack of awareness and knowledge
about the benefits of e-retailing, low accessibility to many
areas of the state due to the state’s critical location, delay
in product delivery, consumers’ fear of getting different
product or lower quality product than what was ordered,
consumers’ fear of personal information theft and inability
to touch, see and feel the product physically. Fear of getting
products other than the ordered product is not flimsy.
There have occurred many cases here till now where
consumers are delivered either some other product than
the ordered product or no product inside the package at
all! Cyber theft of personal information of consumers
resulting in severe problems to the consumer also has been
reported many times. Such incidents make people bear
extra costs in terms of time and effort but in addition, what
is more important is- such incidences shake consumer trust
on e-retailing or a particular e-marketer and severely
damage their goodwill and consumer base. The e-retailers
should work harder on these aspects to form a stronger
base for consumer trust and acceptability in the state. They
should also keep a close eye on the activities of their
product delivery channel members.
Since 1991, after economic reforms explicitly took place in
India as a result of opening-up of the economy with a view
to integrate itself with the global economy, the need to
facilitate international trade both through policy and
procedure reforms has become the foundation stone of
India’s trade and fiscal policies. Electronic commerce (e-
commerce) as part of the information technology revolution
became widely used in the world trade in general and
Indian economy in particular. With advancements in
technology, there have been changes in the methodology
for business transactions. As a symbol of globalisation, e-
commerce represents the cutting edge of success in this
digital age and it has changed and is still changing the
way business is conducted around the world. The
commercialisation of the internet has driven electronic
commerce to become one of the most capable channels for
inter-organisational business processes. And Electronic
Retailing is a significant part of this.16
As a part of the globalised and liberalized economy, we
can not stand apart from the global trend of technological
development, wide application of Information and
Communication Technology and application of internet
in almost every sphere of our lives. Therefore the
consumers and corporate houses in combination and
coordination should work towards a healthy overall
growth of the society. E-marketers by paying greater
attention to catering to the specific needs and difficulties
of different regions can ensure simultaneous all-round
growth for itself and the target markets.
REFERENCES
Books:
Dr. Singh Harjit (2009). Retail Management: A Global
Perspective (Text and Cases). New Delhi, S. Chand &
Company Ltd.
Bajaj Chetan (2011). Retail Management. Oxford University
Press, Reprint.
Chan Henry (2013). E-Commerce: Fundamentals and
Applications. John Wiley & Sons Inc., Reprint.
Websites:
Saha Shantau and Rathore Arvind (2014). An Overview
of Changing Trend of Traditional Retailing to i-Retail
in India. International Journal of Engineering, Business
and Enterprise Applications (IJEBEA), 8(2), 138-144.
Dwivedi Manish, Kumawat Mahesh & Verma Sanjeev
(2012). On-Line Retailing in India: Opportunities
and Challenges. International Journal of Engineering
and Management Sciences, 3(3), 336-338.
smallbusiness.chron.com/effect-internet-modern-businesses-
corporations
smallbusiness.chron.com › Advertising & Marketing › Sales
& Marketing
https://www.nibusinessinfo.co.uk/content/advantages-and-
disadvantages-online-retail
Dr. D. Y. Patil (2015). E-Retailing Issues in Developing
Countries like India. International Journal of
Management & Business Studies, 5(1), 58-61.
Saha Shantau and Rathore Arvind (2014). An Overview
of Changing Trend of Traditional Retailing to i-Retail
in India. International Journal of Engineering, Business
and Enterprise Applications (IJEBEA), 8(2), 138-144.
Chandana Kashyap, Ashima Sharma Borah
( 64 )
www.internetlivestats.com/internet-users/
You’ll never guess where e-commerce is booming in India.
Hint: Not metros. (2014, March 23). Firstpost.Business.
Steve Burt, Leigh Sparks (2003). E-commerce and the Retail
Process: A Review. Journal of Retailing and Consumer
Services, 10, 275–286.
Khalid W. Alrawi, Khaled A. Sabry (2009). E-commerce
evolution: a Gulf region review. International Journal
of Business Information Systems, 4(5).
Doherty, Neil F. and Ellis-Chadwick, Fiona (2010). Internet
retailing: the past, the present and the future.
International Journal of Retail & Distribution
Management, 38(11/12), pp. 943–965.
B. Kusuma, N. Durga Prasad and M. Srinivasa Rao (2013).
A Study on Organized Retailing and its Challenges
and Retail Customer Services. Innovative Journal of
Business and Management, 2(5), 97-102.
Bhavya Malhotra (2014). E-Business: Issues & Challenges
in Indian Perspective. Global Journal of Business
Management and Information Technology, 4,(1), 11-16.
Banerjee Monami and Dr. Banerjee Neelotpaul (2012). An
empirical study on factors influencing consumers’
trust in E-tailers – evidence from India. International
Journal of Business and Social Research (IJBSR), 2(7),
46-61.
Sarbapriya Ray (2011). Emerging Trend of E-Commerce in
India: Some Crucial Issues, Prospects and
Challenges. Computer Engineering and Intelligent
Systems. 2(5), 17-35.
Miss Chandana Kashyap
Research Scholar,
Department of Commerce,
Gauhati University,
Guwahati- 781335, Assam
E-mail: [email protected]
Dr. Ashima Sharma Borah
Associate Professor and HoD,
Department of Management,
KC Das Commerce College,
Guwahati, Assam.
E-mail : [email protected]
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 65 )
ANNEXURE
Annexure 1(a): Map of Assam (Political)
Annexure 1(b): map of Nalbari District (Political)
Annexure 2: Rural and Urban disproportion of Internet
user population in India
Annexure 3: E-retailing- India vs. China
Chandana Kashyap, Ashima Sharma Borah
( 66 )
Annexure 4: List of Top 10 Countries by Internet Usage
Rank Countr
y Total
population
Country's share of World
Population
Total Internet
Users
Yearly Growth Rate of Internet
Users (%)
Penetration (% of Pop.
with Internet)
Country's share of World
Internet Users
1 China 1,393,783,836 19.24% 641,601,070 4% 46.03% 21.97%
2 US 322,583,006 4.45% 279,834,232 7% 86.75% 9.58% 3 India 1,267,401,849 17.50% 243,198,922 14% 19.19% 8.33%
4 Japan 126,999,808 1.75% 109,252,912 8% 86.03% 3.74%
5 Brazil 202,033,670 2.79% 107,822,831 7% 53.37% 3.69%
6 Russia 142,467,651 1.97% 84,437,793
10% 59.27% 2.89%
7 German
y 82,652,256 1.14% 71,727,551 2% 86.78% 2.46%
8 Nigeria 178,516,904 2.46% 67,101,452
16% 37.59% 2.30%
9 UK 63,489,234 0.88% 57,075,826 3% 89.90% 1.95%
10 France 64,641,279 0.89% 55,429,382 3% 85.75% 1.90%
[Source: http://www.internetlivestats.com/internet-users/]
Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam
( 67 )
INTRODUCTION
The positive impact on organization is possible where the social media implementedthrough the strategy and governance. The social net working is the fastest growingactive social media. China is the most socially preferred market in the world, with 84percent of internet users contributing at least once a month to either social networking,blogging, video uploading, photo sharing, micro blogging or forums and followed byRussia, Brazil and India. The 36 percent of social media users post brand related contentand 60 percent of employees would like help from employers to share relevant content(source KPMG). The 84 percent of job seekers have a Facebook profile and 61 percent ofmillennial turn to the web and other external resources, corporate e-mails increasing by20-25 percent per year, 41 percent of 2011 university graduates used social media intheir job enquiry. Hence social media is useful to increase productivity and employeeengagement and foster innovation via collaboration.
REVIEW OF LITERATURE
Search engine journal.com (Feb 2012) identified that 80 percent of employers recruittheir workforce through the social media and linked in. Burson - Marsteller (Feb 2011)opined that 84 percent of the Fortune Global 100 use at least one social media platformand they also identified that IBM use the GE 12, Ford 10 and 21 You tube channels : 40
Key words
Social Media Youtube,Team Building,Innovation, Vale of anOrganization, Flow ofCommunication
Integration of Tools of Social Media forEnrichment of Human Resources in MultivariateOrganizations
K.Kanaka Raju
ABSTRACT
The positive impact on organization is possible where the social media implemented through the strategyand governance. The social net working is the fastest growing active social media The main objectives ofthis study are to identify the various HR practices which are implemented via social media to enhance theperformance of an employee and examine the organizational issues and uses via social media and tointerpret and analyze the perceptions of respondents on various issues of HR interventions on socialmedia along with the appropriate suggestions to strengthen the social media policy. The data collectedfrom the structured questionnaire and applied the techniques of frequency percentage, descriptivestatistics and chi-square test through the SPSS 16.0 version. The study found that accessibility of keytools of social media enhances the delivery of HR services through the social media, foster of an innovationthrough the collaboration of social media promote the employee engagement. The study also found thatincrease in flow of communication via social media useful to motivation of an employee and also observedthat it helps in contacts with others and building professional reputation increase the efficiency at work.The study also observed that training and development via social media enhances the employee engagementand team building and usage of Youtube increase the performance of an employees, transparency,motivation of an employee, building professional reputation, prevent breach of conduct by an employees,and ease of knowledge and information. It is suggested that every organization should utilize the socialmedia to increase the value of an organization and should conduct an awareness programmes to all theemployees of an organization.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 68 )
percent of corporate twitters engage in customer services.United Airlines (Aug 2011) replaced the manuals and chartbooks of flights and used the 11,000 i-pad devised to carrythe same data. The telegraph (Jan 21,2010) stated that ciscoretracts job offer on twitter. The Guardian (Nov, 2008)published virgin attacks sacks 13 crew members overFacebook posts. U.S. Bureau of Labor statistics identifiedthat 47 percent of the population were playing videogamesand surfing the internet to get information and they willbe composed of millennials by 2014. Chi (2011, 46)identified social media as a “connection between brandsand consumers (Mangold and Faulds 2099) opined thatbusinesses must learn how to use social media in a waythat is consistent with their business plan (Kaplan andHaenlein 2010) found that World Wide Web, a place wherecontent is continuously altered by all operators in a sharingand collaborative.” (Campbell et al. 2011, 87) emphasizedthat users are now creating and consuming used tointeractivity, interoperability, and collaboration . Kaplanand Haenlein (2010, 61) opined that social media as “agroup of Internet based applications that build on Web2.0” Sinclaire and Vogus (2011, 294) cite O’Reilly’s (2005)identified that create user generated content that can beshared, . (Gross & Acquisti, 2005; Ellison, Steinfield &Lampe, 2007; Lenhart & Madden, 2007; Winder, 2007; Boyd& Ellison, 2007 as cited in Cox 2010) extracted social mediapermits users to connect with each other and postcomments on each other’s pages, and join virtual groupsbased on common interests such as fashion or politics.(Gross & Acquisti, 2005; Ellison, Steinfield & Lampe, 2007;Lenhart & Madden, 2007; Winder, 2007; Boyd & Ellison,2007 as cited in Cox 2010) opined that social media isdifferent because it allows participants to unite bygenerating personal information profiles and invitingfriends and colleagues
OBJECTIVES OF THE STUDY
1. To identify the various HR practices which areimplemented via Social Media to enhance theperformance of an employee.
2. To examine the various organizational uses viaSocial Media.
3. To interpret and analyze the perception ofrespondents on various issues of HR inventions onsocial media.
4. To offer a suitable suggestions to strengthen theutilization of social media to achieve a successfulHR practices of an organization.
METHODOLOGY OF THE STUDY
The data collected from the 150 respondents through thestructured questionnaire and SPSS 16.0 version was usedto analyze the data and applied the techniques of frequencypercentage, descriptive statistics and chi-square test.
RESEARCH PROBLEM
After verifying the existing literature it was found that afew researchers were wrote on social media and framedthat possibility of implementation of HR practices throughthe social media.
RESEARCH QUESTION
Possibility of implementation of HR practices through thesocial media.
Note : Generation X and Y will almost positively grow disappointedif an organization does not use social media or fails to properlymanage or recognize its use.
OPPORTUNITIES OF SOCIAL MEDIA
It is assist with the collaboration with employees,candidates, customers and suppliers. It is also useful toasses the top performance of an employees through thetalent management by initiating the various approachesof the social media, and it also plays approaches of thesocial media, and it also plays an important role inemployee concentric HR (Human Resources) andemployee engagement to view a unified culture.
Talent Acquisition and Talent Management – SocialMedia : Progressive organization concentrates on annualperformance cycle and turn towards the real time feedbackand coaching and makes true that 360 degree feedback areality, immediate response from internal and externalcustomers.
Integration of Tools of Social Media for Enrichment of Human Resources in Multivariate Organizations
( 69 )
Source : Self
Managing the potential Risks – Social Media :
Every organization has a challenge regarding creation,execution and enforcement of social media policies andmany companies do not establish policies to govern socialmedia usage or can find their policy difficult to enforcedue to lack of employee engagement and training on thetopic. The companies begin to realize the time value to begained by social media adoption, consideration of workforce risk is essential for avoidance of loss of employeegood will, information breaches and reputational damage.The cross functional representation of IT, Legal, HR,Compliance, marketing and risk management that analysisthe current and planned use of social media against currentcommunications related policies.
Perceptions of the Respondents
Table 1: Distribution of Respondents by their Age Age
Frequency Percent Valid
Percent Cumulative
Percent Valid 21-30 67 44.7 44.7 44.7
31-40 33 22.0 22.0 66.7 41-50 23 15.3 15.3 82.0
Above50 27 18.0 18.0 100.0 Total 150 100.0 100.0
Source:SPSS:Field Study
Table -1 : This table shows the distribution of respondentsage, the majority of the respondents represented from theage group of 21-30 years, followed by 31-40 years, 41,-50years and above 50 years. Hence, it can be concluded thatthe majority of the respondents represented from the agegroup of 21-30 years.
Table 2: Distribution of Respondents by their Gender
Gender Frequency Percent Valid Percent
Cumulative Percent
Valid Male 55 36.7 36.7 36.7 Female 95 63.3 63.3 100.0 Total 150 100.0 100.0
Source:SPSS: Field Study
Table- 2 : This table distributes the gender of therespondents. The majority of the respondents (63.3 percent)represented from the female group and rest of thepercentage (36.7 percent) represented from the malecategory. Hence, it can be concluded that the majority ofthe respondents represented from the female category.
Table 3 : Distribution of Respondents by their MaritalStatus
Marital Status Frequency Percent
Valid Percent
Cumulative Percent
Valid Married 75 50.0 50.0 50.0 Unmarried 75 50.0 50.0 100.0 Total 150 100.0 100.0
Source:SPSS: Field Study
Table-3 : This table shows the marital status of therespondents. The fifty percent of the respondents marriedand remaining fifty percent of the respondents unmarried.Hence, it can be concluded that half-of-the respondentsgot married.
Table 4 : Distribution of Respondents by theirEducational Qualifications
Educational Qualifications Frequency Percent
Valid Percent
Cumulative Percent
Valid Graduation 65 43.3 43.3 43.3 Post Graduation 29 19.3 19.3 62.7 Professional Degree 27 18.0 18.0 80.7
PhD 29 19.3 19.3 100.0 Total 150 100.0 100.0
Source:SPSS :Field Study
Table-4 : This table distributes the educationalqualifications of the respondents. The 43.3 percent ofrespondents posses the qualification of graduation, 19.3percent of them post graduation, 18 percent of themprofessional degree and 19.3 percent of them posses thedoctorate. Hence, it can be concluded that the majority ofthe respondents represented from the graduation, followedby the post graduation, professional degree and Ph.D.
K.Kanaka Raju
( 70 )
Table 5: Responsibility of Professionals to CreateOrganization Media Policy
Name of Professionals Frequency Percent Valid
Percent Cumulative
Percent Valid Information
Technology 36 24.0 24.0 24.0
Marketing 38 25.3 25.3 49.3 Public Relations 76 50.7 50.7 100.0
Total 150 100.0 100.0
Source:SPSS :Field Study
Table-5 : This table furnishes the information of kind ofprofessional are responsible for organization media policy.It tell us that the half-of the respondents (50.7 percent)opined that public relations officer was responsible fororganizing of social media policy, followed by themarketing manager and information technology manager.Hence, it can be concluded that the majority of therespondents opined that public relations officer was aptlyto look after the social media policy.
Table 6: Professionals Responsible for Leading of anOrganizations Social Media Policy
Name of Professionals Frequency Percent Valid
Percent Cumulative
Percent Valid Marketing 38 25.3 25.3 25.3
Information Technology 19 12.7 12.7 38.0
Public Relations 93 62.0 62.0 100.0
Total 150 100.0 100.0
Source:SPSS :Field Study
Table-6 : This table tells us that kind of professionalsresponsible for leading of an organization social mediapolicy. The majority of the respondents (62 percent) agreedthat public relations officer responsible for leading of anorganizational social media policy followed by themarketing manager and information technology manager.Hence, it can be concluded that the majority of therespondents opined that public relations officersresponsible for leading of an organizations social mediapolicy.
Table 7 a: Ho1: Accessibility of key tools of socialmedia do not enhances the delivery of HR Service
through the social media.
HR Service Delivery Enhance Through the Social Media
Employees can able to access the key tools of social media
Disagree Nueatral Agree Total Disagree 19
(33.33) 19
(33.3) 0
(0) 57
(100.0)
Nueatral 0 (0)
0 (0)
36 (100.0)
36 (100.0)
Agree 0 (0)
19 (33.3)
38 (66.7)
57 (100.00)
Total 19 (12.7)
38 (25.3)
93 (62.0)
150 (100.0)
Source:SPSS: Field Study
Table 7 b:Chi-Square Value
Particulars Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 59.1406a 4 .000 Likelihood Ratio 73.977 4 .000 Linear-by-Linear Association 25.00 1 .000
N of Valid Cases 150
Table-7 a &b :
Hypothesis -1 :
Null Hypothesis (Ho): Accessibility of key tools of socialmedia do not enhances the delivery of HR services throughthe social media.
Alternative Hypothesis (Ha) : Accessibility of Key tools ofsocial media enhances the delivery of HR services throughthe social media.
Analysis : The calculated Pearson chi-square value wasthe 59.140 at df was 4 and the level of significance was0.000. Hence, it can be concluded that the proposed nullhypothesis was rejected and alternative hypothesis wasaccepted and inferred that accessibility of key tools ofsocial media enhances the delivery of HR services throughthe social media.
Hypothesis 2:
Null Hypothesis: Foster of an innovation through thecollaboration of social media does not promote theemployee engagement
Alternative Hypothesis: Foster of an innovation throughthe collaboration of social media promote the employeeengagement
Integration of Tools of Social Media for Enrichment of Human Resources in Multivariate Organizations
( 71 )
Table-8 a Promote Employee Engagement
Foster Innovation through the collaboration
Strongly Disagree
Nueatral Agree Total
Strongly Disagree
19 (100)
0 (0)
0 (0)
19 (100.0)
Disagree 0 (0)
0 (0)
36 (100.0)
36 (100.0)
Nueatral 0 (0)
0 (0)
38 (100)
38 (100.00)
Agree 0 (0) 19 (33.3)
38 (66.7)
57 (100.0)
Total 19 (12.7)
19 (12.7)
112 (74.7)
150 (100)
Table-8bParticulars Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 1.830E2a 6 .000
Likelihood Ratio 149.907 6 .000 Linear-by-Linear Association 43.932 1 .000
N of Valid Cases 150 Source: SPSS:Field Study
Analysis : The calculated Pearson chi-square value wasthe 1.830E2 at df was 6 and the level of significance was0.000. Hence, it can be concluded that the proposed nullhypothesis was rejected and alternative hypothesis wasaccepted and inferred that Foster of an innovation throughthe collaboration of social media promote the employeeengagement
Hypothesis3:
Null Hypothesis: Increase in flow of communication donot useful for motivation of an employees
Alternative Hypothesis: Increase in flow of communicationuseful for motivation of an employees
Table-9 a Motivation of an employees
Increase in flow of communication with members
Strongly Disagree
Agree Total
Agree 0 (0)
57 (100)
57 (100)
Strongly Agree
19 (20.4)
74 (79.6)
93 (100.0)
Total 19 (12.7)
131 (87.3)
150 (100.0)
Table-9b :Particulars Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 13.334 1 .000 Likelihood Ratio 19.827 1 .000 Linear-by-Linear Association 13.245 1 .000
N of Valid Cases 150
Source : SPSS Field Study
Analysis : The calculated Pearson chi-square value wasthe 13.334 at df was 1 and the level of significance was0.000. Hence, it can be concluded that the proposed nullhypothesis was rejected and alternative hypothesis wasaccepted and inferred that Increase in flow ofcommunication useful to motivation of an employee
Hypothesis 4:
Null Hypothesis: Social media helps in contacts withothers and building professional reputation do notincrease the efficiency at work.
Alternative Hypothesis: Social media helps in contactswith others and building professional increase theefficiency at work.
Table 10 a
Increase the efficiency at work.
Social media helps in contacts with others and building professional reputation
Neutral Agree Strongly Agree
Total
Agree 56
(50) 56
(50) 0
(0) 112
(100.0)
Strongly Agree
0 (0)
19 (50)
19 (50.0)
38 (100.0)
Total 56 (37.3)
75 (50)
19 (12.7)
150 (100.00)
Source: SPSS:Field Study
Table 10bParticulars Value df Asymp. Sig.
(2-sided) Pearson Chi-Square 75.000 2 .000 Likelihood Ratio 84.895 2 .000 Linear-by-Linear Association 64.178 1 .000
N of Valid Cases 150
Source: SPSS :Field Study
Analysis : The chi-square value at 2 of df was 75.00 andthe value of significance was 0.000, hence it can beconcluded that the proposed null hypothesis was rejectedand alternative hypothesis was accepted and confirmedthat Social Media helps in contacts with others andbuilding professional reputation increase the efficiency atwork.
Hypothesis 5:
Null Hypothesis: Training and development via socialmedia do not enhances the employee engagement andteam building.
K.Kanaka Raju
( 72 )
Alternative Hypothesis: Training and development viasocial media enhances the employee engagement andteam building.
Table-11a
Employee engagement and team building.
Training and development via social media
Strongly Disagree Nueatral Agree Total
Disagree
0 (0)
19 (100.0)
0 (0)
19 (100.0)
Agree 0 (0)
93 (100.0)
0 (0)
93 (100.0)
Strongly Agree
19 (50)
0 (0)
19 (50)
38 (100.00)
Total 19 (12.7)
112 (74.7)
19 (12.7)
150 (100.0)
Table-11b
Particulars Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1.500E2 4 .000 Likelihood Ratio 169.790 4 .000 Linear-by-Linear Association 5.096 1 .024
N of Valid Cases 150
Source: SPSSField Study
Analysis : The value of chi-square was 15.00E2 at df was 4and the value of significance was 0.000, hence it can beconcluded that the proposed null hypothesis was rejectedand alternative hypothesis was accepted and confirmedthat training and development via social media enhancesthe employee engagement and team building.
Hypotheis-6 :
Null Hypothesis (Ho) : Recruitment and selection via socialmedia do not increase the production of an organization.
Alternative Hypothesis (Ha) : Recruitment and selectionvia social media increase the production of anorganization.
Table-12 a
Production of an organization Recruitment and selection via social media
Strongly Disagree Disagree Agree Strongly
Agree Total
Disagree
0 (0)
0 (0)
19 (100.0)
0 (0)
19 (100.0)
Neutral 19 (50.0)
0 (0)
19 (50.0)
0 (0)
38 (100.0)
Agree 0 (0)
19 (20.4)
55 (59.1)
19 (20.4)
93 (100.00)
Total 19 (12.7)
19 (12.7)
93 (62.0)
19 (12.7)
150 (100.0)
Table-12b
Particulars Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 84.721 6 .000 Likelihood Ratio 93.302 6 .000 Linear-by-Linear Association 2.967 1 .085
N of Valid Cases 150 Source: SPSSField Study
Analysis : The calculated value of Pearson chi-square was1.500E2 at df was 4 and the value of significance was0.000, hence it can be concluded that the proposed nullhypothesis was rejected and alternative hypothesis wasaccepted and confirmed that recruitment and selection viasocial media increase the production of an organization.
Table 13: Awareness of the Social Media Policy and ItsRisks and Benefits
Awareness of Social Media
Policy Frequency Percent Valid
Percent Cumulative
Percent
Valid Yes 95 63.3 63.3 63.3 No 36 24.0 24.0 87.3 Cant Say 19 12.7 12.7 100.0 Total 150 100.0 100.0
Analysis: The above table shows that the awareness ofthe social media policy the majority of therespondents(63.3 per cent) knew about the social mediapolicy and meager number of respondents(24 per cent )did not know about the social media policy. Hence, it canbe concluded that the majority of the respondents knewthe awareness of the respondents.
Table 14: Utilization of You Tube to Train anEmployee
Utilization of You Tube Frequency Percent Valid
Percent Cumulative
Percent Valid Yes 114 76.0 76.0 76.0
No 36 24.0 24.0 100.0 Total 150 100.0 100.0
Source: SPSS :Field Study
Table-14 : This table discloses that the utilization of an“Youtube” to train an employee. The majority of therespondents (76 percent) favoured towards the utilizationof Youtube to train an employee and meagre percentage ofrespondents (24 percent) disfavoured regarding utilizationof the Youtube.
Integration of Tools of Social Media for Enrichment of Human Resources in Multivariate Organizations
( 73 )
Table 15:Descriptive Statistics of Various Statementsof the Social Media Policy
Statements of the Social Media Policy N Mean Std.
Deviation Social Media Policy useful to check breach of conduct by the employees
150 3.6200 .86444
Recruiting policies and practices should be reviewed through the social media
150 3.2400 1.30913
Social Media is useful to assess the teams performance through the internal and external customers
150 3.9867 .70460
Employees can able to access the key tools of social media. 150 3.0000 .87470
HR Service delivery enhances through the social media 150 3.4933 .71181
Social media has the potential to transform talent management and performance management.
150 3.4933 .50163
Employee engagement and employee communication can be accelerated with social media.
150 3.8733 .60531
Valid N (listwise) 150
Source: SPSS :Field Study
Table-15 : This tables describes the various statements ofthe social media policy and majority of the respondentsagreed towards the social media is useful to assess theteam’s performance through the internal and externalcustomers, followed by the engagement andcommunication of an employee through the social media.Social Media has the potential to transform talentmanagement and performance management.
Table 16 : Descriptive Statistics of the Advantages ofthe Social Media
Advantages of the Social Media N Mean Std.
Deviation Increase Productivity 150 3.4933 1.23564 Promote Employee Engagement 150 3.4933 1.00833
Foster innovation through the collaboration 150 2.8867 1.05891
Valid N (listwise) 150
Source: SPSS:Field Study
Table-16 : This table projects the advantages of the socialmedia. The preferred advantage by the respondents wasthe increase in productivity as well as the promotion of anemployee engagement and followed by the fosterinnovation through the collaboration.
Table 17:Descriptive Statistics of the Constructs forLikelihood of Acceptance for Implementation via
Social MediaConstructs for Likelihood of
Acceptance for Implementation via Social
Media
N Mean Std. Deviation
Ease of availability of information / Recruiting Tool 150 4.2667 .82468
Transparency 150 3.8867 .59682 Increase in flow of communication with non-family members
150 4.6200 .48701
Seeking of the opinion 150 4.2533 .43638 Ability to understand the values of the family and overcoming the perceived bias
150 3.5067 .71181
Overcome the ceiling of glass 150 3.0000 .71419 Motivation of employees 150 3.6200 1.00114 Valid N (listwise) 150
Source:SPSS:Field Study
Table-17 : This table narrates the constructs for likelihoodof acceptance for implementation via social media,favoured construct was the increase in flow ofcommunication, followed by the ease of availability ofinformation, seeking of an opinion, transparency,motivation of an employee, ability to understand the valuesof the family and overcome the ceiling of glass.
Table 18:Descriptive Statistics of the HR PracticesWhich are Implemented Via Social Media
HR Practices Which are Implemented Via Social Media N Mean Std.
Deviation Youtube is useful for training of an employee 150 3.7467 1.10025
Social Media Policy useful to check breach of conduct by the employees 150 3.6200 .86444
Social Media helps in contacts with others and building professional reputation
150 4.2533 .43638
Increase the efficiency at work 150 3.7533 .66491 Increase in communication with non-family members 150 4.1133 1.05891
Opinion of an employees and employee engagement enhances the performance at work.
150 3.4933 .50163
Social Media helps to women at their working place 150 3.7467 .66743
Recruiters can able to monitor the profile of an employee through a back ground check
150 4.2533 .43638
Work life becomes difficult through the 24x7 on social media 150 4.1267 1.28124
Team building activities and collaboration with fellow employees increases performance.
150 4.1133 .93073
Valid N (listwise) 150
Source:SPSS:Field Study
K.Kanaka Raju
( 74 )
Table-18 : This table exhibits the HR practices which areimplemented via social media to enhance the performanceof an employee. The more favoured response by therespondents was the social media helps in contacts withothers and building professional reputation, followed bythe work life becomes difficult through the 24x7 on socialmedia. Increase in communication, increase theperformance through team building and collaboration,overcome the problems by women, utilization of a youtube,useful to check breach of conduct by the employees,enhance the performance at work through the employeeengagement.
Table 19: Descriptive Statistics of the OrganizationalUses by Utilization of the Social Media
Organizational Uses by Utilization of the Social
Media N Mean Std.
Deviation
Recruitment and Selection 150 3.4933 .71181 Socializing and on boarding 150 3.3733 .48531 Felicitation of an employee 150 2.4933 .70231 Organizational Culture 150 4.0000 .71419 Employee Engagement and team building 150 3.8733 .78831
Knowledge / Information sharing 150 4.6267 .48531
Training and Development 150 4.0000 .87470 Valid N (listwise) 150
Source:SPSS:Field Study
Table-19 : This table exhibits the organizational uses byutilization of the social media, the respondents preferredorganizational use was sharing of the knowledge /information followed by the training and development,organizational culture, employee engagement and teambuilding, recruitment and selection, socializing andfelicitation of an employee.
FINDINGS OF THE STUDY
1. The study found that accessibility of key tools ofsocial media enhances the delivery of HR servicesthrough the social media.
2. The study also found that foster of an innovationthrough the collaboration of social media promotethe employee engagement.
3. The study also identified that increase in flow ofcommunication via social media useful to motivationof an employee.
4. The study observed that social media helps incontacts with others and building professionalreputation increase the efficiency at work.
5. It was exhibited that training and development viasocial media enhances the employee engagementand team building and it was also observed that therecruitment and selection via social media increasethe production of an organization.
6. The study came to know that the majority of therespondents suggests the use the youtube to trainan employee.
7. The respondents identified that social media isuseful to assess the team performances, engagementand communication of any employee and transformthe talent management and performancemanagements, increase the flow of communication,ease of availability of an information, transparency,motivation of an employee.
8. The study also identified the specified HR practicesthrough the social media. It helps in contacts withothers and building professional reputation,overcome the problems by the women, utilization ofYoutube, useful to check breach of conduct by theemployees, enhance the performance at workthrough the employee engagement, recruitment andselection, organizational culture and ease ofknowledge and information.
CONCLUSION AND SUGGESTIONS
Finally, it can be concluded that the implementation ofHR practices via social media was more helpful to anorganization through decrease in consumption of time fordecision making, as a result speedy and qualitativedecisions can be able to implement in the organizationwhich leads to enhance the profitability. It is suggestedthat every organization should utilize the social media toincrease the productivity.The organization have the ableto utilize the social media to acquire additional benefitslike enhance the public image, improve interactions withcustomers and promote employee engagement, but theseare acquired only with the managing of the internal andexternal risks by the organization.
Integration of Tools of Social Media for Enrichment of Human Resources in Multivariate Organizations
( 75 )
REFERENCES
Bourlakis, Michael, Savvas Papagiannidis, and Feng Li.(2009). Retail Spatial Evolution: paving the way fromtraditional to metaverse retailing. ElectronicConsumer Research 9:135-148.
Casaló, Luis V., Flavián Carlos, and Miguel Guinalíu.(2008). Promoting Consumer’s Participation inVirtual Brand Communities: A New Paradigm inBranding Strategy. Journal of MarketingCommunications 14: 19-36. Cha, Jiyoung. 2009.“Shopping on Social Networking
Cox, Shirley A. (2010). Online Social Network MemberAttitude Toward Online Advertising Formats. MAthesis, The Rochester Institute of Technology. Chu,Shu-Chuan. 2011, Viral advertising in social media:Participation in Facebook groups and responsesamong college-aged users. Journal of InteractiveAdvertising 12: 30-43.
Di Pietro, Loredana and Elenora Pantano (2012). AnEmpirical Investigation of Social Network Influenceon Consumer Purchasing Decision: The Case ofFacebook. Journal of Direct Data and DigitalMarketing Practice 14: 18-29. Ferguson,
Georgi, Dominik and Moritz Mink (2012). eCCIq: Thequality of electronic customer-to customerinteraction, Journal of Retailing and Consumer Serviceshttp://dx.doi.org/10.1016/j.jretconser.2012.08.002.25
Golan, Guy J. and Lior Zaidner (2008). Creative Strategiesin Viral Advertising: An Application of Taylor’s Six-Segment Message Strategy Wheel. Journal of Computer–Mediated Communications 13: 959-972.
Hassanein, Khaled and Milena Head (2005-6). “The Impactof Infusing Social Presence in the Web Interface: An
Investigation across Product Types. InteractiveJournal of Electronic Commerce 10: 31-55.
Heinonen, Kristina (2011). Consumer activity in socialmedia: Managerial approaches to consumers’ socialmedia behavior. Journal of Consumer Behavior 10:356-364.
Hill, Shawndra, Foster Provost, and Chirs Volinsky (2006).Network Based Marketing: Identifying LikelyAdaptors via Consumer Networks. StatisticalScience 21: 256-276.
Kaplan, Andreas M. and Michael Haenlein (2010). Usersof the World, Unite! The Challenges andOpportunities of Social Media. Business Horizons 53:59-68.
Karen Isaac Son and Search Peacey, Human Resourcesand Social Media, KPMG, 1-15
Mady, Tarek T. (2011). Sentiment toward marketing: Shouldwe care about consumer alienation and readinessto use technology? Journal of Consumer Behavior 10:192-204.
Mangold, Glynn W., and David J. Faulds. (2009). SocialMedia: The New Hybrid Element of the PromotionMix. Business Horizons 52: 357-365
Pavlou, Paul A., and David W. Stewart (2000). Measuringthe Effects and Effectiveness of InteractionAdvertising: A Research Agenda. Journal ofInteractive Advertising 1: 62-78.
Pehlivan, Ekin, Funda Sarican, and Pierre Berthon(2011).
Shankar,Venkatesh, Jeffery Inman, Murali Mantrala, EileenKelley, and Ross Rizley (2011). Innovations inShopper Marketing: Current Insights and FutureResearch Issues. Journal of Retailing 1:s29-s42,doi:10.1016/j.jretai.2011.04.007
Dr.K.Kanaka RajuAssistant ProfessorDepartment of Management Studies,Andhra University Campus,Andhra Pradesh
Email : [email protected]
K.Kanaka Raju
( 76 )
The present era can be termed as jet era as the pace of life is morning vehemently and as
such people are always in need for fast services available to them to fulfill such
requirements the technology has developed to such an extent that usage of internet
expanded unpredictably high. With the availability of communication system,
technological development and digital information, people are by and large relied on
internet.
Not only in the literary or working field but in every walk of life one needs to encounter
with it and make use of it and thus it goes on expanding its network throughout the
world any piece of information whether relating to news or with democratic, policies, to
new science and technology employment opportunities, so forth and so on are all
available in the internet, which one can receive within seconds. All these possibilities
effectively connect people and organization to the world wide users. Again the social
networking sites like Facebook, twitter, what Sapp, weblog, and other crawlers like
Google +, YouTube etc. are very usefully in exchanging ideas worldwide.
Social media is a broad term for applications or tools that enable the creation and
exchange of user-generated content over the Internet. Social media occur in a variety of
formats including chat rooms, weblogs, social blogs, wikis, micro blogging, internet
fore, podcasts, pictures, video, and rating and social bookmarking. Examples of social
media include, but are not limited to Facebook, LinkedIn, YouTube, Flickr and Twitter.
Key words
social media, marketing,
recruitment and
cybercrimes
Social Media-Marketing, Recruitment and CyberCrime – A Case Study of Hyderabad City
Mohammad Azmat Ali and Patrick Anthony
ABSTRACT
The present era can be termed as jet era as the pace of life is morning vehemently and as such
people are always in need for fast services available to them to fulfill such requirements the
technology has developed to such an extent that usage of internet expanded unpredictably high.
With the availability of communication system, technological development and digital
information, people are by and large relied on internet.The purpose of the study is to the
implications of social media on marketing, recruitment process and awareness of cyber-crime of
citizens of Hyderabad city.The study used primary and secondary data. The primary data
collected through questionnaire. Questionnaire prepared on basis if literature reviews. The
questionnaire measured using multiple items.A structured questionnaire is administered to
collect data from respondents. The study constitutes 206 sample size from Hyderabad city.
Dimensions analysis test independent samples t test and one way ANOVA deployed to
demonstrate the statistical significance of these items on citizens. Significant differences are
found in social media on marketing, recruitment process and awareness of cyber-crime of citizens
of Hyderabad city with respect to their demographics.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 77 )
THE TOP MOST POPULAR SOCIAL NETWORKING
SITES
The following are the top most15 popular social
networking sites as derived from theeBizMBA Rank which
is a continually updated average of each website’s Alexi
Global Traffic Rank and U.S. Traffic Rank from both
Compete and Quant cast. Denotes an estimate for sites
with limited data as on 1 March 2015.
Table 1:The following are the top most15 popular
social networking sites
Rank Social
Networking Sites
Rank Social
Networking Sites
Rank Social
Networking Sites
1 Facebook 6 Tumblr 11 Meet up
2 Twitter 7 Tustargam 12 Tagged
3 LinkedIn 8 VK 13 Ask.fm
4 Pinterest 9 Flickr 14 MeetMe
5 Google Plus+ 10 Vine 15 ClassMates
Source:http://www.ebizmba.com/articles/social-networking-
websites on 01 October 2015.
India may have not succeeded that much, so that it could
be referred as one of the developed country but it will
certainly obtain a place of recognition in the technological
field. Though earlier certain departments like Agricultural
fields, small scale inside industries. We’re not in touch
with technological benefits but as the pace of its
development and utilization expanded its influence on
all large and small sectors couldbe felt. Especially the
service sectors and corporate sectors are highly benefited
through this progress in internet. People are getting
recruited more through this procedure than with man to
man recruitment. There is a sector which is highly
influenced and takes its advantage and that is the
marketing field. From a car to bag, all necessary
equipment’s, household materials, a readymade house
itself is available to buy and sell.Its facilities are helpful to
everyone and no one is untouched with it.
LITERATURE REVIEW
Social media’ is a broad term for applications or tools that
enable the creation and exchange of user-generated content
over the Internet. The present time can be termed as jet era
as the pace of life is morning very fast and as such people
are always in need for fast services available to them to
fulfill such requirements the technology has developed to
such an extent that usage of internet expanded
unpredictably high. However, e-commerce as a percentage
of internet perception continues to be very small, I-Cube
survey shows that in 2008. As for his survey and now
trend is very different. India will be the fastest growing
market for online retail by 2015. According to Tan and
Guo, the internet is viewed by customers as a world of
chaos. Purchase is made only if the perceived benefits are
more than the risks. Social media imperative that trust in
online information is one of the most crucial factors for
successes.Identifythe risks faced by users of online social
networking services (SNSs) in the UK and to develop a
typology of risk that can be used to assess regulatory
effectiveness - David Haynes and Lyn Robinson 2015.
Cybercrime is often traditional crime (e.g. fraud, identify
theft, child pornography) albeit executed swiftly and to
vast numbers of potential victims, as well as unauthorized
access, damage and interference to computer systems
criminals. In response to the threat of cybercrime there is
an urgent need to reform methods of MLA and to develop
transnational policing capability-RodericBroadhurst
2006.
OBJECTIVES
The present research study focuses on the following
objectives:
1) To study the implications of social media on
marketing
2) To study the recruitment process under social media
3) To study the awareness of cyber-crime under social
media
HYPOTHESIS
The present research study the following hypotheses: :
H01
There is no significant difference in gender with
regard to awareness of social media marketing
H02
There is no significant difference along the different
age groups in social media- marketing awareness
H03
There is no significant difference among the
respondents of different educational levels to their
social media- marketing awareness
H04
There is no significant difference in gender with
regard to awareness of social media recruitment
H05
There is no significant difference along the different
age groups in social media- recruitment
Mohammad Azmat Ali, Patrick Anthony
( 78 )
H06
There is no significant difference among the
respondents of different educational levels to their
social mediarecruitment
H07
There is no significant difference in gender with
regard to awareness of social media cyber crime
H08
There is no significant difference along the different
age groups in social media- cyber crime
H09
There is no significant difference among the
respondents of different educational levels to their
social media cyber crime
METHODOLOGY
The study used primary and secondary data. The primary
data collected through questionnaire. Questionnaire
prepared on basis if literature reviews. The questionnaire
measured using multiple items. Some of the scale items
represented in the survey instrument utilized a 7 point
scale, yes or no questions and ranking questions. The
questionnaire was distributed to 250 citizens of Hyderabad
226 responses were received. After eliminating unfilled
and partially filled response, the final sample size was
206. Dimensions analysis test independent samples t-
test and one way ANOVA deployed to demonstrate the
statistical significance of these items on citizens.
Figure:1 Social media - Marketing, Recruitment and
Cybercrime dimensions and items
SOCIAL MEDIA – MARKETING
Marketing companies were used to know the consumer
interests on their product. But now-days the trend totally
changed. The usage of social media role is increasing
day- to-day. All marketing transactionsare linked with
internet. At present the role of social media became
mandatory.By referring social medias Facebook, Twitter,
LinkedIn apps the marketing.
Using social media merchandisers interact with the choice
and tastes of consumer. Referring to social media
vendorsis getting more information according to customer
tastes and preferences. Developed countries like America
their first step is referring information from the social
Medias then only they are paying attention to release a
product into market.
KPMJ Annalistic AmithKanna said that if a company
invested any product that will interact with the social
medias. The Apple Company is going to launch Apple
watch on the basis of that it uploaded features about that
product which that has going to produce For that on that
people going attention towards, that product in comments
basis. Now a day’s social media became a platform of
interaction. This Generation is showing Interests to share
their personal to other people through social media. People
interests likes, dislike, wishes everything appears as status
and their social network. Based on that Marketing future
investments, making of product depend before purchasing
any product desires and knowledge about products are
clearly mentioned on social media.Based on customer
choice only markets are going to spread product and
marketing process.
SOCIAL MEDIA FOR ADVERTISING UPCOMING
PRODUCT FEATURES
Research on social media had conducted by some national
Research institutions found their investments 15% of
budget on social media.Hyundai’s, kretra Mahindra &
Mahindra TUV300 had presented products using social
Medias before the finalized product into market sector.
Technology employee’s logics which marketing companies
apply for getting more benefits from the customers.Simply
started that customers using methodology of E- Commerce
which is a profitable platform for vender as well as for
customer too.Linking information with social networks in
dealing a lot of technical implementation of business,
technical methods using social medias bot marketing
organization and customers are getting equal benefits.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 79 )
Table 2 : Gender wise perceptions towards awareness
on social media- marketing
Gender -Group Statistics
Gender N Mean
Std. Deviation
Std. Error Mean
Marketing MALE 152 5.2018 .59078 .04792
FEMALE 54 5.2346 .70229 .09557
Above table shows that the mean and standard deviation
for the male employees perception towards awareness on
social media- Marketing Mean =5.2018,
SD=.59078respectively while for female employees
perception towards awareness on social media-online
marketing Mean=5.2346, SD=.70229. Levene’s test is used
to analyse the equality of variances is carried out follows:
Mohammad Azmat Ali, Patrick Anthony
Table 3 : Independent Samples test towards awareness on social media- Marketing
Independent Samples Test
Levene's Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
Difference
Lower Upper
Marketing Equal variances assumed
.833 .363 -.333 204 .739 -.03281 .09849 -.22700 .16137
Equal variances not assumed
-.307 81.197 .760 -.03281 .10691 -.24552 .17989
The table above shows Levene’s test is used to analyse the
equality of variances, since it is insignificant (F=.833,
p=.363> 0.05) hence, equal variances are assumed and
considered the t-value as -.333at 204 degrees of freedom
and which is insignificant (p=.363> 0.05).Therefore, p
value is above 0.05 H01
null hypothesis is accepted and
can be concluded that there is no significant difference
between male and female citizensof Hyderabad towards
the awareness on social media marketing.
Table 4 : Descriptive towards awareness on social media- Marketing
Marketing
N Mean Std.
Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
below 21 Years 49 5.4218 .69647 .09950 5.2217 5.6218 3.67 6.67
+21-30 years 102 5.1993 .58069 .05750 5.0853 5.3134 3.67 7.00
+31-40 Years 39 4.9744 .54281 .08692 4.7984 5.1503 3.67 6.00
Above 40 Years 16 5.2083 .63099 .15775 4.8721 5.5446 4.00 6.00
Total 206 5.2104 .62032 .04322 5.1251 5.2956 3.67 7.00
Above table shows that, the mean values of perception of
citizens of below 21 years is higher than the grand mean
and the mean values of the remain three groups are lower
than the grand mean.
( 80 )
Table 5 : ANOVA test towards awareness on social media- Marketing
ANOVA
Marketing
Sum of Squares df Mean Square F Sig.
Between Groups 4.375 3 1.458 3.953 .009
Within Groups 74.510 202 .369
Total 78.885 205
The table above shows, a significant F value is found; F (3,
202) =3.953; p = 0.009, there is a significant difference exists
among the various groups of citizens with regards to their
perceptions towards their awareness on social media-
Marketing. Therefore, p value is less than 0.05 H02
null
hypothesis is rejected and concluded that there is a
significant difference exists among the various age groups
of citizens with regards to their awareness on social media-
Marketing.
However to know further, which age group of employees
differ significantly, Turkey HSD post-hoc test is conducted
and the results are presented in table.
Table 6 : Post Hoc test - Multiple Comparisons towards awareness on social media- Marketing
Multiple Comparisons
Marketing -Tukey HSD
(I) Age (J) Age Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
below21 Years +21-30 years .22242 .10557 .154 -.0510 .4959
+31-40 Years .44741* .13033 .004 .1098 .7850
Above 40 Years .21344 .17488 .615 -.2396 .6665
+21-30 years below 21 Years -.22242 .10557 .154 -.4959 .0510
+31-40 Years .22499 .11434 .204 -.0712 .5212
Above 40 Years -.00899 .16331 1.000 -.4320 .4141
+31-40 Years below 21 Years -.44741* .13033 .004 -.7850 -.1098
+21-30 years -.22499 .11434 .204 -.5212 .0712
Above 40 Years -.23397 .18031 .566 -.7011 .2331
Above 40 Years Below 21 Years -.21344 .17488 .615 -.6665 .2396
+21-30 years .00899 .16331 1.000 -.4141 .4320
+31-40 Years .23397 .18031 .566 -.2331 .7011
*. The mean difference is significant at the 0.05 level.
*. The mean difference is significant at the 0.05 level.
Above shows that the Turkey HSD Post-Hoc test, it is
found that, there is no significant difference exist between
below 21 years and +31 – 40 Years (Mean Difference
=.44741*) , but employees belong to rest of the age groups
differ significantly with regards to their perception
towards awareness on social media- Marketing.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 81 )
Table 7: Descriptive towards awareness on social media- Marketing
Descriptive
Marketing
N Mean Std.
Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
Intermediate or below
43 4.9690 .46470 .07087 4.8260 5.1120 3.67 6.00
Degree 39 4.9744 .47992 .07685 4.8188 5.1299 3.67 5.67
Post-Graduation 63 5.1958 .51024 .06428 5.0673 5.3243 4.00 6.00
Professional degree 61 5.5464 .74544 .09544 5.3555 5.7374 3.67 7.00
Total 206 5.2104 .62032 .04322 5.1251 5.2956 3.67 7.00
Skill Development and Entrepreneurship for Micro and Small Enterprises
Above table shows that, the mean values of perception of
citizens of Professional degreeMean 5.5464than the grand
mean and the mean values of the remainthree education
level group are lower than the grand mean.
Table 8 : ANOVA test towards awareness on social media- Marketing
ANOVA
Marketing
Sum of Squares df Mean Square F Sig.
Between Groups 11.581 3 3.860 11.586 .000
Within Groups 67.304 202 .333
Total 78.885 205
The table above shows, a significant F value is found; F (3,
202) =11.586; p = 0.000, there is a significant difference
exists among the various groups of citizens with regards
to their awareness on social media- Marketing. Therefore,
p value is less than 0.05 H03
null hypothesis is rejected
and concluded that there is a significant difference exists
among the various education levels with regards to their
awareness on social media- Marketing.
However to know further, which group towards awareness
on social media- Marketing differ significantly, Turkey
HSD post-hoc test is conducted and the results are
presented in table.
Mohammad Azmat Ali, Patrick Anthony
( 82 )
Table 9 : Table no: Post Hoc test - Multiple Comparisons towards awareness on social media- Marketing
Multiple Comparisons
Marketing - Tukey HSD
(I) Education (J) Education Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
Intermediate or below
Degree -.00537 .12764 1.000 -.3360 .3253
Post-Graduation -.22677 .11418 .197 -.5226 .0690
Professional degree -.57746* .11494 .000 -.8752 -.2797
Degree Intermediate or below .00537 .12764 1.000 -.3253 .3360
Post-Graduation -.22141 .11761 .239 -.5261 .0833
Professional degree -.57209* .11834 .000 -.8787 -.2655
Post-Graduation Intermediate or below .22677 .11418 .197 -.0690 .5226
Degree .22141 .11761 .239 -.0833 .5261
Professional degree -.35068* .10369 .005 -.6193 -.0821
Professional degree Intermediate or below .57746* .11494 .000 .2797 .8752
Degree .57209* .11834 .000 .2655 .8787
Post-Graduation .35068* .10369 .005 .0821 .6193
*. The mean difference is significant at the 0.05 level.
Above shows that the Turkey HSD Post-Hoc test, it is
found that, there is no significant difference exist between
below Professional degree and Intermediate or below
(Mean Difference =-.57746*) , but employees belong to rest
of the age groups differ significantly with regards to their
perception towards awareness on social media- Marketing.
Table 10 : Ranks of Social Media- respondent opinions
Rank-1 Rank-2 Rank-3 Rank-4 Rank-5 Rank-6 Total No of
Respondents
Google+ 3 4 6 40 107 46 206
Linkedin 1 38 84 37 38 8 206 Twitter - 2 68 125 4 7 206
Facebook 118 82 6 - - - 206 Classmates - - 4 4 55 143 206
Whatsapp 81 84 39 2 - - 206
Source: Primary data
Social media in majority users networks of Facebook, Whatsapp and Linkedin.
SOCIAL MEDIA - EMPLOYMENT RECRUITMENT
The perceptions of social media entering into Employment
sector for example; of a person is going to apply any job
before that he must upload his information to the website
of hire Organization. The company who is offering job
management refers information of applicant person. Simply
the total process of employment is also using social media
features E-Business have been increased to a great extent.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 83 )
Table 11 : Gender wise perceptions towards awareness on social media- Recruitment
Gender - Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
Recruitment MALE 152 5.1206 .63680 .05165
FEMALE 54 5.2222 .70711 .09623
Above table shows that the mean and standard deviation
for the male employees perception towards awareness on
social media- Recruitment Mean =5.1206,
SD=.63680respectively while for female employees
perception towards awareness on social media-
Recruitment Mean=5.2222, SD=.70711Levene’s test is used
to analyse the equality of variances is carried out follows:
Table 12 : Independent Samples test towards awareness on social media- Recruitment
Independent Samples Test
Levene's Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
Difference
Lower Upper
Recruitment Equal variances assumed
.555 .457 -.978 204 .329 -.10161 .10389 -.30645 .10323
Equal variances not assumed
-.930 85.452 .355 -.10161 .10921 -.31873 .11552
The table above shows Levene’s test is used to analyse the
equality of variances, since it is insignificant (F=.555,
p=.457> 0.05) hence, equal variances are assumed and
considered the t-value as -.978at 204 degrees of freedom
and which is insignificant (p=.457 > 0.05).Therefore, p
value is above 0.05 H04
null hypothesis is accepted and
can be concluded that there is no significant difference
between male and female towards awareness on social
media- Recruitment.
Table 13 : Descriptive towards awareness on social media- Recruitment
Descriptive
Recruitment
N Mean Std. Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
below 21 Years 49 5.4558 .64709 .09244 5.2699 5.6416 4.00 6.83
+21-30 years 102 5.0441 .67728 .06706 4.9111 5.1771 2.83 6.33
+31-40 Years 39 5.1325 .52730 .08443 4.9615 5.3034 3.83 5.83
Above 40 Years 16 4.8958 .54049 .13512 4.6078 5.1838 4.00 5.83
Total 206 5.1472 .65572 .04569 5.0572 5.2373 2.83 6.83
Above table shows that, the mean values of perception of
citizens below 21 Years is higher than the grand meanand the mean values of the remain three age groups are
lower than the grand mean.
Mohammad Azmat Ali, Patrick Anthony
( 84 )
Table 14 : ANOVA test towards awareness on social media- Recruitment
ANOVA
Recruitment
Recruitment
Sum of Squares df Mean Square F Sig.
Between Groups 6.769 3 2.256 5.601 .001
Within Groups 81.375 202 .403
Total 88.145 205
The table above shows, a significant F value is found; F (3,
202) =5.601; p = 0.001, there is a significant difference exists
among the various age groups of citizens with regards to
their perceptions towards awareness on social media-
Recruitment. Therefore, p value is less than 0.05 H05
null
hypothesis is rejected and concluded that there is a
significant difference exists among the various age groups
of citizens with regards to their perceptions towards
recruitment on social media.
However to know further, which age group of citizens
differ significantly, Turkey HSD post-hoc test is conducted
and the results are presented in table.
Table 15 : Table no: Post Hoc test - Multiple Comparisons towards awareness on social media- Recruitment
process and Education levels
Multiple Comparisons
Recruitment - Tukey HSD
(I) Age (J) Age Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
below 21 Years +21-30 years .41166* .11032 .001 .1259 .6975
+31-40 Years .32330 .13620 .085 -.0295 .6761
Above 40 Years .55995* .18276 .013 .0865 1.0334
+21-30 years below 21 Years -.41166* .11032 .001 -.6975 -.1259
+31-40 Years -.08836 .11949 .881 -.3979 .2212
Above 40 Years .14828 .17067 .821 -.2938 .5904
+31-40 Years below 21 Years -.32330 .13620 .085 -.6761 .0295
+21-30 years .08836 .11949 .881 -.2212 .3979
Above 40 Years .23665 .18843 .592 -.2515 .7248
Above 40 Years below 21 Years -.55995* .18276 .013 -1.0334 -.0865
+21-30 years -.14828 .17067 .821 -.5904 .2938
+31-40 Years -.23665 .18843 .592 -.7248 .2515
*. The mean difference is significant at the 0.05 level.
*. The mean difference is significant at the 0.05 level.
Above table shows that the Turkey HSD Post-Hoc test, it
is found that, there is no significant difference exist
between below 21 years and +21-30 years and below 21
Years (Mean Difference =-.41166) , but citizens belong to
rest of the age groups differ significantly with regards to
their perception towards awareness on social media-
Recruitment process.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 85 )
Table 16 : Descriptive towards awareness on social media- Recruitment Process
Descriptive
Recruitment
Recruitment
N Mean Std.
Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
Intermediate or below
43 5.1512 .54532 .08316 4.9833 5.3190 2.83 5.83
Degree 39 5.2821 .35900 .05749 5.1657 5.3984 4.33 5.83
Post-Graduation 63 4.7381 .65700 .08277 4.5726 4.9036 2.83 5.83
Professional degree 61 5.4809 .65765 .08420 5.3124 5.6493 3.33 6.83
Total 206 5.1472 .65572 .04569 5.0572 5.2373 2.83 6.83
Above table shows that, the mean values of perceptionon
education levels social media- recruitment process of
citizens of Professional degree5.4809and Degree5.2821are
higher than the grand mean and the mean values of the
remain two education levelssocial media- recruitment
process are lower than the grand mean.
Table 17 : Independent Samples test towards awareness on social media- Recruitment Process
ANOVA
Recruitment
Sum of Squares df Mean Square F Sig.
Between Groups 18.046 3 6.015 17.334 .000
Within Groups 70.099 202 .347
Total 88.145 205
The table above shows, a significant F value is found; F (3,
2022) =17.334; p = 0.000, there is a significant difference
exists among the various education levels of citizens with
regards to their Independent Samples test towards
awareness on social media- Recruitment. Therefore, p value
is less than 0.05 H06
null hypothesis is rejected and
concluded that there is a significant difference exists
among the various education levels of citizens with regards
to their perceptions towards awareness on social media-
Recruitment process.
However to know further, which education levels of citizens
differ significantly, Turkey HSD post-hoc test is conducted
and the results are presented in table.
Mohammad Azmat Ali, Patrick Anthony
( 86 )
Table 18 : Post Hoc Test - Multiple Comparisons towards awareness on social media- Recruitment process and
Education level
Multiple Comparisons
Recruitment-Tukey HSD
(I) Education (J) Education Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Intermediate or below Degree -.13089 .13026 .747 -.4683 .2066
Post -Graduation .41307* .11653 .003 .1112 .7149
Professional degree -.32971* .11730 .028 -.6336 -.0258
Degree Intermediate or below .13089 .13026 .747 -.2066 .4683
Post -Graduation .54396* .12003 .000 .2330 .8549
Professional degree -.19882 .12078 .355 -.5117 .1141
Post -Graduation Intermediate or below -.41307* .11653 .003 -.7149 -.1112
Degree -.54396* .12003 .000 -.8549 -.2330
Professional degree -.74278* .10582 .000 -1.0169 -.4687
Professional degree Intermediate or below .32971* .11730 .028 .0258 .6336
Degree .19882 .12078 .355 -.1141 .5117
Post -Graduation .74278* .10582 .000 .4687 1.0169
*. The mean difference is significant at the 0.05 level.
*. The mean difference is significant at the 0.05 level.
Above table shows that the Turkey HSD Post-Hoc test, it
is found that, there is no significant difference exist
between below Professional degree and Intermediate or
below (Mean Difference =-.32971*) , but citizens belong to
rest of the age groups differ significantly with regards to
their perception towards awareness on social media-
Recruitment and Education level.
CYBER EXTORTION (CYBER CRIME)
Even having the uncountable advantages available from
internet,the wrong deeds done through it cannot be
negated. It may be considered as a gift of technology but
depraved sort of beings misuses its application and
commits several crimes and that is the other side of the
coin one can say.
The cyber-crime is not a new phenomenon.People with
extra-ordinary bend of mind, first take into consideration
the wrong means instead of looking at the fairer side of
things. Thatleads to misusing and fraud. For every thief
these is a police to prevent causing damage to one’s
properly so as the crime bureau’s available who traces the
steps of hackers, like with the help of the IP address or so
the operators (criminals) could easily be detected out. It
has been detected that most of the hackers are exploiting
those security systems which are weak and not in under
private controls. They can easily be accessible and the
hackers generally ask to pay in Bit coins, which the
Hyderabad police now call as a hawala system of cyber
space.
What the hackers do after hacking is they procure rouge
websites which they put up for sailing all the confidential
information’s belongs to an individual. The information’s
which they probably sale could range from minor
information’s like email-ID to more personnel documents
like bank status and AADHAAR card number and so on.
For the leakage of all such kind of information the weak,
unguarded systems or operators should not be blamed
alone but some unscrupulous employees are there who
enter such fields just so satisfy their greed. To a lesser extent
the idle government employees could be blamed for not
being attentive in their system to work and alertness
towards security. Releasing personal documents of a
businessman who is supposedly to deal with other dealers
could suffer a huge loss of property whose information
the group of hackers could sell in lakhs.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 87 )
HYDERABAD IN REPORTED CYBER CRIME CASES
Table : 19 Source: The Times of India, Hyderabad on 21 September 2015.
Crime
2012 2013 2014 2015(Till July 21)
Creating fake profiles on social media 4 16 104 49
Abusive/ Threatening SMSs, email, calls and staking 18 45 106 58
pornography - 1 - 0
Matrimonial cheatings 1 2 1 4
Blackmailing - 1 4 3
Job/Visa fraud 1 21 27 17
MLM frauds - 2 1 0
Lottery/Nigerian fraud 3 7 16 8
Hacking 1 - 10 7
ATM/Debit card/Credit Card/Net-banking frauds 6 29 32 35
Loan fraud - - - 7
Identity theft/ Data theft - 1 5 4
Online fraud - 5 12 15
Communal posts 5 10 6 6
Movie uploads ( Copyright violation) 3 - 1 2
Others 5 27 67 25 Total 48 167 392 240
In the above majority cases throughcreating fake profiles
on social media in mail, Facebook, Abusive/ Threatening
SMSs, calls and staking. These crimes, when study
examined 2013 to 2014, the fake profile on social media
crime reported to police increased unbelievable process.
The people get more information of social media for that
gain consumer productions right and basic authorities of
human beings, being that the awareness into existences in
an exclamation. Hacking means illegally of other accounts.
For this hacking people suffer regularly. By using social
media hacking action increasing speed in way, for that
2014 got 10 cases that. Now hacking is taken as very sever
crime for that law is ready to give punishment without
fail. Loan fraud newly 2105 in 10 cases invented. In
previous no fraud was accrued. But presently some
unknown companies are offering loans in very attractively
like without security and low interest method frauds
offering loans and take loans on oral method like this types
of fraudulent companies attracting people very easily. For
that in 2105 loan fraud cases appearing regularly.
The General observations in every year increasing cyber-
crime cases in Hyderabad city. So Telangana state
Government (GHMC) and Hyderabad cyber-crime polices
must take action on hackers and fraud gangs. Now-a-day
Telangana state government is also providing Wi-Fi
facilities in Hyderabad city, so that government could
purchase anti-software products and so, keeping in view
the requirements of the internet users, it will automatically
decrease all sorts of crimes committed through the misuse
of internet. How much the hackers and frauds exploited
internet for their mean interest could easily be noticeable
in the record given above and also the appreciable efforts
made by Hyderabad cyber crimepolice.According to the
experts, only five percent of victims recovered by the online
fraudsters every year and the reason behind this meager
amount of recovery is that the victim’s approach to lodge
complain exceeds time limit.
The estimations made by Central Crime Station (CSC) official’s
exhibits that most of the money cannot be recovered only
due to the late complain made by victims. They have to file
a complaint within 24 hours, their delay in making
complaints makes the matter worse because the money get
transferred on international lines in a very few time.
Joint Commissioner of Police (CCS), Hyderabad toldthat
the victims should know that their delay in lodging
complain lessen the chances oftracing the culprits but if
they approach as early as possible there are chances of
getting money back. As in any online banking transaction
it took 24hours for all gateway clearance. So, with the
victims early approach the culprits can be traced and the
amount can be freezed.
The police also clarifies that one should need to bevery
much sure about issuing their ID cards, voter ID cards and
AADHAAR cards because fraudsters illegally use such
things for opening bank operators did not bother about
investigating the lender or borrowers details and that paved
the way for such crimes. That is why most of the time the
investigators starts enquiring and ends hopelessly nowhere.
Mohammad Azmat Ali, Patrick Anthony
( 88 )
Table 20 : Gender wise perceptions towards awareness on social media- Cyber-crime
Gender - Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
Cybercrime MALE 152 5.3092 .83772 .06795
FEMALE 54 5.4444 .71154 .09683
Above table shows that the mean and standard deviation
for the male citizensperception towards cyber crime Mean
=5.3092, SD=.83772 respectively while for female
employees perception towards supervisor leadership
Mean=5.4444, SD=.71154. Levine’s test is used to analyse
the equality of variances is carried out follows:
Table 21 : Independent Samples test towards awareness on social media- Cyber crime
Independent Samples Test
Levine’s Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
Difference
Lower Upper
Cybercrime Equal variances assumed
3.319 .070 -1.058 204 .291 -.13523 .12782 -.38725 .11678
Equal variances not assumed
-1.143 108.790 .255 -.13523 .11829 -.36969 .09922
The table above shows, Levine’s test is used to analyses
the equality of variances, since it is insignificant (F=3.319,
p=.070> 0.05) hence, equal variances are assumed and we
considered the t-value as -1.058at 204 degrees of freedom
and which is insignificant (p=.070 > 0.05). Therefore, p
value is above 0.05 H07
null hypothesis is accepted and
concluded that there is no significant difference between
the perception of male and female citizen of Hyderabadcity
towards their awareness of social media marketing.
Table 22 : Descriptive towards awareness on social media- Cyber-crime with Age groups
Descriptive
Cybercrime
N Mean Std. Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
below 21 Years 49 5.7143 .79057 .11294 5.4872 5.9414 4.50 7.00
+21-30 years 102 5.2598 .83764 .08294 5.0953 5.4243 2.50 7.00
+31-40 Years 39 5.2692 .60531 .09693 5.0730 5.4654 3.00 6.50
Above 40 Years 16 4.9375 .75000 .18750 4.5379 5.3371 3.00 6.00
Total 206 5.3447 .80707 .05623 5.2338 5.4555 2.50 7.00
Above table shows that, the mean values of perception of
citizens of below 21 years 5.7143 is higher than the grand
mean and the mean values of the remain two education
levels are lower than the grand mean.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 89 )
Table 23 : ANOVA test towards awareness on social media- Cyber-crime
ANOVA
Cybercrime
Sum of Squares df Mean Square F Sig.
Between Groups 10.303 3 3.434 5.630 .001
Within Groups 123.226 202 .610
Total 133.529 205
The table above shows, a significant F value is found; F (3,
202) =5.630; p = 0.001, there is a significant difference exists
among the various age groups of citizens with regards to
their towards awareness on social media- Cyber-crime.
Therefore, p value is less than 0.05 H08
null hypothesis is
rejected and concluded that there is a significant difference
exists among the various age groups of citizens with
regards to their towards awareness on social media- Cyber
crime.
However to know further, which age group of citizens
differ significantly, Turkey HSD post-hoc test is conducted
and the results are presented in table.
Table 24 : Post Hoc test - Multiple Comparisons towards awareness on social media- Cybercrime with Age
Multiple Comparisons
CybercrimeTukey HSD
(I) Age (J) Age Mean Difference
(I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
below 21 Years +21-30 years .45448* .13576 .005 .1028 .8062
+31-40 Years .44505* .16760 .042 .0109 .8792
Above 40 Years .77679* .22489 .004 .1942 1.3594
+21-30 years below 21 Years -.45448* .13576 .005 -.8062 -.1028
+31-40 Years -.00943 .14705 1.000 -.3904 .3715
Above 40 Years .32230 .21002 .419 -.2218 .8664
+31-40 Years below 21 Years -.44505* .16760 .042 -.8792 -.0109
+21-30 years .00943 .14705 1.000 -.3715 .3904
Above 40 Years .33173 .23188 .482 -.2690 .9324
Above 40 Years below 21 Years -.77679* .22489 .004 -1.3594 -.1942
+21-30 years -.32230 .21002 .419 -.8664 .2218
+31-40 Years -.33173 .23188 .482 -.9324 .2690
*. The mean difference is significant at the 0.05 level.
Above table shows that the Turkey HSD Post-Hoc test, it
is found that, there is no significant difference exist
between below Above 40 Years and below 21 Years (Mean
Difference .77679*) , but citizens belong to rest of the age
groups differ significantly with regards to their perception
towards awareness on social media- Cybercrime with Age
group.
Mohammad Azmat Ali, Patrick Anthony
( 90 )
Table 25 :Descriptive towards awareness on social media- Cyber-crime
Descriptive
Cybercrime
N Mean Std.
Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
Intermediate or below
43 5.2209 .64828 .09886 5.0214 5.4204 2.50 6.00
Degree 39 5.3205 .50637 .08108 5.1564 5.4847 3.00 6.00
Post-Graduation 63 4.9603 .74759 .09419 4.7720 5.1486 3.00 6.50
Professional degree 61 5.8443 .87817 .11244 5.6194 6.0692 4.00 7.00
Total 206 5.3447 .80707 .05623 5.2338 5.4555 2.50 7.00
Above table shows that, the mean values of perception of
citizens of Professional degree 5.8443.is higher than the
grand mean and the mean values of the remain three
education levels are lower than the grand mean.
Table 26 : ANOVA test towards awareness on social media- Cyber crime
ANOVA
Cybercrime
Sum of Squares df Mean Square F Sig.
Between Groups 25.213 3 8.404 15.673 .000
Within Groups 108.316 202 .536
Total 133.529 205
The table above shows, a significant F value is found; F (3,
202) =15.673; p = 0.000, there is a significant difference
exists among the various education levels of citizens with
regards to their perceptions towards their awareness on
social media- Cybercrime. Therefore, p value is less than
0.05 H09
null hypothesis is rejected and concluded that
there is a significant difference exists among the various
education levels of citizens with regards to their
perceptions towards their awareness on social media-
Cybercrime.
However to know further, which education levels of citizens
differ significantly, Turkey HSD post-hoc test is conducted
and the results are presented in table.
Table 27 : Post hoc test - Multiple Comparisons towards awareness on social media- Cybercrime with Education
Multiple Comparisons
Cybercrime - Tukey HSD
(I) Education (J) Education Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
Intermediate or below
Degree -.09958 .16192 .927 -.5191 .3199
Post-Graduation .26061 .14485 .277 -.1146 .6359
Professional degree -.62333* .14581 .000 -1.0011 -.2456
Degree Intermediate or below .09958 .16192 .927 -.3199 .5191
Post-Graduation .36020 .14920 .078 -.0263 .7467
Professional degree -.52375* .15013 .003 -.9127 -.1348
Post-Graduation Intermediate or below -.26061 .14485 .277 -.6359 .1146
Degree -.36020 .14920 .078 -.7467 .0263
Professional degree -.88394* .13154 .000 -1.2247 -.5432
Professional degree
Intermediate or below .62333* .14581 .000 .2456 1.0011
Degree .52375* .15013 .003 .1348 .9127
Post-Graduation .88394* .13154 .000 .5432 1.2247
*. The mean difference is significant at the 0.05 level.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 91 )
Above table shows that the Turkey HSD Post-Hoc test, it
is found that, there is no significant difference exist
between Professional degree and Intermediate or below
(Mean Difference .62333*) , but citizens belong to rest of
the age groups differ significantly with regards to their
perception towards awareness on social media-
Cybercrime with education.
Table 28 : Antivirus software mechanism
Yes No Total
Antivirus software mechanism and use Frequency 165 41 206
Percent 80.1% 19.9% 100%
Majority of citizens have awareness and using antivirus software in their systems for pertaining their on line
transactions.
Table no: 29 Awareness on the following cyber frauds
Q) 15 Awareness Yes No Total
A Salami fraud Frequency 126 80 206
Percent 61.2% 38.8% 100%
B Phissing Frequency 53 153 206
Percent 25.7% 74.3% 100%
C Spam Frequency 154 52 206
Percent 74.8% 25.2% 100%
D Creating fake profiles on social media
Frequency 158 48 206
Percent 76.7% 23.3% 100%
E Abusive/ Threatening SMSs, email, calls and staking
Frequency 156 50 206
Percent 75.7% 24.3% 100%
F Pornography Frequency 153 53 206
Percent 74.3% 25.7% 100%
G Matrimonial cheatings Frequency 189 17 206
Percent 91.7% 8.03% 100%
H Blackmailing Frequency 192 14 206
Percent 93.2% 6.8% 100%
I Job/Visa fraud Frequency 177 29 206
Percent 85.9% 14.1% 100%
J MLM frauds Frequency 152 54 206
Percent 73.8% 26.2% 100%
K Lottery/Nigerian fraud Frequency 140 66 206
Percent 68% 32% 100%
L Hacking Frequency 151 55 206
Percent 73.3% 26.7% 100%
M ATM/Debit card/Credit Card/Net-banking frauds
Frequency 156 49 206
Percent 75.7% 24.3% 100%
N Loan fraud Frequency 187 19 206
Percent 90.8% 9.2% 100%
O Identity theft/ Data theft Frequency 145 61 206
Percent 70.4% 29.6% 100%
P Online fraud Frequency 190 16 206
Percent 92.2% 7.8% 100%
Q Communal posts Frequency 154 52 206
Percent 74.8% 25.2% 100%
R Movie uploads ( Copyright violation)
Frequency 139 67 206
Percent 67.5% 32.5% 100%
In the above table in majority citizens wereawareness on
the cyber frauds, except of salami frauds, phishing,
Creating fake profiles on social media,Abusive/
Threatening SMSs, email, calls and staking, Lottery/
Nigerian fraud and Movie uploads. Therefore awareness
need to the created to the citizens about the going menace
of cybercrimes.
Mohammad Azmat Ali, Patrick Anthony
( 92 )
FINDINGS AND SUGGESTIONS
1) Awareness on social media- marketing, recruitment
and cybercrime indicates that there is significant
difference between male and female citizens of
Hyderabad and significant difference exists among
the various age groups, education of citizens.
2) Professional degree citizens have more awareness
on social media- marketing, recruitment and
cybercrime.
3) In majority cases it was observed that creating fake
profiles on social media in mail, , Abusive/
Threatening SMSs, calls and stalking is very
common.
Therefore,there is need to create the awareness about
cybercrime and the utility of social media.
CONCLUSIONS
Social media’ is a broad term for applications or tools that
enable the creation and exchange of user-generated content
over the Internet.The present era can be termed as jet era as
the pace of life is morning vehemently and as such people
are always in need for fast services available to them to
fulfill such requirements the technology has developed to
such an extent that usage of internet expanded
unpredictably high.The study is to the implications of
social media on marketing, recruitment process and
awareness of cyber-crime of citizens of Hyderabad city.
The usage of social media role is increasing day- to-day.
All marketing transactions are linked with internet.
Awareness on social media- marketing, recruitment and
cyber crime that there is different significant difference
between male and female citizens of Hyderabad and
differentsignificant difference exists among the various
age groups, education of citizens. Professional degree
citizens have more awareness on social media- marketing,
recruitment and cybercrime. Majority cases through
creating fake profiles on social media in mail, , Abusive/
Threatening SMSs, calls and staking in Hyderabad city.
Therefore awareness create to citizens cybercrime police
and Government of Telangana state.
LIMITATIONS OF THE STUDY
1) Responses were collected only from 206 sample from
Hyderabad city only
2) Sample drawn from Hyderabad city, so study limit
to only Hyderabad city
FUTURE RESEARCH
1) To statements the theory and utility os social media
studies need to be conducted
2) Social media taken only three perception only, future
studies can include other perceptions.
REFERENCES
Acquisti, A., & Gross, R. (2006). Imagined communities:
Awareness, information sharing, and privacy on the
Facebook. In P. Golle& G. Danezis (Eds.),
Proceedings of 6th Workshop on Privacy Enhancing
Technologies (36-58). Cambridge, UK: Robinson
College
Adamic, L. A., Büyükkökten, O., & Adar, E. (2003). A social
network caught in the Web. First Monday, 8 (6).
Retrieved July 30, 2007 from http://
www.firstmonday.org/issues/issue8_6/adamic/
index.html
Backstrom, L., Huttenlocher, D., Kleinberg, J., &Lan, X.
(2006). Group formation in large social networks:
Membership, growth, and evolution. Proceedings
of 12th International Conference on Knowledge
Discovery in Data Mining (44-54). New York: ACM
Press
Barnes, S. (2006). A privacy paradox: Social networking in
the United States. First Monday, 11 (9). Retrieved
September 8, 2007 from http://
www.firstmonday.org/issues/issue11_9/barnes/
index.html
Benzie, R. (2007, May 3). Facebook banned for Ontario
staffers. The Star. Retrieved July 21, 2007 from http:/
/www.thestar.com/News/article/210014
David Haynes , Lyn Robinson , (2015) “Defining user risk
in social networking services”, Aslib Journal of
Information Management, 67(1), pp.94 – 115
Dwyer, C., Hiltz, S. R., &Passerini, K. (2007). Trust and
privacy concern within social networking sites: A
comparison of Facebook and MySpace. Proceedings
of AMCIS 2007,
H.Tan and J.Guo some methods to Depress the Risks of
the Online Transactions, “ICEC,15-17 August 2005,
XI an China.
Social Media-Marketing, Recruitment and Cyber Crime – A Case Study of Hyderabad City
( 93 )
I-Cube report (2008) “Available at www.iami.in/Upload/
Research/I Cube_2008_Summary_Report_30.pdf
Keystone, CO. Retrieved September 21, 2007 from http://
cs is .pace .edu/~dwyer/research/Dwyer
AMCIS2007.pdf
Haythornthwaite, C. (2005). Social networks and Internet
connectivity effects. Information, Communication,
& Society, 8 (2), 125-147.
Lisa Harris, Alan Rae, (2009) “Social networks: the future
of MARKETING for small business”, Journal of
Business Strategy, 30(5) 24 – 31.
Paolillo, J. C., & Wright, E. (2005). Social network analysis
on the semantic web: Techniques and challenges
for visualizing FOAF. In V. Geroimenko& C. Chen
(Eds.), Visualizing the Semantic Web (229–242).
Berlin: Springer.
RodericBroadhurst, (2006) “Developments in the global
law enforcement of cybercrime”, Policing: An
International Journal of Police Strategies &
Management, 29(3) 408 – 433.
Stutzman, F. (2006). An evaluation of identity-sharing
behavior in social network communities. Journal of
the International Digital Media and Arts
Association, 3 (1), 10- 18.
Wellman, B. (1988). Structural analysis: From method and
metaphor to theory and substance. In B. Wellman &
S. D. Berkowitz (Eds.), Social Structures: A Network
Approach (pp. 19-61). Cambridge, UK: Cambridge
University Press.
WEBLIOGRAPHY
http://www.ebizmba.com/articles/social-networking-
websites
www.ennadu.com
www.namasthetelangananews.com
www.siasathenews.com
http://timesofindia.indiatimes.com
Mohammad Azmat Ali
Department of commerce, Osmania University,
Hyderabad- 500007, Telangana State
E-mail: [email protected]
Dr. Patrick anthony
Assistant Professor
Department of Commerce, Osmania University,
Hyderabad- 500007, Telangana State
E-mail: [email protected]
Mohammad Azmat Ali, Patrick Anthony
( 94 )
INTRODUCTION
The natural way of learning by children is mainly through the use of senses. Of all these
senses, the sense of sight provides rich experiences to the individual. Most of the
experiences that a person gains in this world are received through this sense of sight.
Impressions created by the sense of sight cannot easily be erased. A picture will not only
attract the attention of a pupil but also hold it for long as it appeals to the sense of sight.
That is why; visual literacy is given more importance today.
Key words:
Students Attitude, Audio
Visual aids, Graphs,
Diagrams, Posters, Maps,
Comics, Cartoons, Charts,
Video Conference.
Skilled Based Learning System for Employability –With Reference to B-Schools from EmpiricalPerspective
R.Ramachandran
ABSTRACT
The Teacher must use different innovative teaching technologies that appeal to the different
senses. An Audio-visual aids is not only seen but also heard. When such a Audio-visual aids that
appeals to different senses, called multi-sensory approach, is used, it makes teaching and learning
effective. The Teacher can make use of Audio-visual aids to suit his purpose and can make clear
a difficult concept even to a below-average student very easily. Audio-visual AIDS supplies a
concrete basis for conceptual thinking. They give rise to meaningful concepts to words enriched
by meaningful association. Researchers have also recommended that in education, the appeal
should be to the mind, chiefly through the visual and auditory sense organs, since it is possible
that most of our learning is absorbed through these. Audio Visual aids or Graphic aids are the
form of visuals that are represented on plane surface. The subject matter areas that are represented
in Audio Visual aids or Graphic aids are in an abridged and easily understandable form. They
convey meaning mainly through relatively conventionalized symbols that are nearer to reality
perceptually than verbal symbols. They secure the attention of the pupils by their attractive
format and simplicity of layout. They convey the expected message by combination of visual
and pictorial message made meaningful by suitable captions. Pictures and words blended in
harmony deliver the required information. The idea conveyed by any graphic aid should be a
single concept. The layout and words should not be complicated so as to puzzle the viewer and
make him lose interest in the same. The statement “one good visual which can secure and
maintain attention and educate the viewer in the desired area is worth a thousand words” is
quite correct. Graphics could be truly considered as the shorthand language of the idea presented.
The criteria for good graphics are that they should be simple, bold, legible brief and have
adequate margins. The present paper finds out the students attitude towards audio-visual aids
used by the Teachers. A sample of 500 students of graduates and post graduate of higher
learning B-Schools in Tamil Nadu selected district namely, Cuddalore, Trichy, Coimbatore,
Chennai, Tirunelveli on the basis of convenient sampling technique. The results revealed that
the analysis the result concluded that the students have positive attitude towards audio-visual
aids used by the Teachers and emerge new dimension for learning and applicability for
employability skill development.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 95 )
EMPLOYABILITY
The employability is buzz word in the recent days. How to
view employability? There is no any agreement on this
issue till the time. In a general sense, employability means
having employed. Employability refers to a person’s
capability of gaining initial employment maintaining
employment, and obtaining new employment if required
(Hillage and Pollard, 1998). Employability is the ability of
the graduate to get a satisfying job. (Harvey, 2001).
Employability is having a set of skills, knowledge,
understanding and personal attributes that make a person
more likely to choose and secure occupations in which
they can be satisfied and successful (Pool and Sewell,
2007). Employability skills as including personal image,
international skills, and good habits and attitudes,
Employability is the capability to move self-sufficiency
within the labour market to relalise potential through
sustainable employment, The probability, for a given
groups, at a given time, of finding a job or emerging from
unemployment.
SKILLS BASED EDUCATION – NEED OF THE HOUR
In an Indian setting, the lack of facilities and lack of
motivation in acquiring knowledge for the sake of
knowledge has always been felt during discussion and
interaction in classroom setting. There is a felt-need among
the present school Teachers to make use of newer
techniques and strategies for better understanding and
better presentation of knowledge of science in the school
curriculum. In India, the survey conducted by the Kothari
Commission (1964-66) recognized the lack of quality in
science teaching and called for evolving new strategies
and techniques so as to improve the quality of science and
research. The existing organized methods of teaching-
learning cannot withstand the challenge of the tremendous
development of new ideas and the new information
technologies which are independently moulding the
behavior and learning styles of individuals and societies
at large. This means that the existing teaching-learning
strategy has to be changed.
An effective teaching method requires selection and
application of appropriate technological devices to
maximize the learning. The recent development in science
and technology has brought out many technological tools
to keep the Teachers and learners perform their
responsibilities effectively and efficiently. A judicious
application of technology makes learning environment
more attentive and interesting. Particularly, the teaching
of science subjects requires extensive application of
information and technology in order to maintain a good
learning environment. Kothari Commission (1964-66) tells
that there are three kinds of people: i) those who learn
through hearing, ii) those who learn only after seeing and,
iii) those who learn only after hearing and seeing. When
computers are introduced into the learning environment,
all the three kinds of people will be benefited. The
integration of audio, video along with interactive mode
constitutes the concept of multimedia.
Audio-visual AIDS (Attention, Interest, Desire, and
Satisfaction) technology for education offers a number of
benefits. They allow the Teacher to structure and present
the information with varying special effects to the students.
They can also be used for the storage of audio-visual
information of various types. Audio-visual AIDS provide
a lot of benefits. The benefits for learners include flexibility
of scheduled instruction at a location convenient to
learners, reduced student time, assured progress in skill
development, increased achievement and increased
retention and continuous report to the learners of progress
and accomplishments, specified performance criteria, good
response and feedback. The application of Audio-visual
AIDS would definitely create a good learning environment
in classroom, sustaining attention and motivating the
students to learn effectively. The application of Audio-
visual AIDS may create a congenial learning climate in
schools and can bring real life situations. The investigator
has chosen the topic for the present study in order to
address the problem faced by Teachers, teaching science,
to foster involvement in new teaching approaches, to get a
feeling of satisfaction through learning in the classroom,
to create joyful learning environment and to stimulate
active information processing for effective learning and to
develop their employability skills.
Audio-visual AIDS are the best attention-compellers. They
arouse interest and motivate the students to action and
stimulate physical and mental activity. They save time and
the learning is substantial and durable. The knowledge
gained by the pupil within a short period is retained in his
memory for a longer period. By reviewing and rehearsing
the animated pictures, students get an opportunity to
correct misconceptions and secure additional ideas. A film,
after having been shown to the students, can be reviewed
by active discussion among students and with the Teacher.
By using the Audio-visual AIDS again, the students correct
their mistakes and get a chance to revise what they have
learnt and at the same time gather some additional
R.Ramachandran
( 96 )
information which they had unconsciously overlooked.
An Audio-visual AIDS matches inner urges, instincts, basic
drives and motives of the students and thus proves a potent
motivating force for energizing the learner to learn
effectively. The root of all understanding, thinking and
attitude formation is real experience. But in the classroom
it is not possible to provide such real experience. In such
circumstances, Audio-visual AIDS enables, to some extent,
duplication of such real experience through graphics.
REACH OUT STRATEGY
Successful learning relies on formation of certain strategies
as to adopt or employ definite skills to develop their traits
and personalities for such aids are used. They are;
Graphics are only two-dimensional and should be carefully
planned to offset the limitation. An Audio Visual aids or a
graphic aid by eliminating non–essentials and by using
bold symbolic representations with attractive portrayal
should be able to create interest and secure the attention of
the pupils. Since the message to be conveyed pertains to a
single concept and hence brief, the viewer will not get
perplexed on being exposed to the visual but will try to
read and understand what is implied (visual and
words).Audio Visual aids or a graphic aids could easily
be prepared by and Teacher using simple materials that
are easily available and stored for future use. Making
graphics should form an integral part of the Teacher’s
preparation for teaching. Almost any material involving
illustrations is basically graphic in nature. There can be
an infinite variety of graphic materials. It is difficult to
give a rigid list of these materials. However, through
common usage, the principal categories of graphic aids
described below.
GRAPHS
Line graphs, bar graphs, pictorial graphs and sector (pie)
graphs are the different types of graphical representations.
The nature of variation of two dependent quantities could
be very easily presented by graphical representation.
Interpretation of graphs is easy and very quick. Correct
inferences could be drawn with ease. Pictographs are
graphical representations which use simplified
representational figures.
DIAGRAMS
Diagrams could be used to explain many facts easily using
a variety of symbols and labels. They can be truly
considered as brief visual synopses of facts to be presented.
Diagrams can explain facts more easily than charts.
Technical fields like engineering rely heavily on diagrams
to communicate, detailed, precise information (blueprints).
POSTERS
The poster is a bold basic representation in striking colour
of an idea or concept in an attractive form. A poster catches
the eye and makes the viewer go through the message
conveyed. The visual design is dramatic and hence
dynamic in appeal. Posters are used widely in all walks of
life, to convey forcibly the desired information to the
layman. Posters always attractive and catchy. Good posters
are simple as well as striking. Schools can use
professionally prepared posters for occasions like “wildlife
week”, “Vanamahotsava” etc. and they themselves may
prepare posters creatively for specific needs.
MAPS
A map is an accurate representation on a plane surface in
the form of a diagram drawn to scale, the details of
boundaries of continents, countries etc. Geographical
details like location of mountains, rivers, altitude of a place,
contours of the earth surface and important locations can
also be represented accurately with reference to a
convenient scale with a suitable colour scheme.
COMICS
A comic strip is a form of cartoon depicting a story in
sequence. The events are arranged in the proper order in
an attractive pictorial form appealing much to lower age
groups.
CARTOONS
A cartoon is a metaphorical presentation in the form of a
picture or a sketch. It vigorously presents and dramatizes
humour, satire, caricature or exaggeration about an idea, a
person or a situation. It is expression of humour. By a
humorous presentation, often exaggerating on any
characteristic visual aspect it attracts the attention of the
viewer. A cartoon like the poster is universal in appeal
and conveys only one idea.
CHARTS
Any visual information developed on the chalk board by
the Teacher in the presence of pupils is bound to be most
effective. The effectiveness could be further increased by
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 97 )
the Teacher making judicious use of chalk pieces of
different colours to stress specific aspects. This may not be
possible because of practical reasons. The picture to be
drawn may be simple and may have too many details and
hence much time would be wasted in drawing them on
the chalk board. Further, all Teachers may not have
sufficient skill to draw presentable pictures of diagrams.
While a diagram is a condensed drawing consisting of
lines and symbols which represent the object process, a
chart is a combination of pictorial, graphic, numerical or
verbal material which presents a clear visual summary. It
helps handy to the Teacher. If suitable charts are available
the Teacher could make use of the during teaching. This
will result in considerable saving of time. The same chart
could be used over a number of years. A good collection of
charts in an institution should help the Teacher
considerably. Tree charts, time line charts, Technical
diagrams and process diagrams are also commonly used
in classrooms. Readymade charts are available for use in
almost all areas in all subjects. But it is not difficult for any
Teacher to prepare a chart. In fact a Teacher would find a
chart prepared by him incorporating his own ideas and
lines of approach of the specific topic more useful to him,
when a chart is used for teaching it is essential for all
pupils to focus their attention on any specific aspect in the
chart pointed by the Teacher. Hence the chart should be
large, every detail depicted should be visible to every pupil
in the class wherever he is sitting. The chart should not
contain too minute details or too much written matter
making it necessary for any observer to come near and see.
Simple charts with a neat professional appearance can be
made in minutes with coloured paper, charting tapes and
adhesive letters. Charts are also used to create with a neat
suitable environment in the classroom, laboratory and
contain more written and pictorial information. Each chart
should display information only about one specific area
in a subject. During times when there is no actively in the
room pupils could go near the chart and study its contents.
Such display charts will provide useful visual material
for the pupils when they are not engaged otherwise.
EDUCATIONAL BROADCASTS
The radio broadcast is a powerful medium for mass
communication. In the present day, broadcasts from a
powerful transmitter can be received at distant places. The
range of many transmitters is great and the area covered is
vast. Communication from any part of the world to any
other place, however remote and wherever located, is
possible. Transistor receivers do not require any mains
power supply, but could be operated by dry cells.
Advancement in electronics particularly in the field of solid
state circuits (transistors), integrated circuits, etc., enables
clear sound reception from any fairly powerful transmitter
without much interference even in remote areas. Medium
wave transmitters cater to the nearby surrounding areas
and the same programme when broadcast on short wave
makes reception at distant places possible. Frequency
modulation broadcasts recently introduced in Madras will
enable quality reception without any background noise.
THE RADIO AS AID TO TEACHING
The radio besides being a mass media of communication
can also play a major role in imparting instruction to
school children. Such of these broadcasts are styled as
educational broadcasts. These broadcasts are made during
specific days at specific school hours, mainly for the benefit
of the educational institutions. These broadcasts are on
curricular subjects based on the prescribed syllabus
sequenced to synchronies with the class lessons.
Educational broadcasts will considerably help the Teacher
to supplement his classroom instruction. The Teacher
should prepare the pupils so that they will benefit to the
maximum extent by listening to a specific broadcast. He
should plan for effective listening and also prepare suitable
follow-up work for consolidation.
Booklets are the details of programmes of educational
broadcasts for the year are prepared and printed in
advance by All India Radio and made available to
educational institutions at the beginning of each academic
year. Programmes are arranged separately for the benefit
of elementary, middle and high schools and for university
correspondence course students. The main aim of any
broadcast for educational purpose should be to inspire
the student to gain greater knowledge. This can be achieved
by (a) broadcasting biographies of people who have
contributed to advancement of knowledge in specific areas,
like Sir Isaac Newton, Charles Darwin, Michael Faraday,
Sir C.V.Raman etc., (b) broadcasting events which are
important landmarks in history and which revolutionised
the thinking and life of man, for example, Industrial
Revolution, French Revolution and, Freedom Struggle of
India; (c) broadcasting about progress in science and
technology, industry, practical results of such progress,
etc. Listening to such broadcasts will arouse the interest of
the pupils and will create a desire to acquire greater
knowledge and skill. The library, the laboratory and the
R.Ramachandran
( 98 )
workshop will be put to greater use and with an additional
purpose in a meaningful way.
Listening to a preview of a newly introduced commercial
product, for example, a new model of a bicycle, stressing
its design, special features introduced for safety, economy
and comfortable travel will be of good educational value.
Broadcasts of reviews of good books recently published
will make the pupil know about the same and their special
values. Broadcasts could be made of recording of sound of
a factory as the background superimposed with suitable
commentary. Narration of details of conducted tours
around a place with suitable locational backgrounds will
be very useful to give an idea of the tour. Suitable musical
background makes the programme attractive and more
realistic. Listening to broadcasts of dramas, recitation of
poems, narration of stories, readings and recitations from
books, rendering of classical, instrumental and light music
helps towards harmonious development of the mental
growth of pupils and makes them fit to be useful members
of society.
TAPE – RECORDER
A Tape- recorder is used to record sounds on magnetic
tape which can be reproduced at will as many times as
required. When a new recording is made, the recording
already contained in the tape is automatically erased. A
recorded tape, if kept away from strong magnetic fields,
will retain the recordings for a very long time.
SLIDE – TAPE PRESENTATION
In the centers of higher learning today, the teaching aid
often used with advantage is slide-tape sequence. In this a
pack of slides replaces the filmstrip and this pack of slides
is used in sequential conjunction with correlated
recordings in cassette tape. A pack of slides has certain
decided advantages as compared with filmstrip in such a
presentation: the slides needed for the teaching programme
could easily be prepared by the Teacher to suit his/her
requirements; diagrams and photographs may be suitably
included as needed; the presentation sequence of slides
could be altered to suit groups of pupils of differing entry
behaviour; any particular slide may be deleted or a new
one added to suit changing requirements of instruction;
any slide in which the visual may have become obsolete or
may be presented in a better way could be replaced by a
more suitable one.
Slide-tape presentation has a dynamic appeal to pupils
since the associated sound effects and suitable
commentary are played along-side. The Teacher, with a
little training, can use the tape-recorder with ease and
effectiveness. The Teacher’s commentary may be made
more attractive and appealing with suitable background
music and sound effect. These could be easily recorded by
any Teacher with some amount of imagination. Here, the
Teacher can first record the complete commentary for the
slide sequence in one table. The background music suitable
to create proper mood for understanding the slide visuals
may be recorded in another tape, along with associated
background sounds. For example, if a horse rider is shown
in the slide, the pounding of hooves may be incorporated
in the background effect; if a jungle scene is to be shown,
the cry of animals, the sound of running water, from the
background. The final recording is made with the
commentary replayed along with the background music
and sound effects on two tape –recorders and the mixed
re-recording of the final tape done on a third recorder. All
recordings should preferably be made during night time,
when disturbing sounds will be minimal. When sound
material for use with a particular slide has been recorded,
a single short peal from the bell will indicate to the operator
of the slide projector that the side being shown should be
changed and the next one brought on. Many projectors
with automatic slide changing mechanisms are now
available and a high frequency sound pulse from the tape
acts as a cue for automatic slide change in some of these.
Present day slide projectors are more compact and efficient
than those of the past and are fitted with low voltage
halogen lamps and utilise a large percentage of light output.
The slides produced using a camera with near focusing
attachment, are made using 35m.m. perforated film with a
picture size of 36mmx24mm. Slides can be made with black
and white film is more suitable than coloured film. From
the resulting negative, a positive film print is taken and
this positive could be used to get further prints which
would display the diagrams clearly as bright lines on dark
backgrounds. Such lines of diagrams can also be toned to
suitable colours using required dyes (dye toning).
The mounted slides are kept in the required sequence in a
linear or circular magazine for use. With non-automatic
slide projectors, the operator should change the slide on
hearing the cue-bell from the recording in the cassette tape
recorder. The same set of slides could be used for instruction
in different languages with suitable sound tracks recorded
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 99 )
in different languages in separate cassettes. The recorded
sound could be easily changed by recording if needed.
The slide-tape sequence, suitably produced can be almost
as effective and dynamic as a motion picture and it appeals
to the eye and ear of pupils.
TELE- LECTURE
Tele-lecture represents a means of conducting off-campus
courses in a number of widely scattered sites through the
use of tape-recorded lecturers and amplified telephone
calls, with the professor remaining on campus for all of
the class session. Tele-lecturer can be offered in any
community that has telephone service. Instead of the
instructor travelling to various places for meeting a fixed
number of students as is necessary for an off-campus class,
tele-lecture can combine a number of small cases.
Each week participating classes receive by mail a one or
two-hour taped lecture. The taped lecture is played at a
class session arranged by the class at site at a time and
place convenient to the group. In addition, each week at a
designated time, all participating classes meet at a designed
spot. They are connected by an amplified telephone call to
the professor on the campus. This call will 50 minutes and
is used to answer questions, clarify lectures, a supplement
to the lecture material which was taped. Two-way
communication between students and the professor is thus
provided. A student moderator can control the microphone
placed in the class. Tele-lecture can benefit high school
students also for they can interview a local businessman
and get vocational guidance by this method. One class
member in each site is designated as the “On-Site Course
Assistant”. He is responsible for registration, taking
instructions from the course Assistant”. He is responsible
for registration, taking instructions from the course director,
receiving tapes, administering tests, returning all materials
to the college and carrying all, necessary communications
with tele-lecture coordinator in the campus office when a
video-tele-lecture can be arranged, closed circuit television
add an extra dimension. Students can see the speaker as
he answers their questions.
INSTRUCTIONAL TELEVISION (ITV)
Many telecasts, in addition to programmes exclusively for
schools, can be considered educational in a general way
and viewed by pupils with advantage. Hence Educational
Television (ETV) includes programmes whose primary
interest is to educate rather than entertain. ETV generally
includes instructional television and non-commercialised
television programmes. Instructional television (ITV)
includes programmes related directly to an organized
programme of formed instruction and is directed to
individual viewers who come under non-up work by the
Teacher is essential to consolidate the gain of knowledge.
VIDEOCASSETTE RECORDER
The video cassette which has made its appearance in recent
times has helped to enhance the educational and
entertainment value of TV. Such recorders and the software
needed for them, such as video cassettes are available now
in a variety of makes and are now fabricated by India
manufactures also. At present such recorders appear to be
a bit costly; but their value and popularly are bound to
make their prices lower in the near future and they will
have a place in classroom instruction on a fairly large
scale even in the near future. Not only can many pre-
recorded cassettes of interest and value to pupils be
recorded and educational TV programmes telecast over
networks can be reordered and replayed whenever
necessary. All video cassette recorders (VCR) made now
record events in colour and are played back using colour
monitors (TV sets). The replay in colour with associated
sound makes viewing dynamic and its impact on the
viewers is considerable. The recording can be played back
on one or more monitor’s simultaneously facilitating large
audience viewing in different classrooms. Operating a
VCR is easy and there is no complicated threading as in
the case of motion picture projectors; and the VCR is more
portable and versatile than the motion picture
projector.Here mention may also be made of new projection
TV systems with 6’-10’ screens and facilities for front of
back projection. These, when they become popular in use,
will be ideal for large audience in school and community
viewing.
VIDEO TAPE
Storage of instruction for repetitive use is easily
accomplished now with the use of video tapes. They may
be played back though monitors. Aural Aids and TV in a
studio or classroom. Video tape can provide virtually
instantaneous reproduction and in that sense, it is superior
to films. Video cassettes player to his own television set,
inserts a cassette and presses a button. The obvious
advantage of the cassette is that it is portable and can be
used and reused at will.
R.Ramachandran
( 100 )
COMPUTERS
Computer is most important invention which has capacity
for storing or memorising a large amount of information
and producing or retrieving any of them when called for.
The increasing importance of informatics in day-to-day
life has resulted in the emergence of computers in education
at the international level. The worldwide recognition
gained for the importance of computers has compelled
educationists to revise the existing curricula to include
informatics components. Even the developing countries
have realized that unless they invest heavily in computer
education, they will be left behind in the informatics
revolution. Computers are being used in education to
prepare the children for the informatics future by training
them in programming and related skills for work in the
informatics industry. They are also being used as
educational aids to improve children’s skills in academic
subjects at all levels of education. Introduction of
computers in education has brought out changes in the
content and methods of education. However, lack of
resources remains one of the main obstacles to the
introduction and development of informatics in education
in a large way in developing countries.
The most striking innovation in the field of educational
technology is the use of computers. Computer is included
in the hardware approach of educational technology. It is
one of the machines of automation in teaching and
learning and is used for presenting individualized
instruction. The main objective of teaching through
computer is to provide the needed flexibility for
individualizing the educational process. It meets the
specific needs of the student in a way in which is almost
impossible to do in a face-to face student-Teacher
relationship.
Computers should have a major role in the teaching-
learning process. Computers have become an essential
class room tool for the acquisition, analysis, presentation,
and communication of data in ways that allow students
to become active participants in research and learning.
The computers offer students very important resources for
learning concepts through simulations, graphics, sound,
data manipulation and model building. Computers can
improve scientific learning and facilitate communication
of ideas and concepts. There are three roles for computer
in education. First, it functions as a tutor for students by
presenting material, evaluating responses, and depending
on the basis of the evaluation, deciding what to present
next. Second, it is a tool that helps students perform
calculations, analyze data, keep records, or write papers.
Third, it functions as tutee by having told what to do
through programming. A computer program can be
designed to create models for experimental purpose.
Students, those particularly in higher educations, have
the benefits of using computer as a computational tool.
They learn a programming language and write a program
to solve some of their course work problems treating the
computer as an aid in much the same way as a slide rule
or a set of mathematical tables. Computers are capable of
giving almost instant feedback, tirelessly, no matter how
many learners ‘get it wrong’ and it is equally well known
that human tutors have limited value when it comes to
learners repeatedly getting things wrong.
Power Point Presentation and Video Conferencing
Multimedia refers to any computer-mediated software or
interactive application that integrates text, color, graphical
images, animation, audio sound, and full motion video in
a single application. Multimedia learning systems consist
of animation and narration, which offer a potential venue
for improving student understanding. Multimedia
programme is an integral part of the educational
technology. As a technique, it offers a high potential in
application at different stages of education for the purpose
of enhancing the teaching and learning processes, as is
evident from the experience of developed countries. The
integration of multimedia technology into the
communication environment has the potential to
transform the students from passive recipients of
information to active participants in a media-rich learning
process. The introduction of multimedia or any other
computer-based information technology is not intended
to substitute a presenter. This new technology is intended
to provide the presenter with a powerful tool that can
greatly enhance communication by delivering a
multisensory experience. With interactive multimedia
technology, a Teacher can communicate with the students
by means of a presentation that becomes more than
message-it becomes an active, exciting experience in a
multisensory environment to create a multisensory
experience. Multimedia reaches users in many different
ways, enabling them to retain more knowledge and
increase their understanding. There are 4 steps in learning
like attention, rehearsal, encoding and retrieval. A well
designed multimedia application demands the
simultaneous attention of several senses through dual
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 101 )
encoding or the process of appealing to more than one
sense simultaneously. Dual encoding facilitates and
enhances the rehearsal process. Multimedia helps retrieval
by associating sound, text and images with the concept
being presented. Using text, images, animation and sound
simultaneously greatly improves the students’ retention
of the knowledge and directs the students’ attention to
classroom (Louis, 2001). It consists of the combination of
video and movie clips and sound, text and graphic files
all controlled by a piece of software and a computer which
is equipped with a sound card, a video card, a CD-ROM
drive and speakers or headphone. Sometimes, there is also
a videodisk player, which is controlled by the software.
Computer based multimedia delivers information in a
variety of ways but achieves its greatest effectiveness
through interaction. In the first case, music and informative
knowledge combine to convey the message. In the second
case, technology provides a more effective presentation
wherein information, images and sounds are technically
and aesthetically integrated, focusing on a single specific
purpose. The ability of students to work independently
and to receive instruction suited to their needs and
learning styles is inherently attractive.
STUDY REVIEW
Every research work is in position to undergo to reveals
that the research gap and hence following reviews are
collected. William H.Jr (2001) concluded that there was no
evidence of direct relationship between small class size
and good attitude toward science. But he suggested that
class affect achievement and which in turn affect attitude.
There did, however, strong association exits between
achievement and attitude and between achievements and
class size.
Larry, E. (2002) studied the relationship between science
attitude self concept and science Teachers / pupils
compatibility and concluded that boys possessed a more
positive attitude and concept towards science than did
girls. May, A.M (2002) developed the test on scientific
attitudes (TOSA), taking the point of view that attitudes
must be inferred from the behavior of students. They
developed a multiple – choice format test. The developed
behavioral definitions of eight attitudes: (1) critical
mindedness, (2) suspended judgment (3) Respect for
evidence (4) Honesty, (5) Objectivity, (6) Willingness to
change opinions, (7) Open – mindedness and (8)
Questioning attitude. The behavioral definitions to these
eight attitudes were used to develop items.
Clay (2004) investigated attitudes towards education,
critical thinking ability and specific effective behavious of
(1) Students who had studied, the BSCS environmental
models “Investing your Environment” (IYE), (2) Those
students using one of BSCS biological science version and
(3) Those studying models of Biology. He found that the
ability of students who had experienced BSCS Biological
science was significantly increased but no other differences
were found among the students on any of the other
variables. Barry.J. (2005) studied the relationship between
students perceptions of their science class room learning
environment and attitude to four different scores of
scientific information experiments, books, promote positive
attitude towards experiment as a source of information,
while less favorable environment promoted more positive
attitude to the more authoritarian sources of information.
Williams (2006) “A study of the attitude of graduates
students towards general science and its relationship with
achievement and its subjects”. In her study it is found to
examine if there are any differences among the different
groups of graduates students such as boys and girls. Rural
pupil and urban colleges’ pupils in respect of their
achievement in science, attitude towards science and
attitude forwards science education.
Rajan, (2008), “An evaluation of the teaching of Biology at
the Higher Secondary stage in Tamil Nadu. In the study it
is found that as many as 87.8% of the +2 Biology student
have a favorable attitude towards the study of Biology.
The +2 boys studying in urban schools do not have a more
favorable attitude towards the study of Biology then the
boys studying rural school. The +2 girls studying in urban
schools do not have a more favorable attitude towards the
study of Biology then the boys studying urban schools.
The +2 girls studying in rural schools have a more favorable
attitude towards the study of Biology than the girls
studying in rural schools. The +2 girls studying in urban
schools have a more favorable attitude towards the study
of Biology than the girls studying in rural schools.
Rani (2010) “A study of problems of science education
and attitude of students towards science in college of East
Khasi Hiils District, Meghalaya. In her study it is found
that made and female students were found to be
homogeneous in their attitude towards science. The science
attitude scores did not show any statistically significant
difference in the case of students of different types and
locale of colleges. But tribal and non-tribal students
differed significantly in their science attitude scores.
R.Ramachandran
( 102 )
Rajasekar (2011) “A study of students achievement in
Physics as related to certain variables, in the study it is
found that as much as 88.92% of the students have a
relatively favorable attitude towards the study of physics
and only 11.08% of them have a relatively unfavorable
attitude towards it and the trend is screen in respect of the
sub sample too. There is no significance difference between
the boys and girls in respect of their attitude towards the
study of physics. There is significance difference between
the urban and the rural students in respect of their attitude
towards the study of physics. Moreover the rural students
are found to be better than their urban counterparts in
their favorableness of attitude towards the study of
physics.
Research Gap
A very few study have been made emphasis either on
science or arts and fostering on certain variables such as
attitude, teaching way, learning environment and critical
ability and specific effective behaviours of learners. The
studies relating to link these variables by certain
methodological issues and have not been made to analyses
the B-Schools in perspective of utility of learning tools as
skill base learning system for employability and therefore
the present study is taken up to analyses the dimension of
learning and applicability for employability skill
enrichment.
RESEARCH DESIGN
Methodology is an important aspect of any research work.
There are different methods followed at various stages of
any investigation. The details of methods followed in this
study such as selection of tools, sample frame, collection
of data, and analysis of data are involved in this paper.
The study has been designed with the students’ attitude
towards Audio-visual aids used by the Teachers
achievement. The major aim of the present study is to
determine the students’ Audio-visual aids used by the
Teacher. The data were collected by using questionnaire
as an instrument. For this study the samples were drawn
using random sample method. Sample size of the study
that is selected from the sampling unit. A sample of 500
respondents in Tamil Nadu selected district in each district
one hundred samples has taken on the basis of convenient
sampling technique. The researcher conducted his study
at respondents of under graduates and post graduates in
higher level learning B-Schools in Tamil Nadu selected
district namely Cuddalore, Trichy, Coimbatore, Chennai,
Tirunelveli, which combats all forms of economic, cultural,
social and technical issues in the study population. The
study period covers from April 2015 to July 2015. The
collected data were analyses using appropriate statistical
techniques. The descriptive statistics, differential analysis
and regression analysis were computed.
STUDY OBJECTIVES
The study has the following primary objectives for the
research study.
1. To analyses the student attitude towards Audio-
visual aids used by the Teachers of the entire and its
sub samples.
2. To compare the attitude towards Audio-visual aids
of male and female students and with their medium
of instruction.
3. To bring out the attitude towards Audio-visual aids
on the basis of their demographic variables.
LIMITATIONS OF THE STUDY
Though the research has been properly planned
and well executed, there are certain limitations, which are
inherent in nature and are out of the researcher’s control.
The effectiveness of the project is felt only when the results
are read along with the limitations and constraints faced
during the course of this study. The following are the
limitations.
1. The responses from the respondents could be casual
in nature. This may be due to lack of interest or time
on their part and some of the information provided
by the respondents might not be correct.
2. Getting timely responses from the respondents was
a difficult task.
DISCUSSION AND RESULTS
This paper furnishes the analyses and interpretation of
the collected data for “Skilled based Learning System for
Employability – with reference to B-Schools from Empirical
Perspective”. Various statistical procedures such as F-test,
t-test, regression analysis and factor analysis were used.
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 103 )
Table 1: Mean and Standard Deviation of the students’ attitude towards Audio visual aids used by the Teachers
Variable Groups N Mean Standard Deviation
Entire Total 500 71.78 8.58
Type of the college Government 262 70.48 6.50
Private 238 73.30 10.33
Locality of the college Urban 274 72.24 8.11
Rural 226 71.14 9.19
Course BBA/BBM 286 72.26 9.37
MBA 214 71.00 7.08
Gender Male 274 70.97 7.41
Female 226 72.90 9.89
Community
SC 94 72.89 8.84
ST 136 70.69 5.04
BC 100 73.20 12.16
BCM 112 72.08 9.22
OC 58 68.33 3.18
Religion
Hindu 145 70.31 4.09
Muslim 187 72.30 9.56
Christian 168 72.29 9.75
Degree UG 256 69.19 5.37
PG 244 74.58 10.37
Medium of instruction
Tamil 180 70.20 9.64
English 192 71.75 4.19
Hindi 128 75.00 11.60
Birth order of the child Only child 287 71.79 8.56
One among the children 213 71.77 8.64
Parental literacy (Father) Illiterate 284 72.01 8.86
Literate 216 71.41 8.14
Parental literacy (Mother) Illiterate 282 72.07 8.46
Literate 218 71.32 8.78
Source: Primary data
Hypothesis 1: Students have favourable attitude towards
Audio Visual Aids used by the Teachers in B-Schools
From the Table 1, the Mean, SD of students’ attitude towards
audio visual aids subject. The result reveals that, students
of this particular sample have better attitude in audio visual
aids. In the case of Government and Private, Private (73.30)
scored higher mean value than Government (70.48). So,
Private has high level of attitude in audio visual aids than
government. In the case of Urban and Rural, Urban (72.24)
scored higher mean value than Rural (71.14). So, Urban
have high level of attitude in audio visual aids than Rural.
In the case of class, BBA/BBM group scored (72.26) higher
mean value than the other group. So, BBA/BBM has high
level of attitude in audio visual aids than MBA.
Considering the Locality of the college, urban students
(72.24) have high attitude in mathematics than rural
students. Regarding the type of management, Government
B-Schools students (81.12) scored high mean value than
private B-Schools students. (73.47). So, government B-
Schools student have high mathematical attitude.
Regarding parental education, students whose parents
have educated (B-Schools education) they have high
attitude in mathematics. Considering the degree, post
graduate student have high mathematical attitude than
under graduate students. Considering the employment
status, unemployed parents student have high
mathematical attitude. In the case of family income Rs,
5,000 –10,000 income group students have high attitude
in mathematics (83.42) than the other groups. The entire
sample of experimental group taken for the study shows
the mean of 71.78 and S.D. 8.58. From this, it is observed
that the students attitude towards audio visual aids used
by the Teachers (71.18 is above 300 which is average).
R.Ramachandran
( 104 )
Table 2: Mean, SD and t-test for respondent about students’ attitude towards audio visual aids used by the
Teachers on the basis of demographic variables
Demographic variables
Sub Samples N Mean Standard Deviation
F/t-value
Level of Significance
Types of the B-Schools
Government 262 70.48 6.50 2.78 0.01
Private 238 73.30 10.33
Locality of the B-Schools
Urban 274 72.24 8.11 1.07 NS
Rural 226 71.14 9.19
Course BBA/BBM 286 72.26 9.37
1.32 NS MBA 214 71.00 7.08
Gender Male 274 70.97 7.41
1.85 NS Female 226 72.90 9.89
Community
SC 94 72.89 8.84
1.79 NS
ST 136 70.69 5.04
BC 100 73.20 12.16
BCM 112 72.08 9.22
OC 58 68.33 3.18
Total 500 71.78 8.58
Religion
Hindu 145 70.31 4.09
1.56 NS Muslim 187 72.30 9.56
Christian 168 72.29 9.75
Total 500 71.78 8.58
Degree UG 256 69.19 5.37
5.58 0.01 PG 244 74.58 10.37
Medium of instruction
Tamil 180 70.20 9.64
6.49 0.01 English 192 71.75 4.19
Hindi 128 75.00 11.60
Total 500 71.78 8.58
Birth order of the child
Only child 287 71.79 8.56 0.02 NS One among the
children 213 71.77 8.64
Parental literacy (Father)
Illiterate 284 72.01 8.86 0.60 NS
Literate 216 71.41 8.14
Parental literary (Mother)
Illiterate 282 72.07 8.46 0.73 NS
Literate 218 71.32 8.78
Source: Primary data
Hypothesis 2: Students do not differ in their students’
attitude towards audio visual aids used by the Teachers
on the basis of demographic variables.
The calculated t-value (2.78), which is significant at 0.01
level, confirms that there is a significant difference in
student audio visual aids on the basis of type of the B-
Schools. Hence the stated hypothesis is rejected. So
government students have high level of audio visual aids
than private B-Schools students. It seems that more funds
are deployed for such and Teachers’ participation is also
satisfactory.
The calculated t-value (1.07), which is not significant at
0.05 level, confirms that there is no significant difference
in their audio visual aids on the basis of locality of the
college. Hence the stated hypothesis is accepted. It is the
high rationality that it’s due to more concentration and
contraction of mechanisms exists in the B-Schools campus.
The calculated t-value (1.32), which is not significant at
0.05 level, confirms that there is no significant difference
in their audio visual aids on the basis of course. Hence the
stated hypothesis is accepted. The learners have high
significance for their involvement towards adherence for
learning aids adopted by their Teachers. It is also for the
cause of ICT reforms and revolution in the learning
scenario. The calculated t-value (1.85), which is not
significant at 0.05 level, confirms that there is no significant
difference in their audio visual aids on the basis of gender.
Hence the stated hypothesis is accepted. The learners have
much scope and vision for their learning by their gender
practice and them also adaptable to such utility.
The calculated F-ratio (1.79), which is not significant at
0.05 level, confirms that there is no significant difference
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 105 )
in students audio visual aids on the basis of community.
Hence the stated hypothesis is accepted. In this pipeline
the community at large has also favourable to the utility
due to the ICT environment and feels that their may be
much employability opportunity. The calculated F-ratio
(1.56), which is not significant at 0.05 level, confirms that
there is no significant difference in students attitude of
audio visual aids on the basis of religion. Hence the stated
hypothesis is accepted. Regarding the issues of culture,
customs, religion the learning groups has positive role
and also happy over to the environment for the career
concerning. The calculated t-value (5.58), which is
significant at 0.01 level, confirms that there is a significant
difference in student audio visual aids on the basis of
degree. Hence the stated hypothesis is rejected. So post
graduates students have high level of audio visual aids
than under graduates students. Many Teachers at graduate
level and PG level have been impact by this tool and the
learning groups also. The calculated F-ratio (6.49), which
is not significant at 0.05 level, confirms that there is a
significant difference in students attitude of audio visual
aids on the basis of medium of instruction. Hence the stated
hypothesis is rejected. It is the cause for concern and
dispersion for learning among the learners. They have
great privilege over the application of learning aids due to
that, their future perspective. The calculated t-value (0.02),
which is not significant at 0.05 level, confirms that there is
no significant difference in their audio visual aids on the
basis of birth order of the child. Hence the stated hypothesis
is accepted. There is no issue of birth order and it’s based
on learning technology skill. The calculated t-value (0.60),
which is not significant at 0.05 level, confirms that there is
no significant difference in their audio visual aids on the
basis of parental literacy (Father). Hence the stated
hypothesis is accepted. It is a prime factor over the use of
learning aids on the base of parental literacy. It is also a
criterion for assistance at home. The calculated t-value
(0.73), which is not significant at 0.05 level, confirms that
there is no significant difference in their audio visual aids
on the basis of parental literacy (Mother). Hence the stated
hypothesis is accepted. Likewise parental literacy of father,
mothers’ role is also as similar to the phenomenon.
Table 3: Regression Analysis for student demographic characters and their attitude towards audio visual aids
used by the Teachers
Model Summary
Model R R Square Adjusted R
Square Std. Error of the
Estimate
1 .436a .190 .159 7.87
ANOVAb
Model Sum of Squares
df Mean Square F Sig.
Regression .4189.756 11 380.887 6.155 .000a
Residual 17821.724 488 61.881
Total 22011.480 499
Coefficientsa
Model Unstandardized
Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
Name of the B-Schools 58.979 4.376 13.477 .000
Type of the B-Schools 2.387 1.116 .139 2.139 .033**
Locality of the B-Schools -1.000 1.005 -.058 -.995 .320
Class -.500 1.046 -.028 -.478 .633
Gender 1.989 1.052 .115 1.891 .060
Community -1.365 .422 -.190 -3.233 .001**
Religion .757 .627 .068 1.208 .228
Groups 5.255 .947 .306 5.548 .000**
Medium of instruction 2.183 .649 .191 3.365 .001**
Birth order of the child -9.11 1.032 -.001 -.009 .993
Parental literacy (Father) -.143 1.003 -.008 -.143 .887
Parental literacy (Mother) -.585 .955 -.033 -.612 .541
Source: Primary data
a. Dependent Variable: Attitude towards Audi visual aids
** Significant at 0.01 level
R.Ramachandran
( 106 )
According to the regression result it is known that the
demographic variables are influenced nearly 19 per cent
to measure their attitude towards audio visual aids. This
is proved by the obtained r square value (0.19). Further the
calculated F-value (6.15) also significant at 0.01 level. It
indicates that there is a significant influence between
students’ demographic characters and their attitude
towards audio visual aids. Also from the obtained t- values
the demographic variables such as type of B-Schools,
community, group studied and medium of instructions
the students studied are significant at 0.01 level. So it is
concluded that there is a significant difference regarding
attitude towards audio visual aids on the basis of these
variables.
FACTOR ANALYSIS
Factor analysis is done with the main objectives to find
out the underlying common factors among 10 variables
included in this study. Principal component factoring
method with variance rotation is used for factor extraction.
A four factor solution is derived using a score test. Table
shows the results of the factor analysis. Name of all the 10
variables and their respective loadings in all the four factors
are given in the table. An arbitrary value of 0.39 and above
is considered significant loading. A positive loading
indicates that greater the value of the variable greater is
the contribution to the factor. On the other hand, a negative
loading implies that greater the value, lesser its
contribution to the factor or vice versa. Keeping these in
mind, a study of the loadings indicates the presence of
some significant pattern. Effort is made to fix the size of
correlation that is meaningful, club together the variables
with loadings in excess of the criteria and search for a
concept that unifies them, with greater attention to
variables having higher loadings. Variables have been
ordered and grouped by the size of loadings to facilitate
interpretation and shown in Table 4.
Table 4 Factor Analysis - Communalities
Initial Extraction
Audio Visual aids increase reasoning ability 1.000 .445
Target soon after what I have studied through Audio Visual aids 1.000 .698
The Record pelages used in class in useful 1.000 .511
Employability 1.000 .616
Different kinds of programmes do not need audio visual aids. 1.000 .395
Practice of using Audio Visual aids increase memory power 1.000 .662
Audio Visual aids (Drill work) are more important than lab experiments. 1.000 .579
Overuse of teaching aids may be harmful and damaging to learners 1.000 .613
Do audio visual aids provide many hands in activity? 1.000 .773
Do audio visual aids help to explain abstract ideals? 1.000 .658
Source: Primary data
Total Variance Explained
Component
Initial Eigen values Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 1.750 17.503 17.503 1.750 17.503 17.503
2 1.490 14.904 32.407 1.490 14.904 32.407
3 1.473 14.727 47.134 1.473 14.727 47.134
4 1.236 12.357 59.490 1.236 12.357 59.490
5 .952 9.523 69.013
6 .813 8.135 77.148
7 .743 7.432 84.580
8 .642 6.417 90.997
9 .543 5.434 96.431
10 .357 3.569 100.000
Extraction Method: Principal Component Analysis.
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 107 )
Component Matrixa
Component
1 2 3 4
Audio Visual aids increase reasoning ability -.406 -.099 -.496 .153
Target soon after what I have studied through Audio Visual aids
.419 .484 -.360 .398
The Record pelages used in class in useful -.473 .413 -.144 .310
Employability .520 -.529 -.228 -.116
Different kinds of programmes do not need audio visual aids.
-.356 -.479 -.030 .194
Practice of using Audio Visual aids increase memory power
.377 -.189 .425 .551
Audio Visual aids (Drill work) are more important than lab experiments.
.625 -.071 -.186 -.385
Overuse of teaching aids may be harmful and damaging to learners
.323 .171 .569 .394
Do audio visual aids provide many hands in activity? -.344 .027 .696 -.411
Do audio visual aids help to explain abstract ideals? .179 .704 .001 -.361
Extraction Method: Principal Component Analysis.
a. 4 components extracted.
Factor analysis is done among 10 variables used in the
study. The principal component analysis with varimax
rotation was used to find out the percentage of variance of
each factor, which can be grouped together from the total
pool of 10 variables considered in the study. The factor,
variance percentage for each factor is 1.750, 1.490, 1.473,
and 1.236.
The factors are arranged based on the Eigen value namely
F1 (Eigen value 1.750)
F2 (Eigen value 1.490)
F3 (Eigen value 1.473)
F4 (Eigen value 1.236)
These four factors are described as “Students Attitude
towards Audio-Visual Aids Used by the Teachers”. This
model has a strong statistical support and the Kaiser-
Maya-Olkin (KMO) test of sampling adequacy concurs that
the sample taken to process the factor analysis is
statistically sufficient (KMO value = 0.7795).
ANALYSIS RESULTS
The result reveals that, students of this particular sample
have better attitude in audio visual aids. In the case of
Government and Private, Private (73.30) scored higher
mean value than Government (70.48). So, Private have high
level of attitude in audio visual aids than government. In
the case of Urban and Rural, Urban (72.24) scored higher
mean value than Rural (71.14). So, Urban have high level
of attitude in audio visual aids than Rural. In the case of
class, BBA/BBM group scored (72.26) higher mean value
than the other group. So, BBA/BBM has high level of
attitude in audio visual aids than MBA. Considering the
Locality of the college, urban students (72.24) have high
attitude in mathematics than rural students. Regarding
the type of management, Government B-Schools students
(81.12) scored high mean value than private B-Schools
students. (73.47). Hence, government B-Schools student
have high mathematical attitude. Regarding parental
education, students whose parents have educated (B-
Schools education) they have high attitude in mathematics.
Considering the degree, post graduate student have high
mathematical attitude than under graduate students.
Considering the employment status, unemployed parents
student have high mathematical attitude. In the case of
family income Rs,5,000 –10,000 income group students
have high attitude in mathematics (83.42) than the other
groups. The entire sample of experimental group taken for
the study shows the mean of 71.78 and S.D. 8.58. From
this, it is observed that the students attitude towards audio
visual aids used by the Teachers (71.18 is above 300 which
is average).
R.Ramachandran
( 108 )
Inferential Findings of the Study
Students have favourable attitude towards Audio Visual
Aids used by the Teachers in B-Schools. Students differ
in their students’ attitude towards audio visual aids used
by the Teachers on the basis of types of the B-Schools.
Students do not differ in their students’ attitude towards
audio visual aids used by the Teachers on the basis of
locality of the B-Schools. Students do not differ in their
students’ attitude towards audio visual aids used by the
Teachers on the basis of class. Students do not differ in
their students’ attitude towards audio visual aids used by
the Teachers on the basis of gender. Students do not differ
in their students’ attitude towards audio visual aids used
by the Teachers on the basis of community. Students do
not differ in their students’ attitude towards audio visual
aids used by the Teachers on the basis of Religion. Students
differ in their attitude towards audio visual aids used by
the Teachers on the basis of group. Students differ in their
attitude towards audio visual aids used by the Teachers
on the basis of medium of instruction. Students do not
differ in their attitude towards audio visual aids used by
the Teachers on the basis of birth order of the child.
Students do not differ in their attitude towards audio visual
aids used by the Teachers on the basis of parental literacy
(Father). Students do not differ in their attitudes towards
audio visual aids used by the Teachers on the basis of
parental literacy (Mother). These four factors are described
as “Students Attitude towards Audio-Visual Aids Used
by the Teachers”. This model has a strong statistical
support and the Kaiser-Maya-Olkin (KMO) test of sampling
adequacy concurs that the sample taken to process the
factor analysis is statistically sufficient (KMO value =
0.7795).
POLICY IMPLICATIONS AND CONCLUSION
Discussion
Audio visual aids a process of inward journey to unravel
the hidden potentialities of a being. It helps an individual
to develop ones personality. A systematic approach of
Audio visual aids helps an individual to see the all around
development at physical, mental, intellectual and
emotional level. The practice of use of audio visual aids
makes an individual perfect. It removes the unwanted
elements in the mind of the learner. It improves
concentration and brings mental stability. Audio visual
aids is an essential tool for students to achieve higher score
in their studies as if improve concentration, memory and
skills. The present study clearly indicates and recommends
the students to use of audio visual aids as to develop
positive attitude towards everything in their life which
helps to excel themselves in their studies. The entire study
concluded reveals that the uses of audio visual aids have
high achievement and expressed more favourable attitude.
Educational Implications
Audio-visual aids are very important and useful
aids for teaching. As well as it creates high interest among
the students to learn the subjects. So, the department of
education shall take a steps to implement the latest audio-
visual aids to all the colleges for teaching purpose. For
self-learning, these type of aids are very helpful to the
students. Also students are very much interested in using
latest technologies such as computers and internet. In
internet lot of facilities are there to learn new information
with visual appearance. From that students are also get
more interest to use that. In the case of teaching, in older
days Teachers follow interactive methods and oral
demonstration. But these are not creating much interest.
In order to create interest and attention audio-visual aids
are highly useful. So, the concerned educational institution
tries to provide these facilities. So that Teachers and
students get benefited.
Suggestions
The following suggestions are arrived from the research
findings. Research found that use of audio visual aids
will contribute more in students achievement. Also the
result reveals that use of audio visual aids increases the
memory power, concentration. Further it sharpens the
intelligence. Apart from that it reduces misconception in
learning. Further due to use of audio visual aids the sensory
expression would be more exercised. And hence,, the
present research suggested that in all colleges, the students
advised to use of audio visual aids compulsory. The
education departments form a rule for that and advise the
educational institutions make a step to establish separate
infrastructure for this one. Also the Government take a
step to use audio visual aids effectively students in their
academic. This will definitely help the students to be a
good learner imbibing the concepts.
Skilled Based Learning System for Employability – With Reference to B-Schools from Empirical Perspective
( 109 )
CONCLUSION
The present study attempted to identify the students’
attitude towards audio-visual aids used by the Teachers.
For that the researcher framed some objectives. On the basis
of objectives, a questionnaire is framed. After framing the
questionnaire, these are circulated to the selected samples.
500 samples were selected randomly. The responses were
collected and coded using computerised. To test the
hypotheses and characteristics of the data, some standard
statistical tools were used. The statistical tools such as t-
test, F-ratio and regression were used. From the analysis
the result concluded that the students have positive
attitude towards audio-visual aids used by the Teachers.
The present study also results that the emergence of skill
learning in commerce teaching has becomes essence of the
day and it also makes the reach out strategy in their
execution over for their employability criterion for 21st
century in learning and innovation skills, problem solving
skills, communication and collaboration skills,
information, media and technology skills, life and career
skills and competencies skills.
REFERENCES
Barry, J. (2005) “Development of a test of science related
attitudes, science education 62(4) 509-515.
Clay (2004), “A study of the effect of two programs in high
school biology upon critical thinking ability, specific
affective behaviors and attitude towards education:
dissertation abstracts.
Larry, E. (2002) Varo students science attitudes and self
concept in science as a function of rose specific
pupil/Teacher interpersonal compatibility”, San
Francisco, California, National Association for
Research in Science Teaching.
May, A.M (2002), “Test on scientific attitudes (TOSA),
taking the point of view that attitudes”, Dissertation
Abstracts.
Rajan, (2008), “An evaluation of the teaching of Biology at
the Higher Secondary stage in Tamil Nadu”, Ph.D.
education, Annamalai University.
Rajasekar, S., “A study of higher secondary students
achievement in physics as related to certain
variables. Ph.D. in education Annamalai University,
2011.
Rani, S.D., “A study of problems of science education and
attitude of students towards science in higher
secondary school of east khasi hills University, 2010.
Ware, William, H.Jr. “A test of the association of class size
to student’s attitude toward science”. Journal of
Research in Science Teaching, 2001.
Williams (2006), “A study of the attitude of high school
pupils towards general science and its relationship
with achievement and its subjects”, dissertation
abstracts.
Dr. R.Ramachandran
Assistant Professor in Commerce, DDE, Annamalai
University, Annamalai Nagar – 608 002, Tamil Nadu,
India
E-mail : [email protected]
R.Ramachandran
( 110 )
Key words:
Employability skills,
Commerce students,
Cluster analysis, ANOVA,
PLUM Model, Academic
civic engagement;
Academic citizenship
behaviour and BHU.
Capabilities in Employability Skills (SelfPerceived) among Under-Graduate CommerceStudents: A Cross –Sectional Study
Sudhir Chandra Das and Shalakha Rao
ABSTRACT
Objectives: The study mainly consists three specific objectives namely to explore the level of
variation in capabilities in employability skills possessed by undergraduate commerce students
and to segmenting the undergraduates on the basis of structured employability skill behaviour.
Finally, the study is intended to understand the effect of employability skill behaviours on
conceptualization, decision making and social intelligence.
Research Methodology & Design: This research falls under the category of cross-sectional
based on 170 undergraduate respondents covering four different sampling unit of Banaras
Hindu University with equal proportion of gender. Structured self assessment questionnaire of
employability skills adapted from Jackson, Sibson & Riebe (2013) on five different competence
scales (Narayan & Krosnick, 1996; O’Muurcheartaigh, Krosnick & Helic, 1999) have been
used. Three types of analysis have been performed in this work namely ANOVA for measuring
the dependency of employability skills on select demographic structure, secondly Two step
cluster analysis using Schwarz’s Bayesian Information Criterion (BIC) have been
performed for segmenting the students based on self perceived employability skills. Finally,
Ordinal Regression Analysis (PLUM) is applied to measure the impact of skill behaviours on
conceptualisation, decision making and social intelligence.
Findings: It is visualised through one way ANOVA, that maximum cases in employability
skills of commerce graduates are showing high level of dependency on geographical background
(rural/urban/semi-urban), and parents’ occupation. Through Two step cluster analysis, the
study identified employability skill behaviour into two segment, first Cluster-1 (Weak) which
comprises 58.8% of respondents with six variables and Custer-II (Moderate) consisting 41.2%
of UG students with eleven skill indicators found significant at 5% level of significance. The
Pseudo R2 values (e.g. Nagelkerke ; Cox and Snell; and McFadden) shows that majority of
skill behaviours explains a relatively higher proportion of the variation in three different
specific skill outcomes.
Conclusions & Policy Implications: Out of thirty employability skill indicators, which
compressed into ten variables, the study concludes that there is an enough scope for enhancement
in skill behaviours among commerce under-graduates. As demographics of respondents does not
have much influence on employability skills, so institutional responsibilities (Pedagogical
intervention) becomes more important. Secondly, through two step cluster analysis, the study
categorised respondents into low and moderate segment. Understanding the employability skill
behaviours within a given cluster helps educators plan and tailor developmental
opportunities. The PLUM model indicates all of select variables does not have effect on
conceptualization, decision making and social intelligence.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
( 111 )
LITERATURE REVIEW
Employability skills are defined as skills required not only
to gain employment, but also to progress within an
enterprise so as to achieve one’s potential and contribute
successfully to enterprise strategic directions (DEST,
2002). Intense globalization, international mobility and
rapid changes and complexities in society, technology and
the economy (Bowman, 2010) have driven explicit
attention to graduate employability in developed
economies. One critical aspect of any graduate
employability model is skill development (Dacre Pool &
Sewell, 2007). Employability skills also referred to as non-
technical, professional, key, core or generic skills - are
considered vital in enabling graduates to effectively apply
disciplinary knowledge in the workplace context as per
Australian Association of Graduate Employers (AAGE,
2011). Broad consensus on its importance in undergraduate
education has amplified calls for skill development in
higher education worldwide. This is particularly so for
business/management degree programs as the changing
role of today’s managers emerges with revolutionary
practices in information management, planning and risk
management caused by the global financial crisis (Shefrin,
2009). Some universities have developed their own
frameworks/inventory of targeted employability skills and
policies on how they are to be achieved. A series of reviews
found outside India reiterated the important role of
employability skills in achieving graduate work-readiness
and added further momentum to the skills movement.
Globalization; cultural similarities among these developed
economies, their participation in a globalised higher
education system (Marginson, 2006) and their
corresponding skill requirements (Jackson & Chapman,
2011) suggest a universal perspective on graduate
employability. The skills agenda in higher education is
becoming more entrenched as universities concentrate on
developing institution-wide approaches to employability
skill provision to meet industry’s growing demands for
enhanced graduate work-readiness (Confederation of
British Industry, 2010). Despite universities’ efforts, there
is some evidence to suggest that graduates transitioning
from higher education to the workplace in developed
economies are not meeting industry expectations
(Business, Industry and Higher Education Collaboration
Council, 2007; Council for Industry and Higher Education,
2008; National Centre on Education and the Economy,
2007). Although graduates are acknowledged as being
sufficiently equipped with technical know-how, there is
broad consensus they lack certain employability skills
(Shury, Winterbotham, Davies & Oldfield, 2010). A recent
report by the CBI (Confederation of British Industry, 2011)
cited shortcomings in basic graduate numeracy and
literacy skills, in addition to a lack of satisfaction in
business awareness, cultural awareness, problem solving
skills and self-management. In a study of Cranmer (2006)
claims there are inherent and considerable problems with
addressing employability in higher education, particularly
without significant industry involvement. These
difficulties include defining skills, measuring outcomes,
achieving authentic learning, and also the transfer of
acquired skills in graduates from the classroom to the
workplace. Skill deficiencies imply reduced productivity,
organizational under-performance and are likely to impact
on an economy’s ability to achieve sustainable growth
and global competitiveness (Confederation of British
Industry, 2011). It is important to note, however, that
mastery of a broad range of employability skills will not
guarantee improved organizational performance as
industry must manage these skills effectively (Little, 2011).
The UK’s Department for Business, Innovation and Skills
(DBIS, 2010) express “learning how to learn, learning how
to think; intellectual curiosity; the challenge and excitement
of new ideas” as the key focus of employability skill
development in higher education, converging with the
more traditional values of higher order and cognitive
learning than other, more vocationally-oriented, wish lists
of industry-relevant skills.
In 2014, almost one-quarter of participating graduate
employers (23.4%) indicated that they would have
employed a larger number of graduates if more appropriate
graduates had been available (Graduate Outlook, 2014).
According to OECD Skills Outlook 2015, skills acquired
during education are not being put to productive use. The
survey of Adult Skills, a product of the OECD Programme
for the International Assessment of Adult Skills (PIACC),
10% of new graduates have poor literacy skills and 14%
have poor numeracy skills. India Skills Report 2015 also
highlights that out of about three lakh candidates who
appeared for the Wheebox Employability Skill Test across
domains, only 37.22% were found employable.
RESEARCH GAP, RELEVANCE & OBJECTIVES
Research Gap
The foregoing review of national and international
literature on the subject reveals that, there is much research,
both conceptual and empirical, especially in western
Sudhir Chandra Das, Shalakha Rao
( 112 )
countries and other abroad countries. But in India, study
on Employability Skills is less and not much conceptual
as well as empirical work has been conducted in India.
The structured questionnaire regarding self assessment of
employability skills adapted from Jackson, Sibson & Riebe
(2013) is not used anywhere in Indian context, which is
the standard framework for measuring employability
skills. Also in academic institutions there is no evidence
found regarding industry-academia collaboration in
framing contents of syllabus, which is need of the hour for
qualitative higher education. In reference to this, there is
high shortage of comprehensive study of Employability
Skills among Undergraduate Commerce Students in
Academic Institutions. Therefore the present study is an
attempt to fill this vast research gap.
Relevance
Employability is not the same as subject knowledge,
qualifications or specialist experience. A brilliant first class
degree will not be enough to secure a position in a
company. Students have to be aware of what employers
are looking for in any employee. Engagement between
businesses and higher education can be a powerful source
of benefits for both parties, as well as for students. As per
the recent surveys quoted above (Graduate Outlook, 2014;
OECD Skills Outlook 2015; India Skills Report 2015),
there is a high dearth of unemployment due to lack of
skills among qualified graduates. So, this study would be
beneficial for universities/higher education in producing
skilled human capital. Industries will also be benefitted
as they will be provided with proficient workforce. And
this will give a platform in resolving societal problems
(like unemployment, lack of skilfulness, etc.) in our
graduate workforce.
Objectives
The general objective of this paper is to measure students’
perception of their capabilities in employability skills
typically required among commerce undergraduates. The
specific objectives of the study are as follows:
1.1.1. To measure the level (variation) of self perceived
employability skills possessed by under-graduate
commerce students based on select demographic
features;
1.1.2. To design the cluster profile based on structured
capabilities in employability skills; and
1.1.3. To measure the effect of employability skill
behaviours on conceptualization, decision making
and social intelligence (CDI) power.
Hypotheses
Based on literature and objectives, the study has identified
there hypotheses namely:
H01
There is no dependency of the capabilities in
Employability Skill (Self perceived) variables on
various demographic characteristics of the
respondents;
H02
The select variables (employability skills) are not
significant in formation of cluster profile; and
H03
Effects of self-perceived employability skill
behaviour on Conceptualization, Decision
Making and Social Intelligence (CDI) among under-
graduate students are insignificant.
RESEARCH DESIGN
One of the most common and well-known study designs
is adopted in this study, i.e., the cross-sectional study
design. In this type of research study, either the entire
population or a subset thereof is selected, and from these
individuals, data are collected to help answer research
questions of interest. It is called cross-sectional because
the information about X and Y that is gathered represents
what is going on at only one point in time (Chris Olsen
and Diane Marie M. St. George, 2004). It is aimed at
finding out the prevalence of a phenomenon, problem,
attitude or issue by taking a snap-shot or cross-section of
the population. This stands an overall picture as it stands
at the time of the study (Unite for Sight, n.d).
Research Instrument
Data collection is made through a structured questionnaire
regarding self assessment of employability skills adapted
from Jackson, Sibson & Riebe (2013). The study covers 10
specific employability skills and 30 constituent
behaviours (table-1) with 7 demographic indicators
namely name of institutions, residential status, gender,
family occupation, proficiency in Language, Parents’
Education, and Annual Family Income etc.
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
( 113 )
Sudhir Chandra Das, Shalakha Rao
Table 1 : Employability skill BehavioursS.
No. Employability
Skills Behaviour Behaviour Description
1. Working Effectively with Others
Task Collaboration
Complete group tasks through collaborative communication, problem solving, discussion and planning.
Team Working Operate within, and contribute to, a respectful, supportive and cooperative group climate.
Social Intelligence
Acknowledge the complex emotions and viewpoints of others and respond sensitively and appropriately.
Influencing Others
Defend and assert their rights, interests and needs and convince others of the validity of one’s point of view.
2. Communicating Effectively
Verbal & Written Communication
Communicate orally/written formats in a clear and sensitive/structured manner which is appropriately varied according to different audiences and seniority levels.
Giving And Receiving Feedback
Give and receive feedback appropriately and constructively.
Public Speaking Speak publicly and adjust their style according to the nature of the audience.
3. Self-Awareness
Meta-Cognition Reflect on and evaluate personal practices, strengths and weaknesses in the workplace.
Lifelong Learning
Actively seek, monitor and manage knowledge and sustainable opportunities for learning in the context of employment and life.
Career Management
Developing meaningful and realistic career goals and pathways for achieving them in light of labour market conditions.
4. Thinking Critically
Conceptualization
Recognize patterns in detailed documents and scenarios to understand the ‘bigger’ picture.
Evaluation Recognize, evaluate and retain key points in a range of documents and scenarios.
5. Analyzing Data And Using Technology
Numeracy Analyze and use numbers and data accurately and manipulate into relevant information.
Technology Select and use appropriate technology to address diverse tasks and problems.
Information Management
Retrieve, interpret, evaluate and interactively use information in a range of different formats.
6. Problem Solving
Reasoning Use rational and logical reasoning to deduce appropriate and well-reasoned conclusions.
Analyzing And Diagnosing
Analyze facts and circumstances and ask the right questions to diagnose problems.
Decision Making Make appropriate and timely decisions, in light of available information, in sensitive and complex situations.
7. Developing Initiative And Enterprise
Entrepreneurship
Initiate change and add value by embracing new ideas and showing ingenuity and creativity in addressing challenges and problems.
Lateral Thinking Develop a range of solutions using lateral and creative thinking.
Change Management
Manage change and demonstrate flexibility in their approach to all aspects of work.
8. Self Management
Self Efficacy Be self-confident in dealing with the challenges that employment and life present.
Stress Tolerance Persevere and retain effectiveness under pressure or when things go wrong.
Work / Life Balance
Demonstrate the importance of well being and strive to maintain a productive balance of work and life.
9.
Social Responsibility And Accountability
Social Responsibility
Behave in a manner which is sustainable and socially responsible.
Accountability Accept responsibility for own decisions, actions and work outcomes.
Organizational Awareness
Recognize organizational structure, operations, culture and systems and adapt their behaviour and attitudes accordingly.
10.Developing Professionalism
Multi-Tasking Perform more than one task at the same time.
Autonomy Complete tasks in a self-directed manner in the absence of supervision.
Time Management
Manage their time to achieve agreed goals.
( 114 )
Measurement
Participants are advised to self assess their capabilities
against the behaviour descriptors on five different
competence scales (Narayan & Krosnick, 1996;
O’Muurcheartaigh, Krosnick & Helic, 1999), i.e., in case
of Exemplary (5), Significant Strength (4), Fully
Competent (3), Development Needed (2) and Weakness
(1) respectively.
Sampling, Participants and Data Collection
Target Population
The population of this study encompasses commerce
undergraduates from Banaras Hindu University and its
affiliated colleges.
Sampling Unit
Sampling unit consists of passed out students from
Bachelor of Commerce (Honours) at Faculty of Commerce,
BHU; DAV PG College, Varanasi ;Vasanta College for
Women, Varanasi and Arya Mahila PG College, Varanasi.
Sampling Technique
Proportionate stratified random sampling method has been
used to select the sample of respondents. Boys and girls
students’ proportion is equal in the study, i.e., 1:1. The
proportion of Faculty of Commerce, DAV PG College,
Vasanta College for Women and Arya Mahila PG College
is 3:2:1:1 in accordance with the intake strength.
Sample Size Determination
Appropriate size of sample (table:2) has been determined
with at 95% level of confidence by a sampling table for
problems involving sample proportions (p) (Zikmond,
2011).
Table: 2- Size of Respondents
Respondents FOC DAV VCW AMPG Total
Boys 50 35 - - 85
Girls 20 15 25 25 85
Total 70 50 25 25 170
Data Collection
Data collection is made through individual interaction
with commerce graduates. Total 200 questionnaires were
collected from respondents, and thereafter 170
questionnaires were found valid for analysis.
DATA ANALYSIS AND DISCUSSIONS
Data have been analysed on three different stages firstly,
average (composite) mean score of thirty skill indicators
of ten different variables have been calculated (Table-3),
and secondly ANOVA (Table-4 & 5) was conducted after
confirming population normality and homogeneity of
variance. Thereafter, Two Step Cluster analysis have been
conducted for segmenting the respondents profile based
on select employability skill (Table- 6 & 7 and Figure 1 &
2). Finally, Ordinal Logistic Regression (table: 8,9,10 &11)
has been used for measuring the effect size of skill variables
on conceptualization, decision making and social
intelligence.
OBJECTIVE-1
To measure the level (variation) of self perceived
employability skills possessed by undergraduate
commerce students based on select demographic features.
Descriptive statistics of self perceived scores of four different
institutions depicts in the table-3. It can be observed that
mean scores of select variables in institutions projects
moderate. The measurement used in the study based on
five different competence scales (Narayan & Krosnick,
1996; O’Muurcheartaigh, Krosnick & Helic, 1999) namely
Exemplary-EX (5); Significant Strength-SS (4); Fully
Competent-FC (3); Development needed-DN (2); Weakness-
WN (1). It seems that all of institutions’ are having
employability scale as fully competent.
Dependency of the Capabilities in Employability Skill
(Self perceived) Variables on Various demographic
Characteristics of the Respondents
In this sub-section the dependency of employability skill
behaviour on nature of institutions, students’ status,
proficiency in language, parent’s education, income and
gender have been studied. All of 30 variables have been
clubbed into ten items on the basis of composite score. One
way ANOVA of parametric test have been performed after
compiling the normality assumptions. It is to be noted
independent variable not been tested here but on composite
score.
Table- 4 reveals that C_SA (composite score of four
variables) namely task collaboration, team building, social
intelligence and influencing others highly varies in the
select instructions’. Similarly C_AUT comprises three
different skill behaviours (numeracy, technology and
information management) and C_DP which consists
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
( 115 )
Table 3 : Mean and standard deviation of the employability skill variables across different institutionsEmployability Skill variables
Faculty of Commerce DAV PG College AMPG VCW
Mean SD Mean SD Mean SD Mean SD
Task collaboration 3.442 .8786 3.6400 .851 3.2400 .9255 3.680 .85245
Team working 3.642 .9014 3.7400 1.02 3.9600 .6110 4.040 .7895
Social intelligence 3.414 .8763 3.3000 1.12 3.6000 1.040 3.640 1.075
Influencing others 3.257 1.002 3.4200 .882 3.4000 1.000 3.080 1.151
C_WEW 3.439 .539 3.525 .662 3.5500 .5951 3.610 .700
Verbal & written communication
3.1571 1.0444 3.3000 1.05 3.4000 .9128 3.520 1.084
Giving and receiving feedback
3.1286 .86680 3.4200 .970 3.2800 .9798 3.520 .91833
Public speaking 3.0143 .95542 3.1800 .962 3.2000 1.154 3.360 1.410
C_CE 3.100 .632 3.300 .726 3.293 .818 3.466 .957
Meta-cognition 3.1571 .89501 3.3000 .994 2.8400 .8981 3.160 .8981 Lifelong learning 3.4429 1.0163 3.3600 .963 3.200 1.154 3.760 .8793
Career management 3.3429 .97632 3.5400 1.01 3.0800 1.077 3.880 1.092
C_SA 3.314 .666 3.400 .666 3.040 .7535 3.600 .73912
Conceptualisation 3.2143 .84943 3.3200 1.09 3.2000 1.000 3.520 1.004
Evaluation 3.1286 .97685 3.2600 .876 3.1200 1.013 3.520 .71414
C_TC 3.171 .7317 3.2900 .756 3.1600 .8256 3.520 .74274
Numeracy 3.1714 1.021 3.3600 .942 3.1200 1.129 3.520 .8226
Technology 3.1571 .87866 3.4800 1.03 3.0800 1.077 3.560 1.0832
Information management 2.9714 .85077 3.3200 .867 2.9600 .9345 3.280 .89069
C_AUT 3.100 .6888 3.3867 .726 3.0533 .8749 3.453 .73207
Reasoning 3.7143 .99481 3.8000 .832 3.6400 1.075 3.800 1.0408 Analysing and diagnosing 3.4714 .98865 3.4200 .882 3.4000 .9574 3.840 .80000
Decision making 3.4000 .90730 3.5000 .886 3.2000 1.040 3.600 .76376
C_PS 3.528 .7256 3.5733 .653 3.4133 .7532 3.746 .65461 Entrepreneurship 3.0857 1.1130 3.2400 .893 3.2000 .7071 3.720 .84261
Lateral thinking 3.0571 1.0616 3.3800 .966 3.4400 1.044 3.520 1.0456
Change management 3.1857 1.0256 3.3400 1.11 3.0400 1.019 3.080 .90921
C_DE 3.109 .8139 3.3200 .790 3.2267 .7247 3.440 .78008
Self efficacy 3.4857 .92850 3.7200 .881 3.4800 .9626 3.720 .93630
Stress tolerance 3.2714 1.0203 3.2000 1.03 3.0000 1.290 3.400 1.0408
Work / life balance 3.3571 1.0220 3.3800 1.08 3.3600 .9073 3.520 1.0049
C_SM 3.371 .7323 3.4333 .694 3.2800 .8089 3.546 .83821
Social responsibility 3.6714 .95889 3.6400 .920 3.8000 1.154 3.760 1.0519
Accountability 3.6143 1.0114 3.5400 .973 4.1200 .9712 3.960 .97809
Organisational awareness 3.3000 .93793 3.4800 1.03 3.6800 .7483 3.360 .81035
C_SRA 3.528 .7167 3.5533 .798 3.8667 .8165 3.693 .83843
Multi-tasking 3.1429 .96738 3.5000 .839 3.3600 1.220 3.400 1.0000
Autonomy 3.1286 1.0484 3.4200 1.01 3.5200 1.004 3.640 .81035 Time management 3.3143 1.2457 3.3400 .898 3.8400 3.840 4.080 .90921
C_DP 3.1950 .8115 3.4200 .758 3.5733 .8688 3.706 .72214
Table 4 : Dependency of the Employability Skill Variables on Institutions, Student’s Status and Proficiency in LanguageEmployability Skill
Variables Institutions Student’s Status Proficiency in Language
F-Value p-Value F-Value p-Value F-Value p-Value
Working Effectively With Others (C_WEW)
.580 .629 2.644 .074 2.756 .066
Communicating Effectively (C_CE)
1.757 .157 2.631 .075 .628 .535
Self-Awareness (C_SA)
2.912 .036* 3.283 .040* 1.820 .165
Thinking Critically (C_TC)
1.481 .222 4.044 .019* .608 .545
Analysing Data And Using Technology (C_AUT)
2.733 .045* 4.064 .019* 2.018 .136
Problem Solving (C_PS)
1.013 .388 2.489 .086 1.217 .299
Developing Initiative And Enterprise (C_DIE)
1.343 .262 1.669 .191 .972 .380
Self Management (C_SM)
.600 .616 11.570 .000** 3.202 .043*
Social Responsibility And Accountability (C_SRA)
1.359 .257 5.168 .007* .799 .452
Developing Professionalism (C_DP)
3.209 .025* 5.496 .005* .799 .451
* Indicates significant at 0.05 Level. ** Indicates significant at 0.001 level
Sudhir Chandra Das, Shalakha Rao
( 116 )
(muti-tasking, autonomy and time management) also vary
in accordance with the institutions. Rest of the variables
does not varying in select institutions. Among the
capabilities of employability skills variable composite self
management (C_SM) i.e., self efficacy, stress tolerance and
work life balance highly varies with geographical status
of respondents. C_SA (composite score of self awareness),
C_TC (composite score of thinking critically), C_AUT
(composite score of analysing data and using technology)
C_SRA (social responsibility and accountability) and
developing professionalism (C_DP) also show high
dependency on geographical location of the respondents,
whereas other skill behaviour variables are showing
moderate to lower level of dependency. Self management
(C_SM) of employability skill is highly dependent on
proficiency in language of the respondents but all other
variables shows insignificant or lower variations with the
proficiency in language of the respondents.
In the table -5 except C_AUT (analysing data and using
technology), C_DIE (Developing Initiative and Enterprise),
C_SRA (Social Responsibility and Accountability) and
C_DP (Developing Professionalism) other variables
(composite score) namely C_WEW, C_CE, C_SA,C_TC,
C_PS, C_SM are dependent on the parents occupation of
the respondents. Employability skills (self perceived) of
C_WEW, C_TC, are strongly dependent upon the parents
education of the respondents and other variables are
showing moderate to low dependency. Again except C_PS,
all of employability skill variables namely C_WEW, C_CE,
C_SA, C_TC, C_AUT, C_DIE, C_SM, C_SRA and C_DP
are not dependent on the parents’ income of the
respondents. It is also found three composite variables of
employability skills namely C_WEW (Working effectively
with others), C_SRA (Social responsibility and
accountability, C_DP (Developing professionalism) are all
highly dependent on the gender and rest variables are
showing the low dependency.
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
Table 5 : Dependency of the Employability Skill Variables on Parents’ Occupation, Education, Income and Gender
Employability Skill Variables
Parents’ Occupation
Parents Education Parents Income Gender
F-Value P-value F-Value
P-value F-Value P-value T-Value
p-Value
Working Effectively With Others (C_WEW)
4.621 .011* 3.53 .032* .880 .417 -3.729 .000**
Communicating Effectively (C_CE)
3.763 .025* .652 .523 .968 .382 -1.966 .051
Self-Awareness (C_SA)
3.764 .025* .928 .397 .746 .476 -.145 .885
Thinking Critically (C_TC)
4.895 .009* 3.920 .022* 2.60 .077 -1.575 .117
Analysing Data And Using Technology (C_AUT)
2.892 .058 .715 .490 .185 .831 -.581 .562
Problem Solving (C_PS)
3.627 .029* 1.279 .281 3.11 .047* -.877 .383
Developing Initiative And Enterprise (C_DIE)
2.429 .091 2.410 .093 2.02 .135 -1.261 .209
Self Management (C_SM)
3.382 .036* 2.288 .105 1.63 .197 -.171 .865
Social Responsibility And Accountability (C_SRA)
1.861 .159 1.192 .306 .976 .379 -3.500 .001*
developing professionalism (C_DP)
1.924 .149 1.171 .183 .505 .604 -3.392 .001*
( 117 )
Table 6 : Auto-Clustering
Number of Clusters
Schwarz's Bayesian Criterion (BIC) BIC Changea
Ratio of BIC Changesb
Ratio of Distance Measuresc
1 7300.034
2 7112.784 -187.250 1.000 1.895
3 7157.025 44.240 -.236 1.348
4 7268.050 111.025 -.593 1.213
5 7412.726 144.677 -.773 1.056
6 7565.802 153.076 -.817 1.068
7 7728.445 162.642 -.869 1.015
8 7893.135 164.690 -.880 1.002
9 8058.041 164.907 -.881 1.074
10 8232.501 174.460 -.932 1.022
11 8409.669 177.167 -.946 1.083
12 8596.443 186.774 -.997 1.117
13 8795.423 198.981 -1.063 1.014
14 8995.825 200.401 -1.070 1.010
15 9197.206 201.382 -1.075 1.016
a. The changes are from the previous number of clusters in the table.
b. The ratios of changes are relative to the change for the two cluster solution.
c. The ratios of distance measures are based on the current number of clusters against the previous number of clusters.
Sudhir Chandra Das, Shalakha Rao
OBJECTIVE: II
To Segment the Students Profile based on Self Perceived
Capabilities in Employability Skill
Two-Step Cluster Analysis: The clustering method used
is a two-step cluster program, which gives the user the
ability to determine the appropriate number of clusters,
and then classify them using a non-hierarchical routine.
The procedure is relatively new, and as recommended by
Hair et al. (2010), it is useful in this particular study due to
the sample size (150-500 cases) and the number of variables
being analyzed. Garson (2009) also encourages the use of
the two-step method for large datasets using both
continuous data and categorical variables with three or
more levels. The two-step clustering method offers a
particular advantage to educational administrators and
recruiters, because of its ability to handle categorical
variables, as well as continuous variables.
The two-step procedure in SPSS is based on Banfield and
Rafferty’s (1993) work with clustering methods for
continuous variables based on the reduction in log
likelihood when two clusters are merged. Further, the two-
step procedure extends the work of Melia and Heckerman
(1998) who took a similar probabilistic approach to
clustering categorical variables. Zhang et al. (1996)
developed BIRCH clustering for larger datasets, reducing
them to sub-clusters which are analyzed in a second step
much like traditional clustering methods. The two-step
procedure in SPSS innovatively combines these works,
resulting in an effective clustering solution for the
employability skill dataset due to its size and the number
and types of variables being investigated.
The Auto-Clustering statistics table in SPSS output can be
used to assess the optimal number of clusters in our
analysis, as shown in the table 6. To determine the number
of clusters automatically, the method uses two stages. In
the first one, the indicator BIC (Schwarz’s Bayesian
Information Criterion) or AIC (Akaike’s Information
Criterion) is calculated for each number of clusters from a
specified range; then this indicator is used to find an initial
estimation for the number of clusters. Although the lowest
BIC coefficient is for seven clusters, according to the SPSS
algorithm, the optimal number of clusters is two, because
the largest ratio of distances is for two clusters.
To validate the appropriate number of clusters, the
agglomeration schedule was reviewed, looking for
substantial changes in heterogeneity (i.e., how different
observations in one cluster are from those in another) (Hair
et al., 2010). The agglomeration coefficient measures the
( 118 )
increase in heterogeneity occurring from the combination
of two clusters. In the study of Hair et al. (2010) suggest a
reasonable approach to determining the number of clusters
is to measure the percentage change in heterogeneity. A
25% change in the agglomeration coefficient is evident
between two and three clusters. Thus, the two cluster
solution was selected. The cluster distribution table shows
the frequency of each cluster. Of the 170 cases assigned to
clusters (Table: 7), 100 were assigned to the first cluster, 70
to the second.
Figure 1. Weak Cluster (Employability Skill)
ATTRIBUTE IMPORTANCE: The “by variable”
importance charts are produced with a separate chart for
each cluster. The variables are lined up on the Y axis, in
descending order of importance. The dashed vertical lines
mark the critical values for determining the significance of
each variable. For categorical variables to be considered
significant, its x2 statistic must exceed the dashed line in
either a positive or negative direction. Since the importance
measures for cluster -1 show few variables like as self
efficacy, information management, lateral thinking,
feedback, conceptualization and stress tolerance exceed
the critical value in this chart, and it can be concluded that
all of the categorical variables are not contributing to the
formation of the first cluster.
In the second cluster, SPSS gives the importance plot for
each categorical variables .It is be noted that four different
variables namely self efficacy, information management,
lateral thinking and feedback are discriminant variables
Figure 2. (Moderate Cluster)
in the formation of second cluster and found significant at
5% level of significance. Other variables like as
conceptualization, stress tolerance, meta-cognition, time
management, public speaking and multitasking are also
found significant in the second cluster which comprise
41.2% of total sample size. In both the cluster the positive
variables contribute more to differentiation. The cluster-1
is found weak employability skill behaviour profile among
commerce undergraduates which occupies 58.8% of total
sample size whereas, the second cluster are most
significant whereas maximum variables found significant.
It can be concluded that employability of commerce
graduates of Banaras Hindu University are moderate in
number.
OBJECTIVE: III
Effects of Self-perceived Employability Skill behaviours
on Conceptualization, Decision Making and Social
Intelligence Power.
For measuring the influence of seventeen skill behaviours
on conceptualization, decision making and social
intelligence, the ordinal regression analysis (PLUM-
Polytomous Universal Model) has been performed.
Twenty seven (27) employability skill behaviour with five
point scale has been taken as independent variables,
whereas conceptualization, decision making, and social
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
Table 7 : Cluster Distribution
( 119 )
intelligence behaviour of under-graduate students were
assessed by five point scale considered as dependent
variable. In the next phase the same independent variables
have been used for measuring their impact on three different
generic outcome variables.
The significant Chi-Square statistic (p<.001) to all the three
cases indicates (table: 8) that the final model gives a
significant improvement over the baseline intercept-only
model. The conclusion is that there is association between
the dependent and independent variable(s) in
complimentary Log-log link function.
Goodness –of- fit statistics (table: 9) are intended to test
whether the observed data are inconsistent with the fitted
model. In this case the null hypothesis is accepted and it
can be concluded that the observed data were consistent
with the estimated values in the fitted model since the p
was insignificant, since all the three cases p> 0.05.
For ordinal regression models it not possible to compute
the same R2 statistic as in linear regression so, three
approximations are computed instead (Table: 10). what
constitutes a “good” R2 value depends upon the nature of
the outcome and the explanatory variables. Here, the
pseudo R2 values (table: 10) indicates the extent of variation
on outcome of three different variables. In the case of
Conceptualization, it is found that only 11 skill variables
(Team building, feedback, meta cognition, lifelong learning,
career management, Numeracy, Reasoning, analyzing and
Diagnosing, stress tolerance, organizational awareness,
multitasking) creates 69.8% variation (Nagelkerke effect
size) and found significant at 5% level of significance.
With regard to Decision Making as dependent variable,
only Six skill variables (namely influencing others,
feedback, career management, stress tolerance,
organizational awareness, and multi-tasking) shows
79.6% effects (Nagelkerke effect size) on decision making
and found significance at .o5 level. As far as Social
Intelligence is concerned, maximum around seventeen
skill variables (task collaboration, influencing others,
communication, public speaking, meta-cognition, lifelong
learning, career management, numeracy, reasoning, lateral
thinking, change management, stress tolerance, WLB,
accountability, organizational awareness, multi-tasking
and time management) has creates 81.9% variance on
power of social intelligence.
It is to be noted that ordinal model has constrained it to be
so through the proportional odds (PO) assumption. The
significance p values all the three cases p >0.05 indicated
Table 8 : Model Fitting Information
Model
Model Fitting Criteria
-2 Log Likelihood Chi-Square d.f Sig.
CL DM SI CL DM SI CL DM SI CL DM SI
Intercept Only
466.8 441.4 474.2
---
---
---
---
---
---
---
---
---
Final 286.6 214.3 225.2 180.15 227.03 249.08 106 100 102 .000 .000 .000
Table 9 : Goodness- of –Fit Statistics
Chi Square d.f Significance
CL DM SI CL DM SI CL DM SI
Pearson 6221.809 2820.189 647.982 570 570 574 .000 .017 .000
Deviance 286.680 214.380 225.203 570 570 574 1.000 1.000 1.000
Table 10 : Effect Size
Criteria Conceptualization Decision Making Social Intelligence
Cox and Snell .653 .737 .769
Nagelkerke .698 .796 .819 McFadden .386 .514 .525
Table 11 : Test of Parallel Lines
Model -2 Log Likelihood Chi-Square d.f Sig.
CL DM SI CL DM SI CL DM SI CL DM SI
Null Hypothesis General
286.68
.000
214.38
173.7a
225.2
.000
--
286.6
--
40.616
--
225.20
---
318
--
318
--
306
--
.896
--
1.000
---
1.00
Sudhir Chandra Das, Shalakha Rao
( 120 )
that there were no significant difference for the
corresponding slope coefficients across the response
categories, suggesting that the model assumption of
parallel lines were not violated in three different models
with the Complementary Log-log link.
CONCLUSIONS AND IMPLICATIONS FOR
INDUSTRY AND HIGHER EDUCATION
It is widely accepted that enhancing undergraduate
employability is now integral to degree programs and that
“people leaving higher education should be confident not
only that their knowledge, skills and capabilities for
entering the world of work are appropriate, but that they
are able to articulate these to potential employers”
(Butcher, Smith, Kettle & Burton, 2011). Gamble, Patrick
and Peach’s (2010) study found that students were more
employable through a better understanding of required
skill standards and their ability to perform in the
workplace. The present study is an endeavour to
understanding the competency among commerce
graduates possessed for the requirement of industry. The
study concludes since the employability skills are not
creating any variation on demographical indicators of
respondents, except few variables like as student’s status
and parents’ occupation, thus educators and policy
makers must focus on Pedagogical interventions. In this
context the study suggests to adopt Academic Civic
Engagement (ACE) which is a unique experimental
pedagogy that enables the students to know self and
society while applying their domain knowledge in some
real-scenario problem-solving in some community
organization as part of an academic project. The study
also suggests project or problem based learning (PBL)
into the teaching and learning methods, in order to provide
students with opportunities to develop some of the skills
demanded by industry. Project based learning brings
together learning through experimentation and learning
by doing. In particular, for subjects such as programming,
the classroom instruction can be supported by practical
work (Poindexter, 2003). The growing use of team working
in organisations requires that universities produce
graduates with knowledge and experience of team working
and who have developed some team skills. The team project
is an opportunity to learn from mistakes, and develop
collective and individual skills. According to Atherton
(2005), the range of activities, linking them together and
synthesising the problems, provides opportunities for
developing cognitive, affective and psycho-motor skills.
Team projects incorporate elements of collaborative and
co-operative working, promoting team working skills
acquisition (Prichard et al. 2006), and encouraging
learning in a social situation.
The study used Clustering methods to find hidden
patterns. Since, most data taken from the real world (as in
banking field, in our case) contains categorical attributes,
classical clustering algorithms cannot work efficiently
with such data. To solve this problem, the scholar adopted
Two-Step method, which determines the optimal number
of clusters automatically. The study found that significant
portion of UG commerce students is not having
employability skills as they possessing very minimum
number of employability skill behaviour. However, in the
second cluster which covers 41.2% of respondents’ profile
which may be considered modest groups, but even all select
skills are not significant at 5% or 1% level.
Based on ordinal regression model, the author concludes
that three important outcome skill behaviour namely
conceptualization, decision making and social intelligence
which are not influenced by some selective variables,
hence, instructors/policy makers/educational institutions
must focus on identified predictor variables. Finally, the
study suggests, that academic citizenship behaviour
(ACB) can be useful in employing students for extra-role
behaviour by understanding Big Five personality
measure (John, 1989) i.e., levels of extraversion,
agreeableness, conscientiousness, neuroticism, and
openness to experience of undergraduates.
LIMITATIONS AND FURTHER RESEARCH
In response to the continuing disparity between industry
expectations and higher education provision, this study
examines the self assessed capabilities of 170 commerce
under-graduates in employability kill typically considered
important by industry in developing economies. The study
is concentrated only four different campuses of Banaras
Hindu University and purely based on self assessment.
Whereas, self-assessment whose benefits and flaws have
attracted significant debate (Lew, Alwis, Schmidt, 2010;
Oliver, Harper, Sadler & Krause, 2011). Future research
must also investigate the larger number of respondents in
different institutions with more demographic features.
Validating a student’s potential with regard to
employability skill requires a longitudinal approach in
future research. Further, employability skill is a
multidimensional and there are other, significant
influences on graduate workplace performance, and
associated skill gaps, beyond employability skills not
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
( 121 )
discussed in this paper. Moreover, ambiguity in skill
definitions is inherently difficult. This problem is widely
acknowledged and continues to plague the study.
Therefore, future study must be after clarifying industry
requirements (Indian context) of graduates and thereafter
assessing their current performance (employability skill)
would be more beneficial.
REFERENCES
Australian Association of Graduate Employers (AAGE),
(2011), ‘2011 AAGE Employer Survey’, AAGE,
Sydney, Australia.
Atherton, J. S. (2005). Learning and teaching: Bloom’s
taxonomy. UK, Retrieved from: h t t p : / /
www.learning and teaching. info/learning/
bloomtax.htm
Bowman, K. (2010), ‘Background paper for the AQF Council
on generic skills, retrieved fromhttp://
www.aqf.edu.au/Portals/0/Documents/
Generic%20skills%20background%20paper%20FINAL.pdf.
Business, Industry and Higher Education Collaboration
Council (BIHECC) (2007), ‘Graduate employability
skills’, BIHECC, Canberra.
Banfield, J. D., & Rafferty, A. E., (1993). Model based
Gaussian and non- Gaussian clustering.
Biometrics 49, 803-821.
Butcher, V., Smith, J., Kettle, J., & Burton, L. (2011). Review
of good practice in employability and
enterprise development by Centres for Excellence in
Teaching and Learning: Summary report. London,
United Kingdom: HEFCE.
Confederation of British Industry (CBI) (2010), ‘Ready to
grow: business priorities for education and skills’, CBI,
London.
Confederation of British Industry (CBI) (2011), ‘Building
for growth: business priorities for education and skills –
Education and skills survey 2011’, CBI, London.
Council for Industry and Higher Education (CIHE) (2008),
‘Graduate employability: What do employers think and
want?’ CIHE, London.
Cranmer, S. (2006), ‘Enhancing graduate employability:
best intentions and mixed outcomes’. Studies in
Higher Education, 31(2), 169-84.
Dacre Pool, L., and Sewell, P. (2007), ‘The key to
employability: Developing a practical model of
graduate employability’, Education + Training, 49
(4), 277-289.
Department for Business Innovation and Skills (DBIS)
(2010, 15 July). ‘A new era for universities’. Speech
presented by Vince Cable, Secretary of State, UK.
Retrieved from http://www.bis.gov.uk/news/
speeches/vince-cable-higher-education.
DEST (2002b), Striving for quality: learning, teaching and
scholarship, Higher Education Review Process,
Department of Education, Science and Training,
Canberra.
Gamble, N., Patrick, C., & Peach, D. (2010).
Internationalising work-integrated learning:
Creating global citizens to meet the economic crisis
and the skills shortage. Higher Education
Research & Development, 29(5), 535-546.
Garson, G. D. (2009). Regression. Retrieved from http://
faculty.chass.ncsu. edu/garson/PA765/
cluster.htm.
Graduate Outlook 2014 (n.d.), Melbourne: Graduate Careers
Australia, GCA 2014.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010).
Multivariate Data Analysis (7th ed.). Upper
Saddle River, NJ: Pearson Prentice-Hall.
India Skills Report 2015 (n.d.). Powered by Wheebox,
Gurgaon, Haryana.
Jackson, D., and Chapman, E. (2011), ‘Non-technical
competencies in undergraduate business degree programs:
Australian and UK perspectives’, Studies in Higher
Education, accessed by http://dx.doi.org/10.1080/
03075079.2010.527935.
John, O. P. (1989). Towards a taxonomy of personality
descriptors. In D. M. Buss & N. Cantor (Eds.),
Personality psychology: Recent trends and emerging
directions (pp.261–271). New York: Springer.
Jackson, D., Sibson, R., and Riebe, L. (2013) ‘Delivering
work-ready business graduates – keeping our promises
and evaluating our performance: An Australian case
study’. Journal of Teaching and Learning for
Graduate Employability, 4(1), 2-22.
Sudhir Chandra Das, Shalakha Rao
( 122 )
Little, B. (2011), ‘Employability for the workers – what does
this mean?’, Education + Training, 53 (1), 57-66.
Lew, M., Alwis, W., and Schmidt, H. (2010), Accuracy of
students’ self-assessment and theirbelief about
its utility’, Assessment & Evaluation in Higher
Education, 35 (10). 135- 136.
Marginson, S. (2006). ‘Dynamics of national and global
competition in higher education’, Higher Education,
52, 1–39.
Melia, M., & Heckerman, D. (1998). An experimental
comparison of several clustering and
initialization methods. Microsoft Research Technical
Report, MSR-TR-98-06.
National Center on Education and the Economy (NCEE)
(2007), ‘Tough choices or tough times: The report of the
new Commission on the Skills of the American Workforce’,
NCEE, Washington.
OECD (2014), ‘OECD Skills Outlook 2015: Youth, Skills and
Employability’, OECD Publishing. Accessed by http:/
/dx.doi.org/10.1787/9789264234178-en.
Olsen, Chris, and George, D. M. M. St. (2004). ‘Cross-
Sectional Study Design and Data Analysis’, The Young
Epidemiology Scholars Program (YES).
Oliver, B., Harper, W., Sadler, R., and Krause, K. (2011),
‘Approaches to monitoring and a s s u r i n g
academic standards in higher education’,
Proceedings of HERDSA Conference, 4 – 7
July, Griffith University, Gold Coast.
Prichard, J., Stratford, R., & Bizo, L. (2006). Team-skills
training enhances collaborative learning.
Learning and Instruction, 16, 256-265.
Phillips, D. C., & Burbules, N. C. (2000). Post positivism and
educational research. Lanham, MD: Rowman
& Littlefield.
Poindexter, S. (2003). Assessing active alternatives for
teaching programming. Journal of Information
Technology Education, 2, 257-265. Retrieved from
http://www. jite. org/ documents/Vol2/v2p257-
265-25.pdf.
Shefrin, H. (2009), ‘Ending the management illusion:
preventing another financial crisis’, Ivey Business
Journal, January/February. Retrieved from http://
www.iveybusine ssjournal. com/
article.asp?intArticle_ID=805.
Shury,J., Winterbotham, M., Davies, B., and Oldfield, K.
(2010), ‘National Employer Skills Survey for England
2009’. IFF Research and UK Commission for
Employment and Skills, London.
Unite for Sight (n.d.). ‘Study Design and Sampling-Research
Methodology Course’, Retrieved from http://
www.uniteforsight.org/research-methodology/
module2.
Zigmond G. William (2011). Business Research Methods,
Gengage Learning India Edition (7): Delhi
Zhang, T., Ramakrishnon, R., & Livny, M. (1996). BIRCH:
Method for very large databases. Proceedings of
the ACM Management of Data, 103-114. Montreal,
Canada.
Dr. Sudhir Chandra Das
Professor of OB & HR
Faculty of Commerce, Banaras Hindu University
Email : [email protected]
Ms. Shalakha Rao
Doctoral Scholar
Faculty of Commerce, BHU
Email : [email protected]
Capabilities in Employability Skills (Self Perceived) among Under-Graduate Commerce Students: A Cross –Sectional Study
( 123 )
Key words
Growth Drives, Investment
Opportunities, FDI Policy,
Foriegn Investors and
Agencies
Growth Driver of an Indian Economy-Make-in-India
K. Kanaka Raju
ABSTRACT
The main objectives of this paper are to examine the how far Make-in-India is responsible for
developing of the country and interpret and analyze the perceptions of respondents regarding
various issues of the Make-in-India along with suitable suggestions to strengthen the Make-in-
India. The data collected from the structured questionnaire through the 150 respondents (50
respondents from the each category of academician, corporate and accountant). The secondary
data obtained from the journals and websites. The frequency of percentage and regression
techniques was applied to infer the results. The study found that Make-in-India useful to develop
the Indian Economy and they wanted to relax the norms of FDI policy to further strengthening
of the Make-in-India. The study also found that only 29.8 percent of variation in Make-in-India
was explained by the investment opportunities, growth drivers of various sectors, agencies and
the foreign investors. This study also identified that growth drives of various sectors were the
more favourable response towards the developed country through the Make-in-India and followed
by investment opportunities, foreign investors and agencies. Finally it is suggested that the
necessary authority should take necessary action to develop the other activities (Digital India,
Swacha Bharat) because of the technique of Make-in-India only was not sufficient to view a
comprehensive self-reliance of a country.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
INTRODUCTION
“Doing Business 2015” report in the World Banks, India ranks 142nd out of 182 economies
lagging significantly behind China (90th) and Vietnam (78th), but also behind neighbours,
Nepal (108th), Bhutan (125th), Pakistan (128th). The India also seeks a challenges on
various issues of least ranking when compared with other countries, regarding
construction permits (184th), enforcing contracts (186th), starting a business (158th),
paying taxes (156th), getting electricity (137th) and resolving insolvency (137th). India’s
only success regarding protection of minority investors and occupied the 7th rank.
Foreign companies do not feel free with the India’s poor infrastructure, land purchase
agreements, excessive regulation, frequent power cuts and rigid labour laws. The
growth of Gross National Product (GNP) averaging 7.7 percent between 2002 and 2011
and it declined to about 5 percent in 2013 and 2014. The second reason was the mismatch
between demand and supply of jobs and manpower. India requires a number of jobs for
its young people, every year 12 million people join the work force but only 5 million
new jobs available. By the year 2022, the India’s labour force is anticipated to increase
to 600 million. The ability of job creation can help to divert from agriculture sector to
other sectors.
The third reason was India’s manufacturing sector contributes only 15 percent of GDP
and it was lesser productive when compared to its competitors, further India posses
( 124 )
the peculiar economic development model, facilitating
incentives to skilled labour only, but other countries
succeeds in facilitating incentives for job creating
manufacturing industries, there by China contributes 34
percent of GDP through the manufacturing sector and
pronounced that “Work Shop of the World”.The fourth
reason is increasing in the labour costs, India requires to
ameliorates its business situation in order to gain of the
manufacturing orders to countries offering prospects of
higher profits and to take advantage of shedding of
millions of jobs by China.The 2014 OECD Economic survey
of India emphasized that India must have a flexible
inflation – targeting frame work, strengthen and implement
a broad national value – added tax (GST) and reduce energy
subsidies and also emphasized on minimize the barriers
to manufacturing growth and adopt a flexible labour laws,
access to the more workers, provide the better education
and training programmes, increase the women’s economic
participation rate through the gender specific policies.
The mission of “Invest India agency” is investment
promotion and facilitation is the “back-end” of the
initiative of “Make in India” which was established as a
joint venture between the Department of Industrial Policy
and promotion with the Ministry of Commerce and
Industry (DIPP – 35% Stake), 28 State Governments (0.5%
Stake each) and the Federation of Indian Chambers of
Commerce and Industry (FICCI, 51% Stake). Doing
business in India today is much more difficult than
elsewhere (Enrico D Ambrogio), but Prime Minister of India
(Narendra Modi) launched the initiative of “Make in India”
to attract investors and India to become a global
manufacturing hub in 25th September 2014 and addressed
a 500 domestic and international entrepreneurs in New
Delhi in 25 priority sectors, with the logo shows a striding
lion made of cogs with the campaign name across its body.
The India can become a global leader in 25 sectors i.e.,
Chemicals, IT, Automobiles, Pharma, Textiles, Ports,
Aviation, Leather, Tourism and Hospitality, Wellness and
Railways etc., Each sector identified with the growth
drivers, investment opportunities, Sector specific FDI,
policies and agencies. The single point interaction for
investors assist to obtain regulatory clearance for foreign
investors. The government will identify the innovative and
technological companies to transform them in to global
champions and integrate in to global value chain. The
investor facilitation cell to help the foreign investors arrival
to departure from India, this cell also identify the most
significant companies in various sectors in indentified
countries. The prominent corporates, business chambers,
Growth Driver of an Indian Economy-Make-in-India
state governments and foreign companies are part of this
programme.
REVIEW OF LITERATURE
Samridhi Goyal , Prabhjot Kaur , Kawalpreet Singh(2015)
opined that to make INDIA a manufacturing hub its
human resource and financial assistance will play a major
role. Men and Money being the two most vital organ of a
business demands cautious capitalization and
innovation and they focused on an effectively motivated
and competitive human resource and availability of finance
in hand of the manufacturer decide the survival of a
company.
Satish Y. Deodhar(2015) expressed his opinion on Make
in India is an old mantra. It was very much there during
India’s colonial period and the post-independence
decades till 1991, free market is the engine of growth for
the economy and government has to provide the necessary
lubricant for it to work. This involves reforming industrial,
labour, and land acquisition laws; liberalizing inflow of
FDI and technology; simplifying and integrating state/
center administrative compliances for business;
government staying away from economic activities which
do not qualify for market failure argument, and, instead
concentrating on improving comparative advantage of the
country by investing in merit goods such as basic research,
primary education, and primary healthcare.
Research Problem: After verifying the existing literature
no appropriate research was done on make-in-India,
probably because of it was a new concept. Based on this
following research question was formed.
Research Question: How far the Make in India leads the
India towards the developed country.
OBJECTIVES OF THE STUDY
The study carried with the following objectives
1. To examine the statistics, strengths, reasons and
investment opportunities of Make-in-India along
with the role of agencies and foreign investors in
promotion of Make-in-India.
2. To examine the how fare Make-in-India is
responsible for developing of the country.
3. To interpret and analyze the perceptions of
respondents regarding various issues of the Make-
in-India.
( 125 )
4. To offer a suitable suggestions to strengthen the
Make-in-India.
METHODOLOGY OF THE STUDY
The data collected from the structured questionnaire
through the 150 respondents (50 respondents from the
each category of academician, corporate and accountant)
and the secondary data obtained from the journals and
website. The SPSS 16.0 version was used to infer the results
through applying the techniques of the frequency of
percentage, regression analysis etc.,
Strengths-Make-in-India
Construction: 1,000 billion US $ investments in 12th plan
(2012-17), 650 billion investments for urban infrastructure
in next 20 years
Defence Manufacturing: 3rd largest armed forces in the
world, 250 billion ‘ to be invested in 7-8 years
Electrical Machinery: US $ 9.4 billion of exports in 2013-
14. Export growth rate 14.8 percent for last 8 years
Electrical System: 3rd Largest pool of scientists in the world,
29 US $ billion consumer electronics market by 2020. 94.2
b US $ projected by 2015. Growth rate 9.88 percent by 2011-
15. National Knowledge Network (NKN) and National
Optical Fibre Network (NOFN)
IT industry: 118 billion US $ by 2014. 600 offshore
development centres for 78 countries. 225 billion US $ by
2020.
Leather Industry: 11 billion US $ industry. 66 US $ exports
in 2013-14. 10 percent of world’s leather production. 24
percent growth for next 5 years. 55 percent of work force
below 35.
Film Industry :220 billion US $ by 2018. 918 billion ‘ in
2013. 3rd largest TV market in the world. 40 million ‘
animation industry. 800 TV channels
Mining: 302 billion tones of coal. 3108 operational mines.
6th largest bauxite reserves. 5th Largest iron ore reserves.
Oil and Gas Industry: Ranks amongst India’s six core
industries. Fourth largest consumer. 70 billion US $ across
the oil and gas value chain by 2012-17.
Pharma Ceuticals: 3rd largest by 2020. 20 percent global
exports in generics, 45 billion US $ revenue by 2020. 26.16
billion US $ generics by 2016. 200 billion US $ on
infrastructure by 2024.
Ports: 87 new projects. 73 public private partnerships. 60
non-major ports. 800 million metric tones. 12 major ports.
430 billion ‘ invested between 2010-14.
Reasons to Invest in India-Make-in-India:
Construction: Modernization of the construction
industry, Ease of access to funding for the sector, sustained
demand for industrial and real estate sector.
Defence Manufacturing: Bolster exports in the longterm,
Introduced in the Capital Purchase agreements .Developing
Capabilities for exports in the defence sector. High
government allocation.
Electrical Machinery Power for all, 88.5 GW of capacity
by 2017 and GW 93 by 2022, capacity addition in power
generation. Scope of direct exports.
Electrical System: 94.2 billion US $ by 2015.Adequately
developed electronic Manufacturing Services (EMS)
industry, NKN, NOFN. 3rd largest. Availability of skilled
manpower of semiconductor design and embedded
software. manpower of semiconductor design and
embedded software.
IT industry: 8 percent of GDP. 7 percent of global market
by exports. More utilization of testing services of India.
Fostered several IT centres.
Leather Industry: Huge domestic market, Great Potential
for exports. Domestic market is expected to double in the
next 5 years. Comparative advantages in cost of production
and labour costs.
Film Industry : 1785.8 billion ‘ by 2018, with projected
growth in 16 percent. Third largest TV market after China
and USA
Oil and Gas Industry: Longer duration of 20 to 30 years
.Demand grow substantially over the next 15 years.
Convenient exports.
Pharma Ceuticals: India will become a top three by 2020.
6th largest market (size). Cost of production is less than
that of USA. Skilled work foce
Ports: Increase in cargo handling capacity. 28 PPP
terminals. Increase in capacity of 558 MMTPA. 2289 MMT
by 2017. Cargo traffic 943 MMT by 2017. Approximation
of SEZs to Ports.
K. Kanaka Raju
( 126 )
Statistics-Make-in-India
Defence Manufacturing: ‘ 1 billion for technology
development fund. ‘ 22.5 billion to strengthen and
modernize border infrastructure, exemption from Basic
Custom Duty (BCD). Countervailing Duty (CVD) on
imported goods.
Electrical Machinery: Tax incentives, Weighted tax
deduction of 200 percent. Under Sec. 35 (2AA) and Sec. 35
(2AB) of IT Act. Special incentive packages for mega
projects. Export incentives. Area based incentives.
Electrical System: Customs duty reduced from 10 percent
to Zero on LCD, LED panels, Education cess, investment
linked tax incentive, electronic manufacturing, clusters,
export incentives, area based incentives and state
incentives.
IT industry: 5 billion ‘ for Pan India programme. Digital
India. National Rural Internet and technology mission. E-
Kranti, Export incentives, area based incentives, State
incentives.
Leather Industry: Delicensed, IDLS, Sub Scheme of ILDP,
MLC, Mega Leather Clusters, 500 milion for Upgradation
Installation of Common Effluent Treatment Plants (CETPs).
Film Industry : 1000 million ‘ for growth of community
radio stations. 500 million ‘ for Pan-India programme
named Digital India and a National Rural Internet. 100
million ‘ to promote good governance and state incentives.
Oil and Gas Industry: Exploration and drilling costs are
100 percent .Tax deductable. State incentives, Focus Market
Scheme, Area based incentives, SEZs, NIMZs (National
Investment and Manufacturing Zones)
Pharma Ceuticals: Control programmes funded by the
Global Fund to Fight (AIDS, TB and Malaria, GFATM),
Investment allowance, Export incentives, area based
incentives, units in clusters, state incentives and R&D
benefits.
Ports: 116.35 billion ‘ for outer Harbour Project, Jal Marg
Vikas for 42 billion ‘ for 6 years. Exemption Section 80IA
under the Income Tax Act for infrastructure development.
Investment Opportunities -Make-in-Ind
Defence Manufacturing: Defence products
Manufacturing, Supply Chain Sourcing Opportunity and
Defence Offsets.
Electrical Machinery: Generation of Mechinery Biolers,
turbines, Generators – Projected to grow by 25-30 billion
by 2022.
Transmission and Development (T&D) is expected to grow
to US $ 70-75 billion from US $ 17.3 billion in 2012-13
Electrical System: Setting up of electronic manufacturing
clusters, Semiconductor wafer fabrication (FAB), electronic
components, semiconductor design, Electronics
Manufacturing Services (EMS), Telecom products and
Industrial / Consumer Electronics
IT industry: Setting of IT services, BPM, Software Product
Companies, shared service centres, Business process as a
Service (BPaaS), Cloud-based services, IS outsourcing, IT
consulting, Software testing, Tele command Semi
conductors
Leather Industry: Special focus sector for growth and
employment generation, possibility to create new
production centres
Film Industry : 125 billion ‘ in 2012 increased to 253 billion
‘ by 2018, teleport hub of Asia, 3D films, Joint Productions,
Co-production agreements, single window system for
shooting permissions. Growth in International animation
Films
Mining: Iron Steel, Coal, Aluminium, Base Metals, Precious
Metals and Minerals
Oil and Gas Industry: Shale, Coal Gasification, and
services and equipment companies, pipeline
transportations, partnership in upstream sector
Pharma Ceuticals: 7.2% increase in market share by 2016.
DMF = Drug Master Filings, CRAMS – Contract Research
and Manufacturing Service Industry. Double digit growth
in next 5 years
Ports: Port Development, Port Support Services, Ship repair
facilities
Foreign Investors -Make-in-In
Defence Manufacturing: BAE India Systems (UK), Pilatus
(Switzerland), Lockhead Martin (USA), Boeing India (USA),
Raytheon (USA), MBDA (France), IAI (Israel), Rafael (Israel)
Electrical Machinery: MHI (Japan), Hitachi (Japan),
Babcock (UK), Alstom (France), Toshiba (Japan), Ansaldo
(Italy), Colfax Corporation (USA), Schneider Electric
(France), Legrand (France) and GE (USA)
Growth Driver of an Indian Economy-Make-in-India
( 127 )
Electrical System: Samsung (South Korea), IBM (USA), LG
(South Korea), Tower Semi Conductor Limited (Israel), Dell
(USA), GE (USA), Jabil (USA), Motorola (USA), Lenovo
(China), Flextronics (USA), Nokia (Finland), Lite-on
(Taiwan), Fox Conn (Taiwan), Bosch (Germany), Applied
Materials (USA)
IT industry: Accenture (Ireland), Cugnizant (USA), HP
(USA), Capgemini (France), IBM (USA), Atos (France),
Microsoft (USA), CDNS (USA), Intel (USA), Dell
international (USA), Agilent Technologies (USA), Mentor
Graphics (USA), Oracle Corporation (USA), Qualcomm
(USA), Steria (France), Ricoh (Japan), SAP (Germany),
TIBCO (USA), Phillips (Netherlands)
Leather Industry: Apache Group (Taiwan), Feng Tay Shoes
(Taiwan), Itares (Italy)
Film Industry : Walt Disney (USA), NBC Universal (USA),
Ogilvy and Mather (USA), Blackstone (USA), Inter public
Group (UK), Bloomberg (USA), News Corp (USA), Sony
(Japan), Leo Burnett (USA), BBC (UK)
Mining: BHP Billion (Australia), Rio Tinto (Australia), Vedanta
Resources (UK), Indian Resources Limited (Australia), JFE
Steel Corporation (Japan), Australian Indian Resources
(Australia), China Steel Corporation (Taiwan), NSL
Consolidated (Australia), Kolar Gold (Guernsey)
Oil and Gas Industry: British Petroleum (UK), Cairn
Energy (India), Shell (UK), BG Group (Scottland), Niko
Resources (Canda)
Pharma Ceuticals: Teva Pharma Ceuticals (Israel), Nipro
Corporation (Japan), Procter and Camble (USA), Pfizer
(USA), Glaxo Smith Kline (UK), Johnson & Johnson (USA),
Suke Pharmaceuticals (Japan)
Ports: AP Moller Maersk (Denmark), PSA Singapore
(Singapore), Dubai Ports World (UAE), Jon Del Nul NV
(Belgium), Royal Boskalis (West Minister)
Agencies-Make-in-India
Defence Manufacturing: Ministry of Defence, Govt. of
India, Department of Defence production, Ministry of
Defence, Dept. of Industrial Policy and Promotion Ministry
of Commerce Industry, Defence and Strategic Industries
Association of India.
Electrical Machinery: The Department of Heavy industries,
Industry Associations, Indian Electrical and Electronics
Manufacturers Association, Engineering Export
Promotion Council
Electrical System: The Department of Electronics &
Information Technology, Ministry of Communications &
Information Technology, Govt. of India.
IT industry: Department of Electronics & IT, Ministry of
Communications & Information Technology, Govt. of
India, National Association of Software and Services
Companies, Indian Software Product Industry .Round
Table, Data Security Council of India.
Leather Industry: Foot wear Design and Development
Agency (FDDI), Council for Leather Exports (CLE), Central
Leather Research Institute (CLRI)
Film Industry : Ministry of Information and Broadcasting,
Govt. of India. Indian motion picture producers
Association, Film and Television Producers Guild of India,
News Paper Association of India, Indian Music Industry.
Mining: The Ministry of Mines, Govt. of India, Federation
of India Mineral Industries, The Geological Survey of India,
The Indian Bureau of Mines, The Aluminium Association
of India.
Oil and Gas Industry: Ministry of Petroleum and Natural
Gas, Oil Industry Development Board, Petroleum
Conservation Research Association, Directorate General
of Hydro Carbons, Petroleum Planning and Analysis Cell
Pharma Ceuticals: Department of Pharmaceuticals, India
Drug Manufacturers Association, Federation of Pharma
Entrepreneurs, Confederation of Indian Pharmaceutical
Industry.
Ports: Directorate General of Shipping, Indian Ports
Association (IPA), Inland Waterways Authority of India
(IWAI), Directorate General of Lighthouses and Light Ships
(DGLL)
Personnel Profile of the Respondents:
Table1:Distribution of Respondents by their Age
Age Frequency Percent Valid Percent
Cumulative Per cent
21-40 40 26.7 26.7 26.7
41-60 60 40.0 40.0 66.7
61-80 50 33.3 33.3 100.0 Total 150 100.0 100.0
Source:SPSS:Field Study
Table-1 : The above table narrates about the distribution
of respondents based on their age. The 40 percent of the
respondents belonged to the age group of 41-60 years,
followed by the 61-80 years and 21-40 years. Hence, it can
K. Kanaka Raju
( 128 )
be concluded that higher number of respondents belonged
to the age group of 41-60 years.
Table 2 : Distribution of Respondents based on their
Designation
Age Frequency Percent Valid Percent
Cumulative Per cent
Academician 50 33.3 33.3 33.3
Corporates 50 33.3 33.3 66.7 Accountant 50 33.3 33.3 100.0 Total 150 100.0 100.0
Source:SPSS:Field Study
Table-2 : This table narrates about the distribution of
respondents based on their designation. The equal number
of respondents (50, 33.3%) selected from each category of
academician, corporate and accountants.
Table 3 : Distribution of Respondents by their
Educational Qualifications
Educational Qualifications
Frequency Percent Valid Percent
Cumulative Per cent
Degree 10 6.7 6.7 6.7
M.Com 20 13.3 13.3 20.0
ICWAI 50 33.3 33.3 53.3
CA 30 20.0 20.0 73.3
M.B.A 10 6.7 6.7 80.0
M.Phil 20 13.3 13.3 93.3
Ph.D 10 6.7 6.7 100.0
Total 150 100.0 100.0
Source:SPSS:Field Study
Table-3 : This table tell us about the educational
qualifications of the respondents. The higher number of
respondents (33.3 percent) posses the qualification of
ICWAI, followed by the C.A., M.Phil, MBA and Ph.D.
Table 4 : Distribution of Respondents on their
Marital Status
Marital Status
Frequency Percent Valid Percent
Cumulative Per cent
Married 120 80.0 80.0 80.0
Unmarried 30 20.0 20.0 100.0 Total 150 100.0 100.0
Source:SPSS:Field Study
Table-4 : It is evident that the majority of the respondents
(80 percent) represented from the married category and 20
percent of them belonged to the unmarried category. Hence,
it can be concluded that the majority of the respondents
belonged to the married category.
Table 5: Respondents Opinion on Accept the Concept
of Make- In -India
Acceptance Frequency Percent Valid Percent
Cumulative Per cent
Accept 130 86.7 86.7 86.7
Not Accept 20 13.3 13.3 100.0
Total 150 100.0 100.0
Source:SPSS:Field Study
Table-5 : This table explains whether there is concept of
make in India accepted or rejected by the respondents. The
table exhibits that 86.7 percent of respondents accept the
concept of Make-in-India and remaining them (13.3percent)
not accepted, but it was practically evident that majority
of the respondents accept to introduce the concept of Make-
in-India.
Table 6: Relax the Norms of FDI Policy which are
Congruent with the Make - In- India
Norms of FDI
Frequency Percent Valid Percent
Cumulative Per cent
Yes 110 73.3 73.3 73.3
No 40 26.7 26.7 100.0
Total 150 100.0 100.0
Source:SPSS:Field Study
Table-6 : This table discloses the perceptions of the
respondents regarding relaxation of norms of FDI policy
which were congruent with Make-in-India. The majority
of the respondents (73.3 percent) wanted to relax the norms
of FDI policy to strengthen the Make-in-India and rest of
the respondents (26.7 percent) did not want to relax the
norms of FDI policy to strengthen the Make-in-India.
Table 7: Make In India Leads our Country towards
Developed Country
Norms of FDI
Frequency Percent Valid Percent
Cumulative Per cent
Yes 96 64.0 64.0 64.0
No 54 36.0 36.0 100.0
Total 150 100.0 100.0
Source:SPSS:Field Study
Table-7 : This table exhibits that whether the Make-in-
India leads our country towards developed country. The
majority of the respondents (64 percent) opined that Make-
in-India useful to develop the India from developing
country to developed country and rest of the respondents
(36 percent) opined that this concept may not lead to
develop the country. Hence, it can be concluded that the
majority of the respondents agreed that Make-in-India
leads our country towards developed country.
Growth Driver of an Indian Economy-Make-in-India
( 129 )
Table 8: Variables entered/Removed
Model Variables Entered Variables Removed
Method
Investment opportunities of various sectors are sufficient to implement the Make-in-India, Agencies play an important role in Make in India, Growth drivers of various sectors are sufficient to implement the Make in India, Foreign investors will play an important role rather than domestic investors regarding Make in Indiaa
Source:SPSS:Field Study
a. All requested variables entered.
b.Dependent Variable: Make In India Leads our Country
towards Developed Country
Table-8 : This table considers the entered variables as the
independent variables, these are investment opportunities
of various sectors, agencies, growth drivers of various
sectors and foreign investors and the dependent variable
was the Make-in-India leads our country towards
developed country.
Table 9: Test of Variability in towards Developed
Country with the Help of Make-in-India through the
Various Independent Variables.
Model R R Square
Adjusted R Square
Std.Error of the
Estimate
1 0.546 0.298 0.278 0.40917
Source:SPSS:Field Study
a. Predictors: (Constant), Investment opportunities of
various sectors are sufficient to implement , Agencies
play an important role in Make in India, Growth
drivers of various sectors are sufficient to implement
the Make in India, Foreign investors will play an
important role rather than domestic investors
regarding Make in India.
b. Dependent Variable: Make In India Leads our
Country towards Developed Country
Table-9 : This table narrates about the variation in Make-
in-India leads our country towards the developed country,
through the investment opportunities of various sectors,
agencies, growth drivers of various sectors and foreign
investors. The correlation coefficient was the (0.546) and
square of it (0.546)2 was considered as a coefficient of
determination (0.298) and came to knew that 29.8 percent
variation in towards developed country through the Make-
in-India was explained by the investment opportunities
of various sectors, agencies, foreign investors and growth
drivers of various sectors. The adjusted R square implies
that selected sample size was suitable, because of its value
was less than 1.00 and std. error of the estimate was very
less at 0.40917 and it was conveyed that to fit for regression
equation or model.
Table 10: Test of Difference Between Various
Independent Variables to Make In India Leads our
Country towards Developed Country
Model Sum of Squares
df Mean Square
F Sig
Regression 10.285 4 2.571 15.358 000a
Residual 24.275 145 .167
Total 34.560 149
Source:SPSS:Field Study
Predictors: (Constant), Investment opportunities of various
sectors are sufficient to implement the Make-in-India,
Agencies play an important role in Make in India, Growth
drivers of various sectors are sufficient to implement the
Make in India, Foreign investors will play an important
role rather than domestic investors regarding Make in India
b. Dependent Variable: Make In India Leads our
Country towards Developed Country
Table-10 :
Null Hypothesis (H0) : There is no significant difference
between make in India leads the developed country to the
investment opportunities, agencies, growth drivers and
foreign investors.
Alternative Hypothesis (Ha): There is a significant
difference between make in India leads the developed
country to the investment opportunities, agencies, growth
drivers and foreign investors.
K. Kanaka Raju
( 130 )
Analysis : The sum of residual value was much more than
the sum of the regression value at degree of freedom was
149 and the value of F was 15.358 and the value of
significance was 0.000, hence, it can be concluded that
there was a significant difference between the help of Make
in India to the investment opportunities, agencies, growth
drivers and foreign investors.
Table 11: Test of More Favorable Response Towards
the Developed Country through Make-in-India.
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig. B Std. Error Beta
1 (Constant) 2.187 .364 6.007 .000
Agencies play an important role in Make in India
-.364 .057 -.463 -6.404 .000
Growth drivers of various sectors are sufficient to
implement the Make in India
.131 .053 .196 2.446 .016
Foreign investors will play
an important role rather than domestic investors regarding Make in India
.030 .069 .036 .435 .664
Investment opportunities of various sectors are
sufficient to implement the Make-in-India
.037 .062 .052 .598 .551
a. Dependent Variable: Make In India Leads our Country towards Developed Country
Source:SPSS:Field Study
Table-11: This table discloses the more favourable response
towards the developed country through the various
independent variables. The table tells us that the growth
drivers of various sectors was more favourable response
towards the developed country through the Make-in-India,
followed by the investment opportunities of various
sectors, foreign investors and the agencies. Finally, it can
be concluded that the most favourable response was the
growth drivers of various sectors and the least preference
was the agencies.
FINDINGS OF THE STUDY
1. The study found that the majority of the respondents
favourable towards introducing of concept of Make-
in-India and also majority of them wanted to relax
the norms of FDI policy to promote the concept of
Make-in-India.
2. The majority of the respondents opined that Make-
in-India useful to develop the country.
3. The 29.8 percent of variation in Make-in-India leads
towards developed country was explained by the
investment opportunities of various sectors,
agencies, growth drivers of various sectors and the
foreign investors and found that there was a
significant difference between dependent variable
to the independent variable statistically.
4. The study found that growth drivers were the more
favourable response towards the developed country
through Make-in-India and followed by other
variables investment opportunities foreign investors
and agencies.
SUGGESTIONS
1. Optimising regulatory process of business
2. Simplify the procedure to issue license.
3. Registration of a new business in a single day instead
of 27 days
4. Introduce the unique company ID
5. 7 steps of electricity supply will be reduced to one
step.
6. Registration of property through an online in a single
procedure.
7. The number of taxes will be reduced and simplify
the procedure of payment of taxes
8. Establish a fast – track commercial courts, decision
will be taken by these courts within 60 days instead
of current average of 3 years.
9. Introduce a single bankruptcy law in place of
existing four overlapping ones.
CONCLUSION
Finally, it can be concluded that only a meagre portion
only influence towards the developed country through
the Make-in-India, and it indicates that the other factors
also influence the developing of the country like, Digital
India, Swachha Bharat and other schemes. But the Make-
in-India should promote the self-reliance in making of the
all nature of products from all available sectors.
Growth Driver of an Indian Economy-Make-in-India
( 131 )
REFERENCES
Make in India : How PM Modi’s Ambitious plan will make
India Manufacturing Super Power – ET Bureau, Sep.
25, 2014, 9.34 AM IST.
Make in India for more Made in India posted by Members
Research Service, January 22, 2015, filed under at a
glance, Economic Development, Enrico D
Ambrogio, Entrepreneurs, India, Jobs.
http://www.makeinindia.com/sectors/
Samridhi Goyal , Prabhjot Kaur , Kawalpreet Singh(2015)
Role of HR and Financial Services in Making “Make
in India” Campaign a Success, , IOSR Journal of
Business and Management (IOSR-JBM) e-ISSN:
2278-487X, p-ISSN: 2319-7668. Volume 17, 20-24
www.iosrjournals.org DOI: 10.9790/487X-
17242024 www.iosrjournals.org 20 | Page
Satish Y. Deodhar(2015) . Make in India: Re-chanting the
Mantra with a Difference ,W.P. No.2015-02-02,
February 2015.
Dr. K. Kanaka Raju
Assistant Professor
Department of Commerce and Management Studies,
Andhra University Campus,
Tadepalligudem,
West Godavari –District.
Email : [email protected].
K. Kanaka Raju
( 132 )
Key words
Demographic Dividend,
Make in India, Teach in
India
Make in India vs. Teach in India: A Case study ofHigher Education in India
Kripa Shankar Jaiswal
ABSTRACT
By 2020, India will become the world’s youngest country with 64% of its population in the
working age group. This population will rise by 12.5 crore, creating a need for 10 crore new jobs.
Contrary to this picture, the reality is that as per the National Employability Report 2014 states
that less than 1% of engineering graduates are employable in real sense. This presents the grim
reality of the higher education scenario in the country. India is riding high on the back of “Make
in India” campaign in order to make the country favourite destination for the foreign investors.
But with dilapidated higher education scenario in the country, it will not be possible for the
nation to capitalize the demographic dividend of the country. The need of the hour is to launch
emphasise on “Teach in India” campaign so that our workforce can be turned into skilled
workforce and reap the benefits of churning out the country into a manufacturing hub. The
present paper will expose the readers to the present scenario of Indian higher education and how
by focusing on “Teach in India’ the country can tread on the path of “Make in India”.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
INTRODUCTION
In its size and diversity, India has the third largest higher education system in the
world, next only to China and the United States1 and it is expected to become the first
largest within the upcoming fifteen years. For a highly populated country like India,
quality higher education serves as the lifeline. The key to reap the demographic dividends
lies in the quality higher education. By 2030, India will be amongst the youngest nations
in the world. With nearly 140 million people in the college-going age group, one in
every four graduates in the world will be a product of the Indian education system.
Indian higher education has progressed by leaps and bounds post Independence era.
At present we have gross enrolment ratio of about 17.9% now, while an ambitious
target of 25.2% has been envisaged by the end of 12th Plan2. This is indeed, a herculean
task India, still lacks behind on several fronts when we talk about the scenario of
higher education. With no Indian university figuring in top 200 universities across the
globe, the task becomes difficult all the more as it stages the dilapidated state of the
Indian universities in present scenario.
The Framework of Indian Higher Education: Higher education typically comprises
under-graduate, post graduate degrees and pre-doctoral and doctoral programs. The
institutions of higher learning providing the above mentioned programs in India fall
into the following broad categories:
a) Universities: These are established by an Act of Parliament or State Legislature
and are of unitary or affiliating type. They are called Central Universities and
State Universities respectively. Colleges form a part of these universities where
they provide higher education to the students.
( 133 )
b) Deemed to be Universities: These institutions are
given deemed to be university status by the Central
Government on the recommendation of the UGC in
terms of Section 3 of the UGC Act. Some of these
institutions offer advanced level courses in a
particular field or specialization while others award
general degrees.
c) Private Universities: These are established by
various State governments through their own
legislation.
d) Institutes of National Importance: These Institutes
are declared as such by the Government of India by
an Act of Parliament and are empowered to award
degrees. In some cases, such Institutes are also set
up by the Government through an Act of State
Legislation.
e) Premier Institutes of Management: These are the
Institutes that have been set up by the Central
Government and are outside the formal university
system. They offer Post-Graduate Diploma
Programmes which are equivalent to Master ’s
Degree Programmes in area of management.
The emphasis on higher education in India can be
understood by the number of universities currently present
in India and the quality of education they provide. As of
2014, there are more than 677 universities, 37,204 colleges
and 11443 stand-alone institutions in India, as per the
latest statistics from the website of India’s HRD ministry.
These numbers would only have increased by now.
• 225 private universities
• 46 central Universities
• 1 central/ national open university
• 13 state open Universities
• 73 institutes of national importance (INI)
• 336 state public universities
• 5 institute under state legislature act
• 38 deemed universities (Government)
• 11 deemed universities (Government Aided)
• 3 other universities
Objective of Higher Education: According to the National
policy on Education (NPE) -86 [1, Part V, p.14], ¯Higher
education provides people with an opportunity to reflect
on the critical social, economic, cultural, moral and
spiritual issues facing humanity. It contributes to national
development through dissemination of specialized
knowledge and skills. It is therefore crucial factor for
survival. Being at the apex of the educational pyramid, it
Kripa Shankar Jaiswal
has also a key role in producing teachers for the education
system. Thus, we see that the aim & objective of the higher
education is to change the lives of human being living in
the society. This change has to take place in totality.
Higher Education Scenario in India: In present scenario,
Indian higher education has to face a plethora of problems.
Some of these problems can be summed up in the following
words below:
1. Traditional & Outdated Course Curriculum: This
is one of the most common problems that higher
education in India is facing today when it comes to
course curriculum. Baring few exceptions like IITs,
IIMs & IIS, the course curriculum of Indian
university system (or higher education) have become
outdated and old fashioned. The present higher
education seems to have stuck with the traditional
courses like B.A, & B.Sc, etc. where they are
introduced to the same old course content which is
being taught for decades. With no significant change
in course content, the students lose creativity and
enthusiasm to study, thereby resulting in the loss of
inventing and discovering of new facts. However,
what is ironical is the fact that the same students
excel with flying colours when they go abroad for
higher studies. As the foreign universities have
updated with creative course contents, the students
studying there develop a feel for creativity and
invention.
2. Non- Vocational Courses: Another problem with
the course curriculum of Indian higher education
system is that it is not vocational in nature.
Vocational courses are technical courses specially
meant for low-skilled and medium-skilled workers.
Vocational training and education has got immense
potential to channelize inefficient worker into
productive workers. A skilled workforce is an
indispensible weapon in the hands of an industrial
country to combat the evils of underdevelopment
and poverty. Countries like China, Japan, Korea,
Singapore, Germany etc. have registered historical
successes mainly due to the presence of a highly
competitive and skilled workforce. But India, in spite
of having a huge population of young and energetic
workforce has failed to gain the required momentum
of growth. Skill development has for long been
neglected and still over 90 percent of our workforce
at present times is devoid of any formal training
prior to employment. This is significantly due to the
( 134 )
non adoption of vocational courses in higher
education. Of course, few changes have taken place
in this area and now the respective governments
are emphasizing towards development of new
vocational course to impart training based teaching
to the students.
3. Absence of University-Industry Partnerships in
Doctoral Research in India: In India, barring few
instances like healthcare, pharmacy, agriculture,
extension services, etc., the corporate sector remains
averse to employing human resource in possession
of the doctoral degrees. Those pursuing Ph.Ds in
non-science disciplines depend completely on the
jobs arising in the academics sector. However, there
are simply too many PhDs produced every year for
the higher education establishment to absorb them
all. Naturally, the Ph.d holders look for jobs in the
corporate sector which is quite a cumbersome task.
They are often rejected due to the very Ph.D degree
they owe. Even if they succeed to land up with a job
in the corporate sector, the corporate fails to
capitalize the knowledge of these Ph.D holders citing
their research degrees as redundant for them.
Therefore, to combat this non absorbance of Ph.d
holders by the corporate sector, it becomes imperative
to promote university-industry partnerships to
generated qualified researchers and join the
corporate sector in different capacities. Today,
businesses are looking for innovative solutions from
the academia to help meet their business needs at
technical and managerial front. A market-driven
approach to doctoral level has to be fostered in order
to encourage manpower development in the country.
4. Quality Degradation: Degrading quality is one of
the gravest issues at present times. Not only in terms
of academic course curriculums, faculty
recruitments and research, but also in the field of
infrastructure, the higher education has been
affected by quality degradation. The focus is more
on quantity rather than on quality. Rising cases of
plagiarism, below standard research work, no
progress on patent works, failure to develop good
and relevant case studies, etc. are only some
examples to focus on the falling standards of higher
education in India. To address the issues of quality,
the National Policy on Education (1986) and the
Plan of Action (POA-1992) advocated the
establishment of an independent national
accreditation body. Consequently, the NAAC was
established in 1994 with its headquarters at
Bangalore. This body is trying to render its
contribution towards addressing quality related
issues in the present higher education system of
India, but still much needs to be done towards this
aspect.
5. Regional disparity: This is one of the significant
problems when it comes to problems associated with
higher education in India. Most of the IITs, IIMs, IISc
are either situated either in southern or in northern
part of the country. Northeast and far distant areas
have so far has remained neglected. Although new
initiatives have been taken to development centers
of excellence in those areas, but they fail to draw
attention of the students as most of these institutes
lack basic infrastructure and faculties. For example,
the best ITIs imparting quality vocational education
are located in the NCR area of the country,
particularly Haryana. Whereas the other parts of
the country remains mostly neglected. The urgent
need of the hour is to come up with new
establishments across all the states with equal
enthusiasm and sound intentions in mind.
6. No or little autonomy: The educational institutions
in the higher education sector are mostly governed
by either the state government or central government
or by the respective ministries. They have to look up
to the respective bodies when it comes to decision
making, thereby resulting in the loss of time. The
bureaucratic mechanism hinders the development
of these institutes in imparting quality education to
the students. Institutes like IIScs, IITs & IIMs which
have got considerable degree of freedom when it
comes to decision making. This is one of the prime
reasons why these institutes have excelled in the
higher education sector. Although some monitoring
and controlling is obviously required in the
governance of institutes in the higher education
sector, it can mostly be limited to implementation of
the rules and regulations passed by the respective
governments in the course of time.
7. Extreme Politicalization: In the present times, the
country is witnessing the entry of political class in
the higher education sector. In the name of providing
educational service to the masses, the political class
are opening up new institutes of education to impart
higher education. A number of management and
Make in India vs. Teach in India: A Case study of Higher Education in India
( 135 )
engineering colleges have mushroomed up across
the lengths and breadths of the country. With no
proper teaching pedagogy, teachers with below
qualification, these institutes are causing severe
harm to the higher education fabric of the country.
In other words, we have done exceptionally well at
the quantity front, but we have failed badly on
quality issues. The emergence of “Shiksha Mafias”
has no done severe damages to the higher education
environment of the country.
8. Slow reforms in Examination Pattern: The pattern
of examination and evaluation should be
progressively changed to continuous internal
evaluation by evolving an open, transparent and
full-proof system with an appropriate mechanism
for effective grievance redressal. The credit and
semester mode should be preferable to the uniform,
annual mode, as the former would give the students
an opportunity to select subject combinations of their
choice and to encourage more focused learning by
dividing the content into manageable chunks3.
9. Delays in Academic Sessions: Universities,
particularly state universities, suffer from the
problem of long delays in the running of academic
sessions. Delay in declaration of results, admissions,
etc. serve as the main catalyst towards the delaying
of the sessions. As a result, many students fail to get
admission of their choice due to this delay.
10. Not based on meritocracy: World class universities
are deeply meritocratic institutions. They hire the
best professors, admit the most intelligent students,
reward the brightest academics, and make all
decisions on the basis of quality. They reject - and
punish - plagiarism, favouritism in appointments,
or corruption of any kind. Much of Indian academe,
unfortunately, does not reflect these values. Some of
the problem is structural. The practice of admitting
students and hiring professors on the basis of rigid
quotas set for particular population groups - up to
49% - however well intentioned or justified virtually
precludes meritocracy. Deeply ingrained in Indian
society and politics, the reservations system may
well be justified - but to have successful world class
universities, meritocracy must be the primary
motivating principle.
11. Absence of high-tech libraries: In India, we have
not been able to meet the requirements of the
Kripa Shankar Jaiswal
students when it comes to providing high-tech
library system. Libraries across the state universities
and colleges are poorly maintained forcing the
students to refrain away from them. as a result, the
students have not yet been able to develop the
reading habit in libraries. Books in libraries are often
kept confined in Indian libraries. The need of the
hour is to come up with high tech libraries so that
students can get maximum benefit of it.
12. Poor Faculty Ration: The institutes of higher learning
under the Ministry of Human Resource
Development (HRD) face a faculty shortage to an
extent of 35% according to the latest data available
with the government. IITs top the list with 39%
vacancies and Central Universities follow with 38%
vacancies. Delhi University has a shortage of more
than 50% closely followed by University of
Allahabad. Out of IIMs, IIM Indore is facing a 52%
shortage while IIM Ranchi is facing a 48% shortage.
The older IIMs at Ahmedabad, Calcutta & Bangalore
are also facing a severe shortage of faculty. IIM
Ahmedabad is the worst hit with a 29% shortage.
Out of the NITs, 5 of them are facing a shortage of
over 40%. NIT Delhi tops the list with 50% shortage
of faculty. The NITs in Raipur, Uttarakhand &
Meghalaya are each facing only an 8% shortage of
faculty. In terms of the overall numbers, NITs seem
to be better placed than the IITs with only a 29%
shortage of faculty4.
13. Little Collaboration with Foreign/Inter Country
Universities: There is almost no or little
collaboration of Indian universities/colleges with
foreign or other state/central universities within the
country. Collaboration promotes cultural exchanges
resulting in the overall development of the students.
Also, good things can also be exchanged with the
help of collaborations.
14. No Control Mechanism on Private institutes: The
emergence of private institutes in the higher
education sector has deeply hurt the soul of
education system in India. Although these private
institutes perform much better in terms of
infrastructure, they perform fairly low when it comes
to imparting education higher education to the
students. The faculty profiles of these institutes are
below average as they are hired without any
qualification laid down by the UGC. This is perhaps
( 136 )
the reason why thousands of engineering and
management colleges are being devoid of students
in recent years. In the absence of any control
mechanism, these institutes are flourishing and
destroying the fabric of higher education in India.
Most of the bodies like, UGC, AICTE are mainly
concerned with the approvals and sanctions. A
statutory body needs to be evolved to control the
functioning of such institutes.
Imperatives to address the problems & issues
1. The course content should be market driven. The
course content should be drafted in such a manner
that it is capable to meet the skill needs of the market
and offer employability to the students pursuing
higher education. Written assignments, seminars,
problem solving sessions, projects, field studies and
so on should become integral to any reform in
pedagogy. Through a dialogic process, the teacher
should induce the student to think, innovate and
challenge existing ideas and generate new
knowledge.
2. A research driven culture needs to be developed at
the earliest. Corporate- Academic Interface is an
urgent need of the hour.
3. Examination pattern needs to be modified. Our
present system is marks based and not knowledge
based. We need to devise a examination system
which should evaluate the students on the
parameters of creativity, innovation, learning etc. It
should not be based on simple copy evaluation
technique.
4. Universities should be made more accountable and
autonomy should be linked up with accountability.
We need a decentralized democratic system of
academic governance that would translate the ideal
of socially accountable autonomy into a living
reality.
5. A system of academic audit needs to be developed
which should be compulsorily posted and updated
at regular intervals.
6. Different exams are being conducted for the
recruitment of the faculty in the university system.
There is NET, SLET, SET, etc. We need to evolve on a
single examination pattern like ‘Indian Educational
Service’ similar to that of IAS, IPS, etc.
7. More foreign collaboration or inter university
collaboration should be promoted. This will
facilitate in the exchange of ‘USPs’ with each other.
8. State universities/colleges have very poor
infrastructure facilities. The government must pour
in enough funds to improve the infrastructure of
such universities.
9. The private organizations should also ensure that
they must invest a substantial amount of their profits
in CSR initiative, more specifically in the academic
sector. As the private institutions are financially in
a much better position to invest in this sector, they
should come forward voluntarily and render
vocational education and training to the unskilled
workforce. They are better equipped with the
required knowledge and mechanism to impart
vocational education to the students. For this
purpose, they can utilise the infrastructure of the
government institutions to provide quality training
to the needed worker.
CONCLUSION
The present government has given great impetus on
initiatives like “Make in India”, “Manufacture in India”,
etc. The roads to the success of all these initiatives pass
through providing good higher education to the students
in the country. Every year thousands of students leave
abroad in search of better education. This leads to the loss
of valuable foreign exchange which could have been
prevented had there been good number of academic
institutions and universities in India. The government
should also focus on “Teach in India” campaign which
could turn the country into a manufacturing hub of learned
and skilled youth. As the country is being governed by the
inequalities that prevail in the higher education scenario,
the need of the hour is to launch a massive “Teach in India’
campaign. The objective of this campaign should be to
encourage the outstanding entrepreneurs, academicians,
NGOs to disseminate vocational education in true sense.
Learning should take place through the proper
amalgamation of Innovation, Inquiry, Teacher and
Technology. All these four components need to be invested
in skill development of the young generation. The
advantage of the Indian workforce is that, they are well
aware with the technology and knows English. With
appropriate training this young crop of workforce can be
trained to make the campaign of “Make in India”
Make in India vs. Teach in India: A Case study of Higher Education in India
( 137 )
successful. It has to be kept in mind that without training
and educating the workforce, it will not be able to capitalize
the advantages and benefits of our rich demographic
dividend. And that will come through investing in “Teach
in India” campaign. “Make in India’ also talks about
“Knowledge Management”. But “Teach in India” will
focus on creating and training “knowledge Workers”.
Therefore, it is quite imperative that the priority should be
give to “Teach in India” campaign. Everything else will
follow the foot prints of our young workforce.
REFERENCES
“India Country Summary of Higher Education” (PDF).
World Bank.
http://timesofindia.indiatimes.com/home/education/
n e w s / H i g h e r - E d u c a t i o n - i n - I n d i a - A n -
introspection/articleshow/38776482.cms
Arunachalam, P., 2010. Higher Education Sector in India:
Issues and Imperatives. Journal of Global Economy,,
Volume 6 (No 4), p. 288.
https://factly.in/35-faculty-positions-in-higher-
education-india-institutes/ accessed on 28/09/15.
Prof. Kripa Shankar Jaiswal
Dean
Faculty of Commerce & Management Studies
Director
Institute of Management Studies
Mahatma Gandhi Kashi Vidyapith
Varanasi- 221002, U.P.
Kripa Shankar Jaiswal
( 138 )
Key words
Nuclear Power Generation,
Coal Energy, Renewable
Energy Resources,
Environment, Community,
Nuclear Power
Corporation of India,
Transmission &
Distribution
Nuclear Power Generation for Industrializationvis-a-vis Impact on Environment and Community :A Case Study of India
Sanket Vij, Narender Garg and H J Ghosh Roy
ABSTRACT
The present study examines the status of Nuclear Power Generation for Industrialization vis-a-
vis Impact on Environment and Community in India from divergent angles. The need of Nuclear
Technologies for power generation has been widely recognized especially in the under developed
and developing countries with an objective to meet the industrial demand for energy. The study
identified and highlights the different factors related to power generation, which have impact on
Environment and Community in India. At present 51 Nuclear Power Generation Units are
established and operating in the six states of India i.e. Maharashtra, Rajasthan, Karnataka,
Tamilnadu, Uttarpradesh, and Gujarat and these states were included in the study and data was
collected from 3000 respondents. The results of the analysis would enable the Nuclear Power
Corporation of India and Ministry of Environment to further recognize the need and impact of
nuclear power generation on Environment and Community in India.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
INTRODUCTION
Power Sector in India has grown significantly since independence both in the installed
electricity generating capacity and Transmission & Distribution (T&D) system. The
total power generating capacity of (utilities & non utilities) has increased from meagre
1362 MW in 1947 to 267 GW at the end of March, 2015.The per capita electricity
consumption which was mere 16.3 kWh in 1947 has increased to 1010 KW h in 2014-
15. On 31st March, 1947, there was no electricity in any of the village of India and by 31st
March 2015, 577629 villages were electrified (Exhibit No. 1.0). However, the per capita
consumption in India was 819 KWh and 884 KWh in 2010-11 and 2011-12 as compare
to Global per capita consumption 2933 KWh and 2972 KWh in 2010-11 and 2011-12,
respectively. (Key World Energy Statistics - IEA, 2013)
Despite this, the growth of electricity demand has surpassed the power supply and our
country has been facing power shortages during peak electricity demand inspite of the
manifold growth overthe years. Government of India lays special emphasis on reduction
of T&D losses and demand side management to optimally utilize the limited resources.
(Central Electricity Authority, 2015)
Out of Total Gross Electricity Generation in India Mode-wise, 75.61% (835838 GWh)
electricity was generated through Coal, 11.60% (129244 GWh) electricity was generated
through Hydro, 5.59% (61780 GWh) electricity was generated through Renewable
Energy Resources (R.E.S.), 3.72% (41075 GWh) electricity was generated through Gas,
3.27% (36102 GWh) electricity was generated through Nuclear Plants and 0.13% (1407
GWh) electricity was generated through Diesel at the end of 3rd year of 12th Plan, which
is very low as compare to most of the developed economies of the world (Exhibit No. 2.0
& Exhibit No. 3.0)
( 139 )
Sanket Vij, Narender Garg, H J Ghosh Roy
Plan-wise Growth of Electricity Sector in India Exhibit No. 1.0
PLAN-WISE GROWTH OF ELECTRICITY SECTOR IN INDIA UTILITIES
(Source : Central Electricity Authority, 2015)
S.No As on during financial year ending with Installed Capacity electrified
No.of Villages (MW)
Length of T & D Lines (Ckt.
kms.X#)
Per Capita Consumption
(KWhX$) 1 31.12.1947 1362 N.A. 23238 16.3
2 31.12.1950 1713 3061 29271 18.2 3 31.03.1956( Bid of the 1st PI31) 2836 7294 85427 30.9
4 31 03.1961 ( Bid of the 2nd Plan) 4653 21754 157887 45.9 5 31.03.1966 (End of Hie 3rd Han) 9027 45148 541704 73.9
6 31.03 1969( Bid of the 3 Annual Plans) 12957 73739 886301 97.9 7 31.03.1974( Bid of the 4»l Ran) 16664 156729 1546097 126.2
S 31.03.1979( Bid of the 5th R an) 26680 232770 2145919 171.6 9 31 03 1930( Bid of the 2 Annual Rans) 28448 249799 2351609 172.4
10 31.03.1985( Bid of the 6th Ran) 42585 370332 3211956 228.7 11 31.03.1990( Bid of the 7th Ran) 63636 470838 4407601 329.2
12 31.03.1992( Bid of the 2 Annual Rans) 69065 487170 4574200 347.5 13 31.03.1997( Bid of the 8tl Ran) 85795 498836 5141413 464.6
14 31.03.2002( Bid of the 9th Ran) 105046 512153 6030148 559.2
15 31.03.2007 (Bid of 10»l Ran ) 132329 482864 6939894 671.9 16 31.03.2012 (Bid of 11tl Ran ) 199877 556633 8726092 883.6
17 31.03.2013(End of 1st year of 12H Ran) 223343 560552 9080556 914.4 18 31.03.2014(End of llnd yea of 12th Ran) 245259 572414 9534584" 957.0
19 31.03.2015(End of 11 li- d yea of 12th Plan)
271722 577629"* 10558177@ 1010
N.A. Not Available (*) Provisional
(^) As per revised definition of village electrification and 2001 Census
(#) Includes 440 Volts Distibution Lines @ Estimated
$ Per capita Consumption = Gross Eelctrical Energy Availability/Mid Year Popuation
Mode-Wise and Plan-Wise Growth of Electricity in India (Exhibit No. 2.0)
(GWlh)
S.No During financial year ending with Hydro Thermal Total Nuclear RES Total
Coal $ Gas Diesel
1 1947 2195 1733 0 144 1877 0 0 4073
2 1950 2519 2587 0 200 2787 0 0 5106 3 1955-56(End ol the 1st Plan) 4295 5367 0 233 5600 0 0 9662
4 1960-61 (End of the 2nd Plan) 7837 9100 0 368 9468 0 0 16937 5 1965-66(End of the 3rd Plan) 15225 17765 69 324 18158 0 0 32990
6 1968-69(End of the 3 Annual Plans) 20723 26711 124 194 27029 0 0 47434 7 1973-74(End ot the 4th Plan) 28972 34653 343 125 35321 2396 0 66689
8 1978-79(End of the 5th Plan) 47159 52024 515 55 52594 2770 0 102523 9 1979-80(End of the Annual Plan) 45478 55720 500 53 56273 2876 0 104627
10 1984-85(End of the 6th Plan) 53948 9695 7 1834 45 98836 4075 0 156659 11 1989-90 (End of the 7th Plan) 62116 172643 5962 85 178690 4625 6 245438
12 1991-92(End of the 2 Annual Plans) 72757 197163 11450 95 208708 5525 38 287029 13 1996-97(End of the 8th Plan) 68901 269378 26985 679 317042 9071 876 395889
14 2001-02(End of the 9th Plan) 73579 370864 47099 4317 422300 19475 2065 517439 15 2006-07(End of the 10th Plan ) 113502 461794 64157 2539 526490 18802 9860 670654
16 2011-12(End of the 11th Plan) 130511 612497 93281 2649 708427 3228656 51226 922451 17 2012-13(End of 1st year of 12th Plan) 113720 691341 66864 2449 760454 32866 57449 964489
18 2013-14(End of IInd year of 12th Plan) 134847 746087 44522 1868 792477 34228 59615 1021167
19 2014-15(End of IInd year of 12th Plan) 129244 835838 41075 1407 878320 36102 61780 1105446
$ Includes Lignite
RES Renewable Energy Sources
Source : Central Electricity Authority, 2015
( 140 )
Out of Total 938823 GWh electricity consumption, 42.10%
(395331 GWh) electricity was consumed by Industrial
sector, 23.53% (220894 GWh) electricity was consumed by
Domestic sector, 18.45% (173200 GWh) electricity was
consumed by Agriculture Sector, 8.77% (782322 GWh)
electricity was consumed by Commercial Sector, 5.37%
(50392 GWh) electricity was consumed for Miscellaneous
purpose and 1.79% (16794 GWh) electricity was consumed
for Traction purpose at the end of 3rd year of 12th Plan.
(Exhibit No. 4.0)
Out of total install capacity of 276783 MW in India, the
share of State sector was 34.7% (96015 MW), Central sector
was 26.8% (74171 MW) and private sector was 38.5%
(106597 MW). The share of Coal Plants in the total installed
capacity in India is 60.8% (168,208 MW). (Exhibit No. 5.0)
Mode-wise Installed Capacity Exhibit No. 5.0
Fuel Thermal
Total Coal Gas Oil Hydro Nuclear RES Total MW 192,535 168,208 23,333 994 41,997 5,780 36,471 276,783
%age 69.6 60.8 8.4 0.4 15.2 2.1 13.2 100
Globally, it is well established that emissions from coal-
fired power are responsible for significant levels of illness
and premature death. Debi Goenka & Sarath Guttikunda
(2013) study on Coal Kills : An Assessment of Death and
Disease caused by India’s Dirtiest Energy Source uses database
of coal-fired power plants compiled by Urban Emissions
for the operational period of 2011-12 and derived the
pollution impact generated by selected coal plants and
the same is summarized below :
Nuclear Power Generation for Industrialization vis-a-vis Impact on Environment and Community : A Case Study of India
Mode-Wise % Share in Electricity Generation in various countries - 2012
(Exhibit No. 3.0) United
States People's Republic of China
Japan Russian Feder- ation
India Germany Canada France Korea United Kingdom
Italy Australia South Africa
Brazil
� Others 5.86 2.95 5.16 0.33 5.55 20.90 3.27 4.91 0.77 10.49 17.95 4.00 0.17 7.30
� Hydro 6.52 17.31 7.35 15.51 14.15 3.40 59.99 10.50 0.75 1.46 14.09 5.64 0.78 75.22
� Nuclear 18.76 1.95 1.55 16.60 3.50 15.96 14.95 76.05 28.32 19.51 0.00 0.00 5.73 2.90
� Gas 29.61 1.72 38.71 49.13 10.11 12.45 10.65 3.90 21.09 27.73 43.41 19.93 0.00 8.47
� Oil 0.77 0.14 12.23 2.62 0.29 1.22 1.10 0.78 3.99 0.85 6.35 1.63 0.08 3.55
� Coal 38.48 75.93 34.99 15.80 66.40 46.06 10.04 3.87 45.09 39.95 18.20 68.80 93.84 2.57
Source : International Energy Agency (IEA) (Except India)
Plan/Category-Wise growth of Electricity Consumption in India
(Exhibit No. 4.0)No During financial year ending with Domesti
c Total Comm-
ercial Total Industrial Total Traction Total Agricul
ture Total Misc. % to
To tal Total
1 1947 423 10.11 178 4.26 2960 70.78 277 6.62 125 2.99 219 5.24 4182
2 1950 525 9.36 309 5.51 4057 72.32 3C8 5.49 162 2.89 249 4.44 5610
3 1955-56 (End of the 1st Plan) 934 9.20 546 5.38 7514 74.03 405 3.99 316 3.11 435 4.29 10193
4 1960-61 (End of the 2nd Plan) 1492 8.88 848 5.05 12547 74.67 454 2.70 833 4.96 633 3.75 16804
5 1965-66(End of the 3rd Plan) 2355 7.73 1650 5.42 22996 74.19 1057 3.47 1892 6.21 905 2.97 33455
6 196859(End of the 3Annual Plans) 3184 7.69 2126 5.14 29931 72.31 1247 3.01 3465 8.37 1439 3.48 41392
7 1973-74(End of the 4th Plan) 4645 8.36 2388 5.38 37791 68.02 1531 2.76 6310 11.36 2292 4.13 55557
8 1978-79(End of the 5th Plan) 7576 9.02 4330 5.15 54440 64.81 2186 2.60 12028 14.32 3445 4.10 84005
9 1979-80(End of the 2 Annual Plans) 8402 9.85 4657 5.46 53236 62.35 2301 2.70 13452 15.76 3316 3.89 85334
10 1984-85 (End of the 6th Plan) 15506 12.45 6937 5.57 73520 59.02 2880 2.31 20961 16.83 4765 3.83 124569
11 1989-90 (End of the 7th Plan) 29577 15.16 9548 4.89 100373 51.45 4070 2.09 44056 22.58 7474 3.83 195098
12 1991-92(End of the 2 Annual Plans) 35854 15.51 12332 5.20 110844 47.94 4523 1.96 59557 25.33 9394 4.06 231201
13 1996-97(End at the 8th Plan) 55267 17.53 17519 5.56 139253 44.17 6594 2.09 84019 26.65 12642 4.01 315294
14 2001-02(End at the 9th Plan) 79694 21.27 24139 6.44 159937 42.57 8106 2.16 81673 21.80 21551 5.75 374670
15 2006-07(End of 10th Plan) 111002 21.12 40220 7.65 241216 45.89 10800 2.05 99023 18.84 23411 4.45 525672
16 2011-12 (End of 11th Plan) 171104 21.79 65381 8.33 352291 44.87 14206 1.81 140960 17.95 41252 5.25 785194
17 2012-13 (End of 1st year of 12th Plan)
183700 22.29 72794 8.83 369988.99 44.40 14103 1.71 147462 17.89 40256 4.88 824301
18 2013-14(End of the year of 12th Plan)
202297 22.95 77558 8.80 380605 43.17 15447 1.75 160331 18.19 45324 5.14 881562
19 2014-15(End of IIIrd Year of 12th Plan)
220894 23.53 82322 8.77 395221 42.10 16794 1.79 173200 18.45 93392 5.37 938823
(Source : Central Electricity Authority, 2015)
( 141 )
Exhibit No. 6.0
Effect Health impacts
Health costs (Crores of Rupees)
Total premature mortality
80,000 to 115,000
16,000-23,000
Child mortality (under 5)
10,000 2100
Respiratory symptoms 625 million 6200
Chronic bronchitis 170,000 900 Chest discomforts 8.4 million 170
Asthma attacks 20.9 million 2100
Emergency room visits
900,000 320
Restricted activity days
160 million 8000
The study revealed that in 2011-2012, emissions from
Indian coal plants resulted in 80,000 to 115,000 premature
deaths and more than 20 million asthma cases from
exposure to total PM10 pollution. The study quantified
additional health impacts such as hundreds of thousands
of heart attacks, emergency room visits, hospital
admissions, and lost workdays caused by coal-based
emissions. The study estimates the monetary cost
associated with these health impacts exceeds Rs.16,000 to
23,000 crores per year. (Debi Goenka & Sarath Guttikunda,
2013)
This burden is not distributed evenly across the population.
Geographically, the largest impact is felt over the states of
Delhi, Haryana, Maharashtra, Madhya Pradesh,
Chhattisgarh, the Indo- Gangetic plain, and most of central
India. Demographically, adverse impacts are especially
severe for the elderly, children, and those with respiratory
disease. In addition, the poor, minority groups, and people
who live in areas downwind of multiple power plants are
likely to be disproportionately exposed to the health risks
and costs of fine particle pollution.
It is estimated that solid waste created by a typical coal
plant includes more than 125,000 tons of ash and 193,000
tons of sludge from the smokestack scrubber each year
and approximately 70 to 180 billion gallons of water is
required for cooling process of the coal plant which
released back into the lake, river, or ocean causes “thermal
pollution” that can decrease fertility of aquatic animals. It
is also depicted that much of the heat produced from
burning coal is wasted. A typical coal power plant uses
only 33-35 percent of the coal’s heat to produce electricity.
The majority of the heat is released into the atmosphere or
absorbed by the cooling water. (source : http://
Sanket Vij, Narender Garg, H J Ghosh Roy
www.ucsusa .org/clean_energy/coalvswind/
c02d.html#.Vh33x-yqqko)
Figure 6: Percentage contribution of secondary
(sulfates and nitrates) aerosols to average PMio
concentrations by season (Dec-]an-Febfor winter; Mar-
Apr-May for spring; Jun-Jul-Aug for summer; and Sep-
Oct-Nov for fall) due to the emissionsfrom coal fired
thermalpower plants in India
Exhibit No. 7.0
Source : Debi Goenka & Sarath Guttikunda (2013)
India has the 5th largest electricity generation sector in the
world of which 66% comes from coal and the above
mentioned impacts are likely to increase significantly in
the future (http://cea.nic.in /reports/yearly /
energy_generation_11_12.pdf). However, looking at limit
of coal reservoirs, high cost of production, and most
importantly related environment issues the government
of India is emphasizing upon enhancing the capacity of
Nuclear Power Plants (NPP) generation in planned
manner to meet the electricity demand and also to take
care of environment because of related advantages of
nuclear energy over coal viz. Lower Greenhouse Gas
Emissions, Powerful and Efficient, Reliable, Cheap
Electricity, Low Fuel Cost, and Easy Transportation etc.
(Nuclear Power Corporation of India, 2015)
The first NPP i.e. Tarapur Atomic Power Station (TAPS)
was established on October 28th, 1969 at Maharashtra. At
present, 51 NPP (10 Units - Tarapur Atomic Power Station
(TAPS), Maharashtra; 21 Units - Rajasthan Atomic Power
( 142 )
Station (RAPS), Rajasthan; 3 Units - Madras Atomic Power
Station (MAPS), Tamilnadu; 10 Units - Kaiga Generating
Station (KGS), Karnataka; 1 Unit Kudankulam Atomic
Power Project, Tamilnadu; 3 Units Narora Atomic Power
Station (NAPS), Uttarpradesh; and 3 Units - Kakrapar
Atomic Power Station (KAPS), Gujarat) are operating in
six states of India. Further, 03 units i.e. Kudankulam
Atomic Power Project, Rajasthan Atomic Power Project
and Kakrapar Atomic Power Project are under stage of
review and will start operating in few month. The total
share of NPP in power generation is 5,780 MW (2.1%). The
first stage of commercially successful nuclear power
programme has indicated that country has command on
the technology through its own R&D base built since the
beginning of establishing Department of Atomic Energy.
The second stage (Fast Breeder Reactor) programme has
been completed. Given the scientific and technological
capability demonstrated so far, the technology required
for optimizing the second stage programme and launching
of the third stage programme has been initiated to assure
long term energy security at the desired capacity.
(Bhardwaj, 2013).
Further, the Quality Management System is implemented
in all phases and activities of NPPs covering Design,
Procurement, Manufacturing, Construction,
Commissioning, Operations and Decommissioning
adopting processes to meet the specified requirements for
quality, reliability and safety. To manage environmental
aspects associated with NPPs, Nuclear Power Corporation
of India (NPCIL) has formed Corporate Environmental
Policy (CEP) in line with National Environment Policy -
2006 of Government of India. Surprisingly, there are very
few studies which have explored and examined the major
issues concerning the impact of NPPs on environment and
community. More particularly, it is found that a little
research has been done publically to explore the impact of
NPPs on environment and community in India.
RESEARCH METHODOLOGY AND OBJECTIVES
The lack of studies conducted in India publicly on the
selected topic, empathized upon the need to make a fresh
attempt to explore and examine the impact of NPPs on
environment and community in India.
Objectives:
• To analyze the Nuclear Power Generation factors
influencing Environment in selected state of India.
• To analyze the Nuclear Power Generation factors
influencing Community Health in selected state of
India.
Hypotheses:
Based upon the review of literature, the present study has
included Radioactive Waste Management (Serviceability),
Nuclear Accident Protection (Attractiveness), Availability of
Quality Nuclear Fuel (Information), Legal Formalities
(Innovation) and Plant Design (Facilities/Accessibility) as core
factors of Environment. In order to test the validity of the
above, a pilot survey was conducted. The hypotheses are
as follows:
Ho: Radioactive Waste Management, Nuclear Accident
Protection, Availability of Quality Nuclear Fuel,
Legal Formalities and Plant Design do not have an
effect on Environment and Community Health.
H1: Radioactive Waste Management, Nuclear Accident
Protection, Availability of Quality Nuclear Fuel,
Legal Formalities and Plant Design have correlations
with Environment and Community Health.
The present research was a systematic attempt to reject Ho
and accept H1 at confidence level of 99%.
RESEARCH METHODOLOGY
The present study was exploratory in nature because only
few studies has been conducted on the selected area and
there is need to achieve new insights into it. The people
who live in the nearby areas of NPPs and staff members of
NPPs had been considered as sample units. All the 51
NPPs operating in six states of India has been included in
the study and sample units were selected using random
sampling approach. The primary data was obtained from
3500 respondents through appropriate questionnaires and
schedules during the period from February 2014 to
September 2015
Data Analysis Approach
In the present study, responses from participants were
coded and tabulated in SPSS 16.0. For analyzing the data,
both simple (average, percentage, weighted average and
mean score etc.) and advanced statistical tools (Standard
Deviation, Bi-variant Correlation, factor analysis,
reliability tests) were used. The test was conducted at 99
per cent confidence level (or 0.01% per cent level of
significance). Radioactive Waste Management, Nuclear
Accident Protection, Availability of Quality Nuclear Fuel, Legal
Nuclear Power Generation for Industrialization vis-a-vis Impact on Environment and Community : A Case Study of India
( 143 )
Formalities and Plant Design were considered as
independent factors and Community Health was
considered as dependent factor. Under five factors 25
statements were given to respondents to rate them. A five
point Likert scale (strongly disagree (1) to strongly agree
(5)) was used.
Gender
(Exhibit No. 8.1)
Frequency Percent
Male 1490 42.6 Female 2010 57.4
Total 3500 100.0
Age Group
(Exhibit No. 8.2)
Frequency Percent
<= 25 510 14.6
26-35 1000 28.6
36-45 1820 52.0 46-55 160 4.6
>=56 10 .3
Total 3500 100.0
Income Group
(Exhibit No. 8.3)
Frequency Percent
Below 18000 1350 38.6
18001-30000 580 16.6
30001- 42000 910 26.0 42001 -54000 310 8.9 54001-66,000 150 4.3
More than 66001 200 5.7
Total 3500 100.0
Education
(Exhibit No. 8.4)
Frequency Percent
Primary 10 .3
Secondary 620 17.7
Diploma 290 8.3 Degree 2220 63.4
P.G. 360 10.3
Total 3500 100.0
SAMPLE STATUS
Out of 3500 responses received, 1490 (42.6%) were males
and 2010 (57.4%) were females; 510 (14.6%) surveyed
respondents belong to below<25yrs, 1000 (28.6%) belong
to 26-35yrs, 1820 (52.0%) belong to 36-45yrs, 160 (4.6%)
belong to 46-55yrs, and 10 (0.3%) belong to >=56yrs age
group; 1350 (38.6%) surveyed respondents belong to 18000
household income, 580 (16.6%) belong to 18001-30000
household income, 910 (26.0%) belong to 30001-42000
household income, 310 (8.9%) belong to 42001-54000
household income, 150 (4.3%) belong to 54001-66000
household income, and 200 (5.7%) belong to more 66001
household income group; 10 (0.3%) surveyed respondents
were having Primary Education; 620 (17.7%) were having
Secondary Education, 290 (8.3%) were having Diploma
Education; 2220 (63.4%) were having Degree Education
and 360 (10.3%) were having post graduate education;
(Exhibit No. 8.0).
ANALYSIS AND INTERPRETATIONS
The frequency distribution (Exhibit No. 8.0) depicted that
the majority of the respondents (52%) belongs to 36 to
45years age group. It is noted that the number of female
respondents (57.4%) was higher than the number of male
respondents (42.6 %). The majority of the respondents
(38.6%) were in the income range of 18,000 and below. It is
also noted that the majority of the respondents were
educated up to degree level (63.4%).
The Kaiser-Meyer-Olkin test and Barlett’s test were carried
out to test the suitability of using factor analysis for the
five independent factors (Radioactive Waste Management,
Nuclear Accident
Protection, Availability of Quality Nuclear Fuel, Legal
Formalities and Plant Design) in the present research. With
Kaiser-Meyer-Olkin measure of 0.876 which is more than
the critical value of 0.5, and Barlett’s significance value of
0.000 which is less than the critical value of 0.05. The
Exhibit No. 9.0 clearly revealed that the factor analysis
will be useful on the five independent factors in the present
research.
Factor Analysis on Independent Factors:
KMO and Bartlett’s Test (Exhibit No. 9.0)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.876
Bartlett's Test of Sphericity Approx. Chi-Square
2707.510
df 300.000 Sig. .000
The Exhibit No. 10.0 empirically revealed that seven factors
have total initial Eigen values of more than 1. The seven
Nuclear Power Generation factors that influence
environment and community health were able to explain
the 59.65% of the total variation found in the present
research. However, close to 40% of the variation remains
unknown.
Sanket Vij, Narender Garg, H J Ghosh Roy
( 144 )
Total Variance Explained (Exhibit No. 10.0)
Component Initial Eigenvalues Extrac tion Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 6.875 27.498 27.498 6.875 27.498 27.498
2 1.918 7.671 35.169 1.918 7.671 35.169
3 1.571 6.285 41.454 1.571 6.285 41.454
4 1.261 5.045 46.499 1.261 5.045 46.499
5 1.125 4.502 51.001 1.125 4.502 51.001
6 1.092 4.369 55.370 1.092 4.369 55.370
7 1.070 4.280 59.650 1.070 4.280 59.650
8 .966 3.863 63.514
9 .907 3.626 67.140
10 .798 3.194 70.333
11 .747 2.988 73.321
12 .712 2.846 76.167
13 .666 2.665 78.833
14 .645 2.578 81.411
15 .551 2.204 83.615
16 .531 2.124 85.739
17 .476 1.906 87.644
18 .454 1.818 89.462
19 .447 1.788 91.250
20 .431 1.723 92.974
21 .413 1.653 94.627
22 .364 1.456 96.082
23 .351 1.402 97.485
24 .339 1.354 98.839
25 .290 1.161 100.000
Rotated Component Matrixa for independent factors (Exhibit No. 11.0) Component
1 2 3 4 5 6 7
Countries Cooperation .562
Population in the region .714
Sources of livelihood .710
Site Selection .741
Human activities .690 Branded .651
Human facilities .671
Use of land and water area .730
Upgradation .466 .542
Reliable .502
Availability of nuclear fuel and cooling water
.651
External threats .498
Environmental threats .499 -.477
Transport arrangements .733 Seismic area evaluation .644
Guidelines for problem solving -.644
Financing costs .629
Functions improvement .681
Construction time .654
Innovative peripheral products .725
Fuel Price .525
Policies .562
Efficiency .526
Legal Formalities .828
Monitoring .758
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 8 iterations.
Nuclear Power Generation for Industrialization vis-a-vis Impact on Environment and Community : A Case Study of India
( 145 )
Extraction Method: Principal Component Analysis.
Exhibit No. 11.0 showed rotated component matrix that
helped to identify the variables/components that
contribute to the Nuclear Power Generation factors that
influence environment and community health. There were
seven factors in total. However, only the factors that found
to relate directly back to the present research’s framework
were chosen to undergo further test. Therefore, the
following variables which were too weak or out of the
framework were eliminated from the further test: 1.
Countries Cooperation 2.Branded 3.Upgradation 4.Reliable
5.Guidelines for problem solving 6.Fuel Price 7.Policies
8.Efficiency.
Factor Analysis on Dependent Factor:
The results of the Exhibit No. 12.0 indicated that the factor
analysis can be used on the dependent factors because
Kaiser-Meyer-Olkin score was above 0.5 and the Barlett’s
significance value was lower than 0.05.
KMO and Bartlett’s Test (Exhibit No. 12.0)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.838
Bartlett's Test of Sphericity
Approx. Chi-Square
634.749
df 10.000
Sig. .000
The Exhibit No. 13.0 empirically revealed that the variables
in the dependent factor were able to explain 60.861% of
the total variance. However, close to 39% of the variation
remains unknown.
Component
Initial Eigenvalues Extrac tion Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance
Cumulative %
1 3.043 60.861 60.861 3.043 60.861 60.861 2 .651 13.012 73.872
3 .505 10.105 83.978 4 .420 8.402 92.380
5 .381 7.620 100.000
Extraction Method: Principal Component Analysis.
The Exhibit No. 14.0 clearly indicated that all the variables
in assessing environment and community health were
found to be useful in explaining impact of NPPs. Therefore,
no variable was eliminated.
Component Matrixa for Dependent Factor
(Exhibit No. 14.
Component
1 Mortality indicators .801
Morbidity indicators .791 Disability indicators .785
Nutritional indicators .770 Social and mental health indicators .753
Extraction Method: Principal Component Analysis
a. 1 components extracted
Reliability Test on Independent and Dependent Factors:
The Exhibit No. 15.0 & 16.0 shows the Cronbach’s alpha
for each variable. It is clearly reveled that all the variables
scored higher than 0.7 in Cronbach’s alpha. (Refer the last
column). Thus, all the variables were reliable in the present
research.
Reliability Statistics using Cronbach’s alpha
(Exhibit No. 16.0)
Cronbach's Alpha Cronbach's Alpha Based on
Standardized Items
N of Items
.880 .885 23
CONCLUSION
Energy is one of the most fundamental parts of our
universe. Energy has come to be known as a ‘strategic
commodity’ and any uncertainty about its supply can
threaten the functioning of the economy, particularly in
developing economies. Achieving energy security in this
strategic sense is of fundamental importance not only to
India’s economic growth but also for the human
development objectives that aim at alleviation of poverty,
unemployment, environmental issues, community health
and meeting the Millennium Development Goals (MDGs).
(ENERGY STATISTICS, 2015)
As the Nuclear Energy provider, the companies have to
understand environmental and community health issues
while generating the power for industries. Since it is well
known that community health results from pollution free
Sanket Vij, Narender Garg, H J Ghosh Roy
( 146 )
environment, it is important for Nuclear Energy providers
to identify the nuclear power generation factors that
influence environment and health. Being aware of these
factors and working on improving these factors will help
Nuclear Energy providers greatly in meeting Millennium
Development Goals through balanced approach. Although
some of the variables under the specific factor are deleted
for some tests, but Nuclear Energy providers should not
choose to neglect those deleted variables. Focusing on all
the possible variables is important because neglecting any
of them might lead to environment imbalance .
REFERENCE
Annual Report 2015, Ministry of Power, Government of
India accessed from powermin.nic.in/ accessed on
13/7/2015
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha if Item
Deleted
Population in the region 91.5829 71.625 .431 .353 .877
Sources of livelihood 91.6943 70.901 .518 .458 .874
Site Selection 91.7000 71.087 .479 .421 .875 Human activities 91.4886 71.087 .527 .405 .874
Human facilities 92.6800 72.081 .241 .170 .885
Use of land and water area 92.3371 72.465 .296 .205 .881
Upgradation 91.8571 70.065 .489 .346 .875 Availability of nuclear fuel and cooling water
91.6971 71.117 .502 .379 .875
External threats 91.9286 69.740 .574 .481 .873
Environmental threats 91.8829 69.588 .524 .448 .874
Transport arrangements 91.7657 70.604 .492 .379 .875 Seismic area evaluation 91.5629 71.376 .443 .336 .876
Financing costs 92.1029 71.336 .403 .289 .877
Functions improvement 91.9371 70.764 .487 .370 .875
Construction time 91.8457 70.618 .508 .424 .874
Innovative peripheral products
92.1029 69.863 .522 .427 .874
Legal Formalities 92.2086 71.673 .330 .353 .880
Monitoring 92.0514 70.439 .465 .402 .876
Mortality indicators 91.8000 69.805 .518 .488 .874 Morbidity indicators 91.7857 70.553 .491 .489 .875
Disability indicators 91.6200 70.798 .534 .470 .874 Nutritional indicators 91.7200 70.449 .542 .491 .874
Social and mental health indicators
91.8429 69.720 .483 .434 .875
Central Electricity Authority, Annual Report 2015, growth
of power in India from 1947 to 2015 accessed from
h t t p : / / w w w . n p t i . i n / D o w n l o a d / M i s c /
CEA%20Growth%20of%20Electricity.pdf accessed
on 10/09/2015
Debi Goenka & Sarath Guttikunda (2013), Coal Kills : An
Assessment of Death and Disease caused by India’s
Dirtiest Energy Source uses, Green peace Report, 2013
Energy statistics 2015, accessed from http://mospi.nic.in/
M o s p i _ N e w / u p l o a d /
Energy_stats_2015_26mar15.pdf accessed on 10/
07/2015
Environmental impacts of coal power: wastes generated,
accessed from http://www.ucsusa.org/
clean_energy/coalvswind/c02d.html#.Vh33x-
yqqko, accessed on 12/03/2015
Nuclear Power Generation for Industrialization vis-a-vis Impact on Environment and Community : A Case Study of India
( 147 )
International Energy Agency annual report 2015, accessed
from http://www.iea.org/ accessed on 03/7/2015
Nuclear Power Corporation of India, Annual Report 2015,
accessed from NPCI.GOV.In accessed on 21/07/
2015
S A Bhardwaj, 2013 Indian Nuclear Power Programme -
Past, Present And Future, Sadhana, Vol. 38, Part 5,
October 2013, Pp. 775-794.
Prof. (Dr.) Sanket Vij
Chairperson & Director Bhagat Phool Singh
Mahila Vishwavidyalaya, Khanpur Kalan,
Haryana (India)
Email: sanketvij @ gmail.com
Prof. (Dr.) Narender Garg
Dean & Head Department of Commerce Maharsahi
Dayanand University,
Rohtak
Email: nkgmdu@ gmail.com
Prof. H J Ghosh Roy
Senior Fellow - ICSSR Maharshi Dayanand University,
Rohtak
Email: drhjghoshroy@ gmail.com
Sanket Vij, Narender Garg, H J Ghosh Roy
( 148 )
Key words
Green Credit, EmissionLevel, Green Environment,Green World, Green Policy
Role of Green Credit and its Impact onIndustrialization – An Empirical Study withSpecial Reference to Select Industries in Bangalore
M Muniraju, Swaminath S and Ganesh S R
ABSTRACT
Economic development is necessary but insufficient for reducing poverty and improving overallliving conditions. Economic growth and industrialization are often associated with increasingconsumption of natural resources, impacting significantly on the environment and the climate.Global consumption of natural resources is already outstripping nature’s capacity to regenerate.The same applies to the impact of waste, pollutants and emissions on the environment andecosystems. The consumption and production patterns of industrialized countries, which arebeing emulated by countries around the globe, are jeopardizing the very foundations on whichlife depends and compromising society’s scope for action – both today and for generations tocome. Especially poorer parts of the population in developing countries face even greaterconstraints on their access to essential resources. It has become an immense challenge for theinternational community. The environment and climate-friendly development paths are thesurvival routes of the nation. Climate change is a major force driving current efforts to identifynew ecologically sustainable patterns for economic activities. If we are able keep the rise in globalaverage temperatures down to 2 degrees Celsius for the current century then industrializedcountries, emerging economies and developing countries alike will have to make a massiveeffort. Decoupling the economic growth from greenhouse gas emissions is an immense challengeto international cooperation. In this regards, efforts are made to carry out an empirical researchin select industries of Bangalore City to identify the Role of Green Credit and its Impact onIndustries. Samples of 456 companies were selected and responses are collected throughstructured questionnaire. The results show that the research paper is rehabilitating the industrieswith less emission and more of green in and around the city.
The Indian Journal of CommerceVol.68, No. 5, January-March, 2016
PREFACE
The realization of sustainable development has never been more necessary than todayfor humankind to continue to prosper and develop. It requires mankind to resolveglobal environmental problems, in particular global warming, and calls for a collectiveeffort on the part of human beings to gather their deepest wisdom. An extensivelydeveloped economy has featured a blind expansion of the “highly energy consumingand highly polluted” industries, with numerous construction projects and illegalenvironmental phenomenon by corporations and enterprises in many areas. It becomesobvious that the environment and resources have been seriously destructed. In fact, thesituation has an unfavorable impact on the social stability and sustainable economicdevelopment, and thus become the core issue of economic problems currently. The corecontent of “Green Finance” is the principle of “Green Credit”, which refers to a series ofadministrative means requiring those commercial banks and other financial institutionsas well as industries required to be carried out to save the earth and create a green in theworld to have a healthy society.
( 149 )
GREEN ECONOMY – GREEN GROWTH AS A NEWPARADIGM?Green Economy and Green Growth should not be seen as anew paradigm, but more as a new impetus to help usrealizethe vision of sustainable development and ensurea balance between its different dimensions. This isessential for the cooperation with developing countriesand emerging economies. Green economy / Green growthstrategies and offers of support should be flexible in designand tailored to the partner country’s specific context.Middle-income countries are seeking economicallyattractive ways of reducing greenhouse gas emissions. Atthe same time, they are anxious to retain their access tonatural resources, so as not to jeopardize existingdevelopment dynamics. For many lowincome countriesthe focus is on adapting to climate change and ensuringthe ecologically, economically and socially balanced useof their own natural resources.
MEANING OF GREEN CREDIT:
In many cultures, “Green” is an affirmation of life. Itindicates growth, fruitfulness and spiritual rejuvenation.Being Green …is growth. It is becoming more efficient inthe operation of your personal and business life by“eliminating wasteful spending based on habits that nolonger serve your purpose”. Being Green…is being fruitful.It is taking advantage of new technology, tools and trendsthat improve your personal and business life…at a fractionof the cost of traditional methods.
Green Credit means encouraging industries to makeEnvironment Friendly and Energy Saving, EmissionReduction arrangements according to Credit Policies.Green credit can be comprehended from three fields,namely environment friendly, energy saving projects andappropriate credit policy as well as punish those projectsor enterprises which halts the rules and regulations ofenvironmental protection and safety.
REVIEW OF LITERATURE:
Environmental and social risks alleged in green creditguidelines refers to the hazards and risks brought by theclients of banks or important related parties inconstruction, production and operating activities that mayharm the society and environmental seriously, includingenergy consumption, pollution, land, health, safety,resettlement, ecological protection, climate change andother related environmental and social issues.(CBRCGreen Credit Guidelines 2012).
M Muniraju, Swaminath S, Ganesh S R
Most of the researches on the Green Credit issues arevirtually based on qualitative analysis, limited to theintroductory and comparative studies on theimplementing status and policy regime of the Green Creditsystem across the nations over the world. The goalmouthof these researches are basically to strengthen andrecognize the purposes of Green Credit principles, that isto reduce the environmental financial risks, call on socialresponsibilities of the corporations, disclose theenvironmental information, and enhance the efficiency inimplementing the Green Credit rules (Zhu & Wang, 2009).Research literatures relating to the three stages of the GreenCredit implementation assessments can also be classifiedin the following three categories respectively: 1)Environmental risk management evaluations prior to theGreen Credit implementation; 2)Potential cost-benefitanalysis on the process of implementing the Green CreditPrinciples; and 3)Performance evaluations after theimplementation of Green Credit principles (Chen & Lu,2011; Dang,2009; Fei, 2008; Zhu &Yu, 2011; Zuo &Guo,2010)
Emission trading is considered to be an economicallysensitive method for reducing the concentrations ofgreenhouse gases, particularly carbon dioxide, in theatmosphere. Urban tree planting projects in specificlocations may be cost effective investments. In the paper ofMelissa R Mchale (2007) suggest that carbon assimilationrate, which is mainly a function of growing season length,has the largest influence on cost effectiveness, howeverresources managers can create more effective projects byreducing costs, planting large-stature trees, andmanipulating a host of other variables that affect energyusage.
There is a need to create awareness, implement and followgreen banking as much as possible in today’s businessworld of innovative technologies as to make ourenvironment friendly and enrich sustainability (HardeepSingh). The above research studies shows that, there areless number of studies was conducted on effect of GreenCredit implementation on Industrial sector. Therefore, thepurpose of this paper is to study and assess the role ofGreen Credit in India and effect of implementing the GreenCredit on Select Industries.
NEED FOR THE STUDY:
So far, most researches on the green credit issues are nearlybased on qualitative analysis, limited to the introductoryand comparative studies on the implementing status and
( 150 )
METHODOLOGY
The research work is descriptive in nature. The study isbased on both Primary data and Secondary Data. Theprimary data was collected through a StructuredQuestionnaire from Top level managers of well-establishedIndustries by conducting telephonic conversationsas wellas personal interviews. The study examines major aspectsconcerned with the Green Credit.
Research Limitations
There had been some problem in getting information fromrespondents as they had to be interviewed in a very shorttime and a few of them were quite busy to give properthought to the questions. The indifferent or unsupportiveattitude of some respondents while responding to thequestions also affected the final findings and observations.The research work is limited only to industries under RedCategory situated in Bangalore city, Karnataka.
SAMPLE SIZE AND TECHNIQUE USED FOR THESTUDY
The research work carried out by taking into considerationof total 3079 Red Category industries situated in BangaloreCity Regions(Ministry of environment and Forests,notification dated 20th December 1999). Namely South,North, East and West Regions. Out of a total 3079Industries only 1817 industries are active and thequestionnaire has been sent to 500 respondents but filled-in questionnaire received from 456 respondents only. TheCluster Sampling technique is used for the study and forthe analysis of Primary Data, Chi-square Test has beenused.
SOURCES OF DATA
Primary data have been collected from the Floor Manager/Manager/Head of Environment Departmentas arespondent from various industries located in BangaloreCity Region, Karnataka. Secondary data collected byreferring various reports of Pollution Control Board,Refereed Articles, Annual Reports of KSPCB, Books,Websites, etc.,
DATA ANALYSIS & INTERPRETATION:
AWARENESS OF GREEN CREDIT AMONGINDUSTRIES SITUATED AT BANGALORE.
The quality of green spaces helps to define the identity oftownsand cities, which can be enhance their attraction for
Role of Green Credit and its Impact on Industrialization – An Empirical Study with Special reference to Select Industries in Bangalore
policy regime of the “Green Credit” system across nationsover the world. The aim of these researches are basically tostrengthen and recognize the purposes of “Green Credit”principles, that is, to reduce environmental financial risks,call on social responsibilities for the corporations, disclosethe environmental information, and enhance theeffectiveness in implementing the “Green Credit” rules.Research results of this respect may include earlydefinitions and progressive researches of environmentalfinances. There is an urgent need in putting all the effortsto bring back the world with Green Credit Concept forhuman civilization survival as well as giving a goodgreenery structure to the generations to come in front of us.More researches has been conducted on Green Bankingand on other financial institutions. Therefore, there is aneed for the study to understand the impact of Green Crediton various Industries.
STATEMENT OF PROBLEM
The industrial sector is a driver of economic growth.Industries are vital in stimulating growth of the economyis closely interconnected with primary and tertiary sectorsthrough its forward and backward linkages. Even thoughwe are witnessing a tremendous growth in industries today,the transformations of land into special economic zonesfor industries areincreasing at a faster rate over a period oftime.It’s an alarming time, where the global temperature isreaching all time high and melting Icebergs. The effortsrequired to achieve low-carbon development must not onlyensure that the burden is spread fairly between poorerand richer countries. There must also be co-benefits in termsof social and economic improvements. While convincingexamples of win-to-win strategies of this sort already existat the micro level, including solutions to promote energyand resource efficiency, there is a noticeable lack of coherentmacro-economic strategies and appropriate policies forthe transition towards a green economy. Therefore, thereis a need to study the role of Green Credit and its impacton Industrialization.
OBJECTIVES
1. To check the awareness of Green Credit amongindustries situated at Bangalore.
2. To understand the impact of Green Credit onIndustries in Bangalore.
3. To offer suggestions to promote Green Credit amongindustries situated at Bangalore.
( 151 )
living, working, investment and tourism. Green Space inurban areas provides substantial environmental benefitsto the economy. There is a requirement ofcreatingawarenessin all the industries about Green Credit.Therefore, the study has been conducted to check theawareness level among the industries about Green Credit.To study the above objective, the researcher has usedprimary data with a well-structured questionnaire bytaking 456 respondents from Red Category Industries inBangalore city Region, Karnataka. Following are the majorRed Category Industries, where the structuredquestionnaire are distributed and responses collected fromrespected managers / respondents.
It is observed that, In case of Pulp and Paper Industriesout of 132 respondents, 57.6 % respondents are not clearwith Green Credit, In case of Pharmaceuticals out of 94respondents, 40.4 % of respondents are not at all aware ofGreen Credit, In case of Iron and Steel out of 138respondents, 56.5 % respondents are not clear with GreenCredit, In case of Cement Industries out of 32 respondents,43.8 % of respondents are aware as well as not at all awareof green credit. It’s a mixed opinion with regards to GreenCredit. In case of Pesticides industries, out of 42respondents, 81 % of respondents are having a littleknowledge towards Green Credit and finally otherindustries (12 in Red Category) are completely not at allaware of Green Credit.
Hence, there is a need for Government as well asEnvironment Pollution Board to pitch the requirement of
M Muniraju, Swaminath S, Ganesh S R
Green Credit Strongly Across all types of Industries andespecially with reference to Red Category Industries whichcreates maximum pollution in Bangalore City.
HYPOTHESIS
H0 There is no significant relationship between life ofexistence of the industry and its concern towardsadoption of green credit.
H1 There is a significant relationship between life ofexistence of the industry and its concern towardsadoption of green credit.
The table value of ÷2 for6 degrees of freedom at 5 per centlevel of significance is12.592. The calculated value of ÷2 is28.895 i.e., the calculated value of ÷2 is higher than thistable value. Hence, the null hypothesis is rejected. Thisleads to the conclusion that there is significant relationshipbetween life of existence of the industry and its concerntowards adoption of green credit.
IMPACT OF GREEN CREDIT ON INDUSTRIES INBANGALORE
Green Credit will influence the Indian economy and theway of life in India to a greatest extent. The Green Creditcontrols the air Pollution naturally and also it avoidsvarious Health Hazardous Diseases to the society. Thepollution from Different industries like Iron and Steel,
Table 1: The Respondents from red category industries has been classified as follows:SI. No. Red Category Industries No. of Industries in Bangalore / Respondents
1 Pulp and Paper industries 132 2 Pharmaceutical Industries 94 3 Iron and Steel industries 138 4 Cement Industries 32 5 Pesticides Industries 42 6 Other industries (12) 18
Total Sample Size 456
Source:Annual Report of Karnataka State Pollution Control Board
Table 2: The Responses Collected from Respondents regarding the awareness of Green Creditin Bangalore City, Karnataka:
Frequency Strongly Aware Aware Neutral Little Not at all Aware Total Industry Res % Res. % Res. % Res. % Res. % Res. % Pulp & Paper - - 56 42.4 76 57.6 - - - - 132 100 Pharmaceuticals 4 4.3 16 17 2 2.1 34 36.2 38 40.4 94 100 Iron & Steel - - 58 42.1 78 56.5 - - 2 1.4 138 100 Cement 4 12.4 14 43.8 - - - - 14 43.8 32 100 Pesticides - - - - - - 34 81 8 19 42 100 Others - - - - - - - - 18 100 18 100
( 152 )
Textiles and Leather, Pulp and Paper, Chemicals, Cement,Petrochemicals and refineries cause various types ofhealth issues to the society by emitting poisonous gassessuch as SO2 (Sulfur Dioxide), NO2 (Nitrogen dioxide),Toxic Chemicals, CO (Carbon Dioxide) and other organicchemicals. The following table represents the detailsregarding the status of Air pollution Control Systemadopted by various industries in different categories offour clusters of Bangalore City, Karnataka.
The above result shows almost all the industries adoptedAir Pollution Control Systems in all the regions. Still thereis a need to study how effectively operating industries cancontrol the pollution. To understand the effectiveness ofAir Controlling methods,following formula will be usedto find out the intensity of air pollution in different clusters
of Bangalore City, Karnataka.
Exceedence Factor= Observed Annual Mean Concentrationof Criteria Pollutant / Annual Standard for the RespectivePollutant and Area Class
The result will be from Four Air Quality Categories like:1. Critical Pollution (C)= When EF is More Than 1.52. High Pollution (H) = When EF is between 1.0 to 1.53. Moderate Pollution (M) = When EF is between 0.5 to 1.04. Low Pollution (L) = When EF is Less Than 0.5
The secondary data collected and analyzedby pointingfour extreme variables such as Sulfur dioxide (SO2),Nitrogen dioxide (NO2), Suspended Particulate Matter(SPM) and Respirable Suspended Particulates (RSPM)have been taken for study.
Industry Existence
INDUSTRY Strongly Aware Aware Neutral Little Not at all
Aware Total
Below 10 years 36 4 14 1 1 56 10 to 20 years 46 10 26 0 0 82 20 to 30 years 85 16 20 0 0 121 30 years & Above 125 33 39 0 0 197
Total 292 63 99 1 1 456
÷2 24.9354, df 6, p 0.0015132
Table 3 : Air Pollution Control Status of Industries Situated across Bangalore City in Four different Clusters /Regions namely Bangalore North, South, East and West:
1. Air Pollution Control Status of Industries - Bangalore City
Large Medium Small Red Orange Green Red Orange Green Red Orange Green
No.of Industries 52 52 220 32 33 142 462 240 2053 Operating 52 51* 215* 32 33 138* 425* 230* 1587*
2. Air Pollution Control Status of Industries - Bangalore South
Large Medium Small Red Orange Green Red Orange Green Red Orange Green
No.of Industries 136 101 214 43 50 177 402 234 1152 Operating 135* 100* 209* 43 49* 169* 374* 175* 826*
3. Air Pollution Control Status of Industries- Bangalore North
Large Medium Small Red Orange Green Red Orange Green Red Orange Green
No.of Industries 71 29 91 27 28 49 262 156 191 Operating 71 29 91 27 28 49 262 156 191
4. Air Pollution Control Status of Industries- Bangalore East
Large Medium Small Red Orange Green Red Orange Green Red Orange Green
No.of Industries 83 40 75 24 33 53 152 137 585 Operating 83 39* 75 24 33 53 151* 136* 584*
Source:Karnataka State Pollution Control Board, 2013-14 Publications
Note:* Indicates those industries where the Air Pollution Control Status is not upto date or still moving towardscontrolling Air Pollution in Bangalore City by adopting Air Pollution Controllers.
Role of Green Credit and its Impact on Industrialization – An Empirical Study with Special reference to Select Industries in Bangalore
( 153 )
Table 4: Air Pollution Level across Bangalore City in Four different Clusters / Regions namely Bangalore North,South, East and West:
Industrial Areas
Regions / Clusters So2 No2 SPM RSPM Air Quality Air Quality Air Quality Air Quality
Bangalore East L L H H Bangalore South L L M M Bangalore North L L L L Bangalore West L L M M
Source:https://data.gov.in/catalog/city-and-location-wise-ambient-air-quality
The variables such as SO2 and NO2 are Low in all theRegions which is very good phenomenon compare to otherpolluted cities in India. But the variables such as SPM andRSPM are moving towards alarming situations. Both SPMand RSPM are showing High Pollution in Bangalore EastRegion, Moderate in Bangalore South and West Region aswell as Low in Bangalore North Region. It is also observedthat, none of the regions are at critical level of pollution.There is a High pollution in Bangalore East and ModeratePollution in Bangalore South Region which requires to becontrolled as early as possible.
FINDINGS1. From the above analysis, it is observed that most of
the industries have implemented strategies to reduceair pollution by using various Air pollution controldevices such as Scrubbers, Air ventilation, Cyclonesand Multi-Cyclones, Bag filters as an air pollutioncontrol tool. Majority of the industries are awareEnvironmental issues and Green Credit policy andthey are trying to implement in their organizations.
2. In case of Pulp and Paper Industries out of 132respondents, 57.6 % respondents are not clear withGreen Credit, In case of Pharmaceuticals out of 94respondents, 40.4 % of respondents are not at allaware of Green Credit, In case of Iron and Steel outof 138 respondents, 56.5 % respondents are not clearwith Green Credit, In case of Cement Industries outof 32 respondents, 43.8 % of respondents are awareas well as not at all aware of green credit. It’s a mixedopinion with regards to Green Credit. In case ofPesticides industries, out of 42 respondents, 81 % ofrespondents are having a little knowledge towardsGreen Credit and finally other industries (12 in RedCategory) are completely not at all aware of GreenCredit.
3. Through Hypothesis testing it is also proved thatthere is significant relationship between number ofyears of existence of the industry and its concerntowards adoption of green credit.
4. It is also found that the variables such as SO2 andNO2 are Low in all the Regions which is very goodphenomenon compare to other polluted cities inIndia. But the variables such as SPM and RSPM aremoving towards alarming situations. Both SPM andRSPM are showing High Pollution in Bangalore EastRegion, Moderate in Bangalore South and WestRegion as well as Low in Bangalore North Region.
5. Finally, we still have many more industries whodon’t adopt themselves to the standard Air PollutionControl System to save the environment in BangaloreCity, Karnataka.
Hence, there is a need for Government as well asEnvironment Pollution Board to pitch the requirement ofGreen Credit Strongly Across all types of Industries andespecially with reference to Red Category Industries whichcreates maximum pollution in Bangalore City.
CONCLUSIONGreen Credit demonstrates how the Government andRegulator of EnvironmentDepartment can work togetherto create a social change by bringing Green Credit Policyas a mandatory requirement for industries in India. A studyby the Karnataka State Pollution Control Board (KSPCB)and the Indian Institute of Science (IISc) has found thatvegetation in Bangalore has decreased by 66 per cent andwater bodies by 74 per cent in the last 40 years. There is atmostneed to create awareness, implement and followGreen Credit in Industries as much as possible in today’sbusiness world of innovative technologies so as to makeour environment human friendly and enrich the economicproductivity. The survival of industries is inverselyproportional to the level of global warming. Therefore, forsustainable of industries, Indian Industries should adoptGreen Credit as a Business Model in an appropriateManner.
RECOMMENDATIONS
The United States practices reforestation, its forests haveactually grown in size over the past century. About one-
M Muniraju, Swaminath S, Ganesh S R
( 154 )
third of the United States — 747 million acres — is coveredwith trees. In fact, we have more trees today than we had70 years ago. And some 4 million more are planted eachday. On the nation’s commercial forests, net annual growthexceeds harvests and losses to insects and disease by animpressive 47 percent each year. (Times of India Report2014). The following recommendations will be helpful forthe sustainable development of the Green Economy.1. Recommendations to plant more number of trees in
Highly Polluted Areas of the City.2. The allotment of 1% of money towards
establishment of Green Corridor on NationalHighways must be effectively implemented and ifpossible, a “GREEN CREDIT COMMTTEE” shouldbe established to monitor the improvements.
3. Government can also consider Green Credit Policyas an initiative under Corporate SocialResponsibility (CSR) to have PPP (Public PrivatePartnership) to build a Green Economy.
4. Establishing Green Credit Standards in convergencewith International Standards.
5. A proper legal system implementing Green CreditPolicy for the entire industrial sector.
6. Granting appropriate Incentive Plans to promoteGreen Energy, Green products, Green Environmentand Green World.
7. Encouraging the Public Engagement as well asimproving the Media Communication to supportGreen Credit Policy across the Country.
SCOPE FOR FURTHER RESEARCH
The above research is focused only on the Red CategoryIndustries situated at Bangalore. Furthermore a researchwork can be focused by taking all categories of Industriesnamely Orange and Green.However, the study can also befocused on Impact of Green Credit on Medium and SmallScale Industries in India, Framework of Green CreditPolicies and its impact on Financial Institutions inIndia,Effect of Green Credit for Sustainability and GreenCredit policy.
REFERENCES
China Banking regulatory Commission, green creditguidelines, 2012.
Chen, W G & Lu L G (2011). External obstacles of greencredit of China Commercial Bank and constructingthe framework of environmental risk management.Guandong Academy Journal of Finance, 26, 66-76
Dang, C F (2009).Thinking about our national commercialbank to promote green credit. Economics and Finance,2, 51-53.
Emma Dirmont, Junee Cilliers, (2007) Green Credit Tool.University of Applied Sceinces Van Hall Larentien.
Fei, Y (2008). On the green credit and environmental riskmanagement. Operational managers, 9, 459-474.
“GIZ Exchange Platform on Green Economy and GreenGrowth” - Deutsche Gesellschaft für InternationaleZusammenarbeit (GIZ), 2nd edition, Aug 2012.
Hardeep Sing & Bikram Pal Singh. An effective &resourceful Contribution of green banking towardssustainability. International journal of advances inengineering science and technology, 41-45.
Melissa R McHale, E.Gregory McPherson & Ingrid C Burke(2007). The potential of urban tree planting to becost effective in carbon credit markets, ELSEVIER, 49-60.
Susan Rutherford (2006).the green buildings guide – toolsfor Local Governments to promote site sustainability.
Zhu, L., & Yu, W Y (2011) interest analysis of participatingthe Green Credit from the perspective based on thegame Theory. Journal of southern agriculture, 42, 1025-1025.
Zhu X G & Wang X J (2009). Deeping the green financialpolicy. World environment, 4. 88-91.
Zuo, R. J & Guo, K J (2010). SWOT analysis on developingGreen Credit in our country’s commercial bank.Finance development Research, 7, 69-72.
Role of Green Credit and its Impact on Industrialization – An Empirical Study with Special reference to Select Industries in Bangalore
Dr. M. MunirajuChairman and Professor, Dept. of Commerce,Bangalore University, Bangalore – 560001,Email : [email protected]
Mr. Swaminath SResearch ScholarDept. of Commerce, Bangalore University,Bangalore – 560001Email : [email protected]
Mr. Ganesh S RResearch ScholarDept. of Commerce, Bangalore UniversityBangalore – 560001Email : [email protected]
Mr President, Past Presidents, Office Bearers, Members of
the Executive Committee and the Life Members of the
Indian Commerce Association, I extend a very warm and
hearty welcome to all of you at this General Body Meeting
of the Indian Commerce Association. I have the pleasure
to report as under:
The 67th All India Commerce Conference was organized
on 27 th-29 th December, 2014 by KIIT University,
Bhubaneswar in collaboration with PG Department of
Commerce, Utkal University, Bhubaneswar.Prof. Jayant
K. Parida, from PG Department of Commerce, Utkal
University, Bhubaneswar was the Conference Secretary.
More than 2000 delegates representing all the States of the
country attended the conference. The three day mega event
was inaugurated by His Excellency MrUbaldo Garcia
Ruiz, Ambassador of the Republic of Costa Rica to India
in the presence of Mr Asif Iqbal, Honorary Counsellor,
Suriname Embassy, Bangalore; Dr PK Patasani, Hon’ble
MP, Bhubaneswar; Prof. P PMathur, VC, KIIT University;
Prof Ramachandra Gowda, President, ICA and Other
Office Bearers and Past Presidents. Speaking at the
inaugural session, Mr. Ubaldo Ruiz said, commerce
education plays a vital role in the development of a country.
Costa Rica has enormous opportunities to do commerce
and business, he said, while calling upon the business
community and industrialist of Odisha to do business and
establish industries in his country. Noting that ethical
values are being compromised in commerce, Mr. Iqbal
suggested, commerce education should be based on value
and ethics combined with knowledge. Prof. Mathur
stressed on technology oriented commerce education,
while Prof. Gowda, in his presidential address, expressed
concern over various financial scams in recent years. Today
commerce has lost human values and ethics, he stated. He
stressed on market and industry oriented commerce
education and skill development
In the afternoon of the first day of the Conference, Seminar
Session was organized on the theme of ‘Corporate Social
Responsibility & Sustainability’ which was chaired by
Dr. PradyotKeshari Pradhan of Utkal University,
Bhubaneshwar. After such a hectic day of serious academic
exercise, the delegates enjoyed relaxing moments in a
beautiful cultural program organized by the Hosts.
On the second day of the Conference, i.e. on December 28,
2014 besides MM Shah Research Gold Medals session,
four other technical sessions were concurrently organized.
SECRETARY’S REPORT, 2015Secretary’s Report presented at the 68thAnnual General Body Meeting of the Indian Commerce Association held
on November 7, 2015 at VinobaBhave University, Hazaribagh
The theme of Manubahi Shah Research Gold Medals
session for this year was ‘Empirical Research in the Area
of International Business’. Dr. Manjit Singh of Punjabi
University, Patiala was the chairperson of the session
which was co-chaired by Prof. SanketVij of B. P. S.
MahilaVishwavidyalaya, Khanpur Kalan, Sonipat. In the
first half of this session ten best papers were presented
before an eminent jury out of which two papers would
receive Gold Medal in valedictory session. Dr K Nirmala
from Bangalore University and Aasif Shah,
DrMalabikaDeo Wayne King from Pondicherry University
won the Gold Medals in this session. The remaining papers
were presented in the second half of the session.
Technical Session-I was on the theme of ‘Services
Marketing : Challenges Ahead’ which was chaired by Dr.
W K Sarwade, Faculty of Management Science, Dr.
BabasahebAmbedkarMarathwada University,
Aurangabad and co-chaired by Dr.Chandrashekhar
Sheelvanth, Dr. Ambedkar College of Arts and Commerce,
Gulbarga.Technical Session-II was on the theme of
‘Developments in Capital market: Market Efficiencies
Revisisted’. Dr. Kshama Agarwal of University of
Rajasthan, Jaipur was the Chairperson and Dr. Elangbam
Nixon Singh from Mizoram University, Aizawl was the
Co-Chairperson.
Technical Session-III was on the theme of ‘Changing
Dimensions of Human Resource Management in
Globalized Era’ which was chaired by Dr. Sanjay Baijal of
Gorakhpur University, Gorakhpur and co-chaired by Dr
Sanjay Ramdas Mali, Principal, Lonavla Education Trust
Dr. B. N. Purandare Arts & Smt. ShantideviGopichandaji
Gupta Commerce, Science College, Lonavla. Technical
Session-IV was on the theme of ‘Insurance Business: Issues
and Perspective’ which was chaired by Dr. D. Chennappa,
Osmania University, Hyderabad and co-chaired by Dr. R.
Ramachandran, Annamalai University, Annamalai
Nagar.
In the evening of the second day the Indian Commerce
Association organized its 67th Annual General Body
Meeting followed by the elections to various posts of the
ICA. The hosts organized a beautiful cultural evening for
the delegates on the night of the second day of the
conference which was not only enjoyed by one and all but
also worked as a big relaxer for the delegates.
( 155 )
The third day of the conference started with presentation
before the jury comprising of five eminent persons of Best
Business Academic of the Year (BBAY) Award in which
two best papers of four technical sessions and of the
seminar session were presented before the Jury. The Jury
selected one best paper from each of the five sessions out
of which the best paper got gold medal and remaining
four papers were awarded silver medals. Dr R K Giridhari
Singh from Mizoram University won the Gold Medal and
DrPrashantaAthma and MrNarendarYarragorla from
Osmania University, MsMallika S. Shetty and Prof S V
Satyanarayan from Osmania University, DrAvinash D
Pathardikar and DrSangetaSahu from VBS Purvanchal
University, and MrBidyutBikashBaishya, Dipanjan
Chakraborty from Assam University won the Silver Medals.
It gives me great pleasure to inform the honorable members
of Indian Commerce Association that the ICA has
instituted Prof. Manubhai M Shah Memorial Award for
Excellence in Commerce and Management with effect from
the year 2012 wherein a cash award of Rs.2 lac and a Gold
Medal is awarded every year to a researcher considering
his/her research contributions in the field of Commerce
Education during the last 10 years. Mr. Anil Shah has
announced onetime endowment of Rs.25 lac for this award
which may increase to Rs.1 crore over the next five years.
In its fourth year, the winner of the award who was
honored in the inaugural session of 67th AICC was Dr.
Banikanta Mishra, Professor of Finance, Xavier Institute
of Management (Xavier University), Bhubaneswar.
Dear friends, the family of ICA is expanding as its
membership base is continuously increasing. We have
more than 6000 individual members and this is showing
an enthusiastic uptrend. As a healthy development, the
new members applying for membership are the young
army of research fellows who are the face of growing and
emerging India. Networking and connectivity
opportunities offered through this platform can help give
the needed facelift to our research landscape through
meaningful contributions of this talented young force in
the wake of competitive challenges. The ease of application
and payment of membership fee offered through
technology based new methods of direct payment using
RTGS and others have been a facilitator. New applicants
have largely availed these modes and have been able to
save the time and effort that goes into the hassles of drafts
and cheques. Other innovative options for payment
available are being detailed out for implementation in days
to come. We have also started issuing membership
certificates to the new members. For the existing members
the non-availability of complete postal addresses is a
challenge which is being met through personally
contacting the members at various podiums. With the
cooperation of our members, wewill soon be able to
complete the address profile and issue certificates to all
members to formally recognize their affiliation to ICA.
The members of ICA have exhibited undiluted
commitment and dedication for the cause of academics,
research and teaching which has resulted in tall
achievements of the members. The members have scaled
great heights which are truly inspirational for other
members and a matter of pride for the ICA family. The
members have assumed offices of administrative
significance, research awards from reputed associations,
research projects from national and international
sponsoring bodies, research and academic publications
in journals and books of highest repute, foreign
collaborations and visits, research consultancy and
liaisons, elevations to chairs of professors and Vice
Chancellors. The very recent being Prof. R. D. Sharma who
has assumed the office of Vice Chancellor of Jammu
University and Prof. Ashok Aimawho has assumed the
prestigious position of Vice Chancellor of Central
University, Jammu. ICA takes pride in the achievements of
its valuable members and wishes them luck for the new
journey and fresh accomplishments.
ICA has been constantly working for the betterment of
profession and stakeholders. One of the landmark
achievements this year has been the purchase of land by
ICA for its head office at Greater Noida. This has been a
cherished and shared dream of all members and has come
to reality this year. This would help build a formal seat of
decision making which lies at the heart of the country in
proximity to important regulatory bodies, ministries and
policy making institutes. This office is expected to provide
all facilities to its members and work as a strategy making
and implementing place and is of absolute necessity in
today’s competitive times. A central secretariat for a
dynamic professional body like ICA has been long felt
need which seems to be on its journey to fulfillment but
will not be possible without strong support. I on behalf of
ICA seek the support of all- members, corporates, institutes,
philanthropists and everybody in terms of finances to help
ICA have its ApnaGhar and cement its place in the fleeting
sands of competition.
The Editorial Board of the Indian Journal of Commerce
deserves congratulations for changing the face of the
journal and unflinching commitment towards enhancing
( 156 )
its quality and wider coverage. The Editorial team has
been able to make the copy of every issue of the journal in
soft copy and seeking consent of the members as to doing
away with the hard copy contributing to the green
initiatives and cutting down the avoidable expenses.
Efforts are constantly being made to lift the content and
quality of the journal and later apply for the impact factor
of this journal which has a long history to its credit. We
wish the journal, its team and the readers best of luck in
building the brand and recognition of the journal amidst
its global audience.
ICA and the IT team has been working since a long time to
refurbish the website and transform it to a dynamic,
informative and interactive platform for sharing, posting
and updating all information. The website now provides
all important information and links which can help our
members and save their valuable time- be it membership,
be it conferences and seminars, or proforma for Chair/Co-
chair for the technical sessions at the ICA conferences.
Many more new age initiatives are being finalized which
will be made available to members.
The ICA initiatives for identifying, promoting and
rewarding research and academic contributions in the
name of the newly instituted MMSMA has been well
received by the members and faculty from premier
institutes of IITs and IIMs and people of the stature of VCs
and directors participating enthusiastically. MMSMA is
gaining good ground and is showing signs of growing to
be accepted and revered like its long established parallels
in sciences (e.g Bhatnagar Award).The ICA acknowledges
and believes in the youth power of India and has
endeavored to identify this potential in the field of research.
From this year, with the initiative, support and sponsorship
of Prof. T. Shiware, Director, Hinduja Group of Colleges,
Saurabh Shiware Young Researcher Award has been
instituted and awarded. The award is in the loving memory
of Mr. Saurabh Shiware who was a young dynamic
academician, researcher and enthusiast of business world
whose lofty dreams remained unfulfilled due to his
untimely death. The award carries a cash prize of Rs.
25000/- and rewards a budding researcher motivating
him/her for achieving greater heights in the research
career. In its maiden year, the award received 12 applicants
from the budding researchers who as per the eligibility
norms were below 35 years of age. These awards are
assessed through detailed and comprehensive analysis
and deliberations by high powered accomplished jury in
an intensive unbiased exercise.
It gives me great pleasure to place on record my deep sense
of gratitude to the President of the ICA Dr. Jayanta K Parida
for his able guidance in the smooth conduct of the activities
of the Association. I would also like to profusely thank
Prof. B P Singh, Prof M B Shukla, Prof P Prurushotham
Rao, Dr. B. B. Taywade, Dr T Shiware, Dr (Ms.)
MalabikaDeo, Dr B Ramesh and all other Past Presidents
of the ICA for their positive contribution in giving
meaningful direction to the activities of the ICA. My thanks
are also due to all office bearers and the members of the
Executive Committee of the ICA for their active cooperation
and support.
Ladies and gentlemen, the onerous responsibilities of the
Secretary of ICA can never be discharged single handedly.
I have been able to do what I could only with the motivation
and support of the honorable members of the ICA for which
I shall always remain indebted. My thanks are also due to
all of the delegates who have come to Hazaribagh in large
numbers inspite of the challenges of the place to make the
68th All India Commerce Conference of the Indian
Commerce Association a memorable event. Before
concluding my report, I would like to thank the
Chairpersons and Co-chairpersons of the Seminar Session
and all the Technical Sessions of the 68th All India
Commerce Conference who have taken lots of pain in
reviewing and selecting papers for presentation in the
different sessions of the Conference. I am also thankful to
the Jury Members of the Best Business Academic of the
Year Award, Prof Manubhai M Shah Memorial Research
Gold Medals Award and of MMSM and SSMYR Award
for the valuable services rendered by them. I am also
thankful to the Key Note Speakers and the Rapporteurs of
the various Sessions for their valuable contribution.
Last but not the least our thanks are also due to Prof.
M.K.Singh, the Conference Secretary and his dedicated
team of colleagues and student volunteers for taking so
much pain in the successful organization of the 68th All
India Commerce Conference of the Indian Commerce
Association. I am sure each one of us will be carrying away
with us memorable experiences and sweet memories to
cherish all through.
Wishing you all happy times ahead.
Hazaribagh BALWINDER SINGH
November 7, 2015 SECRETARY, ICA
( 157 )
A meeting of the Executive Committee of Indian Commerce
Association was held on November 5, 2015 at 5.00 p.m. at
Vinoba Bhave University, Hazaribag, Jharkhand, under
the Chairmanship of Professor Jayant K. Parida, President,
ICA. Following members were present:
1. Prof. Jayant Kumar Parida - (in-the-Chair)
2. Prof. M. Ramchandra Gowda
3. Dr. Anant M. Deshmukh
4. Prof. M. Muniraju
5. Prof. H. K. Singh
6. Prof. M. K. Singh
7. Prof. Debabrata Mitra
8. Dr. Ran Singh Dhaliwal
9. Dr. Shashank Bhushan Lal
10. Prof. M. Jayappa
11. Dr. Ramesh Agadi
12. Dr. Gurcharan Singh
13. Prof. G. P. Prasain
14. Dr. Laxman Kisan Karangale
15. Dr. M. Shivalinge Gowda
16. Dr. Pushkar Nath
17. Dr. Dharmendra K. Tiwari
18. Prof. H. Venkateshwarlu
19. Dr. S. G. Hundekar
20. Dr. T. P. Mahhu Nair
21. Prof. Sasmita Samanta
22. Dr. Ajay Kr. Singh
23. Prof. B. P. Singh
24. Dr. T. A. Shiware
25. Prof. (Ms.) Malabika Deo
26. Dr. B. B. Taywade
27. Prof. P. Purushotam Rao
28. Prof. M. B. Shukla
29. Dr. Balwinder Singh (Secretary)
The President of ICA and Conference Secretary of 68th
AICC-2015,Prof.M.K.Singh welcomed all the EC members
before commencement of meeting thereafter President of
ICA asked the secretary to proceed with the agenda of the
meeting.
The following decisions were taken in the meeting of
Executive Committee of ICA unanimously:
Item 1. Confirmed the minutes of the Executive Committee
meeting of the ICA held on July 12, 2015 at 10.30 a.m. at
Dhanwate National College, Nagpur, Maharashtra, India.
The action taken report (ATR) was presented by the
Secretary. Under matters arising out of minutes Dr. Ajay
Kr. Singh reported that by Nov. 6, 2015, ICA is likely to get
the lease plan which is a prerequisite for possession of
1000 sq. mt. of land at 33 B, Knowledge Park I, near Pari
Chowk, Greater NOIDA, U. P. It was further resolved to
get the possession of land and construct the boundary
wall. After the possession of land, foundation stone laying
ceremony will be organized by ICA and all EC members
will be part of the organizing team of the event.
Item 2: RESOLVED to approve the report of the Secretary
which will be presented by him in the GBM.
Item 3: RESOLVED to approve the final accounts duly
audited for the financial year April 1, 2014 to March 31,
2015 and report of the Managing Editor presented by Prof.
H. K.Singh with certain suggestions which if required may
be incorporated by him and Managing Trustee. Dr. Ajay
Kr. Singh was authorized to file revised Income Tax Return
if it is required after examining the suggestions made by
the EC. Prof. H. K. Singh also informed that The Indian
Journal of Commerce is now available at www.ijoc.in and
the members can browse various issues of the Journal. In
the light of the above it was resolved to recommend to the
GBM to consider print copies of the IJC for selected section
of life members like Institutional Life Members and
Contributors of articles but not to all the life members and
annual members of ICA.
Item 4: RESOLVED to approve the report presented for
holding the All India Commerce and Management Talent
Search Examination (AICMTSE). It was resolved to
organize the next test in September 2016 on any Sunday
and only those students would be eligible to appear for
the test who are Student Members of ICA. It was resolved
to charge Rs.300/- as Student Membership Fee. The
following committee was constituted to work out holding
of off line or on line conduct of test and its cost dimension:
1. National Coordinator
2. President of ICA
Minutes of the Executive Committee Meeting of the IndianCommerce Association (ICA) held on November 5, 2015 at 5.00 p.m.
at Vinoba Bhave University, Hazaribag, Jharkhand, India
( 158 )
3. Secretary of ICA
4. Prof. Sasmita Samanta, Registrar, KIIT
It was suggested to work out tie ups with Industry and
Business for considering this test for recruitment purposes
and Universities in India and abroad for admission
purposes.
Item 5: RESOLVED to recommend to the Annual General
Body (AGM) of the ICA that M/s Alok Sharma & Company,
Chartered Accountants, BJ-57, Shalimar Bagh, Delhi –
110088, be authorized to Audit the accounts as Auditor
for the year 2015-16 and also for submitting the revised
return to Income Tax Office if required again.
Item 6: RESOLVED to appoint Professor P. Purushottam
Rao as the Returing Officer for holding elections during
69th All India Commerce Conference.
Item 7: RESOLVED to approve the List of proposed new
Life Members of ICA those who have paid the requisite
fees to ICA from July 13, 2015 till Nov. 5, 2015 as reported
by the Secretary Dr. Balwinder Singh.
Item 8: RESOLVED to invite the names in the prescribed
format from the General Body of the ICA regarding the
topics for the Seminar session, four Technical Sessions,
and M. M. Shah Research Gold Medal Session to the held
at the time of the 69th annual Conference of the ICA.
Item 9: RESOLVED to invite from the General Body of the
ICA in the prescribed format the names of the Chairpersons
and Co-chairpersons for the Seminar Session, four
Technical Sessions, and M. M. Shah Research Gold Medal
Session to be held at the time of the 69th Annual Conference
of the ICA.
Item 10: RESOLVED to authorize President of ICA to
nominate two members on BBAY Award Jury.
Item 11: RESOLVED to authorize President of ICA to
nominate two members on M. M. Shah Research Gold
Medal Award Jury.
Item 12: The following proposals for holding the 69th
Annual Conference of ICA was placed before the EC:
(a) Professor R. L. Godara, Vice Chancellor,
Hemchandracharya North Gujarat University,
Patan, Gujarat
(b) Professor Arvind Kumar, Lucknow University,
Lucknow, U. P.
Item 13: RESOLVED to recommend to the General Body of
the ICA the name of Professor M. K. Singh for the Post of
the president of the ICA for the next term, i.e. from the
conclusion of 68th AICC upto the conclusion of
the 69th AICC of the ICA.
Item 14: Under any other item with the permission of the
Chair, following decisions were taken unanimously:
(i) RESOLVED to provide hard copy of the
recommendation of the committee for electoral
reforms and other reforms in ICA in terms of regional
structure and state chapters so that it can be placed
as an agenda item in the next meeting of EC.
(ii) RESOLVED to appoint one man Committee of Prof.
H. Ventakeshwarlu for designing a student session
and also separate set of Awards to the best papers
presented by the students.
(iii) RESOLVED to authorize Prof. J. K. Parida to start
Innovation Centre/Entrepreneurship Centre of ICA
at KIIT, Odisha.
(iv) RESOLVED to invite/nominate proposals for topics
and the names of Chair and Co-Chair persons for
different Technical Sessions, Seminar Session, MM
Shah Session, to be held during 69th AICC of ICA
throughout the year on website of ICA till the Annual
General Body meeting at 69th AICC of ICA.
The chairman thanked all the members.
The meeting ended with a vote of thanks to the chair.
Dr. Balwinder Singh
Secretary - ICA
( 159 )
The Annual General Body Meeting of the Indian Commerce
Association was held on November 7, 2015 at 4.00 pm in
the Vivekananda Auditorium, Vinoba Bhave University,
Hazaribagh, under the chairmanship of Professor Jayant
K. Parida, President of ICA. The following decisions were
taken unanimously:
Item 1 : Considered the minutes of the last meeting of the
General Body of the ICA held on December 28, 2014 at
KIIT University, Bhubaneswar
RESOLVED to approve the minutes of the last General
Body Meeting of the ICA.
Item 2 : Considered the Secretary’s Report for the year
2015 as approved by the Executive Committee of the ICA
RESOLVED to approve the Secretary’s Report for the Year
2015.
Item 3 : Considered the recommendation of Executive
Committee regarding audited accounts of the ICA for the
year 2015 and the Managing Editor’s Report.
RESOLVED not to approve the recommendation of
Executive Committee regarding audited accounts of the
ICA for the year 2015 and the Managing Editor’s Report.
The amended Audited Accounts after taking into account
the objections raised by Members of ICA will be presented
in the Next General Body Meeting of ICA for approval.
Item 4 : Considered the recommendations of the Executive
Committee of the ICA about holding AICMTSE, 2016.
RESOLVED to approve the report presented for holding
the All India Commerce and Management Talent Search
Examination (AICMTSE). It was resolved to organize the
next test in September 2016 on any Sunday and only those
students would be eligible to appear for the test who are
Student Members of ICA. It was resolved to charge Rs.300/
- as Student Membership Fee. The following committee
was constituted to work out holding of off line or on line
conduct of test and its cost dimension:
a. National Coordinator
b. President of ICA
c. Secretary of ICA
d. Prof. Sasmita Samanta, Registrar, KIIT
INDIAN COMMERCE ASSOCIATIONMINUTES OF THE ANNUAL GENERAL BODY MEETING OF THE
INDIAN COMMERCE ASSOCIATION HELDON NOVEMBER 7, 2015
It was suggested to work out tie ups with Industry and
Business for considering this test for recruitment purposes
and Universities in India and abroad for admission
purposes.
Item 5 : To report the recommendations of the Executive
Committee of the ICA that the General Body be given
opportunity to elect the hosts of 69th ICA Conference and
they be informed about the institutions from where the
proposals have come along with the proposed Conference
Secretary’s name and elections be held by mentioning these
details in the ballot papers. Each voter shall be given only
one preference.
The proposals received are as follows:
1. Hemchandracharya North Gujarat University,
Patan, Gujarat
Dr. R. L. Godara, Conference Secretary
2. Lucknow University, Lucknow, Uttar Pradesh
Dr. Arvind Kumar, Conference Secretary
Item 6 : Considered the recommendation of Executive
Committee of ICA regarding appointment of Returning
Officer for 2016 ICA elections.
RESOLVED to appoint Prof. P. Purushotam Rao as the
Returning Officer for conducting Elections scheduled to
be held during the 69th All India Commerce Conference in
2016.
Item 7 : Considered the recommendation of Executive
Committee of ICA regarding appointment of auditor.
RESOLVED to reappoint M/s Alok Sharma & Company,
Chartered Accountants, BJ-57, Shalimar Bagh, Delhi –
110088 for the year 2015-16 on the same terms and
conditions
Item 8 : Considered the recommendation of EC of ICA that
Hard Copy of the Journal shall be sent to all Institutional
Members, Contributors and Subscribers to the Journal. Soft
Copy of the Journal shall be sent to All Life members and
shall also be uploaded on the website of the Indian
Commerce Association and of the Journal.
( 160 )
RESOLVED to approve the above recommendation of
Executive Committee of the ICA
Item 9 : To confer the honor of the Fellow of the Indian
Commerce Association to the Chairpersons of the various
Sessions of the 68th All India Commerce Conference and
the new members of the EC of the ICA for their
contributions made to the ICA in particular and academics
in general in terms of the Resolution No 10 of the General
Body Meeting of the ICA held on December 28, 2004 at
Indore.
• Dr Gurcharan Singh Professor, School of Management Studies, Punjabi University, Patiala, Punjab
• Dr Jasveen Kaur Assistant Professor, University Business School, Guru Nanak Dev University,
Amritsar
• Dr. G P Prasain Professor, Department of Commerce, Manipur University, Canchipur, Imphal
• Dr Maheshwar Sahu Professor, P.G.Department of Commerce, Utkal University, Bhubaneswar
• Dr Laxman Kisan Karangale Faculty, B B College, Lonar
• Dr S A Chintaman Faculty, H K Commerce College, Ahmedabad
• Prof. Indrasena Reddy Department of Commerce & Management, Kakatiya University, Warangal.,
(A.P)
• Dr M Shivalingegowda Associate Professor, Vidyavardhaka First Grade College, Sheshadri Iyer Road,
Mysore
• Dr. G. RAJU Professor of Commerce, University of Kerala, Kerala
• Dr Awadhesh Kumar Tiwari Professor, Department of Commerce, D.D.U. Gorakhpur University, Gorakhpur
(U.P.)
• Dr. A M Gurav Professor, Department of Commerce, Shivaji University, Kolhapur, Maharashtra,
• Dr. Ram Sable, Professor, S.N.D.T Women’s University, Mumbai
Item 10 Considered the recommendations of the EC of the
ICA regarding the topics for the Seminar session, four
Technical Sessions and MM Shah Research Gold Medal
Session to be held at the time of 69th Annual Conference of
the ICA.
RESOLVED that committee comprising of the office
bearers of the ICA and Past Presidents present in 68th
AICC shall finalise the topics for the Seminar Session, Four
Technical Sessions, and M. M. Shah Research Gold Medal
Session to be held at the time of the 69th Annual Conference
of the ICA. These shall be based on the suggestions received
from the General Body of the ICA.
Item 11: Considered the recommendations of the EC of the
ICA regarding the names of the Chair persons, Co-chair
persons for the Seminar session, four Technical Sessions
and MM Shah Research Gold Medal Session to be held at
the time of 69th Annual Conference of the ICA
RESOLVED that committee comprising of the office
bearers of the ICA and Past Presidents present in 68th AICC
shall finalise the Sectional Chairpersons/Co-chairpersons
for the Seminar Session, Four Technical Sessions and M.
M. Shah Research Gold Medal Session to be held at the
time of the 69th Annual Conference of the ICA. These shall
be based on the suggestions received from the General
Body of the ICA.
Item 12 Under any other item, following issues were
raised and resolved:
a. To ensure that Quality papers are published in
Indian Journal of Commerce, it was resolved to
constitute a Board of Reviewers. It was further
resolved that Each paper submitted for publication
in the Journal shall be reviewed and Referee report
shall be sent to contributors through email to ensure
transparency and quality.
Item 13: RESOLVED to approve the recommendations of
the EC of the ICA that Prof. M K Singh, Conference Secretary
and Head & Dean, Faculty of Commerce & Business
Management, Vinoba Bhave University, Hazaribagh be
elected as President of the ICA for the next term i.e. upto
the conclusion of the 69th Annual Conference of the ICA
The Chairman thanked all the members of ICA for
cooperation and positive suggestions.
The AGB meeting ended with a vote of thanks to the chair.
November 7, 2015
Balwinder Singh
Secretary, ICA
( 161 )
SAURABH SHIWARE MEMORIAL YOUNG RESEARCHER AWARDIndian Commerce Association
To recognize and reward the budding researchers and their initial efforts and to instill the spirit of active and worldclass researcher as they mature, has instituted the Saurabh Shiware Memorial Young Researcher Award. TheICAaward aims to nurture the young talent which holds the potential to make meaningful contributions in the �eld ofcommerce and allied disciplines and thus improve the landscape of research in the country.
The award, Saurabh Shiware Memorial Young Researcher Award has been instituted to salute the entrepreneurial,innovative and the versatile spirit of Mr. Saurabh Tukaram Shiware. Mr. Saurabh Shiware was an enthusiast learnerand hard worker since his early childhood. With his schooling from St. Xavier's Kolhapur Mr.Saurabh graduatedfrom the Hinduja Institute of Management, Mumbai. To satisfy his entrepreneurial and innovative urge, Mr.Saurabh set up his own business in computer software. His dynamism and un�inching attitude landed him up with alucrative job in Gulf Oil Corporation, Dubai. With his academic and professional commitments, Mr. Saurabh didremain an ardent lover of football and was in the school and college football team. A dedicated student, committedprofessional, zealous sportsperson, Mr. Saurabh was a real talent to reckon with. As destiny would want it, he had anuntimely demise which put an abrupt end to his journey on this earth. To let his spirit and soul live beyond time andphysical boundaries, with the sponsorship of the very generous, Dr. T. Shiware has decided to announce thisICAaward for the young professionals in the discipline who have made some contributions which have the potential tomake a difference to the research scenario and take research in the discipline to the mainstream. The motivating andexemplary personality of Mr. Saurabh Shiware stands as an inspiration for all those who have it in them and theaward aims to recognize such potential for excellence in research.
The award shall comprise of a cash prize of Rs.25,000/ (Rupees Twenty Five Thousand Only), with a certi�cate ofappreciation and a trophy to be awarded each year in the Annual Conference of .ICA
Eligibility Criteria for Award• Awardee must not be more than 35 years of age, as on the last date of Application.• He/she may be from academic/Professional bodies but engaged in research activities in form of publication
of research papers, books, journals, seminar presentation, project work and other such related works duringhis life.
• He/she is eligible to avail the bene�t once in his/her life time.• He/she must have Post Graduate degree in Commerce, Management , , or related subjects.CA ICWAProcedure of Participation1. Submit Bio data containing all research and allied activities undertaken. Bio data may be divided in- -
following parts: Title Sheet: Basic Information of Applicant along with passport size photographa) Education quali�cationb) Employment Details (present & past)c) Research Activities Undertaken with complete details. In case of Journal / Book
Publication, mention publisher name and citation of publication (if available).d) Your Contribution to the �eld of commerce till date.
( 162 )
e) Your views to revolutionize �eld of commerce in next 10 years.f) Any additional information, you wish to provide.g) Enclose valid proof of your age.
2 The last date for submission of such Bio-data is 15th August, 2016.3 Application should be dispatched to:
Dr. Balwinder Singh,Secretary,Indian Commerce Association (ICA),Associate Professor,Department of Commerce, Guru Nanak Dev University,Amritsar 143005, Punjab, India‐
(M: 9417272232) (Email:[email protected])
Other Information1 The secretary, ICA after receiving all the applications will convene the meeting of expert committee on a
suitable date and handover the same to the chairman of the said committee for �nal selection on the basis ofthe well de�ned parameters �nalized . The decision of the committee is �nal and binding and cannot bechallenged in any court of law.
2 Award shall be presented in the inaugural function of the AICC by the Chief Guest in presence of theDonor.
3. The awardee so selected shall be paid third AC class TA to receive the prize and all facilities in theconference like other delegates, free of cost
( 163 )
Last Application Date : 15th August2016.
( 164 )
( 165 )
Procedure of RegistrationFor
69th AICC to be held on 11-13 November, 2016at University of Lucknow, Lucknow
Dear Member,Greetings, in order to streamline the procedures and ensure transparency and ef�ciency, this timeOnline Registration Form cum ID Card Form has been developed so that The ID Cards can behanded over to you at the time of Conference.
Steps for Registration1. Visit www.icandia.info, then Click on Conference, a drop down Box will appear, click on
Online Registration, A page will appear before you. At the Bottom of the page, click on theClick here for Online Registration.Alternatively Click on the following linkhttp://icaindia.info/index.php/component/chronoforms5/?chronoform=ConferenceRegistration69
2. Fill the Form, Giving your Personal Details, Paper Details, ICA Life Member Only, TravelDetails, Payment Particulars, Upload Your Photo and Signatures
3. When You will click on Submit, A PDF Form shall be generated.
4. Take a Print Out of the Form, Attach Demand Draft and send it to
Dr Arvind KumarConference Secretary,69th All India Commerce ConferenceDean, faculty of Commerce, University of Lucknow,Lucknow-226007, Uttar Pradesh, India
Note: All the Papers will be submitted through website Only. Papers emailed directly toChairpersons/ Co-chairperson shall not be entertained.
( 166 )
BOOK REVIEW
GREEN SIGNALS: ECOLOGY, GROWTH AND DEMOCRACY IN INDIABy Jairam Ramesh
Publisher: Oxford University Press IndiaEdition: First Edition, 2015ISBN: 0199457522, 978-0199457526Pages: 596Price: Rs 850
'Green Signals: Ecology, Growth and Democracy in India' is written by Shri JairamRamesh, the former union minister of environment and forests (Independent Charge).The book shows that growth is not just about a rising GDP but about being mindful ofconsequences. It depicts, 1991 moment in country's environmental decision-making,telling the story of how, the doors of the environment ministry were opened to voices forthe �rst time, hitherto unheard, into the policy-making process. It details efforts to changethe way and the environment is viewed both by proponents of environmental securityand those who prize economic growth at all costs.
The book contains 12 chapters which uses the author's narrative on various ecological andenvironmental issues and provides the reader with glimpses of transcripts from the RajyaSabha deliberations, correspondence in the form of letters written to or by the Ministerand invited lectures on topics of seminal interest. The author also touches the severalcontroversial issues including the violation of environmental laws by Adarsh HousingSociety in Mumbai, the go-no-go areas for coal mining, the Bt-Brinjal debate, India's standon Climate Change negotiations, and the various bigticket projects including the POSCOsteel plant, Vedanta's mining plan for Niyamgiri and the Jaitapur nuclear power plant.
Green Signals, supported by facts and �gures, is a record for posterity and a genuinereference. This collection reveals the story of the author's attempt at the highest levels ofgovernance to introduce effective decision making, a transparent and accountableadministration and to make environmental concern an essential component of a nation'squest to accelerate economic growth and end the scourge of poverty and deprivation. Thebook addresses the challenges involved in trying to ensure economic growth withecological security. It takes us through India's coming of age in the global environmentaland climate change community to take on a leadership role that was progressive,proactive, and steeped in national interest.
The book is engrossing and provides a view on the functioning of a minister who believedin taking a pro-active approach. The author gives an insight into the debates, struggles,challenges, and obstacles to bringing environmental considerations into the mainstreamof political and economic decision-making.
( 167 )
( 168 )
The book sketches the attempts of Shri Ramesh to make environmental concern anessential component of the nation's quest to accelerate economic growth and end thescourge of poverty and deprivation. Using speaking orders on signi�cant projects,notes and letters to the Prime Minister, ministerial coworkers, chief ministers amongothers, the author offers an insight into the discussions, challenges and hurdles tobringing environmental concern into the arena of political and economic decision-making. Undoubtedly, the book is useful for researchers, academicians, economicthinkers and as well as for political thinkers.
Dr. Vinay K. SrivastavaSector-6, F-1, 6/160, VaishaliGhaziabad-201010, M: 09310623050
--------------------------------------------------------------------------------------------------------------The author is freelancer writer and Managing Editor of ARASH A JOURNAL OFISMDR and Honorary secretary of the Indian Society for Management Development& Research. He holds D. Phil. from Department of Commerce and BusinessAdministration, University of Allahabad. He has more than 12 years of Academicand 2 years of industry experience and has published more than 60 articles in reputedNews Papers, Magazines and journals. He has authored a book 'Privatization ofPublic Enterprises in India' and edited a book 'Public Enterprises and ChangingScenario'. He can be reached to meetdrvinay@gmail.com--------------------------------------------------------------------------------------------------------------
INDIAN COMMERCE ASSOCIATION
69th
President
Dr M K Singh Head & Dean, Faculty of Commerce & Business Management and Director, Deptt
of Management, Vinoba Bhave University, Hazaribag - 825301 Jharkhand, INDIAExecutive Vice President
Dr.Ananth M. Deshmuk, Professor, Dept. Of Business Mgt., R. T. M., Nagpur University, Nagpur
Secretary
Dr Balwinder Singh Associate Professor, Dept of Commerce, Guru Nanak Dev University, Amritsar-
143005, PunjabJoint Secretary
Dr. M. Muniraju Professor & Head, Dept of Commerce, Bangalore university, BangaloreManaging Editor Cum Treasurer
Dr H. K. Singh, Professor, Faculty of Commerce, Banaras Hindu University, Varanasi-221005
Immediate Past President
Prof.Jayanta Kumar Parida Department of Commerce, Utkal University, Bhubneshwar
Conference Secretary
Dr. Arvind Kumar Dean, Faculty of Commerce, University of Lucknow, Lucknow
EC Members
Dr Pushkarnath Professor, Deptt. of Commerce & Management, Gossner College, Ranchi-834008
Dr. Ram Uddeshya Singh P.G. Deptt. of Commerce, College of Commerce, Patna – 800020 (Bihar)
Dr Sangita M. Jiwankar Associate Professor, Department of Commerce, Dhanwate National College,
Nagpur
Prof.D.M.Khandare Director & Head, School of Commerce & Management Sciences, SRTM
University,Nanded-431606
Prof. H Venkateshwarlu Department of Commerce,Osmania University, Hyderabad - 500 007, Andhra
Pradesh
Dr. S. Ramesh Dean, Post Graduate Department of Commerce & Management, Mount Carmel
College, Banglore
Dr Manjit Singh Professor, School of Applied Management, Punjabi University, Patiala. (147002)
India
Dr. H.C. Purohit Dean, Faculty of Management Studies, Department of Business Economics, VBS
Purvanchal University, Jaunpur (UP)-222001
Dr Debabrata Mitra Professor, Department of Commmerce, University of North Bengal, PO. NBU,
District Darjeeling (WB) 734013
Dr. Ran Singh Dhaliwal Professor, School of Management Studies, Punjabi University, Patiala, Punjab
Dr. Sharada Gangwar Professor, Institute for Excellence in Higher Education, Bhopal
Dr. Shashank Bhushan Lal Associate Professor, Vanijya Mahavidyalay, Patna University, Patna
Prof. B. P. Saraswat Professor, Department of Commerce, MDS University, Ajmer
Dr. Sangale Babasaheb Rambhau Professor, BJS College, Wagholi, Pune
Prof. M. Jayappa RBANMS College, Bangalore
Dr. Ramesh Agadi Professor of Management, Gulbarga University, Gulbarga
Dr Gurcharan Singh Professor, School of Management Studies, Punjabi University Patiala – 147002,
Punjab, India
Dr Jasveen Kaur Assistant Professor, University Business School, Guru Nanak Dev University,
Amritsar-143005
Prof. G P Prasain Department of Commerce, Manipur University,Canchipur, Imphal-795003,
Manipur
Dr Maheshwar Sahu Professor at P.G.Department of Commerce, Utkal University, Bhubaneswar
Dr Laxman Kisan Karangale B B College, Lonar
Dr S A Chintaman H K Commerce College, Ahmedabad
Prof. Indrasena Reddy Department of Commerce & Management, Kakatiya University, Warangal., (A.P) -
506 009.
Dr M Shivalingegowda Associate Professor, Vidyavardhaka First Grade College,Sheshadri Iyer
Road,Mysore 570 001.
Devesh Kumar (President Nominee) Manager - NF & ME, Bihar Rural Livelihoods Promotion Society (JEEVIKA)
Dr Ajay K Singh (Managing Trustee) Associate Professor, Dept of Commerce, Delhi School of Economics, DU, Delhi.
OFFICE BEARERS AND EXECUTIVE COMMITTEE MEMBERS FOR AICC
Sessions Chairpersons Co-Chairpersons
I New Beginnings in Indian Dr. Sandip K Bhatt Dr P.N.HarikumarFinancial System Professor & Head Associate Professor & Head P.G
P. G. Department of Business Studies, Department of Commerce & TourismSardar Patel University, Catholicate CollegeVallabh Vidyanagar- 388120. Anand Pathanamthitta, Kerala-689645
II Globalisation of Markets: Dr. S.G. Hundekar Dr Ajay M. BhamareEmerging Challenges Professor Principal
P.G. Department of Studies in Commerce, Ramanand Arya D.A.V.College,Karnatak University, Datar Colony, Bhandup (E),Dharwad-580 003 Mumbai -400042
III Tourism and Hospitality Industry Dr Khumukcham Tomba Singh Dr Ashok Kumar Singhin India: The Road Ahead Professor Associate Professor & Head,
Department of Commerce P.G.Department of CommerceManipur University Vanijya MahavidyalyaCanchpur: 795005, Manipur Patna University, Patna-800003 (Bihar)
IV Women Empowerment: Dr. Subhash Garg Dr. Mamta JainRealities and Challenges Professor Associate Professor
Deptt. of Management Department of Economic AdministrationDean & Director and Financial Management,Centre for Research, Innovation and Training (CRIT) University of Rajasthan,The IIS University, Jaipur-302 020 Jaipur-302004 (Rajasthan)
V ICA Research Scholar Chairperson Co-Chairperson
Award Prof.Parimal H. Vyas Prof.(Dr.) V.K.SinghVice-Chancellor, Faculty of Management StudiesM.S. University of Baroda Gurukul Kangri UniversityVadodara, Gujarat, India Haridwar. Uttarakhand, India
SeminarSTARTUP INDIA: OPPORTUNITIES Dr Narender Kumar Dr Avinash D. PathardikarAND CHALLENGES Professor, Head & Dean Associate Professor
Department of Commerce, Department of HRDM D University Faculty of Management StudiesRohtak-124001(Haryana) VBS Purvanchal University
Jaunpur-222001 (U.P.)
Manubhai M. Shah Memorial Research Gold Medal (Two)EMPIRICAL RESEARCHES IN THE FIELD OF ACCOUNTING AND FINANCE
Chairperson Co-ChairpersonDr. Kripa Shanker Jaiswal Dr Anthony RodriguesProfessor & Dean Director,Faculty of Commerce & Management Studies Research centre & Reader,Director Department of CommerceInstitute of Management Studies (IMS) Fr. Agnel College of Arts & com,Mahatma Gandhi Kashi Vidyapith, Pilar-Goa-403005Varanasi (U.P.) 221002
Managed on behalf of Managing Editor, Indian Journal of Commerce, by , Gurukul Marg, Mansarovar, Jaipur-302020ICA SFSThe University,IIS
Ph : 9166611999 • Email : [email protected]•Web: www.iisuniv.ac.in
President Prof. (Dr.) M.K. Singh, Head & Dean, Faculty of of Commerce, University Deptt. of Commerce & BusinessManagement, Vinoba Bhave University, Hazaribag -825 301, India, 9431332889. [email protected]
Executive Dr.Ananth M. Deshmukh, Associate Professor, Dept. of Business Mgt., R. T. M. NagpurVice President University, Nagpur, 9823121458. [email protected]
Secretary Dr Balwinder Singh, Associate Professor, Dept of Commerce, Guru Nanak Dev University,Amritsar-143005, Punjab, 9417272232. [email protected]
Joint Secretary Dr. M. Muniraju, Professor, Department of Commerce, Bangalore University, Bengaluru,9448686143. [email protected]
Managing Editor Prof. H. K. Singh, Professor, Faculty of Commerce, Banaras Hindu University, Varanasi 221005, India,cum Treasurer 9415264509. [email protected]
Immediate Prof.Jayanta Kumar Parida, Utkal University, Bhubneshwar, 9437229465. [email protected] President
Conference Secretary Dr. Arvind Kumar, Dean, Faculty of of Commerce. University of Lucknow - 226 007, U.P., [email protected]
INDIAN COMMERCE ASSOCIATION
OFFICE BEARERS
69thTOPICS
FORALL INDIA COMMERCE CONFERENCE11-13 November 2016
Regd. No. 4973/60 Cost is less than 56/-`