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 : hksinghmeera@gmail.com, hksinghmeera@yahoo.co.in

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

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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 : hksinghmeera@gmail.com, 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

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(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: hksinghmeera@gmail.com • hksinghmeera@yahoo.co.in

Published by Prof. H. K. Singh on behalf of the Indian Commerce Association

NOTES FOR CONTRIBUTORS

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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

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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: hksinghmeera@yahoo.co.in • 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

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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

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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.

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• 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.

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• 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

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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.

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Gnyana Ranjan Bal, Hemant Kumar Majhi, Malabika Deo

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Gnyana Ranjan Bal

Assistant Professor

Dept. of Commerce

Guru GhasidasVishwavidyalaya, C.G.

E-mail-gnyana.friend@gmail.com

Hemant Kumar Majhi

Ph.D. Scholar, Dept. of Banking and Technology

Pondicherry University, Pondicherry

E-mail : hemantkumarmajhi09@gmail.com

Dr. Malabika Deo

Professor and Head, Dept. of Commerce

Pondicherry University, Pondicherry

E-mail : deo_malavika@yahoo.co.in

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 : drrajug@yahoo.co.in

Deepika Krishnan

Research Scholar

Faculty of Management Studies

University of Kerala, Thiruvananthapuram

Kerala

Email : deepzkris@gmail.com

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’.

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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: parimalvyas17@gmail.com

Shri Parag Sunil Shukla

Assistant Professor of Commerce & Business Management

[Ces] and Research Scholar

Department Of Commerce & Business Management,

Faculty Of Commerce, Baroda

Email : parag.shukla.msu@gmail.com

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 : mnpandya61@rediffmail.com

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

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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: chandana23k@gmail.com

Dr. Ashima Sharma Borah

Associate Professor and HoD,

Department of Management,

KC Das Commerce College,

Guwahati, Assam.

E-mail : ashimasharmaborah@gmail.com

Opportunities and Challenges of E-Retailing in Assam: A Study with Special Reference to Nalbari District, Assam

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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

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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

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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

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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

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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

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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

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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

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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.

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Dr.K.Kanaka RajuAssistant ProfessorDepartment of Management Studies,Andhra University Campus,Andhra Pradesh

Email : dr.kanakaraju2011@gmail.com

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.

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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: azmath.phd.ou@gmail.com

Dr. Patrick anthony

Assistant Professor

Department of Commerce, Osmania University,

Hyderabad- 500007, Telangana State

E-mail: patrick_ay@rediffmail.com

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 : profram1968@gmail.com

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.

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Australian Association of Graduate Employers (AAGE),

(2011), ‘2011 AAGE Employer Survey’, AAGE,

Sydney, Australia.

Atherton, J. S. (2005). Learning and teaching: Bloom’s

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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

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Biometrics 49, 803-821.

Butcher, V., Smith, J., Kettle, J., & Burton, L. (2011). Review

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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 : dr.kanakaraju2011@gmail.com.

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.

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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

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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.

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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

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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

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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

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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 : drmmr2010@gmail.com

Mr. Swaminath SResearch ScholarDept. of Commerce, Bangalore University,Bangalore – 560001Email : iams_redeblue@yahoo.co.in

Mr. Ganesh S RResearch ScholarDept. of Commerce, Bangalore UniversityBangalore – 560001Email : gani.2mcmG@gmail.com

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.

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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:icaindia47@gmail.com)

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

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Last Application Date : 15th August2016.

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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.

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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.

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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 : subhash.garg@iisuniv.ac.in•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. mantun.ks@gov.in

Executive Dr.Ananth M. Deshmukh, Associate Professor, Dept. of Business Mgt., R. T. M. NagpurVice President University, Nagpur, 9823121458. a.des@rediffmail.com

Secretary Dr Balwinder Singh, Associate Professor, Dept of Commerce, Guru Nanak Dev University,Amritsar-143005, Punjab, 9417272232. bksaini@gmail.com

Joint Secretary Dr. M. Muniraju, Professor, Department of Commerce, Bangalore University, Bengaluru,9448686143. drmmr2010@gmail.com

Managing Editor Prof. H. K. Singh, Professor, Faculty of Commerce, Banaras Hindu University, Varanasi 221005, India,cum Treasurer 9415264509. hksinghmeera@gmail.com

Immediate Prof.Jayanta Kumar Parida, Utkal University, Bhubneshwar, 9437229465. jayantakp123@gmail.comPast President

Conference Secretary Dr. Arvind Kumar, Dean, Faculty of of Commerce. University of Lucknow - 226 007, U.P., 9415028817.arvindk.lu51@gmail.com

INDIAN COMMERCE ASSOCIATION

OFFICE BEARERS

69thTOPICS

FORALL INDIA COMMERCE CONFERENCE11-13 November 2016

Regd. No. 4973/60 Cost is less than 56/-`