editorial · 2018-04-10 · editorial a tribute to ratan tata ratan tata, a corporate icon, turned...

EditorialA TRIBUTE TO RATAN TATA

Ratan Tata, a corporate icon, turned 75 on Friday, 28th December 2012 and retired as Chairman of India’s largestindustrial house abiding by the rule made by him. He passed on the baton to 44-year-old Cyrus Mistry. It marked the endof an era in the history of Tata Group. He left behind a $100-billion empire to his successor. As Chairman of the Tata Grouphe established a legacy that earned him a wide praise as an able corporate leader with values.

Coming to his career, Tata did join the Group as an apprentice on the shop floor of Tata Steel’s Jamshedpur plant in1962. After serving the group in different positions and in different companies, he was appointed as Director-in-Charge ofthe National Radio and Electronics Company in 1971. Ten years later, he was named Chairman of Tata Industries; thegroup’s other promoter holding company. He became the Chairman of its holding company Tata Sons in 1991.

In more than two decades at the helm Ratan Tata, not only consolidated the group’s business in the domesticmarkets but also expanded it globally, acquiring assets, diversifying businesses and forging new linkages. He helped theGroup in attaining the global heights and showed how to do business in an ethical way. He proved himself as a true Indiancorporate leader.

During Tata’s tenure, the group’s revenues grew manifold, totalling USD 100.09 billion (around Rs 475,721 crore) in2011-12 from a turnover of a mere Rs 10,000 crore in 1991. Tata Group’s market capitalisation, which has some 30-odd listedcompanies, is now nearly Rs.4.54 trillion ($825 billion), 33 times more than in 1991 when Tata took over the top job. Duringthis period, the group’s aggregate sales have increased 43 times, while net profit has grown 51 times. Today 58 percent ofthe revenue comes from overseas operations. Their brand has emerged as the 45th global and the number one Indianbrand. At present TATA products and services are present in 85 countries. The group employs over 4,50,000 peopleworldwide.

Tata Group’s global expansion started in 2000 with the acquisition of Britain’s largest tea firm, Tetley for USD 450million. Since then Tata Group has made several big-ticket global acquisitions, including the purchase of Anglo-Dutchsteel maker Corus Group for $12 billion in 2007. Another big acquisition was of iconic British auto makers Jaguar and LandRover by Tata Motors. Other acquisitions include acquisition of controlling stake in government-run Videsh SancharNigam Ltd (VSNL), purchase of heavy vehicles unit of Daewoo Motors, acquisition of Singapore’s NatSteel and purchaseof New York-based The Pierre hotel.

Under the leadership of Ratan Tata, the group made great strides when it capitalised on the sunrise industry ofinformation technology in the 90s. With revenues of over USD 10 billion in 2011-12, Tata Consultancy Services (TCS) istoday India’s largest IT company, ahead of giants in the field like Infosys and Wipro.

Not limiting himself to big-ticket acquisitions, Tata also displayed sensitivity to the needs of the burgeoning middleclass with the launch of ‘Nano’. The small car is to be remembered as Tata’s desire to provide a safer option to many Indianlower-middle class families riding two-wheelers. His decision to establish Nano plant at Singur showed his interest indeveloping industrially backward areas. The corporate social responsibility, which he exhibited towards the victims/sufferers of 26/11 Mumbai incident was exemplary.

He masterminded not only the acquisitions, expansions and entries into new areas but also planned the exit of theGroup from sectors like cement, textiles and cosmetics, which proved to be poor strategic fits. He knows well when to entera new business and when to exit from an existing one.

Ratan Tata is also on the board of various global companies like Fiat SpA and Alcoa. He is on the advisory panelsof Mitsubishi Corp, the American International Group, Rolls Royce and Temasek Holdings etc. He is also a member of theIndian Prime Minister’s Council on Trade and Industry. In 2008, the Government of India honoured him with its second-highest civilian award, the Padma Vibhushan.

Ratan Tata is known for his simplicity, commitment, dedication, values and vision. Future generations have toimbibe his philosophy, emulate his value system and learn how to run a business on ethical lines. On the eve of hisretirement as Chairman of Tata Group we would like to pay our respectful tributes to the ideal Indian Corporate Leader, aVisionary, Padma Vibhushan Ratan Tata.

Chief Editor

Copyright © October 2012 by Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad

Access any latest information about Gokaraju Rangaraju Institute of Engineering & Technology(GRIET) http://griet.ac.in from our web site : http://mgmt2day.griet.ac.in

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Management Today (An International Journal of Management Studies)

Published by

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Management Today(International Journal of Management Studies)

Volume 2 No. 4 October 2012

Contents1. Empirical Evidence of Work Life Balance in Baking Sector

M. Lokanadha Reddy and P. Mohan Reddy ........................................ 1

2. The Committees’ Reports on Urban Co-operative Banks in India

K. Sudhakara Rao ................................................................................................ 13

3. Analysis of Learner Profile Generation Algorithms

Rohini Nair and K.J.Somaiya .................................................................................. 22

4. Exploring the Effects of Consumer Knowledge and Fit Perception in BrandExtension Success

Soumi Paul and Saroj Kumar Datta ........................................................................ 29

5. Demographic Analysis of Patient Satisfaction in Major Healthcare Centres

Silky Vigg Kushwah, Pushpa Negi and Ashok Sharma ................................ 37

6. Select Bibliography on Leadership and Leadership Development (M-Z)

K.V.S. Raju and P.B. Apparao................................................................ 49

Responsibility of Contents of this paper rests uponthe authors and not upon GRIET publications.

ISSN : 2230 - 9764

EMPIRICAL EVIDENCE OF WORK LIFE BALANCE INBAKING SECTOR

M. Lokanadha Reddy1 and P. Mohan Reddy2

1Ph.D. Scholar and 2ProfessorDepartment of Commerce, Sri Venkateswara University

Tirupati, Andhra Pradesh – 517502 [email protected] / [email protected]

Abstract: Work/life balance, in its broadest sense, is defined as a satisfactory level of involvement or ‘fit’ between themultiple roles in a person’s life. Although definitions and explanations vary, work/life balance is generally associatedwith equilibrium, or maintaining an overall sense of harmony in life. The study of work/life balance involves theexamination of people’s ability to manage simultaneously the multi-faceted demands of life. Although work/lifebalance has traditionally been assumed to involve the devotion of equal amounts of time to paid work and non-workroles, more recently the concept has been recognized as more complex and has been developed to incorporateadditional components. The present research paper aims at endeavoring the empirical evidence of work life balanceconcerning employees of public sector and private sector banks. For the purpose of comparative analysis, two banksare chosen purposely each from public and private sector. These are Andhra Bank and Indus Ind Bank. About 50employees belonging to managerial cadre from each bank are chosen at random. Therefore, sample constitutes 100employees. The opinions are elicited from them through administering pre-structured questionnaire. The informationso gathered is tabulated, analysed and interpreted. The banks shall formulate ideal policies for effective work lifebalance. The abnormal working hours shall be reduced so as to manage the stress due to work pressure. Healthcheckup plans shall be introduced so that the morale of the employees is improving in the case of private sectorbanks. Customization of work life balance policy to individual needs is a pre requisite. Job sharing and supportfrom colleagues are key factors to good work life balance for success of the Indian banking sector.

Key words: Work life balance, family-friendly policies (FFPs), work-life benefits and practices (WLBPs)

Introduction

Work-life balance has become anincreasingly invasive concern for employers aswell as employees in the present day context.Demographic changes as seen in the increasingnumber of women in the workplace and dualcareer families have generated an increasinglydiverse workforce and a greater need ofemployees to balance their work and non-worklives (Bharat, 2003; Rajadhyaksha & Bhatnagar,2000; Sekharan, 1992). In response to thesechanges, employers have introduced innovativepractices that allow employees to find greaterwork-life balance (Friedman, Christensen, &DeGroot, 1998). Increasing attrition rates andincreasing demand for work-life balance have

forced organisations to look beyond run of thegreat HR initiatives such as flexible workinghours, alternative work arrangements, leavepolicies and benefits in lieu of family careresponsibilities and employee assistanceprogrammes have become a significant part ofmost of the company benefit programmes andcompensation packages. Such policies, practicesand benefit programmess are generally referredas ‘family-friendly policies’ (FFPs) or ‘work-lifebenefits and practices’ (WLBPs) in literature(Kopelman et al., 2006; Kossek & Ozeki, 1998).The significance and implications of such HRinterventions are many. For instance provision ofWLBPs also contributes to organisationalperformance and effectiveness (Sands & Harper,2007).

Vol. 2, No. 4, October - 2012 Management Today

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Though, work-life balance as a concept hasgot considerable attention and as a campaign hasbeen practiced by various organisations as amatter of policy and strategy, still we are not sureof what constitutes WLBPs. Some organisationsprovide a bundle of policies and programmes suchas alternative work arrangements, leave policies,child-care centers, gymnasiums and recreationfacilities at work in the name of WLBPs. Sinceemployee work-life balance as a concept has gotrecognition from employers and HR managers inIndia only in recent years, the organizationalinitiatives in this regard are hardly known.

The Concept

Work-life balance (WLB) is a broad conceptdenoting the balance between the professional lifeand personal life of an earning person and includesproper prioritizing between “work” (career andengagements) on one hand and “life” (pleasure,leisure, family and spiritual development) on theother. Other terms for this concept often used are“lifestyle balance” and “life balance” (Wikipedia).The expression was first used in UK in the late1970s to describe the balance between anindividual’s work and personal life. In the UnitedStates, this phrase was first used in 1986.

It is pertinent to note that Work-Life Balancedoes not mean an equal balance as it variesovertime. The right balance for one when he / sheis single, will be different when one marries, whenone begets children, when one starts a new careerand when one is nearing retirement. The best work-life balance is different for individuals becausethey have different priorities, different objectives

and, of course, different partners and familymembers hailing from distinct socioeconomicbackgrounds.

Work/life balance, in its broadest sense, isdefined as a satisfactory level of involvement or‘fit’ between the multiple roles in a person’s life.Although definitions and explanations vary, work/life balance is generally associated withequilibrium, or maintaining an overall sense ofharmony in life. The study of work/life balanceinvolves the examination of people’s ability tomanage simultaneously the multi-faceteddemands of life. Although work/life balance hastraditionally been assumed to involve the devotionof equal amounts of time to paid work and non-work roles, more recently the concept has beenrecognized as more complex and has beendeveloped to incorporate additional components.

Aim of the paper

The present research paper aims atendeavoring the empirical evidence of work lifebalance concerning employees of public sectorand private sector banks.

Empirical analysis

For the purpose of comparative analysis, twobanks are chosen purposely each from public andprivate sector. These are Andhra Bank and IndusInd Bank. About 50 employees belonging tomanagerial cadre from each bank are chosen atrandom. Therefore, sample constitutes 100employees. The opinions are elicited from themthrough administering pre-structuredquestionnaire. The information so gathered istabulated, analyzed and interpreted.

Empirical Evidence of Work Life Balance in Baking Sector

Table: 1Normal Working Days in a Week

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Questions Andhra Bank Indus Ind Bank Total Men Women Men Women Andhra Bank Indus Ind Bank

Less than 5 days 0 0 0 0 0 0(0.0) (0.0)

5 days 0 0 0 0 0 0(0.0) (0.0)

6 days 35 15 35 15 50 50(100) (100)

7 days 0 0 0 0 0 0(0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Source: Primary Data

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Table 1 shows the normal working days inweek in select banks, for this purpose thefrequency is distributed less than 5 days not 7days. The opinions are elicited from both men

Questions Andhra Bank Indus Ind Bank TotalMen Women Men Women Andhra Bank Indus Ind Bank

7-8 hours 0 0 0 0 0 0(0.0) (0.0)

8-9 hours 24 9 18 8 33 26(66) (52)

9-10 hours 7 4 11 4 11 15(22) (30)

more than 10 hours 4 2 6 3 6 9(12) (24)

Total 35 15 35 15 50 50(100) (100)


Table 2 shows normal effective workinghours in a day. It is evident from the table thatmajority of employees (66 per cent) in publicsector bank are working about 8 to 9 hours. Butin private sector bank many of the employeesprefer to work about 9 to 10 hours (30 per cent)


Marital status is presented in table 3. It isevident from Table – 3 that majority of employeesof Andhra bank were married (92 per cent) while(76 per cent) in the case of Indus Ind bank. In



Yes 31 15 26 12 46 38(92) (76)

No 4 0 9 3 4 12(8) (24)

Total 35 15 35 15 50 50(100) (100)

Table: 2Normal Effective Working Hours in a Day

and women respondents. It is observed that normalworking days in a week usually be 6 days. It maybe noted that in both the private and public sectorbanks working days are uniform.

Table: 3Marital Status

and, more than 10 hours (24 per cent). Majorityof women employees would like to work innormal working hours (8 to 9 hours). It may beobserved that higher cadre employees have towork more than 10 hours due to work pressure inboth the sectors.

between gender, male employees are more innumber of material status in both the banks whencompared to female employees.

Table: 4Person Responsible to Take Care of Children in the Family

Table 4 shows person responsible to takecare of children in the family. The categoriesinclude spouse, in law, parents, servants and Daycare centers. It is obvious that spouse occupiesprime place in taking the care for children in thecase of Andhra Bank followed by in laws andparents. In the case of private sector banks parents

Table 4.1 shows hours spending withchildren in a day. It is clear that majority of theemployees in both the banks are spending only 2to 3 hours with their children’s. Even some of the

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Andhra Bank Indus Ind Bank TotalMen Women Men Women Andhra Bank Indus Ind Bank

Spouse 16 3 11 0 19 11(41.3) (28.9)

In-Law 10 3 6 3 13 9(28.3) (23.7)

Parents 3 8 8 9 11 17(23.9) (44.7)

Servents 2 1 1 0 3 1(6.5) (2.7)

Creche/day care 0 0 0 0 0 0Centre (0.0) (0.0)Total 31 15 26 12 46 38

(100) (100)

Questions



Less than 2 hours 3 1 6 1 4 7(8.0) (14.0)

2-3 hours 28 12 20 12 40 32(80.0) (64.0)

3-4 hours 4 2 9 2 6 11(12.0) (22.0)

4-5 hours 0 0 0 0 0 0(0.0) (0.0)

more than 5 hours 0 0 0 0 0 0(0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Questions


Table: 4.1Hours Spending With Children in a Day

assume more responsibility in caring the childrenfollowed by spouse and in laws. Servants’ role isvery meager in both the sectors whilst the role ofday care centre is completely nonexistent. On thewhole it may be observed that the responsibilityof children is a usual practice for parents and in-laws of employees.

employees are fall in less than 2 hours. Another22 per cent in case of private sector and 12% incase of public sector are spending 3 to 4 hourswith their children.

Table: 5Ability of Employees for Balancing of Work Life

Ability of employees for balancing of worklife is depicted in Table 5. It is gratifying to notethat cent percent of employees in the case ofAndhra bank and 95 per cent of employees in

5


Yes 35 15 33 14 50 47(100) (94.0)

No 0 0 0 3 0 3(6.0)

Total 35 15 33 14 50 50(100) (100)



Never think 0 0 0 0 0 0(0.0) (0.0)

Rarely 22 10 11 4 32 15(64.0) (30.0)

Some times 13 5 18 9 18 27(36.0) (54.0)

Often 0 0 0 0 0 0(0.0) (0.0)

Always 0 0 6 2 0 0(0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Questions



Table: 6Thinking often about Work other than Working Hours

the case of private bank have ability for balancingwork life. It may be observed that it is good signfor the organization. Moreover, it gives strongfeeling to the organization that they haveappointed right people and thereby a strength.

Table 6 shows thinking often about workother than working hours. For this purpose, 5factors are considered these include never think,rarely, sometimes, often and always. It is apparentthat 64 per cent of the employees in the case ofAndhra Bank rarely think while 30 per cent ofemployees in the case of Indus Ind Bank. About36 per cent of employees in Andhra bank thinksometimes about the organization, whereas 54per cent of employees in the case of Indus Ind

bank. But surprisingly 16 per cent of employeesof Private sector bank always think about workother than working hours. It is stunning to notethat no employee of public sector bank is foundin this scale. It is peculiar to note that never thinkand often are not registered in both the banks. Itmay be concluded that the employees who havemore interest in organization development arethinking about work other than working hoursalso.

Table: 7Feelings towards Time Spent at Work

Table: 8Missing Time with Family and Friends Due to Pressure of Work

Table 8 depicts the missing time with familyand friends due to pressure of work. This can beassessed through five point scale which includesnever, rarely, sometimes, often and always. It isevident that majority of the employees belongingto Andhra Bank (64 per cent) are missingsometimes while often in the case of private sector

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Table 7 shows feeling towards time spent atwork. It is evident that almost equal number ofemployees of both the banks represent 70 per centand 68 per cent in select banks was happy towardstime spent at work. About 30 per cent of employeesof Andhra bank are very happy while 18% in the



Very un happy 0 0 0 0 0 0(0.0) (0.0)

Un happy 0 0 2 0 0 2(0.0) (4.0)

Indiferrent 0 0 4 1 0 5(0.0) (10.0)

Happy 23 12 24 10 35 34(70.0) (68.0)

Very happy 12 3 5 4 15 9(30.0) (18.0)

Total 35 15 35 15 50 50(100) (100)

Questions



Never 0 0 0 0 0 0(0.0) (0.0)

Rarley 5 1 9 3 6 12(12.0) (24.0)

Some times 22 10 6 2 32 8(64.0) (16.0)

Often 8 4 20 10 12 30(24.0) (60.0)

Always 0 0 0 0 0 0(0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Questions


case of Indus Ind bank. Very less number ofemployees are indifferent and unhappy in the caseof private sector. It may be inferred that majorityof both male and female employees of both thebanks are feeling well towards time spent at work.This is welcoming future for both the banks.

bank. About (24.0 per cent) of employees aremissing the quality time with family and friendsdue to pressure of work. It may be noted that neverand always scales registered at zero per cent. Itmay be observed that missing time is morepronounced in the case of public sector bankwhen compared to private sector bank.

Feeling unrest or depressed due to work isshown in Table 9. The scale resembles thepreceding table. It is obvious that 20.0 per cent ofthe employees never felt unrest due to work inAndhra Bank whereas 14.0 per cent of employeesin the case of Indus bank. Majority of theemployees have no feeling of unrest or depressed

Table: 9Feeling Unrest or Depressed Due to Work

Table 10 provides statistical informationregarding managing stress due to work pressure. Theparameters include Yoga/Meditation, entertainment,dance, music and others. It is evident that the majorityof the employees of Andhra Bank (68.0 Per cent)manage stress with music whilst 58.0 per cent ofemployees in the case of private sector bank. It is

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Table: 10Managing Stress Due to Work Pressure



Never 9 1 6 1 10 7(20.0) (14.0)

Rarley 12 6 9 2 18 11(36.0) (22.0)

Some times 13 7 15 7 20 22(40.0) (44.0)

Often 1 1 4 4 2 8(4.0) (16.0)

Always 0 1 4 4 2 2(0.0) (4.0)

Total 35 15 35 15 50 50(100) (100)

Questions



Yoga/Meditation 6 3 11 4 9 15(18.0) (30.0)

Entertainment 0 0 0 0 0 0(0.0) (0.0)

Dance 0 0 0 0 0 0(0.0) (0.0)

Music 24 10 20 9 34 29(68.0) (58.0)

Others 5 2 4 2 7 6(14.0) (12.0)

Total 35 15 35 15 50 50(100) (100)

Questions


due to work in both the banks representing 40.0per cent in Andhra Bank and 44.0 per cent in Indusbank. About 20.0 per cent of employees neverfelt unrest due to work in Andhra Bank whilst about14.0 per cent of employees in the case of privatesector bank. It may be observed that workpressure has no impact on employees’ feelings.

peculiar to note that about 30.0 per cent of privatebank employees manage stress due to workpressure through Yoga/Meditation while 18.0 percent of employees in the case of Andhra Bank. Itmay be inferred that music is the main means formanaging stress followed by Yoga/Meditation.

Table 11 shows separate policy for work lifebalance. It is obvious that majority of theemployees of both the banks (68.0 per cent and72.0 per cent) have expressed that the banks havenot made any separate policy for work life balanceof the employees. The low percentage ofemployees did not agree with the statement. The

Table 12 provides the information regardingthe provisions helpful good work life balance.Majority of the employees of Andhra Bank (32.0per cent each) have opined a flexible starting timeand job sharing are helpful for good work lifebalance. Majority employees of Indus bank (40.0per cent) opined that flexible working time is morehelpful for good work life balance. The flexible

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Table: 11Separate Policy for Work Life Balance


Yes 11 5 10 4 16 14(32.0) (28.0)

No 24 10 25 11 34 36(68.0) (72.0)

Total 35 15 35 15 50 50(100) (100)

Table: 12Provisions Helpful for Good Work Life Balance



Flexible Startin 11 5 5 2 16 7time (32.0) (14.0)

Flexible Ending 5 5 14 6 10 20Time (20.0) (40.0)

Flexible hours 0 0 0 0 0 0(0.0) (0.0)

Job sharing 12 4 7 3 16 10(32.0) (20.0)

Holiday/Paid 5 0 7 3 5 10time off (10.0) (20.0)Others 2 1 2 1 3 3

(6.0) (6.0)Total 35 15 35 15 50 50

(100) (100)

Questions


employees have expressed differently theiropinions regarding the provisions of policy ofwork life balance. These include flexible startingtime, flexible ending time, flexible hours, jobsharing and holiday/paid time off. It is understoodthat both the sectoral banks have not tried toformulate a separate policy concerning work lifebalance.

hours as a provision are not accepted by theemployees of both the banks. Job sharing andpaid time off are also helpful for good work lifebalance, representing 20 per cent of employeeseach in the case of Indus bank. It may be observedthat flexible starting time, flexible ending time andjob sharing are proactive provisions whichpromote good work life balance.

Determinants of work life balance and familycommitments are shown in Table 13. The factorsinclude working from home, technology bringchildren to work place on occasion, supports fromfamily members. It is obvious that majority ofemployees of Andhra Bank (80.0 per cent)opinioned that support from colleagues is themajor factor for work life balance and familycommitment, while 76 per cent of the employees


Spending time for working outs is shown inthe table 14. It is evident that more than 50 percent of the employees did not spend their time forworking outs the rest of the employees for boththe banks have spent for working outsrepresenting 42.0 per cent and 48.0 per cent inAndhra Bank and Indus bank respectively.

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Table: 13Determinants of Work Life Balance and Family Commitments

Table: 14Spending Time for Working Outs



Working from 0 0 4 1 0 5home (0.0) (10.0)

Technology 5 0 3 2 5 5(10.0) (10.0)

Bring childern to 0 2 0 2 2 2work from collagus (4.0) (4.0)

Support from 28 12 28 10 40 38Colleagues (80.0) (76.0)

Support from family 2 1 0 0 3 0members (9.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Questions


Yes 12 9 14 10 21 24(42.0) (48.0)

No 23 6 21 5 29 26(58.0) (52.0)

Total 35 15 35 15 50 50(100) (100)


have expressed the same opinion. Working fromhome is not a influential factor in Andhra Bank,whereas support from family members in the caseof Indus Bank. Equal number of employees hasexpressed their opinions concerning technologyand being children to the work place on theoccasion. It may be noted that support fromcolleagues is the major determinant of work lifebalance and family commitments.

Hours spent for working outs are depicted intable 14.1. It is obvious that majority of theemployees did spend their time for working outsfor 30 minutes duration. It is clear that none of theemployees of both the banks did never spend theirworking out time more than 60 minutes. The restof the employees of the banks working time lie in

Table: 14.1Hours Spent for Working Outs

10



Less than 30 min. 3 0 4 1 3 5(14.3) (20.8)

30 min. 7 6 7 7 13 14(61.9) (58.4)

30 min- 60 min. 2 3 3 2 5 5(23.8) (20.8)

more than 60 min. 0 0 0 0 0 0(0.0) (0.0)

Total 12 9 14 10 21 24(100) (100)

Questions



Strongley agree 3 0 11 3 3 14(6.0) (28.0)

Agree 10 3 20 9 13 29(26.0) (58.0)

Indifferent 22 12 4 3 34 7(68.0) (14.0)

Disagree 0 0 0 0 0 0(0.0) (0.0)

Strongly 0 0 0 0 0 0Disagree (0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)

Questions

Table: 15Customization of Work Life Balance to Individual Needs


between less than 30 minutes and in the range of30 – 60 minutes. Majority of the employees ofboth the banks have expressed that the place forworking outs their time is residence. It may beconcluded that the employees of the banks didnot spent their time more than 60 minutes for theirworking outs. It is a welcoming future for turningout higher productivity.

Table 15 shows customization of work lifebalance to individual needs. It is evident thatmajority of the employees of Andhra Bank (68

per cent) are indifferent towards customization ofwork life balance to individual needs. About 58per cent of employees of Indus Bank have agreedthat the customization of work life balance isessential to individual needs, while about 26 percent of employees in the case of Andhra Bank.About 28 per cent of employees of Indus Bankhave strongly agreed with statement while ameager percent of employees (6.0 per cent) ofAndhra Bank. The opinions are not fall in the scaleof disagree and strongly disagree.

It may be observed that their exist obviousdistinction in the attitude of employees of publicsector bank and private sector bank with regard


Table 16 provides opinions on good work lifebalance. It is obvious that all the employees ofboth the banks have positive outlook that the goodwork life balance leads to efficacy of theorganization and thereby organizational success.

Concluding Remarks

Normal working days in a week usually aresix days. Both the private and public sector banksworking days are uniform. Higher cadreemployees have to work more than 10 hours dueto work pressure in both the sectors. Majority ofemployees of Andhra bank were married (92 percent) while (76 per cent) in the case of Indus Indbank. In between gender, male employees aremore in number of martial status in both the bankswhen compared to female employees. On thewhole, the responsibility of children is a usualpractice for parents and in-laws in the case ofwomen employees. Spouse takes the responsibilityin the case of men employees by and large. It isgratifying to note that cent percent of employeesin the case of Andhra bank and 95 per cent ofemployees in the case of private bank have abilityfor balancing work life. Moreover, it gives strongfeeling to the organization that they haveappointed right people and thereby a strength. Theemployees who have more interest in organizationdevelopment are thinking about work other thanworking hours. Majority of both male and femaleemployees of both the banks are feeling welltowards time spent at work. This is welcomingfuture for both the banks. Missing time is more

pronounced in the case of public sector bankwhen compared to private sector bank. Workpressure has no impact on employees’ feelings.Music is the main means for managing stressfollowed by Yoga/Meditation. Both the sectoralbanks have not tried to formulate a separate policyconcerning work life balance. Flexible startingtime, flexible ending time and job sharing areattractive provisions which promote good worklife balance. Support from colleagues is the majordeterminant of work life balance and familycommitments. The employees of the banks didnot spent their time more than 60 minutes for theirworking outs. It is a good sign for turning outhigher productivity. Their exist obviousdistinction in the attitude of employees of publicsector bank and private sector bank with regardto customization of work life balance to individualneeds. All the employees of both the banks havepositive outlook that the good work life balanceleads to efficacy of the organization and therebyorganizational success.

The banks shall formulate ideal policies foreffective work life balance. The abnormalworking hours shall be reduced so as to managethe stress due to work pressure. Health checkupplans shall be introduced so that the morale ofthe employees is improved in the case of privatesector banks. Customization of work life balancepolicy to individual needs is a pre requisite. Jobsharing and support from colleagues are keyfactors to good work life balance for success ofthe Indian banking sector.

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Yes 35 15 35 15 50 50(100.0) (100.0)

No 0 0 0 0 0 0(0.0) (0.0)

Total 35 15 35 15 50 50(100) (100)


Table: 16Opinions on Good Work Life Balance

to customization of work life balance to individualneeds.

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4. Sekaran U. (1992). Middle-class dual-earnerfamilies and their support systems in urban India,in S. Lewis, D. N. Izraeli, and H. Hootsmans (Eds.),Dual-earner families, International perspectives.pp. 46–61. Newbury Park, CA, Sage.

5. Thomas L.T. and Ganster D.C. (1995). Impact offamily-supportive work variables on work-familyconflict and strain: A control perspective. Journalof Applied Psychology, Vol.80, pp.6-15.

6. Kossek E. E. and Ozeki C. (1998). Work-familyconflict, policies, and the job-life satisfactionrelationship, A review and directions fororganisational behavior-human resources research.Journal of Applied Psychology, Vol.83, pp.139-149.

7. Sands J., and Harper T.L. (2007). Family-FriendlyBenefits and Organisational Performance. BusinessRenaissance Quarterly, Vol.2, pp.107-126.

8. Perry-Smith J.E. and Blum, T.C. (2000). Work-family human resource bundles and perceivedorganisational performance. Academy ofManagement Journal, Vol.43, pp.1107-1117.

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THE COMMITTEES’ REPORTS ON URBAN CO-OPERATIVEBANKS IN INDIA

K. Sudhakara RaoLecturer in Commerce

Sri A S N M Govt. Degree College, PalakolWest Godavari, Andhra Pradesh, India

Ph. 9849828840, E-mail: [email protected]

Abstract: The Indian financial system will grow not only in size but also in complexity as the forces of competitiongain further momentum and financial market acquire greater depth. The policy environment will remain supportiveof healthy growth and development with accent on more operational flexibility as well as greater prudential regulationand supervision. The real success of our financial sector reforms will however depend primarily on the organizationaleffectiveness of the banks, including urban cooperative banks (UCBs), for which initiatives will have to come fromthe banks themselves. The main objectives of UCBs were to meet the banking and credit requirements of the urbanmiddle/lower classes and to protect them from exploitation. The UCBs have been occupying a unique place in theIndian cooperative credit structure and ranked a very significant position in the Indian banking sector, which in therecent years has gone through a lot of turmoil, a series of failure and financial irregularities in Indian UCBs. Thispaper points to the significant role played by the reports of various committees appointed by the Central/Stategovernments or RBI for strengthening and growth of urban co-operative banks in India.

Key Words: Committees, Compendium of Instructions/Guidelines, Need, SAC.

1. Introduction

‘Co-operation’ as is understood today, as aneconomic system, was born as a peaceful reactionagainst the mercantile economy and industrialrevolution which had resulted in the concentrationof wealth, mass poverty and degradation, in aword ‘decay of men’. The ideas of the co-operative movement are basically the same allover the world, its form and content varied fromcountry to country. Co-operation took birth indifferent countries among people with differenteconomic interests and for performing differenteconomic functions. Everywhere, however, itoriginated as a defensive bulwark againstexploitation of the weak by those in a strongereconomic position. Basically, the co-operativemovement was started in India to ameliorate theconditions of the rural masses. However, it wassoon realized that co-operation offers a solutionto the difficulties encountered not only byagriculturists but also by the townsmen in respectof credit as well as other aspects of their businessand life.


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2. Need for Urban Co-operative Banks

The need for Urban Co-operative Banks(UCBs) arises from the fact that joint-stock banksare not interested in providing credit to the urbanmiddle classes. This is because it is notadvantageous for joint- stock banks in developingthe business of small loans on account of highcost of advancing and recovering them. As aresult, the man with limited means in urban areaswould be driven to money lenders or similaragencies to obtain loans at exorbitant rate ofinterest. Thus, the urban co-operative creditmovement started in India with the chief objectof catering to the banking and credit requirementsof the urban middle classes such as small traders,businessmen, the artisans, factory workers and thesalaried people with limited fixed income in urbanor semi-urban areas. Besides protecting the middleclasses and men of modest means from theclutches of the money-lenders the movement isalso expected to inculcate the habit of thrift andsavings amongst them. The movement hasprovided the frugal sections of the community anopportunity of investing their savings and thus hasenabled the hard-pressed people to tide over theperiod of stress and strain. In those days, all theurban credit societies including urban banks weredescribed as “non-agricultural credit societies”.

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Special encouragement was not given by thegovernment for the organization of non-agricultural credit societies. They were expectedto grow themselves without the assistance fromthe state. This has undermined the seriousness ofurban poverty and misery.

The Urban Co-operative Banks (UCBs) havebeen occupying a unique place in the co-operativecredit structure and are expected to assume theleadership in undertaking promotional anddevelopmental programmes for the growth andsuccess of the co-operative movement in urbanand semi-urban centers of India. Several studies –both individual and institutional – have beencarried out on co-operation in general and urbanco-operative banks in particular.

Select review of literature on urban co-operative movement in India has been attemptedin the following lines.

1. Reports of Committees constituted by theGovernment / Reserve Bank of India.

2. Proceedings of the meetings of StandingAdvisory Committee for UCBs conducted bythe RBI.

3. Compendium of Instructions/Guidelines forPrimary Co-operative Banks issued by RBIfrom time to time.

3. Reports of Committees of Government/RBI

3.1. Maclagan Committee

The first and foremost study with regard tourban co-operatives has been made by MaclaganCommittee (1915) on Co-operation. Thedevelopment of urban co-operative societies didnot receive much attention until 1915 when theMaclagan Committee referred to the potentialitiesfor the organization of such societies as a meansof training the upper and middle classes inordinary banking principles. The failure of localjoint-stock banks in the country at that time gavean impetus to the growth of urban co-operativecredit societies. It was felt by the Committee thaturban credit societies were eminently suitableinstitutional agencies for collecting local savingsand to provide relief to those who were in theclutches of money lenders by providing them withfinancial accommodation.

3.2. Central Banking Enquiry Committee

The Central Banking Enquiry Committee(1931) recommended that limited liability co-operative societies generally known as urbanbanks, should be established where necessaryfacilities and conditions exist, for the benefit oflower and middle classes of population. The UCBsare considered to be special societies meant forsalary earners and they are looked upon as thriftsocieties for collecting and investing the savingsof their members. It was envisaged that theseurban banks should be tried to do for the smalltraders, the small merchant and the middle-classpopulation what the commercial banks are doingfor the big trader and big merchant.

3.3. Mehta-Bhansali Committee

The Mehta-Bhansali Committee (1939) madean attempt to define an urban co-operative bank.In the beginning most of the urban banks in Indiawere organized as credit societies and laterconverted into urban banks. According to thisCommittee all urban credit societies having a paid-up share capital of Rs. 20,000 and above andaccepting deposits of money on current accountor otherwise subject to withdrawal by cheques,drafts or order came within the category of UCBs.However, in many provinces this term was usedfor credit societies working in urban areasirrespective of the size of share capital or the natureof deposits accepted by them.

In 1940 the Reserve Bank of India made areview on the co-operative movement in India andhas stated that urban co-operative credit societiesand banks occupy a prominent place among theagencies supplying the credit needs of the peopleresiding in urban areas. They advance loansmostly to small traders, artisans (mostly self–employed) and salary earners on personal securityas well as against gold, silver and produce.

3.4. Committee on Co-operation

A Committee on Co-operation (1940)appointed by the Government of Madras laidstrong emphasis organization of non-agriculturalsocieties in urban areas. The Committee viewedthat “the emphasis laid on rural credit did notprevent a recognition of the fact that the interestsof the small traders, artisans, shopkeepers,industrial employees and others in towns should

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The Committees’ Reports on Urban Co-operative Banks in India

be protected and facilities be provided for,granting reasonable credit to them”. TheCommittee also observed that an examination ofthe urban credit societies or banks shows that, inmany of the towns, there is more than one urbanbank or credit society functioning. This results inthe overlapping of their jurisdiction and anundesirable competition for securing deposits/business.

3.5. Co-operative Planning Committee

In January 1945 the Government of Indiaappointed a committee under the chairmanshipof Mr. R. G. Saraiya, to draw up a plan of co-operative development. Its report was submittedin November 1945. The Committee made adetailed study of the problems facing thecooperative movement in the country and itsrecommendations ranged over bothorganisational and administrative aspects. Itrecommended that urban banks should beorganized in all towns and should function onproper co-operative lines. It opined that urbanbanks should have at least Rs.20,000 as paid-upcapital, if they have to operate on sound lines.

3.6. All India Rural Credit Survey Committee

All India Rural Credit Survey Committee(1954), while identifying the reasons for the failureof the co-operative credit, made an attempt todiscuss the role of urban banks. The Committeepointed out that, in the matter of loans againstpledge of gold and agricultural produce, urbanbanks may be allowed to extend their share ofoperations to villages within a radius of five milesof the area of towns in which they are locatedprovided there are no primary agricultural creditsocieties in the villages concerned.

3.7. Report of the Survey on UCBs

The Report of the Survey on UCBs (1961)made many suggestions for the promotion anddevelopment of UCBs and the full utilization oftheir potentialities. The report also emphasized theneed for active support of the state governmentsin the development of UCBs by ensuring adequatearrangements for their audit, inspection andsupervision. The Report further observed that withthe growth of planning and increase in the tempoof economic development, steps had been taken

to promote the development of various types ofeconomic activities in the sphere of co-operation,much attention had been paid to the promotion ofagricultural co-operatives, industrial co-operativesand various other types of co-operative societies.A similar approach has, however, not been madewith regard to the non-agricultural credit co-operatives or UCBs.

3.8. Study Group on Credit Co-operatives inNon-Agricultural Sector

The Study Group on Credit Co-operatives inNon-Agricultural Sector, appointed by theGovernment of India under the chairmanship ofV.P. Varde in 1963 suggested certain norms. TheStudy Group recommended that a credit co-operative society registered under the State Co-operatives Act in urban or semi-urban areas havinga minimum paid-up share capital of Rs.50,000 andundertaking the provision of banking facilitiescould be termed as an ‘urban co-operative bank’and indicated that urban credit societies and banksare important features of urban co-operativemovement in India and make up to some extentfor the absence of joint-stock banking facilities inthe smallest towns. The Study Group observedthat Credit Co-operatives in the Non-agriculturalSector cover a wide field. These include UCBswhere deposits are withdrawal by cheques andcarry on normal banking functions, Employee’sCo-operative Credit Societies including FactoryWorkers’ Credit Societies which receive depositsfrom members and non-members and meet theserequirements of permanent or semi-permanentsalary earners in a particular organization andother types of Non-agricultural Credit Societiescatering to a particular profession, such as weavers,fishermen, etc., or a particular community orreligious group. Besides these there are aconsiderable number of Women’s Thrift andCredit Societies.

3.9. Working Group on Industrial Finance

The Working Group on Industrial Financethrough Co-operative Banks (1968) appointed bythe Reserve Bank, recognizing the key role ofurban banks in providing finance to cottage andsmall industries, recommended that high priorityto be given to the organization of such banks inareas where there was a sufficient concentrationof cottage and small scale industries carried on

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by individuals as well as by firms and joint-stockcompanies.

3.10. The Committee on Problems of UCBs

The Committee on Problems of UCBs inMaharashtra appointed by the government ofMaharashtra in 1976 under the chairmanship ofV.M. Joglekar focused on the promising role ofUCBs and felt that “UCBs are not just substitutelending agencies for private money lenders whoresort to usurious practices or for the commercialbanks which have been by and large inaccessible.They are better substitutes with a special characterand function. They have, from their veryobjectives, a more positive role to play. This roleimplies that UCBs have to inculcate the habit ofthrift and savings among persons with smallincomes by offering suitable facilities fordepositing their savings.”

3.11. Madhava Das Committee

The RBI appointed a Committee in 1978under the chairmanship of K. Madhava Das,Executive Director of RBI, to study the variousaspects of the working of UCBs in the country, toevaluate the role of primary (urban) co-operativebanks in the banking system and, to indicate theirfuture role, and in particular to assess whether anyadditional facilities or assistance were needed forthem. The report examined overall scenario ofUCBs in India, branch licensing policy of UCBsand the regular mechanism available to controland regulate their activities. It has alsorecommended policy measures, includinglicensing procedure, standards of viability andmeasures for rehabilitation of weak banks. TheCommittee observed that, while there is no changein the basic objectives of UCBs, i.e., promotionof thrift among members and non-members,provision of credit on reasonable terms to personsof limited means, and provision of bankingservices to customers, a new dimensions has beengiven to the operation of these institutions inrecent years with their recognition as appropriateagencies for financing cottage and small scaleindustries carried out by individuals as well asjoint-stock companies.

3.12. Basle Committee

The Basle Committee (1988) on BankingSupervision has underscored the following twin

fundamental objectives of the Basle accord. First,the framework should serve to strengthen thesoundness and stability of international bankingsystem and secondly the framework should be ahigh degree of consistency in its application tobanks in different countries with a view todiminishing the existing source of competitiveinequality among international banks. In thiscontext the Committee observed that the licensingauthority must have the right to set criteria andreject applications for establishment that do notmeet the standards set. The licensing process at aminimum should consist of an assessment of thebanking organizations, ownership, structure,directors and senior management, its operativeplan and internal control, and it’s projectedfinancial condition, including its capital base.

3.13. National Federation of UCBs and CreditSocieties Limited

As per the study made by National Federationof Urban Co-operative Banks and Credit SocietiesLimited (1989), the UCBs act as agencies for thedevelopmental activities in the urban and semi-urban areas just as their rural counterparts, theagricultural credit co-operatives, do so in the ruralareas. The better it would be for all concerned, assuch an arrangement would enable optimummobilization and utilization of the resources ofthese banks for the benefit of priority and weakersections in the urban and semi-urban areas. Thestudy has also suggested that co-operative banks,like central co-operative banks, should havefreedom to open branches within their area ofoperation based on their business needs. Naturally,the UCBs should be kept out of the branchlicensing policy devised for the nationalized/commercial banks. They are small institutions ofsmall people, established to serve their memberswho also own them.

3.14. Expert Committee (MaratheCommittee)

The Reserve Bank of India constituted inSeptember 1991 an Expert Committee under thechairmanship of Marathe on the policy relating tothe licensing of new UCBs and other relatedmatters. The report focused its attention onregistration and licensing of new UCBs, inclusionof primary (urban) co-operative credit societies

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in the list of UCBs, viability of UCBs, licensingof existing UCBs, area of operation, rehabilitationof weak banks, role of State Co-operative Banksand National/State Federations and otherinstitutions connected with UCBs. Essentially,Marathe Committee suggested to dispense with“one district-one bank” licensing policy andrecommended organization of banks based on theneed for an institution and potential for a bank tomobilize deposits and purveying of credit. It alsofelt that existence of commercial banking networkshould not prevent the co-operative initiative.

3.15. Financial System (NarasimhamCommittee, 1991)

The Committee on Financial System(Narasimham Committee, 1991) opined that inorder that the balance sheet of a bank reflects itsactual financial health, a proper system forrecognition of income, classification of assets andprovisioning for bad debts on a prudential basisis necessary. Accordingly, the Committee hasmade certain recommendations regarding theseprudential norms, which were implemented byRBI in respect of commercial banks, subsequentlyRBI considered that it is desirable to apply theseprudential norms also to UCBs with suitablemodifications. Accordingly, the RBI has codifiedthese norms applicable to UCBs and instructedUCBs to implement them in a phased mannerwithin a period of 3 years commencing from 18th

April, 1992.

3.16. The National Federation of UCBs andCredit Societies

The National Federation of Urban Co-operative Banks and Credit Societies (1993) hasmade several studies on the dimensions of growthand the problems of urban co-operatives. Themonograph, brought out in 1985 provided variousphases of UCBs in India and their historicalbackground. It also gave a detailed account oftheir licensing policy, rehabilitation of weak UCBs,the role of RBI in their development and the like.According to National Federation of UCBs andCredit Societies, the development of urbanbanking sector has emerged as a powerful andself reliant institutional agency playing aconstructive role in increasing production, andstrengthening infrastructure in the urban and semi-

urban areas.

3.17. Working Group on instillprofessionalism in the audit of UCBs

A Working Group appointed by RBI underthe chairmanship of Uday M. Chitale in December1995 reviewed the existing audit systems of UCBs.With a view to instill professionalism in the auditof UCBs, the Working Group suggested that auditof UCBs, with deposits of Rs.25 crores and above,be conducted by Chartered Accountants, thus,ending the monopoly of State Governments’ auditof UCBs. It suggested a standard format of auditfor all the states. The Working Group alsosuggested revised audit rating model for UCBs.Regrettably none of the states, not even the co-operatively advanced states, implemented therecommendations of Chitale Working Group.

3.18. Banking Sector Reforms (NarasimhamCommittee II, 1998)

The Committee on Banking Sector Reforms(Narasimham Committee II, 1998) has rightlypointed out that adequacy of capital hastraditionally been regarded as sign of bankingstrength irrespective of whether the institution isowned by Government or not. The Committeeunequivocally expressed its resentment over lowentry point norms for UCBs. It felt the currententry point norms, especially the capitalrequirements are much too liberal and RBI shouldurgently undertake a review of these norms andprescribe revised minimum capital norms for thesebanks. The Committee had also unequivocallyrecommended for ending dual control regimeover UCBs, and felt that dual command is thecausative factor for the UCBs and it is animpediment in effective supervision over them.

3.19. High Power Committee

The Reserve Bank of India appointed a HighPower Committee in May 1999 under thechairmanship of K. Madhava Rao, Ex-ChiefSecretary, and Government of Andhra Pradesh toreview the performance of UCBs and suggestnecessary measures to strengthen this sector. Theterms of references of this Committee are: (i) toevolve objective criteria to determine the need andpotential for organizing UCBs; (ii) to review theexisting entry point norms and examine the

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relevance of special dispensation for less/leastdeveloped areas etc.; (iii) to review the existingpolicy pertaining to branch licensing and area ofoperation of UCBs; (iv) to consider measures fordetermining the future setup of weak/unlicensedbanks; (v) to examine the feasibility of introducingcapital adequacy norms for UCBs; (vi) to examinethe need for conversion of co-operative creditsocieties into primary co-operative banks; and(vii) to suggest necessary legislative amendmentsto Banking Regulation Act and Co-operativeSocieties Act of various states for strengtheningthe urban banking movement. Keeping in viewthe recommendations of this High PowerCommittee, RBI issued directives and revisedguidelines regarding various aspects onorganisation and functioning of UCBs to put onsound footing.

3.20. Expert Committee (Andhra Pradesh)

Government of Andhra Pradesh appointed aExpert Committee (2002) to review thefunctioning of UCBs in the state under thechairmanship of K.Narasimha Murthy. Thesuggestions of the Committee including co-opting6-7 directors from among the shareholders, 3-5from among the depositors and three professionalsfrom the banking, finance, auditing and legalfields to the Boards of Banks, limiting the term ofeach director to a maximum of eight years insteadof an unlimited period, appointment of a qualifiedperson as a chief executive and cappingestablishment expenditure up to 10 per cent. Thepanel also recommended that Committees beformed for dealing with the procedure on auditing,giving loans and asset liability management andsuggested that no loans be given for real estatebusiness, stock market operations, and filmproduction. It also recommended payment of amaximum dividend of 25 per cent to theshareholders and also limiting the term of depositsto 10 years.

3.21. Working Group on IT support for UrbanCooperative Banks

The Reserve Bank constituted a WorkingGroup on December 19, 2007 under theChairmanship of Shri R.Gandhi, RegionalDirector, RBI, New Delhi. The working groupobserved that there is a wide variance among

Urban Cooperative Banks with regard to the usageof Information Technology, as on March 31,2007,16 out of 1853 banks had implemented CoreBanking Solution, with some of them evenoffering to set up/share data centers with smallerUCBs, while over 50 banks did not even havecomputers. The remaining banks existedsomewhere in between. Considering theconcentration of small UCBs, the lack ofuniformity in the levels of computerization andinadequate awareness about the efficacy ofcomputers in enhancing competitiveness, theGroup felt it necessary to articulate the minimumIT infrastructure which should exist in each UCBregardless of its size, location or profitability. Inorder to implement the minimum level of ITinfrastructure by the UCBs as indicated inRecommendation No 1, Core Banking Solution(CBS) would be required to be adopted by thebanks. If banks seek to go for outright purchaseof the Core Banking, including data centre, thecost would be in the range of Rs.1.5 crores to 2crores for 5-10 branches per bank.

3.22. The Expert Committee on Licensing ofNew Urban Co-operative Banks

The Reserve Bank of India constituted TheExpert Committee in Dec, 2010 on Licensing ofUrban Cooperative Banks under the Chairmanshipof Sri. Y.H, Malegam. The Committee submittedits report to the RBI in Aug, 2011 with manyobservations as well as very valuablerecommendations. Reserve Bank followed liberallicensing policy between May 1993 and March1999. However, many UCBs licensed during thisperiod became financially weak. In the AnnualPolicy Statement for 2004-05, RBI announcedlicensing discontinuance and entered in to MoUwith State Governments for co-ordination ofregulatory policies. Since then, there has beenconsiderable improvement in the functioning ofUCBs, only 57.6 per cent of existing UCBs canbe considered as financially sound, UCBs as aclass account for only 3.5 per cent of the depositsand only 2.9 per cent of the advances of thebanking sector, at present 88 UCBs have anegative net worth, The signing of MoUs betweenthe State Governments and RBI and the settingup of TAFCUBs has resulted in a significantimprovement in the health of the UCB sector.

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The Committee recommends the following entry point norms as regards minimum capital fornew UCBs.

It should be made a condition of the licensethat every new UCB should:

· have a Board of Management with theconstitution as specified;

· RBI should have the powers for regulationand control as specified;

· Every UCB should be audited by a CharteredAccountant to be appointed from a panelmaintained by RBI; and

· The Board of Management should follow aCode of Corporate Governance as specifiedby RBI.

4. Meeting of Standing Advisory Committeefor UCBs

The Reserve Bank constituted in 1983, aStanding Advisory Committee on Urban Co-operative Banks (UCBs) under the chairmanshipof its Deputy Governor in-charge of the UrbanBanks Division to advise the RBI on variousaspects pertaining to the UCBs such asorganizational matters, mobilization of resourcesand their deployment including the priority sectorlending, financing under the 20-Point EconomicProgramme, co-ordination with other institutionssuch as IDBI, DICGC, etc., modalities on therehabilitation of weak banks, introduction ofprofessional management, training and educationof personnel of the UCBs. The membership ofthe Standing Advisory Committee includes the

representatives of the Government of India(Ministries of Finance and Agriculture), NABARD,State Governments, Urban Banks Federation/Associations, urban banks and other co-operativeand commercial banks. The RBI has beenconducting meetings of the Standing AdvisoryCommittee (SAC) for UCBs annually.

5. Compendium of Instructions / GuidelinesIssued by RBI

Reserve Bank of India issues from time totime instructions / guidelines regarding, operationsand functioning of UCBs which are published inthe form of ‘Compendium of Instructions /Guidelines issued by RBI’. These compendiacontain seven / eight sections dealing withguidelines for operations of UCBs in the matterof banking regulations and returns; directives onadvances; directives on interest rates on deposits;planning and operations; inspections and licensingof existing PCBs; registration and licensing of newPCBs; and branch licensing of weak banks.

6. Conclusion

The urban co-operative banks were organizedin India at the turn of last century i.e., ten decadesago to cater the credit needs of urban middle class,and now they are occupying an important positionin banking system of India and have a vital roleto play in the attainment of national objectives asenvisaged in the Five Year Plans. Inspite of thefact that these banks have to face the competition

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Sr. No. Particulars Minimum Capital

1 UCB operating in only one state ini. North Eastern Statesii. In other States but confined to unbanked districtsiii. In other States but confined to C & D category population centres of banked districts 50 lakh

2 UCB operating in only one state with 50% or more branches in C & D categorypopulation centres 100 lakh

3 UCB operating in only one State but without requirement to have branches in‘C’ and ‘D’ category population centres. 300 lakh

4. UCB which wishes to operate in more than one state after five years ofsuccessful operation 500 lakh

from commercial banks, they have done well inmatter of expansion of their operations andrendering services. These banks have recorded asignificant growth in the recent past. From timeto time the government or RBI collectedinformation about the UCBs through the variouscommittee reports, these have paved way for thehealthy growth of UCBs bringing about theneeded financial discipline. RBI has fixed normsof viability for urban banks to reduce theincidence of sickness. Besides, prudential normsregarding income recognition, assetsclassification, provisioning and other relatedissues, as recommended by NarasimhamCommittee, have been made applicable to UCBsalso by the RBI. RBI is conducting annuallyStanding Advisory Committee (SAC) meetings forUCBs to review the progress and performance ofthese banks and also is issuing instructions,directives and guidelines in respect of differentmatter connected with organization andfunctioning of UCBs. National Federation ofUCBs, State Level Federations/ Associations ofUCBs are also playing a vital role in the healthypromotion and development of UCBs in thecountry. The State Level Co-operative ApexBanks and Registrars of Co-operatives of StateGovernments are also given directions by the RBIfrom time to time in the matter of UCBsdevelopment. Thus, these are no dearth ofagencies for development of UCBs. But the needof the hour is better co-ordination between RBI,State Governments and other agencies to placethe urban co-operative banking movement on asound footing.

References

1. RBI, Report of the Committee on Co-operation inIndia (Maclagan Committee) 1915, Bombay, 1957.

2. GOI, Report of the Central Banking EnquiryCommittee (1931), Vol.I, Part-1, New Delhi, 1931.

3. RBI, The Mehta-Bhansali Committee (1939),Bombay, 1939

4. RBI, Review on Co-operative Movement in India,1939-40, Bombay, 1940.

5. Government of Madras, The Report of theCommittee on Co-operation in Madras, 1939-40,Madras, 1940.

6. GOI, Report of the Committee on Co-operativePlanning, Bombay, 1945.

7. RBI, Report of All India Rural Credit SurveyCommittee (1954), Bombay, 1954.

8. RBI, Report on the Survey of UCBs, 1957-58,Bombay, 1961.

9. GOI, Report of the Study Group on Credit Co-operatives in the Non-Agricultural Sector (VardeCommittee), Ministry of Community Developmentand Cooperation, 1964.

10. RBI, Report of the Working Group on IndustrialFinance through Co-operative Banks, Bombay,1968.

11. Government of Maharashtra, Report of theCommittee on Problems of Urban Co-operativeBanks in Maharashtra, 1976.

12. RBI, Report of the Committee on Urban Co-operative Banks, (Madhava Das Committee),Bombay, 1979.

13. International Coverage of Capital Measurementand Capital Standards, BIS Publication, 1988.

14. National Federation of Urban Co-operative Banksand Credit Societies Limited, 5th All IndiaConference, Volume of Background Papers, NewDelhi, 1989.

15. RBI, Report of the Committee on Licensing of NewUrban Co-operative Banks (Marathe Committee),Bombay, 1992.

16. RBI, Report of the Committee on Financial System(Narasimham Committee-I), 1991.

17. National Federation of Urban Co-operative Banksand Credit Societies Limited, 6th All IndiaConference, New Delhi, 1993.

18. RBI, Report of the Working Group on Systems andProcedures of Audit in UCBs, 1996.

19. GOI, Report of the Committee on Banking SectorReforms (Narasimham Committee Report-II), 1998.

20. RBI, Report of the High Power Committee on UrbanCo-operative Banks, Mumbai, 1999.

21. Report of the Expert Committee to Review theFunctioning of Urban Co-operative Banks in A.P.,Hyderabad, 2002.

22. RBI, Proceedings and Agenda Notes of Standing

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Advisory Committee for Urban Co-operativeBanks, First Meeting to Twelth Meeting, Bombay,1983-1995.

23. RBI, Compendium of Instructions/GuidelinesIssued by RBI for Primary Co-operative Banks,Bombay, 1986, 1994, 1996 and 1997.

24. RBI, Compendium of Instructions/GuidelinesIssued by RBI for Primary Co-operative Banks,

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Bombay, 1997.

25. Campbell, W.K.H., Practical Co-operation in Asiaand Africa, Cambridge (England), W. Heffer, 1951.

26. Nakkiran, S.,Urban Co-operative Banking inIndia, Rainbow Publications, Coimbatore, 1982.

27. RBI, Report of the Expert Committee on Licensingof New Urban Co-Operative Banks, Mumbai, 2011.


ANALYSIS OF LEARNER PROFILE GENERATION ALGORITHMS

Rohini Nair K.J.SomaiyaUniversity of Mumbai University of Mumbai

K.J.Somaiya College of Engineering & K.J.Somaiya College of [email protected] [email protected]

Abstract: With the rapid growth of computer and Internet technologies, e-learning has become a major trend in thecomputer assisted teaching and learning fields. By observing how learners behave during their online self-study,educators are then capable of comparing, evaluating, and profiling individual learners’ learning processes and thusmaking suggestions to learners with similar characteristics in the same context.Learner profile generation can be achieved by various methods like sequential data mining algorithms wherecomputer logs are analyzed to profile learners in terms of their learning tactic use and motivation in a web-basedlearning environment. Basic steps involved are preprocessing, pattern discovery and pattern analysis- evaluation.Another approach is that of Fuzzy Cognitive Map (FCM) tool which is a soft computing tool and the reason, whichleads to FCM approach, is mainly the observation of uncertainty in learner’s profile description. Therefore, classesin any classification of learner’s profile are considered as fuzzy sets and are represented as vertices of a FuzzyCognitive Map. It is based on Kolb’s learning model which is widely accepted technique.A third approach is that of using genetic algorithm based on adaptive learning for fulfilling multiple constraints todetermine the learning scheme which best suits a learner. Adaptability can be provided at different levels accordingto the context of the learners. For constraint satisfaction problems in which multiple alternative paths have to beexplored, genetic algorithm based approach is best suited.Literature survey done on the above approaches shows that a lot of work is being carried out in the area of learnerprofile generation and understanding of the various approaches. In this report exhaustive study on various methodslike genetic based algorithms, adaptive learning based on Kolb’s learning cycle using FCM tool and sequentialpattern analysis is presented.General Terms : FCM(Fuzzy Cognitive Map),Kolb’s learning cycle

Key Words: Learner profile, adaptive learning, Kolb’s cycle, genetic algorithm, sequential mining, fuzzy sets


ISSN : 2230 - 9764

1. Introduction

Internet has become accessible for wideparties of contemporary societies and its rolecontinuously widens. One of the interestingusages of Internet is e-learning. E-learning systemhas become widely used in educational societybecause of its advantages on enabling learninganywhere and anytime. In e-learning, delivery oflearning contents should adapt to the pre-knowledge of the learner, learner’s pace oflearning, level of comprehension, etc. Selectionof appropriate learning contents and delivery ofthem to learners are challenging tasks of e-learning, because the learning content must beprovided to an acceptable level of the learner’sunderstanding. The sequential data miningalgorithms analyze computer logs to profile

learners in terms of their learning tactic andmotivation in a web-based learning environment.The data mining algorithms are employed todiscover patterns which characterize learnerseither across session or groups based on theirstudy tactic choice and goal orientation. With datamining techniques, instructors can first receive adetailed record of a learner’s behavior. Further, ifthey find similar groups of students, they canclassify them into one group which shows the maincharacteristics of the group, and it allows newstudents to be classified. Finally, the instructorscan discover if there is any relationship betweenthese characteristics and learners’ otherpsychological attributes. The learning diagnosisapproach uses mining association rule. The geneticapproach based on adaptive learning in whichmany learner context parameters considered foradaptive learning scheme generation as depictedin the newly proposed context structure. Theseparameter values are considered as constraints tobe fulfilled for learning scheme generation. In

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Analysis of Learner Profile Generation Algorithms

order to generate a customized learning schemefor a learner, all the context values of the learnershould be satisfied. For fulfilling multipleconstraints, many alternate learning schemesshould be generated and evaluated in order todetermine the learning scheme which best suits alearner. For constraint satisfaction problems inwhich multiple alternative paths have to beexplored, genetic algorithm based approach isbest suited. Hence, the learning scheme isgenerated using the genetic algorithm basedapproach. The next method of learner’s profileand style recognition is based on Fuzzy CognitiveMaps which is a soft computing methodology thathas been successfully used to model complexsystems and to support making decisions. Asystem designed to diagnose in the best possibleway the learner’s profile as it has been classifiedby the experts in the field, can be considered acomplex system FCM methodology.

2. Related Work

Data mining techniques can discover usefulinformation that can be used in formativeevaluation to assist educators establish apedagogical basis for decisions when designingor modifying an environment or teachingapproach. The application of data mining ineducational systems [1] is an iterative cycle ofhypothesis formation, testing, and refinement.Mined knowledge should enter the loop of thesystem and guide, facilitate and enhance learningas a whole. The discovered knowledge can beused not only by providers (educators) but alsoby own users (students).[2] So, the application ofdata mining in educational systems can be orientedto different actors with each particular point ofview. The approach based on sequential patternmining approach where the algorithms areemployed to discover patterns which characterizelearners either across session or groups based ontheir study tactic choice and goal orientation. Withdata mining techniques, instructors can firstreceive a detailed record of a learner’s behavior[3]. Further, if they find similar groups of students,they can classify them into one group whichshows the main characteristics of the group, andit allows new students to be classified. Finally, theinstructors can discover if there is any relationshipbetween these characteristics and learners’ otherpsychological attributes. To profile learners basedon their learning behavior, the studying actions

comprised of the events logged by the system areneeded for the learning pattern extraction. Thesteps[4] are: Preprocessing- The raw learning logsinvolve a complex series of low-level eventsspaced along a time dimension. Through a logparsing mechanism, it matches events in a learninglog to study actions predefined by the researcherand generates a sequence of temporally orderedlearner actions. The data pre-processing phaseincludes the data cleaning, user identification,session identification and data transformationrespectively. Next is the pattern discovery phaseinvolves the discovery of frequent sequences. Thepattern analysis phase involves the analysis of thefrequent patterns generated by the patterndiscovery phase.

The Fuzzy Cognitive Map (FCM)[7] tool inwhich the method of learner’s profile and stylerecognition is used to model complex systems andto support making decisions. A system designedto diagnose in the best possible way the learner’sprofile as it has been classified by the experts inthe field, can be considered a complex systemFCM methodology. According to learning stylemodel, introduced by Kolb, classification isaccording to what “we learn by conceiving andtransforming our experiences”. Also conceptionand elaboration of information are the twodimensions of learning process. As a matter ofinformation elaboration one has to choose amongReflective Observation or ActiveExperimentation. Such choices determine thelearning Style. According to Kolb’s model [8], thefour learning styles and the corresponding perlearning dimension choices are presented. Theused linguistic terms to indicate this amount ofpreference – tendency in a certain behavior orproperty are: very strong, strong , ordinary andweak which are considered as fuzzy variables.Kolb’s Experiential Learning Theory presents acycle of four elements: Concrete Experience,Reflective Observation, AbstractConceptualization, Active Experimentation .FuzzyCognitive Maps (FCM) is a soft computing toolwhich can be considered as a combination of fuzzylogic and neural networks techniques The 3 layersof an FCM [8] are: The inner layer is conformedby the four learner’s profiles according to Kolb’sclassification - Diverger, Assimilator, Converger,Accommodator. The middle layer is the layer ofbasic learner’s characteristics. Learner’sCharacteristics- (LC) Concrete Experience (CE),

23


Abstract Conceptualization (AC), ActiveExperimentation (AE), Reflective Observation(RO).The outer layer has the measurable learningactivity factors (LAF) which are subjects to bediagnosed by the machine. Learning ActivityFactors (LAF)-a set has been used, to the purposeof LS detection. The genetic algorithm based onparameter values which are considered asconstraints to be fulfilled for learning schemegeneration. For fulfilling multiple constraints,many alternate learning schemes should begenerated and evaluated in order to determine thelearning scheme which best suits a learner. Hence,the learning scheme is generated using the geneticalgorithm based approach.Context aware e-learning system [9] provides the learning contentsbased on the individual characteristics of thelearner, where context is referred as anyinformation that can be used to characterize thesituation of an entity where an entity can be aperson, place and a physical or computationalobject..For generating a learning scheme, threelevels of contexts of learner are to be considered.They are Content level, Presentation level andMedia level contexts. Fig 1 illustrates the contextstructure needed to be considered for generatingcontext-aware learning contents.

Content layer deals with learning pathgeneration. The individual learning pathgeneration is important because different learnersmay have different characteristics, priorknowledge or motivation or needs. The secondlevel, Presentation level mainly concentrates onthe learner’s preferences and intentions. For

Comment Level

Presentation Level

Media Level

Figure 1 Structure of learning context

example, a learner may prefer to learn a contentmaterial by Concept, Detailed Concept,

2.1 GSP Algorithm[4]-(Generalized SequentialPattern)

The algorithm used for sequence mining andfor solving sequence mining[5] problems aremostly based on the a priori (level-wise)algorithm. One way to use the level-wise paradigmis to first discover all the frequent items in a level-wise fashion. It means counting the occurrencesof all singleton elements in the database. Then,the transactions are filtered by removing the non-frequent items. At the end of this step, eachtransaction consists of only the frequent elementsit originally contained. This modified databasebecomes an input to the GSP algorithm. Thisprocess requires one pass over thewhole database.

GSP Algorithm makes multiple databasepasses. Given a set of frequent n-1 patterns, thecandidate set for next generation are generatedfrom input set according to the thresholds. Onlyfrequent patterns in the current set are consideredfor generating the next candidate sequence. Apruning phase eliminates subsets of infrequentpatterns. For all patterns P in the candidate set withlength k, all sessions are processed once and thecount is incremented for each detected pattern inthe candidate set. There are two main steps in thealgorithm.

Candidate Generation-Given the set offrequent (k-1)-frequent sequences F(k-1), thecandidates for the next pass are generated byjoining F(k-1) with itself. A pruning phaseeliminates any sequence, at least one of whosesubsequences is not frequent.

Support Counting-Normally, a hash tree–based search is employed for efficient supportcounting. Finally non-maximal frequentsequences are removed.GSP makes multiplepasses over the session set.

2.1.1 GSP Algorithm

F1 = the set of frequent 1-sequence k=2, dowhile F(k-1)!= Null;

Generate candidate sets Ck (set of candidatek-sequences);

For all input sequences s in the database D

do

24


Increment count of all a in Ck if s supports a

Fk = {a ª Ck such that its frequency exceedsthe threshold}

k= k+1;

Result = Set of all frequent sequences is theunion of all Fks

End do

End do

The GSP algorithm discovers frequentsequences, allowing for time constraints such asmaximum gap and minimum gap among thesequence elements

2.1.2 The GSP Algorithm Analysis

The GSP algorithm[6] includes two key steps:

1. Candidate Generation. Given the set offrequent (k-1)-frequent sequences F(k-1), thecandidates for the next pass are generatedby joining F(k-1) with itself. A pruning phaseeliminates any sequence, at least one ofwhose subsequences is not frequent.

2. Support Counting- Normally, a hash tree–based search is employed for efficientsupport counting. Finally non-maximalfrequent sequences are removed.

GSP (Generalized Sequential Pattern) hasdisadvantages because of the huge set ofcandidates could be generated, multiple scans ofdatabase in mining and the real challenge is mininglong sequential patterns.

1.1 Fuzzy Cognitive Map tool[7]

Fuzzy Cognitive Map is based on Kolb’slearning cycle. According to Kolb’s model[7], thefour learning styles and the corresponding perlearning dimension choices are presented at thefollowing table. Below are the basic factors thatcorrespond to learner’s behavior. The proposedfuzzy sets and their corresponding membershipfunctions are:

· Mw(weak cause) the fuzzy set for causalityaround 17.5 % with membership functionµwc.

· Mo(ordinary cause) the fuzzy set forcausality around 42.5 % with membershipfunction µoc.

· Ms(strong cause) the fuzzy set for causalityaround 57.5 % with membership functionµstrc.

· Mvs(very strong cause) the fuzzy set forcausality around 82.5 % with membershipfunction µesc.

2.2.1 Algorithm

Let N be the number of concepts in the FCM

1. Set the number k of learners

2. Set initial values n=0, V0(Ci) for i = 1, 2, , N

from the learner’s profile database. Data havebeen stored as the learner responded tocertain tests. Data have been stored aslinguistic values A

i , and have been turn to

fuzzy degrees V0(Ci) for all concepts except

those in LP.Concepts in LP are set equal to 0for n = 0.

Table 1Basic factors that correspond to learner’s

behaviors

Active x xExperimentation (AE)

Abstract x xConceptualization

(AC)Reflective x x

Observation (RO)Concrete x x

Experience(CE)

Div

erge

r

Ass

imil

ator

Con

verg

er

Acc

omm

odat

or

Figure 2 Kolb’s learning cycleConcrete

Experience

Accommodating Diverging

Active Experimentaion

Converging Assimilating

Reflective Observation

AbstractConceptualization

25


3. Set the initial values for wj,k

according togiven information.

4. For n=n+1, apply the relation (1) and setvalues Vn+1(C

i). Update learner’s profile

database. Following the defuzzification theweights at the edges of the graph arepresented as elements of the adjacent matrixW

n.

5. Set Vn+1=WnVn , where

a. If a Ci does not be influenced by any C

j,

j≠i then wj,i=1 at present n

b. If a Vn(Ci)= m [Vn(Cj)] -1, for a given

measure of competence 0<m<1, then setw

i,j= -m

6. Use the unipolar sigmoid functionf(X) = to transform the coordinates of V n+1

into the interval [0,1].

a. If max 0 < i < k

|V n+1(Ci)- Vn(C

i)| < ε, (ε >0)

then stop and store as result the learner’sprofile which has the highest value V

n+1(C

i)

Using the above membership functions wedefuzzify the fuzzy degrees[8] of LAF causalitiestowards Learning styles.

2.3 Genetic algorithm[9]

Genetic algorithm is based on context awareadaptive learning[9]. For generating a learningscheme, three levels of contexts of learner are tobe considered. There are many learner’sparameters considered for context aware e-learning system. These parameters are used forgenerating learning path. Learning path definesthe sequence of learning activities that is carriedout by the learner going through learning units ine-learning system.

1.3.1 Algorithm

Step 1: Definition of Chromosome String.

The chromosome string considered hereconsists of 3 types of genes, such as content levelgenes, presentation level genes and media levelgenes as shown in figure.

The content level genes are composed of IDsof learning objects which constitute the learningpath of a learner. The presentation level genesrepresent the order of presentation of learningobjects to the learner based on his learning

preference and intention. Each learning object canbe presented in six ways such as concept,example, case study, simulation, demonstrationand detailed concepts. The media level genesrepresent the media of learning object such asaudio, video or text.

Step 2: Initial Population- It is obtained bytaking permutation of each set of genes

Gene Representation

Step 3: Selecting the fitness function:

f= f(s) + f(p) + f(m) ,

where f(s)={effort taken for studying onelearning object with respect to other LO}*{difficulty of LO going to study}

f(p)= “{ Position of abstraction based onpsychology of Learner}*{ Position of each typeof LO in the randomly generated presentation}

f(m) Media level fitness

Step 4: Reproduction Operation.

In the reproduction operation, thechromosome with the larger fitness function valuewill have a higher probability to reproduce thenext generation. The aim of this operation is tochoose good chromosome to achieve the goal ofgene evaluation.

Step 5: Stop Criterion.

The genetic algorithm repeatedly runs thereproduction, cross over and mutation operationsuntil it converge at maximum fitness value.

1. [Start]Generate random population ofchromosomes.

2. [Fitness]Evaluate the fitness f(x) of eachchromosome f(x)=f(s)+f(p)+f(m) where f(s)is content level fitness ,f(p) is presentationlevel fitness, and f(m) is media level fitness.

3. [New population] Create new population byrepeating following steps until the newpopulation complete.

a. [Selection]Select two parent chromo-some from a population according to

ContentLevelGenes

PresentationLevel Genes

MediaLevel Genes

26


their fitness, the better fitness, the biggerchance to be selected.

b. [Cross over] Two point cross over theparents to form new children.

3. RESULTS

In the above subtopics various algorithmsfor analysis of learner profile generation havebeen studied in detail and this section shows thecomparison and results of the three algorithms.

GSP algorithm

Input …….Frequent Set k-1 (F[k-1])

Output……Candidate Set C[k]

Steps-

1. Join F[k-1] with F[k-1]

2. Get rid of infrequent sequences (prune)

3. Order of items matter F[3] = <{1, 2} {4}>, <{1, 2} {5}>,< {1} {4,5}>, < {1, 4} {6}>, < {2} {4, 5}>, < {2} {4}{6}>

After Join: <{1, 2} {4, 5}>, <{1, 2} { 4} {6}> After Prune: <{1, 2} {4, 5}> C[4]= <{1, 2} {4, 5}>Candidate set=< {Risk taking, emotionallyinvolved},{Collaborative learning, scientificapproach}>

Fuzzy cognitive map tool

Below are the fuzzy sets based on the LAFabove

Fuzzy Sets

Mw(weak cause)-17.5% ;Mo(ordinarycause)-42.5 %

Ms(strong cause)-57.5%; Mvs(very strongcause)-82.5 %

Below is a matrix of the LAF versus theweights.

Table 2 Learning Activity Factors withweights assigned

LAF Linguisticweight

1. Risk taking Very strong

2. Emotionally involved Very strong

3. Self directed learning Very strong

4. Collaborative learning Ordinary

5. Scientific/systematic Ordinaryapproach

6. Authority treatment Ordinary

Fig 3 Matrix of LAF v/s weights

<Risk taking, emotionally involved,Collaborative learning,

Scientific approach.>

Weights-.<Very Strong, Very strong,Ordinary, Ordinary>

Genetic algorithm

Chromosome-010101, Fitness Function-8+10+1=19

4. CONCLUSION

After analyzing the three approaches forlearner profile generation we can come to aconclusion that genetic algorithm is the bestamongst them because it has advantages like, anew three level structure for learner’s contextcomprising of the content level, presentation leveland media level is defined. The learning schemegeneration algorithm is designed to be geneticwhere various learner’s context parameter valuesare viewed as constraints to be fulfilled in thelearning scheme generation. Genetic algorithmsare best suitable for handling multiple constraintsatisfaction problems which have manyalternative solutions. Fuzzy logic and neuralnetwork based algorithm known as FCM (FuzzyCognitive Map) tool is also not very advantageousas there are deficiencies caused by thedependence on human experts and learner’sresponse.GSP (Generalized Sequential Pattern)

0.175 0.575 0.825 0.1750.825 0.175 0.425 0.5750.175 0.575 0.425 0.825

0 0 0.175 0.8250 0 .825 0.575 0.175

0.175 0.425 0.825 0.575

27


LAF 1 2 3 4 5 6

Chromosome 0 1 0 0 1 1

Weight 7 8 4 10 4 6

LAF 1 2 3 4 5 6


Weight 7 8 4 10 4 6

Chromosome -010011, FitnessFunction-4+8+6=18

Chromosome -110110, Fitness Function -7+8+10+4=29

LAF 1 2 3 4 5 6


Weight 7 8 4 10 4 6

Fitness values-.<1,2,4,5>

has given the worst result because a huge set ofcandidates could be generated ,multiple scans ofdatabase in mining. The real challenge is mininglong sequential patterns.

5. References

(1) Mingming Zhou,”Data Mining and Student e-Learning Profiles”, International Conference on E-Business and E-Government, 2010.

(2) Rajashree Shettar,” Sequential Pattern Mining FromWeb Log Data”, ISSN: 2250–3676 [IJESAT]INTERNATIONAL JOURNAL OF ENGINEERINGSCIENCE & ADVANCED TECHNOLOGY Volume-2, Issue-2, 204 – 208, Mar-Apr 2012.

(3) Philip H. Winne1, John C. Nesbit1, Vivek Kumar,Allyson F. Hadwin, Susanne P. Lajoie, RogerAzevedo, Nancy E. Perry,” Supporting Self-Regulated Learning with g Study Software: TheLearning Kit Project”, Tech., Inst., Cognition andLearning, Vol. 3, pp. 105-113, © 2006 Old City

Publishing, Inc.

(4) Chih-Ming Chen , Ying-Ling Hsieh, Shih-HsunHsu,” Mining learner profile utilizing associationrule for web-based learning diagnosis”, ExpertSystems with Applications 33,6–22, (2007)

(5) C. Romero, S. Ventura, Department of ComputerSciences, University of Cordoba, Cordoba, Spain,”Educational data mining: A survey from 1995 to2005", Expert Systems with Applications 33, 135–146, (2007).

(6) Murat Ali Bayýr, Ismail H. Toroslu, Ahmet Coþar,”A Performance Comparison of Pattern DiscoveryMethods on Web Log Data” p.445, Print ISBN: 1-4244-0211-5 Digital Object Identifier 10.1109/AICCSA.2006.205129,April 2006.

(7) Dimitrios A. Georgiou and Sotirios D. Botsios,”Learning Style Recognition: A Three Layers FuzzyCognitive Map Schema”, Fuzzy Systems, 2008.FUZZ-IEEE 2008. (IEEE World Congress onComputational Intelligence). IEEE InternationalConference, pages 2202 – 2207, 2007 Date ofConference: 1-6 June 2008

(8) Demetrius A. Georgiou, Despina Makry,” ALearner’s Style and Profile Recognition via FuzzyCognitive Map”, Proceedings of the IEEEInternational Conference on Advanced LearningTechnologies (ICALT’04) 0-7695-2181-9/04$20.00 © 2004 IEEE.

(9) Manju Bhaskar, Minu M Das, Dr.Chitralekha,Dr.S.Sivasatya,” Genetic algorithm based adaptivelearning scheme generation for context aware e-learning “,(IJSCE),International Journal onComputer Science and Engineering , Vol.02,No.4,1271-1279, 2010.

(10) Xu Wei1, Jun Yan,” Learner Profile Design forPersonalized E-learning Systems”, 978-1-4244-4507-3/09/$25.00 ©2009

(11) Riadh Hadj M’tir,Béatrice Rumpler,” LearnersExperiences Reuse to Improve Personalized E-Learning”, Dans IEEE ICTTA’08, Damascu,Syria,2008

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EXPLORING THE EFFECTS OF CONSUMER KNOWLEDGE AND FITPERCEPTION IN BRAND EXTENSION SUCCESS

Soumi Paul1 and Saroj Kumar Datta2

1Mody Institute of Technology and ScienceE-mail: [email protected]

2VIT Business SchoolE-mail: [email protected]

Abstract: The paper examines the impact of consumer knowledge and consumer fit perception that may enhancebrand extension success: at brand category and brand image level. The findings reveal that, in evaluating brandextensions, consumers use not only knowledge about the brand category-level similarity between the extension andthe products already associated with the brand, but also the image uniformity between the brand and the extension.Very favorable reactions occur when brand extensions are made with high brand concept consistency and highproduct feature similarity for both category-oriented and image-oriented brand names. The results also validate theeffect of consumer knowledge on fit perception at category level and brand image level. Marketers need to be awareof whether the parent brand is mainly known for its brand category or image across its all product areas. Anextension of an image oriented brand should be Promoted and positioned with more brand-related knowledgewhereas the promotion of a category related brand extension may include more category related knowledge. Thisparticular study is expected to contribute to the brand extension literature by studying this particular aspect andwill help marketers for promotional and marketing differentiation in case of positioning an extension.

Key Words: brand extension, consumer knowledge, fit perception


ISSN : 2230 - 9764

Introduction

Brand extensions – that is use of establishedbrand names to launch new products (Ex. Use ofthe name of Apple for music system) has becomea very popular new product launch strategy. Thejustification behind brand extension is simple:when a strong brand has been established, thebrand has moved beyond the functional productinto a realm of values. It makes economic senseto try to deliver the same emotional benefits in adifferent market (Mortimer, 2003). Many newproducts generally fail, every year the mostsuccessful ones tend to be brand extensions(Aaker 1991). This strategy is more successfulthan building a new brand name for new productintroductions (Zhang & Sood, 2002). This so-called pioneering advantage is expected to besustainable over time (Carpenter and Nakamoto1989; Kardes et al. 1993; Robinson and Fornell1985). But the process is not as easy as it seems.Consumers’ knowledge plays an important rolein understanding consumer behavior. Knowledge

mainly determines whether there is a trueunderstanding of what a brand stands for. Positiveand accurate understanding of the brand amongsttarget consumers results in high association withthe brand at category or image level. However, itis not enough for a brand to tell consumers whattheir brand means, but the understanding shouldhelp in bridging consumers fit perception.Similarity fit is considered to know how far theconsumer perceives the extended product categoryis similar to the parent product (Smith and Park,1992) or parent brand. It is typically believed thatconsumers have to perceive a consistent approachbetween the original brand and the extension atbrand category level or image level, so that thenew addition could explore, enlarge and enhancethe brand meaning, image and recognition in aprospects mind. In brand extension research thereis hardly any variable rather than fit given so muchattention because of its weightage in the pastliterature. Perceived similarity is found to be themost relevant variable that can highly influencethe acceptance of brand extension (VÖlckner &Settler 2006). In many researches perceived fit isalways found to be a single construct. About fitdefinition, everyone can come up with his or herown typical association. The fit is actually boththe dimensions on different perspective and the

29


whole as a complete construct of the perceiveddimensions. The positive influence of fit alsooccurs both in studies considering fit globally(Gutie´rrez and Rodrý´guez, 1994; Martý´nez andPina, 2005) or focused on the dimensions ofcategory and image fit (Boush et al., 1987; Boushand Loken, 1991; Park et al., 1991; de Magalhaesand Varela, 1997; Seltene, 2004). Consumerknowledge has also been suggested as one of thevariables that have an impact on consumer fitperceptions in a brand extension evaluation(Broniarczyk and Alba 1994). Consumers’knowledge at brand category and image level mayenhance consumers fit perception and brandextension success in the context of introducingan extension with brand category or imageconsistency.

In order to assist marketing practitioners inthis ever-changing business environment, formaking more successful brand extension decisionsand judgments, several researches are alreadyfocused on brand extensions from differentaspects. This particular study explores the role ofdifferent consumer knowledge that enhancesconsumers’ different fit perceptions and brandextension evaluations, and is expected tocontribute to the brand extension literature bystudying this particular aspect and will helpmarketers for promotional and marketingdifferentiation in case of positioning an extension.

Literature Framework and Construction ofHypotheses

Brand extension definition

The terminology of brand extension has beenused inconsistently in the literature (Ambler &Styles, 1997; Grime et al., 2002). Aaker and Keller(1990) refer to “extension” as the general termfor both line and brand extensions. A Lineextension applies an existing brand name to aproduct in one of the firm’s existing categories(ex. Ponds cold cream and Ponds fairness cream).Whereas brand extension strategy consists ofusing an established brand name to launch newproducts (Keller, 2007). The study adopts, brandextensions which are introduced in a differentcategory from the existing business (DePelsmacker et al., 2007). Now-a-days marketersare more likely to obtain the recognition of the

brand name and the loyalty of those consumerswho are already loyal to the parent brand (Aaker,1991; Keller, 1993; Hutton, 1997). Loyalconsumers have already a prior association andknowledge about the brand or the brand productcategories that make them enable to perceive asimilarity between the extension and the parentbrand or brand category. Brands enable consumersto efficiently encode their functional andemotional values in their minds (Franzen andBouwman, 2001).

Consumer knowledge and brand extensionevaluation

Prior knowledge is the information storedwithin memory. This variable is considered animportant variable influencing consumerbehavior. The individual’s knowledge of the brand(Klink and Smith, 2001) can affect reactiontowards extensions. Mostly Consumer knowledgehas been treated as one single variable in previousresearch. However, two different elements ofconsumer knowledge, product knowledge andbrand knowledge have different effects oninformation search behavior and brandevaluations (Bei and Heslin 1997; Fiske etal.1994). ‘Product knowledge’ refers toinformation about product categories, either themost general category, or subcategories stored ina consumer’s memory, where as ‘brandknowledge’ refers to consumer knowledge abouta brand, including brand name, attributes,benefits, concepts, images, and everything thatis associated with the brand (Peter and Olson2005). Muthukrishnan and Weitz (1991) examinethe influence of product knowledge, whereasBroniarczyk and Alba (1994) research the impactof brand knowledge. There have been calls formore studies of consumer knowledge effects inbrand extension evaluations (Czellar, 2003;Grime, Diamantopoulos, & Smith, 2002). Thusthe purpose of this study is to further examinethe roll of two types of consumer knowledge inbrand extension evaluations. Thus, wehypothesize that,

H1: Consumers’ category knowledge will havea significant positive influence onevaluations of category fit related brandextensions.

30

Exploring the effects of Consumer knowledge and fit Perception in Brand extension success

H2: Consumers’ brand knowledge will have asignificant positive influence on evaluationsof brand image fit related brand extensions.

Consumers’ perception of fit and brandextension evaluation

One of the widely accepted findings fromearlier brand extension research is that aperception of fit between the extension and theparent brand and it is found to be the most relevantvariable that can highly influence the acceptanceof brand extension (VÖlckner & sattler 2006).The dimensions of the consumer perceived fitconcerns on one hand the brand “productcategory” and on the other hand the brand“image”. The study proposes to obtain the effectof fit Consumers have to perceive some dimensionof similarity between parent brand and theextension (Boush et al. 1987; Aaker & Keller1990; VÖlckner & Sattler 2006; Ahluwalia 2008).Two general dimensions can be indentifiedunderlying the concept of perceived fit: productcategory fit and brand image fit (Bhat and Reddy,2001; Grime et al., 2002; Czellar, 2003). Thus,individuals can believe that the new product isphysically similar to the other products of thebrand (category fit) or coherent with the generalbrand associations (image fit) (Grime et al., 2002;Czellar, 2003), they are more likely to have apositive attitude towards the extension. Thus, wehypothesize that,

H3: Consumers’ perception of fit at category levelwill have a significant positive influence onevaluations of category fit related brandextensions.

H4: Consumers’ perception of fit at brand levelwill have a significant positive influence onevaluations of brand image fit related brandextensions.

Consumer knowledge impact on fit perception

At the product category level the knowledgeincludes information regarding technology, usage,components used in the manufacturing process.At the brand level the knowledge includes mainlyimage or any unique association that is associatedwith the brand. Especially in brand evaluation, itwas found that consumers who choose brands thatgive more value for the price are knowledgeableabout the product category, whereas those whochoose famous and more expensive brandsconsider the consistency between the brandimages and their personalities, egos, or interestsmore than the functional aspects of products (Beiand Heslin 1997). Thus we hypothesize that,

H5: Brand knowledge has a stronger positiveeffect on brand level fit perception.

H6: Category knowledge has a stronger positiveeffect on category level fit perception.

Fig. 1

Proposed Model of the Study

31


Objectives of the Study

This study attempts to contribute to the brand extension literature by exploring the effects of thecategory knowledge and brand knowledge, brand category fit and brand image fit separately in theconsumers brand extension evaluation process.

It is expected to provide a deeper understanding of whether and how different kinds of consumerknowledge affect the consumers’ different fit perception between a new extension and its parentbrand.

Questionnaire development and main datacollection

Target Respondents: A student sample wasused as it is convenient to obtain and the respondrate are usually high. The research sampleconsisted of 258 respondents, all havingpreferences for using branded products. We havemade a questionnaire for each of the two parentbrands and conducted the study in jaipur.Questionnaire was distributed among businessstudents in the various places of Jaipur. For Titanbracelet 168 and Apple music system 136questionnaires were collected, 16 had to beremoved due to non-response biases. Two fiftyeight complete questionnaires were collected forTitan bracelet and Apple music system.

Measurement and Scaling

Dependent variable – Overall evaluation of

brand extension simply to measure the reactionstowards the proposed brand extension measuredbased on the items used by Bergkvist and rossiter(2007).

Independent variable – Perceived similarityat category and brand level evaluated on a fivepoint likert scale anchored from “not at all similar”through to “very similar “.

Consumer knowledge at category and brandlevel evaluated on five point likert scale with theends “totally disagree” and “totally agree”. Itconsists of two major components: familiarity andexpertise (Alba & Hutchinson 1987).

Analyses

Responses were analyzed using SPSSsoftware and showed a Cronbach’s higher than0.7. It shows that questionnaire is reliable. Resultsare shown in table 2.

Parent Brands TITAN WATCH APPLE COMPUTER(brand category fit extension) (brand image fit extension)

EXTENSIONS Bracelet Music system

Table: 1Selected Brands and Their Extensions

Table 2

Average Cronbach Alpha Value for the Items

Regression analysis for the individual sample

Multiple Regression analysis was employed to test the proposed hypotheses. The model will betested in different phases. First, it will test the impact of different consumer knowledge and fit perceptionon brand extension success considering two extensions separately. Again, we will test the impact ofconsumer knowledge at brand level and category level on consumer fit perception at brand and categorylevel. Two regression models were developed to test the proposed hypotheses.

Dependent variable – overall attitude towards category related brand extension - Titan bracelet

Cronbach’s alpha N of item

.702 5

32


Independent variables (Beta coefficient) t value Significance

Brand Category knowledge .297 3.963 .000

Brand image knowledge .144 1.917 .057

Table 3

Regression Model Tested the Impact of Brand Category and Brand Image Knowledge onConsumer Attitude Towards Brand Extension Evaluation (Titan)

R square value = .107

Table 4

Regression Model Tested the Impact of Brand Category and Brand Image Knowledge onConsumer Attitude towards Brand Extension Evaluation (Apple)

Dependent variable – overall attitude towards image related brand extension – Apple Music System.


Table 3 & 4: Regression model tested the impact of brand category and brand image knowledgeon consumer attitude towards brand extension evaluation

Table 5

Regression Model Tested the Impact of Consumer Perception of Fit at Category or Brand Levelon Consumer Attitude Towards Brand Extension Evaluation (Titan)

Table 6

Regression Model Tested the Impact of Consumer Perception of Fit at Category or Brand Levelon Consumer Attitude Towards Brand Extension Evaluation (Apple)










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Dependent variable – overall attitude towards category related brand extension - Titan bracelet Rsquare value =. 344.

Dependent variable – overall attitude towards category related brand extension – Apple MusicSystem.

R square value =. 342

Table 5 & 6: Regression model tested the impact of consumer perception of fit at category orbrand level on consumer attitude towards brand extension evaluation

Regression analysis for the entire sample

Table 7

Regression Model Tested the Impact of Brand Category and Brand Image Knowledge onConsumer Fit Perceptions in Brand Extension Evaluation at Category Level (Titan).

Dependent variable – consumer fit perception of Titan bracelet


Table 7: Regression model tested the impact of brand category and brand image knowledge onconsumer fit perceptions in brand extension evaluation at category level.

Table 8

The Forth Regression Model Tested the Impact of Brand Category and Brand ImageKnowledge on Consumers Fit Perception in Brand Extension Evaluation at Brand Image

Level (Apple).

Table 8: The forth regression model tested the impact of brand category and brand imageknowledge on consumers fit perception in brand extension evaluation at brand image level.

Dependent variable – consumer fit perception of Apple music system


Findings and Discussions







As per the analysis, the findings reveal that,in evaluating brand extensions, consumers usebrand category knowledge when the extensionseems to be more category related (H1) and brandimage knowledge when they found imageuniformity between the brand and the extension

(H2). So, different effects of category knowledgeand of brand image knowledge were found in thisstudy. Very favorable reactions occur when brandextensions are made with high brand conceptconsistency and high product feature similarity forboth category-oriented and image-oriented brand

34


names (H3 & H4). The results also validate theeffect of consumer knowledge on fit perceptionat category level and brand image level. Two ofthe hypotheses about the positive effect ofconsumer brand knowledge and categoryknowledge on brand image and category fitperception were supported (H5 & H6). Theseresults provided some valuable insights forunderstanding the role of consumer knowledgein consumer fit perception and brand extensionevaluations. The findings suggest that categoryknowledge and brand knowledge have differenteffects in brand extension evaluations. For a brandimage similar extension, the higher the brandknowledge higher the consumer brand image fitperceptions between the parent brand andextended product and when it is brand categoryrelated extension, category knowledge has thehigher impact on category fit perception.

Implications and Future Scope of the Study

The main strength of this area of study is thatbrand category and brand image knowledge;consumers fit perception at category and brandlevels are treated separately, in brand extensionevaluation. This particular study supports thefindings from previous research that suggests thatconsumer knowledge has an impact on consumerfit perceptions in the context of brand extensionevaluations (Muthu Krishnan & Weitz, 1991). Thisstudy confirms that both kind of consumerknowledge have positive and significant effect onconsumer fit perception both at category level andbrand level. This is expected the result of this studyto provide more empirical evidences for the roleof consumer knowledge on consumer fitperception and in brand extension at brandcategory and image level. A consumer with highbrand knowledge tends to perceive higher brandimage fit when the extension is consistent withbrand image and perceive higher brand categoryfit when the extension is consistent with brand’smost common or known category.

In the literature of consumer brand extensionevaluations limited studies have investigated theeffects of brand category and brand imageknowledge separately. This has led to someconfusion in the consumer brand extensionevaluation literature – whether these two variables

both effect consumers fit perception or only oneof them, and whether they have equal influencesor not (Grime et al., 2002). Thus, this studyattempts to clarify the confusion in the literaturethat they have different effect and it depends onextension type whether it is image related orcategory related. Furthermore, findings of thisstudy may also have implications for marketingpractice in the areas of branding, promotion, andpositioning of brand extensions. A firm could usedifferent marketing strategies to promote andposition their extensions. An extension of animage oriented brand should be promoted andpositioned with more brand-related informationwhereas the promotion of a category related brandextension may include more most common andknown category information.

This research may encourage further studyin consumer brand extension evaluationsconsidering this particular aspect in differentindustry and location. This particular studyconsiders direct relationship between consumerknowledge and fit perception but researchers mayexamine their relationships in other respects inbrand extension evaluation.

References:

1. Alba, J.W. and Hutchinson, J.W. (1987).Dimensionsof consumer expertise. Journal of consumerresearch, 13 (4), 411-454.

2. Buil, Isabel, Leslie de Chernatony, & Leif E. Hem.(2009). Brand extension Strategies: Perceived fit,Brand type, and culture influences. EuropeanJournal of Marketing, 43(11/12).

3. Dens, Nathalie, De Pelsmacker, Patrick. (2010).“Attitudes toward the extension and parent brandin response to extension advertising “. Journal ofbusiness research , volume 63 issue 11 ,pp.1237-1244.

4. Glynn, M.S. & Brodie, R.J. (1998). The importanceof brand-specific associations in brand extension:further empirical results. Journal of Product &Brand Management, 7(6), 509-518.

5. Hem, Leif E & Iversen, Nina M. (2009). Effects ofdifferent types of perceived similarity andsubjective knowledge in evaluations of brandextensions. International Journal of MarketResearch. 51(6), 797 – 815.

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6. Hsiang-Ming Lee, Ching-Chi Lee, Cou-Chen Wu .(2011) .Brand image strategy affects brand equityafter M&A. European Journal of Marketing, 45(7/8), 1091 – 1111.

7. Ian Grime, Adamantios Diamantopoulos, GarethSmith. (2002) .Consumer evaluations of extensionsand their effects on the core brand: Key issues andresearch propositions. European Journal ofMarketing, 36(11/12), 1415 – 1438.

8. Keller, K.L. (2007). Strategic Brand Management:Building, Measuring, and Managing BrandEquity.3rd ed., Prentice-Hall, New York, NY.

9. Leon P. (2004). Consumer Evaluations of BrandExtensions: Can B2B Brands be extended into theconsumer market. Maastricht University, Facultyof Economics and business administration, masterthesis, International management studies,Retrieved 30.09.2012 from http://www.brandchanne l . com/ images /Papers /206_BtoB_brandextensions.pdf.

10. Ma, Y., (2005). The Role of Consumer Knowledgein Consumer Evaluation of Brand Extension,

11. M.S. thesis, Auckland University of Technology,New Zealand.

12. Martínez, E. & Pina M. J. (2010) .Consumerresponses to brand extensions a comprehensivemodel. European Journal of Marketing. 44 (7/8),pp.1182 – 1205.

13. Oakley, James L, Balachander, S. , Sriram S. (2005)“Understanding the Simultaneous Effects ofCategory Fit and Order of Entry on ConsumerPerceptions of Brand Extensions “ extended

abstract, Advances in Consumer Research Volume32 .

14. Park, D.H. & Kim, S. (2008). The effects of consumerknowledge on message processing of electronicword-of-mouth via online consumer reviews.Electronic Commerce Research and Applications,7(4), 399.

15. Pina M. J., Martinez E., de Chernatony L., Drury S.(2006).The effect of service brand extensions oncorporate image: An empirical model. EuropeanJournal of Marketing, 40 (1/2), 174 – 197.

16. S Lipps . (2009).The reciprocal effect of luxurybrand extensions on perceived brand luxury andon parent brand attitude Repercussions of thecurrent trend of ‚Cheap Chic. Master Thesis.Retrieved on 12.08.2012 from arno.unimaas.nl .

17. Shah, Reshma H. & Mittal B. (1997) .Toward aTheory of Intergenerational Influence in ConsumerBehavior: An Exploratory Essay. Advances inConsumer Research, 24, 55-60.

18. Thamaraiselvan N. Raja J. (2008). How doconsumers evaluate brand extensions – researchfindings from India. Journal of Services Research,8(1), pages 43 – 62.

19. Völckner, F. & Sattler, H. (2006). Drivers of BrandExtension Success. Journal of Marketing, 70(2),18-34.

20. Zhang, S. and Sood, S. (2002), “”Deep” and“surface” cues: Brand extension evaluations bychildren and adults”, Journal of ConsumerResearch, 29(1), pp. 129–41.

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Authors note:

Correspondence concerning the paper should be addressed to Soumi Paul ,Research Scholar,Faculty of Management Studies ,Mody Institute of Technology and Science (Deemed University u/s3 of the UGC Act, 1956) ,Lakshmangarh-332311, Rajasthan ,India Mobile: +918820040086, E-mail: [email protected].

Prof. (Dr.) SarojKumarDatta ,Director , VIT Business School, VIT University,(DeemedUniversity u/s 3 of the UGC Act, 1956), Vellore – 632014, Tamil Nadu,India,Phone: 0416 - 220 2707 / 2245567, E-mail: [email protected]


DEMOGRAPHIC ANALYSIS OF PATIENT SATISFACTION IN MAJORHEALTHCARE CENTRES

Silky Vigg Kushwah1, Pushpa Negi2 and Ashok Sharma3

1Associate Professor,Jagannath International Management School, New Delhi

2Associate Professor,Symbiosis Institute of Management, New Delhi.

3Assistant Professor,Jagannath International Management School, New Delhi

Abstract: Healthcare industry today, is a rapidly growing industry. According to Mckinsy & Co. healthcare spendingin India will double over next ten years. Its progress has been splendid and is targeting more and more customers.Both public and private hospitals form a significant part of the healthcare industry along with pharmaceuticals andother applied sciences. There are many people in the country who live below poverty line and are even devoid ofbasic healthcare facilities. The rest of the population excluding the upper class is in a dilemma whether to fall a preyto expensive private hospitals or succumb to mediocre facilities of government hospitals. The study aims at throwinglight on the satisfaction levels of patients visiting these healthcare centres in N.C.R. The study considers four majorplayers in the market providing healthcare facilities in the National Capital Region (N.C.R.) and used primary datato fulfil the objectives. Few hypotheses have been formed and tested by using tests like ‘z’ test and ‘t’ test. The studyrevealed that there is no significant difference in the satisfaction levels of patients falling in different age-groupsand of different occupations and gender, whereas the difference in satisfaction levels of the patients was noted whentests were conducted on the basis of hospitals i.e. public and private hospitals. The findings of the study will not onlyhelp the hospitals to improve their services but will also help the future patients to understand what importantservices to be expected from a hospital and help them in selecting the appropriate hospitals.

Key Words: Service Quality, Patient Satisfaction, Health care centres.


ISSN : 2230 - 9764

Introduction

Today, in the service sector, the stand of anorganisation in the market can be determined bythe service it provides, the quality of its serviceand the satisfaction of the customers availingthose services. It cannot be denied that thequantitative parameters such as balance sheets,cash flow statements, ratios, P&LA/c etc. areimportant to assess an organisation but qualitativeanalysis along, gives a complete picture. Ratherit helps organisations to prepare for their futurein a better way and devise policies. Thus it isimperative to find out answers to questions like;what do we mean by ‘service’? What is ‘qualityof service’? What is the nature of ‘customersatisfaction’? Service and quality of service areinter-related concepts which are ultimately usedto maximize customer satisfaction. The project

undertaken intends to throw light on patientsatisfaction levels in four major hospitals in N.C.R.So it is important to understand these concepts incontext of the hospitals before we march towardsthe core of the project.

Service Quality

Service quality is the degree and the directionof discrepancy between consumer’s perceptionand the exceptions in the term of different butrelatively important dimension of the servicequality which can affect their future behaviour.(Parsasuraman, Zeithamal and Berry, 1985)

Quality of service has been studied in thearea of business management for the yearsbecause the market is more competitive and themarketing management has transferred its focusfrom internal performance such a production toan external interest such as customer satisfactionand customer’s perception of service quality.(Gronroos, 1992)

Quality has been defined in various ways byquality guru’s like Juran, Deming, Crosby. Crospy

37


holds that conformance to requirement is quality.The essence of this definition as applicable tohospitals, quality may be defined as the ability tosatisfy the patients’/customers’ requirements andneeds to the fullest and be able to replicate this onan on-going basis.

Nature of Patient Satisfaction

People who visit hospitals come from varyingsocio-economic and cultural backgrounds.Satisfaction from services provided will differfrom person to person and even for the sameperson at different points of time, depending onthe mood and mid-set of the same user at aparticular point of time. Unlike in the case ofmanufacturing companies where the goods aremanufactured and then sold to customers, inhospitals a patient is a part and parcel of the processthat provides the services. The service is createdwith the involvement of the patient, if there is nopatient there can be no service .Thus it should beunderstood that all improvement at a hospital musthave its patients as the focal point and as suchpatient satisfaction is a good determinant of thequality of services provided by a hospital. It isimportant for long-term quality development andimprovement.

A survey suggested that private healthcarewill form a large chunk of spending rising from$14 billion to $33 billion in India by 2012. Thisfigure could rise by an additional $8 billion ifhealth insurance cover is available to the rich andthe middle class, according to McKinsey & Co.Since every coin has two sides, the facts statedabove are encouraging but not enlightening.

Review of Literature

Patient satisfaction is one of the majorparameters or the parameter that determines thesuccess of the hospital concerned. However, inthis world of cut-throat competition, it is verydifficult to maximize satisfaction levels. Researchand surveys are important tools acting aslighthouses which help in guiding theorganisations to achieve the desired results or givethem direction. Many research and surveys havebeen carried out to determine patient satisfactionin different hospitals to improve the quality ofservices provided. Some have given enlighteningfindings and solutions.

Laurent et al., (2006), the aim of this studywas to assess clinical staff’s on the results of in-patient satisfaction surveys and use within thequality improvement process. A total of 261questionnaires were returned and analysed. , 94%of the responders had a favourable opinion of thepatient satisfaction surveys. They considered thatthe patient was able judge hospital service quality,especially in its relational and environmentaldimensions. The specific results the departmentwere less well known than the overall hospital (60versus 76%). These results were formallydiscussed the department according to 40% ofresponders; 40% declared these data resulted inimprovement actions and considered they led tomodifications in their behaviour with patient.

The study of Ruth et al., (2008) identifiedthe factors that explain patient satisfaction withgeneral practice physicians and hence that maydrive patients’ choice of practice. He resultsdepicted that confidence and trust in the doctor isthe most important factor in explaining thevariation in overall patient satisfaction (predicting82% of satisfaction levels accurately). The sevenvariables relating to the relationship betweenpatient and doctor have stronger explanatorypower than other aspects of the generalpractitioner (GP) experience. The variables withthe lowest overall predictive power are whetherthe patient was told how long they would have towait in the surgery (72%), the length of time theyhad to wait after their appointment time (74%) andability to get through to the surgery on the phone(74%).

Jawahar (2007) intended to know thesatisfaction level of patients and also get afeedback about the services provided in theoutpatient departments. Hence this study wasundertaken with objectives to study the awarenessof patients about the outpatient departmentservices, to evaluate the performance of theservices in the patient’s perspective, and to identifythe problems of the patients and suggest measuresfor improvement in Sree Chitra Tirunal Institutefor Medical Sciences & Technology (SCTIMST).It was found that majority of the patients aresatisfied with the services provided. They weresatisfied with the guidance, logistic arrangements,support services, nursing care, Doctor’s

38

Demographic Analysis of Patient Satisfaction in Major Healthcare Centres

consultation etc. wherever there is delay inconsultation; it is to be explored to elicit thelacunae. It is worthwhile to note that there is scopefor improvement of the Out Patient DepartmentServices. Therefore it can be concluded that theOPD services form an important component ofHospital services and feedback of patients are vitalin quality improvement.

Rao et al., (2006) developed a reliable andvalid scale to measure in-patient and outpatientperceptions of quality in India and identifiedaspects of perceived quality which have largeeffects on patient satisfaction. The associationbetween patient satisfaction and perceived qualitydimensions is examined in Primary health centers,community health centers, district hospitals, andfemale district hospitals in the state of UttarPradesh in north India. A 16-item scale havinggood reliability and validity was developed. Fivedimensions of perceived quality are identified—medicine availability, medical information, staffbehavior, doctor behavior, and hospitalinfrastructure. Patient perceptions of quality atpublic health facilities are slightly better thanneutral. Multivariate regression analysis resultsindicate that for outpatients, doctor behavior hasthe largest effect on general patient satisfactionfollowed by medicine availability, hospitalinfrastructure, staff behavior, and medicalinformation. For in-patients, staff behavior has thelargest effect followed by doctor behavior,medicine availability, medical information, andhospital infrastructure.

The aim of the project by Li (2008) was toconduct an anonymous postal survey of clients’satisfaction with Breastfeeding Education andSupport Services (BESS). An anonymous surveywas posted on 16 November 2005 and again on31 January 2006, to all women who had attendedBESS in September 2005. The response rate was60.5% (78/129). Eighty per cent (62/78) of therespondents attended day-stay, 33% (26/78)attended short-stay and 15% (12/78) attended theoutpatient clinic. The percentage of women whoresponded “strongly agree” to the statement“Overall, I am satisfied with the services” was 49%(35/72) and 50% (6/12) for those who went today/short-stay and the outpatient clinicrespectively. Overall, 56% of all respondents

responded that the quality of BESS was “betterthan expected”. The most common breastfeedingproblem reported was difficulty attaching the babyto the breast, followed by nipple damage, low milksupply and painful feeding. The results found thatBESS seems to have provided a satisfactoryservice to most clients. Most respondents wereclearly satisfied with the support given by theIBCLCs and have also responded that the staffwere professional and knowledgeable in their fieldof work.

Suzanne (1995) conducted a patientsatisfaction survey on the cardiothoracic surgicalward (CW 16) between June and October 1993.The survey was designed to assess the level ofsatisfaction patients had with their hospitalisationon CW 16 both preoperatively and postoperativelyand also with their visit to the preadmission clinic(if applicable). These questionnaires weredistributed to patients either the day before theiranticipated discharge from CW 16 or the morningof the day of discharge. Patients were informedthat their responses would remain anonymous. Thesurvey results proved most informative.Significantly, the responses to the preadmissionclinic were overwhelmingly positive with manypatients stating that attendance at the clinicdispelled their fears and worries. Two particularareas of nursing care were shown to needimprovement. These were patient education onthe topic of warfarin therapy and the promotionof patient/family attendance at the ward-baseddischarge education sessions. Based on the resultsof the survey, efforts will be made to extendpatient/family attendance at both the preadmissionclinic and ward-based discharge educationsessions, and to improve the education of patientson the ward with respect to the warfarin regimen.Interventions aimed at reducing the level of noiseon CW 16, particularly at night and during therest period from 1.00 - 3.00 pm.

Syed et al., (2007) attempted to identify thedeterminants of patient satisfaction with public,private and foreign hospitals. A survey wasconducted involving inpatients in public andprivate hospitals in Dhaka City and patients whohave experienced hospital services in a foreigncountry. Their views were obtained through exitpolls using probability and non-probability (for

39


foreign hospital patients) sampling procedures.Regression models were derived to identify keyfactors influencing patient satisfaction in thedifferent types of hospitals. Doctors’ serviceorientation, a composite of 13 measures, is themost important factor explaining patientsatisfaction.

After going through extensive literature, itwas found that although many studies have beenconducted on satisfaction of patients towardshospitals, few studies were found in Indiancontext. This study is concentrated on Indianhospitals and the attitude of Indian patientstowards these hospitals and services provided bythese hospitals. The study undertaken has certainobjectives which gives it guidelines. Followingare the objectives:

· To prepare a self-made questionnaire.

· To ascertain the satisfaction levels of patientson the basis of ‘hospitals’ i.e. public sectorvs. private sector hospitals.

· To ascertain the satisfaction levels of patientson the basis of ‘age-groups’

· To ascertain the satisfaction levels of patientson the basis of ‘occupation’.

· To ascertain the satisfaction levels of patientson the basis of ‘gender’.

· To open new avenues of research in thehealthcare industry.

Research Design and Methods

The study is exploratory and descriptive innature. The population of the study includedpeople who have visited the mentioned hospitalsnamely: All India Institute of Medical Sciences(AIIMS), Apollo Hospitals and Clinics, MaxHealthcare Centres, Fortis Hospitals. The samplingframe incorporated the list of these patients in therespective hospitals. Individuals visiting thesample hospitals have been considered as thesampling element selected through Judgementalsampling technique (non-probability technique).The sampling size of the study was 117 patients.Data has been collected through a self madequestionnaire which includes relevant variables.

Tools Used For Data Analysis

Item to total Correlation: To check theconsistency of the questionnaire.

Reliability Tests: To check the reliability ofdata item of the questionnaire.

Z-Test: To compare the significancedifference between two variables.

T-Test: To compare the significant differencebetween two variables.

Hypothesis formed

The following hypotheses were formed tofulfil all the objectives of the study:

Ho1: There is no significant difference in the satisfactionlevels between patients visiting Fortis and Apollo.

Ho2: There is no significant difference in the satisfactionlevels between patients visiting Apollo and AIIMS.

Ho3: There is no significant difference in the satisfactionlevels between patients visiting AIIMS and Max.

Ho4: There is no significant difference in the satisfactionlevels between patients visiting Max and Fortis.

Ho5: There is no significant difference in the satisfactionlevels between patients visiting Max and Apollo.

Ho6: There is no significant difference in the satisfactionlevels between patients visiting AIIMS and Fortis.

Ho7: There is no significant difference in satisfactionlevels of patients between age-groups ‘below 20’and ’20-35’.

Ho8: There is no significant difference in satisfactionlevels of patients between age-groups ’35-50’ and’20-35’.

Ho9: There is no significant difference in satisfactionlevels of patients between age-groups ’35-50’ and’50-65’.

Ho10: There is no significant difference in satisfactionlevels of patients between age-groups ‘below 20’and ’50 and above’.

Ho11: There is no significant difference in satisfactionlevels of patients between age-groups ‘below 20’and ’35-50’.

Ho12: There is no significant difference in satisfactionlevels of patients between age-groups ’50 andabove’ and ’20-35’.

40


Ho13: There is no significant difference in satisfactionlevels between patients who are self-employed andthose who are salaried.

Ho14: There is no significant difference in satisfactionlevels between patients who are business personsand those who are salaried.

Ho15: There is no significant difference in satisfactionlevels between patients who are business personsand those who fall in ‘others’ category.

Ho16: There is no significant difference in satisfactionlevels between patients who fall in ‘others’ categoryand those who are self-employed.

Ho17: There is no significant difference in satisfactionlevels between patients who are self-employed andthose who are business persons.

Ho18: There is no significant difference in satisfactionlevels between patients who fall in ‘others’ categoryand those who are salaried.

Ho19: There is no significant difference in satisfactionlevels of male and female patients.

Scope of the Study

This project is meant to understand the majorfactors affecting patient satisfaction in thehealthcare industry. Study has tried to compareservices among major hospitals in N.C.R.Comparison is made on the basis of hospitalswhich are- AIIMS, Fortis Hospitals, MaxHealthcare Centres and Apollo Hospitals andClinics; on the basis of age-groups of patientswhich are- below 20, 20-35, 35-50 and above 50;on the basis of occupation of patients which hasfollowing the categories- salaried, self-employed,businesspersons and others; on the basis ofgender- male and female. This helps us to findvarying satisfaction levels when comparison isdone with different parameters. Further it wouldlead to the understanding of specific patient typepsyche.

Study would help to know that whichorganisation provides better services, to an extent.An understanding would develop regarding thefactors which affect patient satisfaction to a greaterdegree. It would also help to know factor-wisesatisfaction of patients.

Analysis and Discussion

After collecting the data with the help of

questionnaires filled, various tests were applied.These statistical tools led to analysis of the dataand further the findings and conclusions discussedin later chapters.

Consistency Measure

First of all consistency of all the items in thequestionnaire were checked through item to totalcorrelation. Under this, correlation of every itemwith total was measured and the computed valuewas compared with standard value (i.e.0.1580).If the computed value was found less thanstandard value than whole factor / statement wasdropped and was termed as inconsistent. All theitems were consistent and thus accepted. No itemwas dropped.

Reliability

Then reliability test was carried out usingSPSS software and the reliability test value of alphawas found to be 0.796. It is considered that thereliability value more than 0.7 is good and it canbe seen that the reliability methods applied hasthe reliability value is quite higher (Table 2) thanthe standard value, so the scale was highly reliable.

Validity

Face validity was applied to thequestionnaires and it was found to be very high.

T-Test

On the basis of hospitals

T-test was applied to test the hypotheses Ho1,Ho2, Ho3, Ho4 Ho5, and Ho6 to find out thesignificant differences in the satisfaction levelsbetween patients visiting different hospitals. Bycomparing the t-value and table value (criticalvalue) (refer table 3), it was found that thesatisfaction level of patients of all the samplehospitals is significantly different from oneanother except the satisfaction levels betweenpatients visiting Apollo and AIIMS. The reasonfor this might be that both these hospitals cateralmost the same category of services, being theclosest competitors. Both these hospitals carry agood brand image making the patients feel thatthey are in safe hands. The time taken to start thetreatment in these hospitals is less as compared toother sample hospitals (viz. Max and Fortis) todiagnose the problem and start the effective

41


treatment.

On the Basis of Age-Groups

T-test was used to test the hypotheses Ho7,Ho8, Ho9, Ho10, Ho11, and Ho12 to find out thesignificant differences in the satisfaction levelsbetween patients of different age groups. Bycomparing the T-value and the table value (criticalvalue) (refer table 4), it was found that the tablevalue is more than the T value in all the caseswhich clearly states that the null hypothesis (fromHo7 to Ho12) is accepted and there is nosignificant difference in the satisfaction levels ofthe patients of different age groups. This meansthat the satisfaction levels of the patient does notget affected taking age as a factor. There seems tobe some other factors that affect the satisfactionlevel of the patients.

On The Basis Of Occupation

T-test was used to test the hypotheses Ho13,Ho14, Ho15, Ho16, Ho17, and Ho18 to find outthe significant differences in the satisfaction levelsbetween patients of different occupations. Bycomparing the t-value and the table value (criticalvalue) (refer table 5), it was found that the tablevalue is more than the T value in all the caseswhich clearly states that the null hypothesis (fromHo13 to Ho18) is accepted and there is nosignificant difference in the satisfaction levelsbetween patients of different occupation.

Z-Test

Z-test is one of the statistical tools appliedhere to find out the significant differences in thesatisfaction levels of male and female patients. Ifthe value of Z is lesser than 1.96 at 5% level ofsignificance, then the hypothesis would beaccepted and if it comes out to be greater than1.96 at 5% level of significance, then it would berejected. The value of Z is less than 1.96 i.e.0.0129 (refer table 6). Thus the hypothesis isaccepted and it can be said that there is nosignificant difference in the satisfaction levels ofmale and female patients.

Conclusion

The tests conducted on the basis of age-groups reveal that there is no significant differencein the satisfaction levels of patients falling in

different age-groups and of different occupations.The same can be said about male and femalepatients. It can be concluded that the hospitalsprovide similar kind of facilities and services totheir patients irrespective of their age-groups,occupations and gender. However, there seemsto be a difference in satisfaction levels of thepatients when tests were conducted on the basisof hospitals. This can be attributed to the fact thatevery hospital has a clientele or if we see the otherway round, every customer/patient has a particularhospital to bank upon. However, the clientele hasbeen shared by AIIMS and Apollo, as seen by thetests conducted. To be more specific may be thepatients of these two hospitals could be able torelate well with the doctors then the patients ofother sample hospitals as it’s not only themedicines or the type of treatment that buildshigher satisfaction level but the patientssatisfaction level also depends upon the behaviourof doctors, the attention given to the patients, thetime taken to start the treatment.

Amidst all the testing and analysis, an aspectthat has not been highlighted, is the affordabilityof the patients. When the patients were asked tofill the questionnaire, the ‘overall experience’depended a lot on the ‘charges for treatment’. Inthe current scenario, healthcare facilities areexpensive and providers need to focus a little bitmore on social welfare. The under privilegedcannot afford to go to these large hospitals andrely more on private practitioner or small nursinghomes.

There is still a lot of scope for improvementin the healthcare industry in India. This studyhopes to act as a small lamp of light along withother lighthouses of research in findingappropriate solutions to the concerning problems.

References

1. Dr. S. K. Jawahar. 2007. A Study on OutPatient Satisfaction at a Super SpecialtyHospital in India. Internet Journal of MedicalUpdate. 2(2):13-17.

2. Gautam Kumra, Palash Mitra and ChandrikaPasricha, India Pharma 2015. Unlocking thePotential of the Indian PharmaceuticalsMarket. Mickensy and Company. 1 – 28.

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3. Laurent Boyer, Patrice Francois, ElisabethDoutre, Georges Weil and Jose Labarere.2006. Perception and use of the results ofpatient satisfaction surveys by care providersin a French teaching hospital. InternationalJournal for Quality in Health Care. 18(5).359-364. DOI:10.1093/intqhc/mzl029.

4. Li Yen Chin and Lisa H. Amir. 2008. Surveyof Patient Satisfaction with the BreastfeedingEducation and Support Services of the RoyalWomen’s Hospital, Melbourne. BMC HealthService Research. 8. 83. DOI:10.1186/14726963-8-83.

5. Rao, Krishna Dipankar, Peters, DavidH.,Bandeen-Roche, Karen. 2006. TowardsPatient-Centered Health Services in India—A Scale to Measure Patient Perceptions ofQuality. International Journal for Quality inHealth Care. 18(6). 414-421. DOI:10.1093/

intqhc/mzl049

6. Ruth Robertson, Anna Dixon, Julian LeGrand. (2008). Patient Choice in GeneralPractice: The Implications of PatientSatisfaction Surveys. Journal of HealthServices Research and Policy. 13. 67-72.DOI:10.1258/jhsrp.2007.007055.

7. Suzanne McNamee.1995. Patient satisfactionsurvey, St Vincent’s NursingM o n o g r a p h 1 9 9 5 . h t t p : / /www.ciap.health.nsw.gov.au/hospolic/stvincents/1995/a03.html.

8. Syed Saad Andaleeb, Nazlee Siddiqui andShahjahan Khandakar (2007), Patientsatisfaction with health services inBangladesh Health Policy and Planning, Vol22(4), pp 263-273. DOI:10.1093/heapol/czm017.

Annexure

Table 1:

Showing Statistics of Correlation of Satisfaction

S.No. Items Computed Consistency Accepted/Dropped

Correlation

Value

1 Helpfulness & courtesy of staff 0.4409 Consistent Accepted

2 Waiting time at the billing counter 0.5355 Consistent Accepted

3 Ease of getting an appointment 0.5187 Consistent Accepted

4 Information provided 0.3880 Consistent Accepted

5 Helpfulness & courtesy of the doctor 0.4196 Consistent Accepted

6 Time spent by the doctor 0.3699 Consistent Accepted

7 Explanation about diagnosis &treatment by the doctor 0.3320 Consistent Accepted

8 Your involvement in decision making 0.3798 Consistent Accepted

43


9 Maintained privacy duringconsultation by the doctor 0.2790 Consistent Accepted

10 Information about health promotion& disease prevention 0.4598 Consistent Accepted

11 Waiting time for final reports 0.5697 Consistent Accepted

12 Cleanliness 0.3648 Consistent Accepted

13 Seating arrangement 0.2389 Consistent Accepted

14 Courtesy of security staff 0.4327 Consistent Accepted

15 Services at cafeteria 0.4154 Consistent Accepted

16 Response to queries 0.4972 Consistent Accepted

17 Billing accuracy 0.5834 Consistent Accepted

18 Promptness in discharge 0.5214 Consistent Accepted

19 Accessibility to doctors 0.4908 Consistent Accepted

20 Room accommodation & services 0.2970 Consistent Accepted

21 Overall healthcare facilities 0.2906 Consistent Accepted

22 Infrastructure 0.4061 Consistent Accepted

23 Co-ordination of departments 0.6311 Consistent Accepted

24 Charges for treatment 0.5706 Consistent Accepted

25 Overall experience 0.5995 Consistent Accepted

Table 2:

Reliability Statistics

Cronbach’s

Alpha N of Items

.796 11

Reliability Statistics

44


Table 3:

T test Statistics (on the basis of hospitals)

T Test Mean Standard Standard T- Table Significance/between Deviation Error value Value Insignificancevariables

Satisfaction Fortis 71.64 11.32 10.19 4.43 1.9972 Significant

levels between Apollo 60.16 9.22patients visitingFortis and Apollo.

Satisfaction Apollo 60.16 9.22 8.03 1.73 2.0021 Insignificant

levels between AIIMS 56.5 5.96patients visitingApollo andAIIMS.

Satisfaction AIIMS 56.5 5.96 4.73 2.32 2.0031 Significant

levels between Max 53.6 3.59patients visitingAIIMS and Max.

Satisfaction Max 53.6 3.59 8.03 8.7 2.003 Significant

levels between Fortis 71.64 11.32patients visitingMax and Fortis.

Satisfaction Max 53.6 3.59 7.03 2.07 1.9961 Significant

levels between Apollo 60.16 9.22patients visitingMax and Apollo.

Significant AIIMS 56.5 5.96 9.19 5.8 2.0072 Significant

difference in the Fortis 71.64 11.32satisfaction levelsbetween patientsvisiting AIIMSand Fortis.

45


Table 4:

T test Statistics (on the basis of age groups)

46


T Test Mean Standard Standard T- Table Significance/between Deviation Error value Value Insignificancevariables

Satisfaction Below 20 59.85 11.24levels of patients 11.27 0.65 1.992 Insignificantbetween age- 20-35 61.53 11.32groups ‘below20’ and ’20-35’.

Satisfaction 20-35 61.53 11.32levels of patients 10.9 0.102 2.005 Insignificantbetween age- 35-50 61.21 10.11groups ’35-50’and ’20-35’

Satisfaction 35-50 61.21 10.11 8.8 1.14 2.0326 Insignificant

levels of patients 50 and 57.84 7.48between age- abovegroups ’35-50’and ’50-65’.

Satisfaction 50 and 57.84 7.48levels of patients above 10.22 0.69 2.004 Insignificant

between age- Below 59.85 11.24groups ‘below 2020’ and ’50and above’.

Satisfaction 35-50 61.21 10.11levels of patients 10.9 0.43 2.004 Insignificantbetween age- Below 59.85 11.24groups ‘below 2020’ and ’35-50’.

Satisfaction 20-35 61.53 11.32levels of patients 10.26 1.255 2.005 Insignificantbetween age- 50 and 57.84 7.48groups ’50 and aboveabove’and ’20-35’.

Table 5:T test Statistics (on the basis of occupation)

47


T Test Mean Standard Standard T- Table Significance/between Deviation Error value Value InsignificancevariablesSatisfaction Self- 64.13 11.33levels between employedpatients who are 10.38 1.55 Insignificantself-employed Salaried 59.36 9.44and those whoare salaried.Satisfaction Business 59.28 10.24levels between personspatients who are 9.8 0.02 Insignificantbusinesspersons Salaried 59.36 9.44and those whoare salaried.Satisfaction Business 59.28 10.24levels between personspatients who are 10.3 0.08 Insignificantbusinesspersons Others 59.07 10.35and those whofall in ‘others’category.Satisfaction Others 59.07 10.35levels between 10.64 1.86 Insignificantpatients who fall Self- 64.13 11.32in ‘others’ employedcategory andthose who areself-employed.Satisfaction Self- 64.13 11.33levels between employedpatients who are 10.74 1.56 Insignificantself-employed Business 59.28 10.24and those who personsare business-persons.Satisfaction Others 59.07 10.35levels between 10.06 0.116 Insignificantpatients who fall Salaried 59.28 10.24in ‘others’category andthose who aresalaried.

Table 6: Z test Statistics (on the basis of gender

Z Test Mean Standard Standard Z- Table Significance/between Deviation Error value Value InsignificancevariablesSatisfaction Males 2.437 0.458 0.077 0.0129 1.96 Insignificantlevels of male Females 2.436 0.421and femalepatients.

48

Contributors

Dr.Silky Vigg Kushwah, Associate Professor, Jagannath International Management School,Affilliated to Guru Gobind Singh Indraprastha University,OCF,B-9, Vasant Kunj, New Delhi-110070.Ph:0-9711131652

Dr.Pushpa Negi, Associate Professor, Symbiosis Institute of Management, New Delhi.

Mr.Ashok Sharma, Assistant Professor, Jagannath International Management School, Affilliatedto Guru Gobind Singh Indraprastha University,OCF,B-9, Vasant Kunj, New Delhi-110070.

We, the authors hereby declare that the manuscript is the original piece of work and is not sentfor publication or accepted or under review neither process nor published elsewhere.


SELECT BIBLIOGRAPHY ON LEADERSHIP AND LEADERSHIPDEVELOPMENT (M-Z)

Compiled and Edited byK.V.S.Raju and P.B.Apparao

Dept. of Management Studies, GRIET, Hyderabad


ISSN : 2230 - 9764

For the purpose of providing a direction tothe research on “leadership” and “leadershipdevelopment” a humble attempt has been madeto collect, edit and present bibliography on thesubject concerned. Already two parts of thebibliography, arranged in alphabetical order, havebeen published in the last two issues. This is incontinuation of the two parts published earlier.

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