BSNL 1

EDITORIAL BOARD

EditorBrajaraj Mohanty

Professor, Xavier Institute of ManagementBhubaneswar

Members

John C.Camillus, Donald R.Beall Professor of Strategic Management,University of Pittsburgh, Pittsburgh,U.S.A.

S.K. Chakraborty, Founder- Convenor, Management Centre for Human Values,Indian Institute of Management, Kolkata

Keith D’Souza, Director (Organizational Effectiveness), Pfizer Limited, MumbaiJ.M. Denton, Professor & Head of International Affairs, University of Stellenbosch

Business School, Bellville, South Africa, email:[email protected] Ghosh, Director, Management Education Centre,

Heritage Institute of Technology, KolkataM.G. Jomon, Associate Professor, XLRI, Jamshedpur

Jerome Joseph, Professor, Indian Institute of Management, AhmedabadOswald A. Mascarenhas, s.j., Kellstadt Professor of Marketing,

University of Detroit-Mercy, DetroitSasi Misra, Distinguished Fellow, Entrepreneurship Development Institute of India,

AhmedabadAmar KJR Nayak, Associate Professor, Xavier Institute of Management, Bhubaneswar

Gopal Krishna Nayak, Director, International Institute of Information Technology,Bhubaneswar

H.K. Pradhan, Professor, XLRI, JamshedpurV.Ranganathan, Professor, Indian Institute of Management, Bangalore

Latha Ravindran, Professor, Xavier Institute of Manavement, BhubaneswarSubhash Sharma, Dean, Indian Business Academy, Bangalore

W.S. William, Professor & Dean (Academic), Xavier Institute of Management, Bhubaneswar

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Editor, ILAKSHAN

XIMB Journal of ManagementXavier Institute of Management

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XIMB JOURNAL OF MANAGEMENTVolume V Issue No. 1 March, 2008

Xavier Institute of ManagementBhubaneswar - 751 013

ILAKSHAN

March, 2008

ISSN 0973-1954

Regd. No. : ORIENG/2006/18251

PublisherDr P. T. Joseph s.j.DirectorXavier Institute of ManagementBhubaneswar

PrinterDr P. T. Joseph s.j.DirectorXavier Institute of Management,Xavier Square, Bhubaneswar - 751013

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Copyright with Xavier Institute ofManagement. No part of the publication may bereproduced in any form without prior permissionof Editor, Vilakshan-XIMB Journal ofManagement, Xavier Institute of Management,Bhubaneswar. However, the views expressed inthe papers are those of the authors and not ofthe Editoral Board or Publisher.

Contents

ARTICLES

1. An Analysis of Microfinance Rating Models S. K. Mitra, 1

Rajnish Ranjan

& Shivi Negi

2. Factors Affecting Emotional Intelligence:An Shamira Malekar 23

Empirical Study for Students of Secondary & R.P.Mohanty

Schools and Professional Colleges

3. Exchange Rate, FII and Stock Index Ajaysingh Rajput 43

Relationship in India & Keyur Thaker

4. Attribute Based Perceptual Mapping of Cement P.Shahida, 57

Brands: an Empirical Study Rajendra Nargundkar

& Gaurav Hiremath

5. Work Role Characteristics as Determinants J. Reeves Wesley 65

of Job Satisfaction: An empirical analysis & P.R. Muthuswamy

6. Empirical Examination of A Cost Allocation Ajay Kumar Pillai 75

Model: using the Theory of Planned Behaviour

7. Valuation of Intellectual Capital: The case of Nikhil R. Nayak, 93

Financial Services Industry in India Munmun Mohanty

& B. B. Mishra

8. Measuring Technical Efficiency of Coal Mines Sreekumar, 113

using Data Envelopment Analysis – A Case Rohita Kumar Mishra

Study of Mahanadi Coal Fields Ltd. & Debendra Kumar Mahalik

PERSPECTIVES

9. Beyond Whistleblowing: A Study on Socrates, Bibhu Prasan Patra 125

Satyendra and Manjunath

10. Private Equity — Gaining Momentum Naliniprava Tripathy 147

MANAGEMENT CASES

11. Fabindia Overseas Private Limited B. Mohanty 157

& Rajeev Roy

12. BSNL – Making the Elephant Dance M. N. Tripathi 167

13. The Case of Raw Material Supply in the Wood Debadutta Kumar Panda 179

Carving Clusters of Orissa

BOOK REVIEWS

14. Managing Creativity D. Chakraborty 189

15. New Mantras in Corporate Corridors A.S. Abani 195

An Analysis of Microfinance Rating Models*

S. K. Mitra,1 Rajnish Ranjan2 and Shivi Negi3

* Received November 20, 20081 Professor, Institute of Management Technology, Nagpur, email: [email protected] PG PRM Student (26th Batch), Institute of Rural Management, Anand,

email: [email protected] PG PRM Student (26th Batch), Institute of Rural Management, Anand,

email: [email protected]

Abstract

Microfinance has emerged as a very important paradigm for meeting the credit requirements of poorpeople, who were until recently outside the coverage of formal banking institutions. But a lack oftransparency in the microfinance sector and information asymmetry between microfinance institutions(MFIs) and lenders have made lenders apprehensive of lending to MFIs. MFI rating is designed toremove such constraints. There are around 16 rating agencies the world over. At present, in India onlytwo agencies are involved in MFI rating, and between them most of the ratings are done by M-CRIL.These rating agencies adopt different methodologies, rating models, and rating scales for assessing theperformance of client MFIs. This study examines the increasing importance of MFI ratings in thedevelopment of the microfinance sector. It looks at some of the popular rating agencies and their models,and does a comparative analysis of these. It also examines the feedback received from different stakeholderswith respect to the ratings and the key challenges related to MFI rating. (For the abbreviations used inthis paper see Appendix - 1)

1.0 INTRODUCTION

Microfinance is being acceptedincreasingly as a powerful tool for thesocial and economic empowerment ofmarginalised communities, especiallywomen. Over time, microfinance hascome to include a broader range ofservices (credit, savings, insurance, etc.)as it was realised that the poor peoplewho lack access to traditional formalfinancial institutions require a variety offinancial products.

In other words, a microfinance institution(MFI) is an organisation that offersfinancial services to low-incomepopulations. Within the microfinanceindustry, the term microfinanceinstitution has come to refer to a widerange of organisations dedicated toproviding these services, such as NGOs,credit unions, co-operatives, privatecommercial banks, and NBFCs. Diverseoperating models, legal forms, andfinancing arrangements have resulted insignificant variation in the depth and




2 Vilakshan, XIMB Journal of Management ; March, 2008

breadth of financial disclosure acrossthese institutions. Other than the leadinginstitutions, few MFIs follow globalfinancial disclosure guidelines formicrofinance. This has resulted ingrowing disparity and informationasymmetry among the whole spectrumof MFIs in terms of the way in which theyconduct their operations.

In addition, in recent years, it has beenobserved that microfinance has had anasymmetric growth across the country,with instances of differences in the ratesof interest charged to the members beingbrought to light. Concerns have beenexpressed about the methods adopted byMFIs to gain business, which raisesdoubts about their long-termsustainability. This situation has led tothe need for finding a way to identifygood MFIs from the point of view of bothdonors and investors. Donors andinvestors also want to know how welltheir money is being managed by an MFI.This calls for an evaluation mechanismthat can rate the credibility of an MFI interms of both credit and socialdeliverables. All these issues haveencouraged the recent development ofMFI rating agencies as these ratings haveemerged as a solution in this regard. MFIrating is a tool designed to overcomeproblems with the availability, reliability,and quality of information on the risksand performance of MFIs.

2.0 MFI RATINGS : A BRIEF

A rating represents an assessment of aspecific debtor’s creditworthiness, that is,

of how likely it is that the MFI (debtor)will repay the debt. It involves a detailedassessment of an MFI’s creditworthinessand forming an opinion on the relativeability of the MFI to make timelyrepayments of all loan obligations tolenders.

As the microfinance rating industrymatures, microfinance rating serviceshave drawn attention increasingly frominvestors and donors (Rating Fund 2005).The total number of ratings andassessments has grown by 84 per centin a span of four years recently, from152 in 2001 to 281 in 2005 (Rating FundMarket Survey 2005). It is estimated thatby 2005–06 more than 650 MFIs (aroundmore than half of all MFIs in the world)will have been evaluated by an externalrating agency and will have alsoupdated their rating with a secondevaluation (Microfinance Rating andAssessment Fund 2006). The largemajority of these are situated in LatinAmerica and Asia. This indicates thegrowing realisation about theimportance of MFI ratings. It has beennow acknowledged that MFI ratings areimportant not only for MFIs andinvestors but also for the entire sector.The importance of MFI ratings can begauged from Figure - 1.

The term rating is used usually asshorthand for credit rating. In the earlyphase of the development of MFI ratings,it was mainly main stream raters that usedto rate MFIs. In this case, the MFIs werebenchmarked against the banking sector.

3Mitra et.al, An Analysis of Microfinance ...

Figure-1: Utility of MFI Rating

UTILITY OF MFI RATING

For MFI For Investors For the Sector

• Obtaining funding

• Comparing performance with other MFIs

• Assessing performance

• Identifying MFIs

• Evaluating MFIs

• Follow-up on funded MFIs

• Improved access to data

• Gaining trust from sector and outside

It was only later when the demand forrating agencies catering specifically to themicrofinance sector arose that specialisedMFI raters emerged to meet the needsof this niche market. For instance,ACCIÓN International adapted theCAMEL approach to the analysis offinancial institutions in evaluating theiraffiliate MFIs in the early 1990s. The ideaof creating a specialised rating agency(oriented toward investors) emergedonly later with the creation of Micro Ratein 1996. Specialised rating formicrofinance most closely resemblesmain stream rating, although it goesbeyond mere payment capacity to captureaspects of institutional performanceparticular to microfinance.

Sixteen rating agencies are now active inthis market. If the MFI industry is still

young, MFI rating agencies are evenyounger. Since the first rating agency wasestablished in 1996, many other MFIrating agencies have come into themarket with their own models andmethodologies for assessing theperformance of the client MFI.

3.0 OBJECTIVES OF THE STUDY

In the study, an analysis of variousmicrofinance rating agencies has beendone. In addition, their methodologieshave been compared with the followingobjectives in mind:

• To gain an in-depth understandingof the different MFI rating modelsof the various rating agencies.

• To do a comparative study of thedifferent rating agencies and theirmodels.


• To learn about the viewpoints of thestakeholders with respect to MFIratings, that is, the MFIs themselves,banks, and capital providers likeUnits and NABARD.

3.1 Rating Agencies Selected for theStudy

To meet the first two objectives of ourstudy, we chose six rating agencies (seeTable-1) out of the 16 rating agencies thatare involved in MFI rating the worldover. In choosing the rating agencies, wehave taken three parameters intoconsideration. The first parameter is theexperience of the rating agency, which isgiven by the number of MFI ratings thatit has conducted. A rating agency like

JCR-VIS was not considered because ofthis reason, as it had done only five MFIratings until 2005 (www.ratingfund.org).The second parameter is the availabilityof secondary information about therating agency on the Internet and throughother sources. There is very littleinformation available about PEARLS.Consequently, it could not be studied.The third parameter is the availability ofthe reports in English on the Internet. Arating agency like Apoyo and Asociadosdoes not have its rating reports andrelated articles available in English on theInternet. Consequently, it could not bestudied.

Of the six rating agencies selected for thestudy, we have taken two reports of the

Table-1: List of the Rating Agencies Studied

Rating Rating Rated MFI Rating NumberAgency Model Obtained of MFI

Ratings doneuntil 2005

ACCIÓN CAMEL 1. ‘Bereke’ Kazakhstan 3.42 / 5 NAInternational Microcredit organisation

2. SOEGSOL 2.89/ 5MicroRate - 1. Amhara Credit & α- 280

Savings Institution2. CMF β

Microfinanza srl - 1. SEF International Ltd BB+ 902. ACME BBB+

Planet Rating GIRAFE 1. ABA A- 1652. ECLOF D

CRISIL MICROS 1. ESAF mfR5 182. BASIX mfR2

M-CRIL - 1. Spandana α+ 3652. Grameen Koota β (Nov. 2006)

http://www.ratingfund.org)


MFI rating for each(www.mixmarket.com). Care has beentaken to take one report with a rating onthe higher side of the rating scale andanother with a rating on the lower side.For a better understanding of the ratingmethodology of each of the rating modelsused by these agencies, we have takenthe help of the technical guides issued bythese agencies. Thus, 12 rating orassessment reports (two from each of thesix rating agencies) completed between2000 and 2006 were selected for our study(see Table - 1).

3.2 An Overview of the Selected RatingAgencies

3.2.1 ACCIÓN International

The original CAMEL was developed in1978 by the US Federal Reserve toevaluate the solvency of US banks. In1993, ACCIÓN adapted CAMEL to theneeds of microfinance. ACCIÓN does notissue credit ratings, but uses CAMEL asan institutional assessment tool. Themajority of ACCIÓN’s clients areaffiliates of their network, and most oftheir reviews are conducted in Africa andLatin America. ACCIÓN CAMELreviews and rates five areas of financialand managerial performance: capitaladequacy, asset quality, management,earnings, and liquidity management.

3.2.2 Micro Rate

Micro Rate is a US company specialisingin the rating of Latin American MFIs. Itis the leading and also the oldest ratingagency specialising in the evaluation of

MFIs. Micro Rate has evolved a risk-driven methodology that combines themeasuring of credit worthiness with anassessment of an institution’s excellencein microfinance. Rather than following aformula, evaluation teams use theirexperience to identify those areas criticalto the performance of the particular MFI.Micro Rate analyses five areas of MFIperformance and risk: microfinanceoperations, portfolio quality,management and organisation,governance and strategic positioning,and financial performance.

3.2.3 MicroFinanza

MicroFinanza Rating was created in 2001as a division of MicroFinanza Srl.MicroFinanza Rating has wideexperience in rating and assessing MFIswith different legal structures and inoperating in various economic, political,and legal environments, and in bothrural and urban contexts. Its ratingmethodology is based on quantitativeand qualitative assessment factors. Thequantitative analysis is alwaysintegrated with the description and putin the context of the used indicators. Thequalitative analysis includes a carefulevaluation of institutional ownership,governance, and market positioning, aswell as a complete assessment of thedifferent organisational, operational,and management aspects. The ratingscale and grades are syntheticevaluations of the credit risk andfiduciary risk profile of the MFI ratedby MicroFinanza.

http://www.mixmarket.com)


3.2.4 Planet Rating

Planet Rating was created in 1999 as adepartment of the internationalmicrofinance NGO, Planet Finance. Lateron it became an independent agencyspecialising in MF ratings. Planet Ratingis a European company that evaluatesMFIs worldwide. Its goal is to help MFIsattract new sources of financing, to buildthe capacity for MFI self-evaluation, andto promote transparency in themicrofinance sector. Planet Ratingprovides rating services based on theGIRAFE methodology, which takes intoaccount G-Governance, I-Information,R-Risk management, A-Activities andservices, F-Financing and liquidity, andE-Efficiency and profitability. PlanetRating currently is testing a newcomponent for its evaluation system.GIRAFE-S is an assessment of an MFI’seffort to make a positive social impact onits clients’ welfare by meeting unsatisfieddemand for credit and other financialservices and by expanding the overallopportunities for clients.

3.2.5 CRISIL

CRISIL was established in 1987. It wasthe first credit rating agency to undertakeratings for entities such as banks, financialinstitutions, utilities, municipal bodies,insurance companies, and green-fieldprojects, as well as for new instrumentssuch as asset and mortgage-backedsecurities and other structuredobligations. CRISIL, which is India’spremier credit rating agency, alsofeatures among the top four rating

agencies in the world in terms of both itscoverage and its analytical strength.CRISIL uses the MICROS methodology,specifically designed for MFIs, whichstands for Management, Institutionalarrangement, Capital adequacy and assetquality, Resources, Operationaleffectiveness, and Scalability andsustainability. The thrust is on the MFI’smanagement ability, institutionalarrangement, and financial strength tosustain and scale up operations.

3.2.6 M-CRIL

M-CRIL is the world’s no. 1 microfinancerating agency (http://www.mixmarket.org). The mission of M-CRIL is to facilitate the delivery ofmicrofinance services in the developingcountries of Asia by minimisinginformation asymmetry and mitigatingthe limitations caused by lack of relationsbetween commercial investors and MFIs.

M-CRIL’s methodology groups 30indicators under three broad areas—governance and organisational aspects,management systems and humanresources, and financial strength.

4.0 COMPARISON OF THE DIFFERENT RAT-ING AGENCIES AND THEIR MODELS

4.1 Market Share of the Rating Agencies

Out of the six rating agencies studied,only one (CRISIL) is a main stream raterwhile the other five are specialised ratingagencies. All are recently establishedagencies, with the oldest being ACCIÓNCAMEL, which started MFI ratings in1993. Micro Rate, which was established

http://www.mixmarket.org)

7

in 1996 and which started MFI ratings in1997, is the first and oldest specialisedMFI rating agency in the world. ThoughCRISIL was established in 1987, it startedMFI ratings only in 2001. Amongst thesix rating agencies examined in this study,CRISIL and MicroFinanza entered theMFI rating industry most recently, thatis, in 2001.

As per the findings of the Rating FundMarket Survey 2004–05, M-CRIL is themost active specialised agency, with 44per cent of global assessments performed

Mitra et.al, An Analysis of Microfinance ...

in 2004–2005. Micro Rate comes second,with 24 per cent of total assessmentscompleted worldwide. Planet Rating andMicroFinanza follow next, with 19 percent and 13 per cent respectively. Amongthe main stream rating agencies, CRISILcontributed 20 per cent of all credit riskratings performed globally in 2004–05(Rating Fund Market Survey 2005). TheFund Market Survey 2004–05 has donethe rating of rating agencies and the topthree rating agencies in different regionsof the world are shown in Table-2

Table -2: Top Three Rating Agencies in Different Regions of the World (2004–05)

First Second Third

Asia M-CRIL (75%) CRISIL (21%) JCR-VIS (3%)Sub-Saharan Africa Micro Rate (66%) Planet Rating (31%) MicroFinanza (3%)CEE/NIS MicroFinanza (64%) Planet Rating (34%) M-CRIL (3%)MENA Planet Rating (91%) MicroFinanza (9%)

4.2 Regarding Rating Models andReports

Most of the MFI evaluations reviewedhere demonstrate depth, variety (in termsof coverage), and consistency (in termsof a clear methodology). Ratings andassessments of MFIs focus more on assetquality and efficiency in order to attractinvestments. In recent times, the socialperformance of MFIs has also gainedimportance. All rating agencies havechosen to establish their ownmethodologies to rate MFIs. ACCIÓN-CAMEL uses CAMEL, Planet Rating usesGIRAFE, while CRISIL uses the MICROSmodel.

Different rating agencies use differentscales. These are difficult to comparebecause those using the same grades donot always assign the same meaning tothe grades. The scales are very different,with their own definitions, and hence itis difficult to relate the scores assignedto MFIs by several raters.

Out of the six MFI rating agencies, onlythree claim to study the social performanceof MFIs: MicroFinanza, Planet Rating, andM-CRIL. Planet Rating has developed theGIRAFE-S model, which includes socialevaluation and is based on CERISE. Thefirst MFI assessed under this methodologywas Enda, from Tunisia, in 2005. M-CRIL


has recently launched a new social ratingservice for MFIs. This social ratingconsiders the MFI’s adherence to its socialmission, the depth of outreach to low-income clients, and the suitability ofproducts to client needs. In 2004, M-CRILconducted a pilot rating exercise in India,evaluating the social performance ofBullockcart Workers DevelopmentAssociation (BWDA).

Generally, two kinds of reports areoffered by rating agencies. One is thecredit rating report and the other is therisk assessment report.

4.2.1 Credit Rating Report.

Out of the six rating agencies that westudied, four (CRISIL, M-CRIL, MicroRate, and MicroFinanza) give creditrating reports that present their views onthe creditworthiness of MFIs. They allgive overall credit rating reports, andtheir methodologies concentrate onevaluating the financial soundness of theorganisation. Two agencies, Micro Rateand M-CRIL, have adapted theirmethodologies to offer both a creditrating and a global risk rating.

4.2.2 Risk Assessment Report

Five rating agencies (ACCIÓN, CRISIL,M-CRIL, Micro Rate, and Planet Rating)give risk assessment reports that arebroader than credit reports but thatmay not include some points that areof interest to investors, such asprobability of default by MFIs. In thesereports, the agencies issue an

assessment of different componentsalong with the item scores of thecomponent. Some agencies also issue acomposite score (ACCIÓN withCAMEL, CRISIL with MICROS, andPlanet Rating with GIRAFE).

4.3 Rating Parameters

Rating reports consider certain commonparameters in assessing the performanceof the client MFI for the purpose of rating.These parameters and our findings onthese parameters are as follows:

4.3.1 External Risks

Three rating agencies (MicroFinanza,CRISIL, and Planet Rating) give theiropinions on the conditions of thecountry’s economy and themicrofinance sector. They also studythe levels of competition and regulationin the sector.

4.3.2 Internal Risks

The most important systems for avoidinginternal risks are internal controlsystems and MIS. All the modelsexamined these two aspects in detail.They provide sufficient informationabout the organisations’ internal controlsystem designed to avoid fraud and tokeep a check on operations. They alsogive details about the kind of MIS andloan-tracking system that anorganisation has.

4.3.3 Credit Risks

All rating reports give details about thefinancial condition of MFIs. The portfolio


at risk (PAR) has emerged as the mostimportant ratio for representing thequality of a portfolio. In addition, allreports give the write-off ratios and theloan-loss reserves.

4.3.4 Profitability

All the reports give details of theprofitability of MFIs. All the ratings useReturn on Equity (ROE) and Return onAssets (ROA) to show the profitabilityof MFIs. In addition, all ratings useOperational Self-Sufficiency (OSS) andFinancial Self- Sufficiency (FSS) to showwhether an organisation is earningenough revenue to meet its expenses ornot.

4.3.5 Efficiency

Cost per borrower and loan officer peraccount are two important parametersthat are used to judge the efficiency ofMFIs. Operating expense ratio is alsoused by all rating agencies to find thelevel of expenses.

4.3.6 Adjustments

All the rating agencies make thefollowing adjustments in the financialstatements of the MFI in order to presentthe true picture:

• Loan write-offs removed from thebalance-sheet portfolio

• Inflation adjustments

• Adjustments for subsidised debtinterest (example: reflect what theMFI should have paid to clients formandatory savings)

• Shadow expenses of the value ofimplicit subsidies

4.4 Comparison of the Rating Models

The six rating agencies and their modelsalong with rating methodologies havebeen shown in a comparative manner inTable -3.

Table-3: Comparative Analysis of the MFI Rating Agencies and their Models

Parameter ACCIÓN Micro Rate Planet CRISIL M-CRIL MicroInternational Rating Finanza

ABOUT THE MFI RATING AGENCY

Started MFI 1993 1997 1999 2001 1998 2001rating from

Regional Latin Latin Africa, South Asia, South Asia, CEE/NIS,coverage America, America, Latin South-east South-east Latin(2004) Africa Africa America, Asia Asia America,

East Asia, South-eastCEE/NISAsia,MENA,Africa


Price range NA Fees forcredit rating$15,000;Forglobal riskassessment$7,000–$15,000;Annualupdates$5,000–$8,000

Fee forglobal riskassessment $8,000–$15,500

Fee forglobal riskassessmentLowestcharge:$6,500;Highestcharge:$10,800

Fee forcreditratings$5,000–$11,000

Fee forglobal riskassessment$ 8 , 0 0 0 –$15,500

ABOUT THE RATING MODEL

No. ofindicatorsused forrating

21

C-capitaladequacyA-assetqualityM-managementE-earningsL-liquiditymanagement

-

•Microfinanceoperations

•Portfolioquality

•Management&organisation

•Governance& strategicpositioning

•Financialperformance

26

G:governance

I:informationR: riskmanagementA: activities& services

F: financing& liquidity

E: efficiency&profitability

M:managementI:institutionalarrangementC: capitaladequacy &assetqualityR:resourcesO:operationaleffectivenessS:scalability &sustainability

30

Theindicatorscover threemain areas:• Organisa-tional &governanceaspects

•Managerial& resourcestrength

•Financialperformance

•Governance&operationalstructure

•Assetsstructure &quality§Internalcontrol &riskmanagement

•FinancialstructureStrategicobjectives& financialneeds

1. Riskassessment

2. Training

1. Creditratings

2. Globalriskassessment

1. Ratings2. Pro-formarating3. Training4. Consultancywork forapexinstitutions5. Customisedevaluationservices6. GIRAFE-S

1.Creditrating

2.Riskassessment

1.Creditrating2.Riskassessment3.Specia-lised studiesof the MFsector4.Inter-nationalBestPracticesAdvisoryServices5.Quarterlymonitoring 6.Socialrating

Productsandservicesoffered

1.Institu-tionaldiagnostic2.Assess-ment/privaterating3.Rating4. SPA(SocialPerfor-manceAssess-ment)


KEY DIFFERENTIATING FACTORS

Highlights ofreport

Verycompre-hensive

• Shortanalyticalreport withbenchmarkingcomparisons

•Wellbalanced inboth factualandperformanceanalysis

• Exhaustivefactual detail

•Wellbalancedin bothfactual andperformanceinputs

•Cleardefinitionof risklevel

•Strong oncommentsin capacityconstraints,management,governance,bestpractices,trackrecord, andbench-marking

•Ratingopiniongearedmoretowardscredit riskandrepaymentcapacity

•Bench-marking ofkeyparametersagainstMFIs in M-CRIL’sexistingdatabase

•Commentson the riskgrade andthesuggestedlendingamount andconditions

Ratingsinclude ariskprofileandbenchmarkinganalysis,andconsidercarefullythespecificoperationalenviron-ment andthe targetmarket ofthe MFI

Quantitative 46% 30% 43% 45% 51% 40%

Qualitative 54% 70% 57% 55% 49% 60%

Rating scale Rating isgiven on ascale of 0 to5. Thiscorrespondsto analphabeticalrating ofAAA to D.

Issues acompositescoreranging from0 to 5.Globalrating isgivenranging fromG1 to G5;Compositerating isgivenranging frome to a.

8-pointgradingscale ofmfR1 tomfR8, withmfR1 beingthe highestrating andmfR8 beingthe lowestrating

From α+++to y

10 grades,from AAA(highest)to D(lowest

ExcellenceinMicrofinance– α++ to γ-Creditrating –AAA toDDShort-term debt –A1+ to C


•Does notapply a rigidratingformula;rating teamsuse theirexperience toidentifythose areascritical to theperformanceof theparticularMFI

focusesmore onmanagementthan on risk

both creditrisk andriskassessmentsfor MFIs

•Highdomainknowledgeof thefinancialsector

the ratedorganisation

•Maintainsa compre-hensivedatabase ofall its ratingactions,which isused forbench-markingMFIs

theachieve-ment ofthe MFI’sdoublebottomlinethroughits socialrating

A p p r o a c hbias

Strong onmanage-ment,profitability,andbenchmark-ingpractices

Strong onfinancialtrackrecord andbench-markingagainstpeers

Strong onmanage-ment,governance,and bestpractices

Strong onfinancialparameters

Strong oncapacityconstraintsbased onspecificissues

What itdoes nottake intoaccount

•Does notm e a s u r ecredit risk

•Does notrate theinstitution

•Does notprovidereal ratingsbut ratheroffers arationale

•Does notcurrentlyrate thecredit riskof an MFIand make it

•MFgrading isnot a creditrating anddoes notindicate the

•Does nottake intoaccountexternalenvironmentalfactors

•Lessfocus oninternalcontrolsystem.

Salientfeatures

•Conducts averydetailedassessment

•Focusesmore onsustainability

•Verystrong onfinancialaspects likecapitaladequacyand assetmanagement.

•Trackschanges inMFIfundingsources

•BenchmarksMFIs topeers in asemi-annual MFIcomparison

•ComparesMFIs onperformanceand risk

•Has verygoodunderstandingof the MFsector

•Offersvariety ofproducts andservices

•Gives moreweight to‘fiduciary’risk

• Metho-dology

•RatesMFIs/NGOsinternation-ally to takeintoaccountexternalrisksfactors

•Hasadoptedhybrid MFratingmodel,whichincludes

•M-CRIL isthe pioneerin socialrating.

•AlthoughM-CRILratings arevalid onlyfor oneyear, theratingrecommen-dationskeep inview thelong-termprospects of

•Ratingsinclude arisk profileandbenchmarkinganalysis,andconsidercarefullythe specificoperationalenvironmentand thetargetmarket ofthe MFI

•Assesses


in terms ofits impactat the clientlevel

•Onlythoseaspects thatthe‘market’assesses asimportantareincluded inthe rating

for anopinion onthe MFI’screditworthiness

•Does notprovideconsultingservices

availabletoinvestors

creditworthinessof an MFI(obligor)

•MFgradingcannot alsobecomparedwith acreditratingassigned toa debtinstrumentof the sameMFI

•Less focuson systemsandprocedures

5.0 VIEWS OF STAKEHOLDERS ON MFI RAT-INGS

Meetings were set up to elicit the opinionsof the different stakeholders—MFIs,banks, Unitus, and NABARD—on theissue of MFI ratings. The list of thevarious stakeholders visited is given inAppendix 2.

5.1 Feedback of MFIs on Ratings

Feedback was sought from the eight MFIssituated in and around Hyderabad andBangalore on their experience withratings. The trend that emerged was thatthe MFI would go in for a rating onlywhen it was in need of funds and thecreditor had laid out the rating asessential. Thus, many MFIs like Outreachhave gone in for a rating only when itwas required for SIDBI funding. Only afew MFIs like Grameen Koota have gonein for a rating from the view ofperformance evaluation. Some MFIs like

Outreach have not gone in for a ratingfor the last few years as they were in aconsolidation phase and were not in needof funds.

In general, MFIs were satisfied with theservices of the rating agencies. MFIsfound the rating reports very helpful inidentifying the strengths and weaknessesof their organisations and in identifyingthe areas for improvement. Rating reportsare also used to attract new sources offunding, to appear more transparent tocurrent and potential partners andfunders, and to benchmark performancewith other institutions. The generalfeedback on the present rating model wasthat it is skewed towards the financials.The social impact of the MFI is not takeninto account while conducting a rating.Some of the MFIs also demanded thattheir performance should be measuredin terms of the achievement of theirmission and vision. All the MFIs agreed


that social rating is important, but theyhave different opinions on the questionof how this should be done. BSS felt thatthe same rating should incorporate bothcredit and social parameters. On theother hand, Ujjivan felt that it would bebetter to have different ratings for creditand social purposes.

Recognition of the rating by the lenders,both national and international, is veryimportant. This fact came to light throughthe experience of SKS. Until recently, SKSwas able to meet its credit requirementsthrough national lenders like banks. Inthis situation, the rating by M-CRIL camein handy as M-CRIL is a specialised ratingagency for MFIs and has a good brandvalue in this sector. But now, because ofrapid growth, the credit requirement ofSKS has grown tremendously. For thisreason it is on the lookout forinternational lenders and for funds fromthe capital market. Keeping this in mind,SKS has decided to go in for a CRISILrating this year. The reason given for thisby Jennifer Leonard, VP Finance, SKSwas that CRISIL has a wider appeal thanM-CRIL, which extends beyond themicrofinance sector in India. For globaltransactions, SKS would go in for a ratingby Fitch in the future, she said.

Among the things that MFIs did not likeabout the raters’ methodology was thelack of flexibility in adapting themethodology to the local context. Thereis a demand and a need for a flexiblerating model that provides reasonablescope for customisation according to the

needs of the client MFI. This point wasbrought to light by ASP and Sharada’sWomen’s Association for Weaker SectionIt was felt that the current rating modelsare too rigid in their approach.

An often repeated complaint of the MFIsregarding the rating agencies is the lackof interaction between MFIs and fieldworkers. The raters only interview boardmembers and do not interact much withthe field staff and SHG members. TheMFIs felt that to get the full picture, theraters should interact more with thepeople working at the grass-roots levelin the organisation. According to them,the time spent on site was too short. TheMFIs also expressed the need for moreexperienced and professional raters.Grameen Koota, ASP, Ujjivan, andSharada’s Women’s Association forWeaker Section were not satisfied withthe qualifications and field experiencesof the raters. In their opinion, the ratershad not been in this field long enough tounderstand the intricacies of themicrofinance sector well.

In addition, some MFIs like GrameenKoota felt that there is a lack of practicalrecommendations in the final report. TheCEO of Grameen Koota expressed theview that the rating does not bring outanything new for them. It only helps toconfirm what the organisation alreadyfeels and knows about its strengths andweaknesses. Thus, there are no surprisesin the rating report for the organisation.MFIs feel that too much attention is paidto past activities and operations and that


not enough attention is paid to the futureprospects of the organisation.

Another dimension brought to light wasby ASP. ASP pointed to the fact thatcurrent ratings are not suitable formeasuring the performance of a co-operative. A separate rating model isrequired for co-operative-based MFIs.APMAS with a strategic alliance with M-CRIL is catering to this niche market.

Grameen Koota brought forth the issuethat the ratings done, especially thoseconducted by M-CRIL, are tooconservative in their projections. TheCEO of Grameen Koota said that thereis a need for a more optimistic outlook.He said that the degree of awarenessamong MFIs about their weaknessesshould also be considered in the rating.

With regard to the issue ofbenchmarking, MFIs (Grameen Koota,Ujjivan) expressed the view that it ishelpful, but added that it should be donewith respect to legal form as well as tothe geographical environment in whichan MFI is operating. Benchmarkingshould also be done on the socialperformance of the MFI. The need forsensitivity analysis, competitor analysis,and environment analysis in the ratingreports was expressed by Ujjivan.

5.2 Feedback of Banks and Investors onRatings

Investors require a rating report beforeinvesting in an MFI. Investors use reportsmostly for initial background screening,monitoring, and investment picking. All

of them consider rating reports ascomplementary to their own duediligence. For example, ICICI carries outan internal assessment procedure to findout the credit worthiness of an MFI. Thisconsists of nine-point assessment criteria;it generally checks the history of thecredit performance and reliability of thepromoters. Investors save some due-diligence time by using rating reports.The most useful sections in rating reportsare credit risk, PAR, portfoliocomposition, profitability and efficiency,internal risks, management, principalprocess, and systems. Investors wouldlike to see more information on cash flowand solvency projections; socialindicators and impact; country risk;interest rate risk; and law, regulation, andfinancial markets. The importanceattributed to the grading in rating reportsvaries. It was stressed that grades couldbe very useful, but only when the reportsare standardised and are based onprobability of default. In general,investors use and appreciate access torating reports, but would prefer it ifrating reports adopted a morestandardised format. At present, thereseems to be too much diversity in themethodology used by specialised raters,which is confusing for investors who arenot familiar with the different ratingagencies.

5.3 Feedback of NABARD on Ratings

Through its funding requirements, SIDBIhas contributed significantly to thedemand for ratings by MFIs, thus


enhancing transparency in the sector.NABARD has recently followed suit withthe establishment of the MFI GradingScheme in partnership with CRISIL,whereby it agrees to fund the ratings ofsmall and medium-sized institutions withthe purpose of increasing the amount ofbank credit available to them. Under thisscheme, small and medium-sized MFIsand their potential bank partners arereimbursed for the professional fee ofobtaining an MFI grading from CRISIL.The most extensive information on themicrofinance sector is held by SIDBI (40MFIs) and NABARD (>100 suchorganisations).

According to Mr Krishnan Jindal, DeputyGeneral Manager, one of the key factorsfor the success of MFIs is their capacityto deliver. The success of an MFI restson two pillars: scale and sustainability.Scale refers to the MFI’s reach among thetarget market, or clientcoverage. Sustainability refers to the costof providing financial services aftersuitable adjustments have been made.Some of the problems faced by MFIs inthis context are: weak institutionalcapacity; lack of a viable and sustainabledelivery system; relatively small financialbase; and huge investment requirementsin staff training and client orientation.These constraints militate against anyattempt to reach a greater number of thetarget clientele in an effective andefficient manner. Another point is thatin the very short run, MFIs may be ableto expand their present reach because ofdonations and other subsidies, but unless

they become viable and sustainable, theeffort cannot be sustained. The aboveproblems faced by MFIs are the key riskfactors that need to be assessed inevolving a suitable rating methodologyfor them.

5.4 Feedback of Unitus on Ratings

The opinion of Unitus was that for anyMFI rating model to be successful, therating parameters need to bestandardized in line with the CGAPguidelines on financial ratios. Unituspersonnel also expressed the view thatthe rating market in India is now matureenough to bear some cost of the ratings.Nevertheless, funding would be requiredfor some more time.

6.0 KEY CHALLENGES FACINGMICROFINANCE ASSESSMENTS

Microfinance assessments can contributeto improving transparency in the field ofmicrofinance. However, we realised thatseveral challenges with regard to ratingsrequire attention: improving information,standardising indicators and definitions,increasing the frequency of assessments,and reducing their costs.

6.1 Improving information

Microfinance assessments begin with theinformation provided by the MFI in itsfinancial statements and operationalrecords. However, this information isnot always accurate or complete. Theindustry has much work to do indeveloping appropriate and reliableinternal information systems, as well as


strengthening internal controls andaudits.

6.2 Standardising indicators and theirdefinitions

It has been found that widely agreedupon definitions exist only for a fewterms, such as average loan balance,operational efficiency, adjusted return onassets, adjusted return on equity, andreturn on average assets. The resultingconfusion leads to frequentmisinterpretation of indicators.Definitions of indicators will have to beclarified and standardised so that themicrofinance industry can have alanguage for evaluation that everyone canspeak and understand.

6.3 Increasing frequency of reporting

MFI assets tend to be short term, withloan terms as short as three months.Because micro loans are typicallyunsecured, loan repayment can be muchmore volatile in the case of MFIs than inthe case of commercial banks. Thus, thefinancial position of MFIs can deteriorateseriously over the course of a month ortwo. In light of this, the prevailingreporting cycles for MFIs—quarterly,semi-annual, or even yearly—are oftennot frequent enough. This pattern makesit hard to monitor MFIs effectively. Inaddition, once an MFI has been rated orevaluated, the report is meaningful onlyfor a short period of time, generally forone year. From an investor’s point ofview, a yearly update is a minimumrequirement, since the volume and typeof financing needed by an MFI—as well

as the risk of that MFI—are changingcontinuously.

6.4 Reducing costs of assessments

The cost of rating an MFI according tobest standards is estimated by ACCIÓN,Micro Rate, and Planet Finance atbetween US$5,000 and US$25,000 InIndia, the M-CRIL rating costs around Rs2 lakh, while the CRISIL rating costsaround Rs 9 lakh. Most of the ratings arestill subsidised by either SIDBI orNABARD. Thus, there is a need forcoming up with new rating agencies thatcan deliver ratings at a reasonable cost.The challenge for the agencies is to re-engineer their assessment systems,reducing costs without unduly loweringquality standards.

7.0 KEY FINDINGS

• This study of different MFI ratingagencies and their methodologieshas brought out several key issuespertaining to ratings. The first issuerelates to the current scenario ofrating in India. In India, there areonly two players active in the ratingmarket. These are M-CRIL andCRISIL. Between the two, M-CRILhas done the majority of the ratings.The factors that have contributed toits popularity are lower pricing anda good brand name, which comesfrom being an established andspecialised rating agency.Interactions with MFIs revealed thatthe key factors that could provide acomparative advantage to a newrating agency in India are pricing,


time taken, and field experience ofrater personnel.

7.1 Social Ratings

Credit rating and global risk assessmentboth pay more attention to the financialsustainability of the organisation.Though financial sustainability is nodoubt important, it reveals only half ofthe microfinance story. Most of the MFIsalso have a social mission, such asproviding credit support to familieshitherto excluded from the bankingsector and thus reducing theirvulnerability and poverty. Thus, theperformance of any MFI needs to beunderstood in the context of its socialmission in order to get a completepicture.

This gap is sought to be filled by socialratings. Social rating basically assesseshow far an MFI has been able to achieveits social mission in accordance withaccepted social values. Thus, credit ratingcombined with social rating enables acomparison of both the financial andsocial performances of MFIs. In this way,social rating helps in assessing the doublebottom line of MFIs. Thus, it serves threepurposes. First, it is a useful aid for bothinvestors and donors in evaluating anMFI and accordingly making effective useof their microfinance resources in termsof investments in this sector. Second, italso helps MFIs in improving their socialperformance just as credit ratings helpthem in improving their financialperformance by providing a valuablebasis for assessment. Third, it helps in

benchmarking social performance acrossthe whole microfinance industry.

Previously, only two MFI ratingagencies—MicroFinanza and PlanetRating—used to provide social ratings.But seeing its potential and the demandfrom both MFIs and donors, M-CRIL hasrecently introduced a social ratingproduct to meet this requirement ofvarious interest groups.

8.0 CONCLUDING REMARKS

In recent years, the demand formicrofinance ratings has increased inboth India and abroad. In India, althoughat present only M-CRIL and CRISIL areactive players in this market, there isroom for new entrants, which wouldensure healthy competition. Many ratingagencies have invested in productdiversification and have expanded therange of services they offer to meet thenew demands of MFI clients. Realisingthe importance of meeting the specificrequirements of the microfinance sector,many specialised rating agencies are nowextending their range of rating servicesto include social performanceassessments for donors and MFImanagement, and mini-ratings forsmaller and/or younger MFIs that arenot yet ready to go in for a full-fledgedrating. Other add-ons like institutionaldiagnostics, country analyses, andinvestment fund ratings are beingincorporated currently into the ratingreport to present a more holistic view.As a result of this product diversificationand the expansion into new areas,


competition among the rating agencies,especially in India, is expected to becomemore intense.

The development of MFIs has in turn ledto the emergence of specialised MFIrating agencies. These agencies play avery important role as they providevaluable information to both donors andinvestors about MFI performance. Bydoing so, they contribute to promotingtransparency in the microfinance sector,which is an indispensable quality. Thus,for the development of the microfinancesector, ratings should be encouraged asthese are beneficial for every stakeholderin this field.

REFERENCES

ACCION (2006) “Accion Camel,” Accessed fromthe website of ACCION, http://www.accion.org/camel.asp

CGAP (2003) “Definitions of Selected FinancialTerms, Ratios, and Adjustments forMicrofinance” Accessed from the website ofhttp://www.cgap.org/portal/binary/com.epicentric.contentmanagement.servlet.ContentDel iveryServle t/Documents/Guideline_definitions.pdf MicrofinanceConsensus Guidelines, September 2003.

CRISIL (2006) “The NABARD-CRISIL MFIGrading Scheme,” Accessed from the websiteof CRISIL, http://www.crisil.com/credit-ratings-risk-assessment/nabard-crisil-mfi-grading-scheme.htm

Ghate, Prabhu (2006) “Microfinance in India: AState of the Sector Report, 2006,” Accessedfrom the website of Microfinance India,w w w . m i c r o f i n a n c e i n d i a . o r g /index.asp?P=L&ID=38

M-CRIL (2006) “Rating of MicrofinanceInstitutions,” Accessed from the website ofM-Cril, http://www.m-cril.com/services.html

Microfinance Rating and Assessment Fund(2006) “Microfinance Ratings: RaisingAwareness Among MFIs.” . Accessed fromthe website of Rating Fund,w w w . r a t i n g f u n d . o r g /document_view.aspx?id=79

MICROFINAZA (2006) “Microfinanza Rating,”Accessed from the website of Microfinanza,www.microfinanza.com/Site/Inglese/Services.htm

MICRORATE (2006) “The MicroRateMethodology,” Accessed from the websiteof Microrate, http://www.microrate.com/rat-metho.html

MixMarket (2006) “Partners (MarketFacilitations)”, Accessed from the website ofThe Mix Market, http://w w w. m i x m ar k e t . or g /e n /p a r t n er s /partners.quick.search.asp

Planet Rating (2006) “GIRAFE methodology,”Accessed from the website of Planet rating,ht tp: //w ww. pla net ra t ing .co m/E N/methode.php

Rating Fund (2005) “Key data on the MF RatingIndustry and the Rating Fund-II Forum onMFI Ratings: Towards a Sustainable Market.”Accessed from the website of Rating Fund,w w w . r a t i n g f u n d . o r g /document_view.aspx?id=42

Rating Fund Market Survey (2005) “TheMicrofinance Rating Market Outlook.”Accessed from the website of Rating Fund,w w w . r a t i n g f u n d . o r g /document_view.aspx?id=70

http://www.accion.org/camel.asp

http://www.cgap.org/portal/binary/

http://www.crisil.com/credit

http://www.m-cril.com/

http://www.microfinanza.com/Site/Inglese/

http://www.microrate.com/

http://www.mixmarket.org/en/partners/

http://www.planetrating.com/EN/


Rosenberg, Richard (2003) “Core performanceindicators for Microfinance,” Accessed fromthe website of CGAP, http://cgap.org/p o r t a l / b i n a r y / c o m .epicentric.contentmanagement. servlet.ContentDel iveryServle t/Documents/Core_Performance.pdf

Rosenberg, Richard et al (2003) “Microfinanceconsensus guidelines: Disclosure guidelinesfor financial reporting by microfinance

institutions,” Accessed from the website ofCGAP,

h t t p : / /w w w . t h e m i x . o r g / s t a n d a r d s /CGAP_2003_Microfinance_Consensus_Guidelines_Disclosure.pdf

Sinha, Sanjay et al (2003) “Risk management inmicrofinance: How M-CRIL supports theprovision of financial services to low incomeclients,” Accessed from the website of M-CRIL , http://m-cril.com/publications.html

http://cgap.org/

http://www.themix.org/standards/

http://m-cril.com/publications.html


APPENDIX 1LIST OF ABBREVIATIONS

APMAS Andhra Pradesh Mahila Abhivruddhi Society

ASP Ankuram-Sangamam-Poram

BSS Bharatha Swamukti Samsthe

CEE Central and Eastern Europe

CEO Chief Executive Officer

CERISE Centre for Russian International Socio-Political and Economic Studies

CGAP Consultative Group to Assist the Poor

FSS Financial Self-Sufficiency

ICICI Industrial Credit and Investment Corporation of India

M-CRIL Micro-Credit Ratings International Ltd

MENA Middle East and North Africa

MFI Microfinance Institution

NABARD National Bank for Agriculture and Rural Development

NBFC Non-Banking Financial Company

NGO Non-Governmental Organisation

NIS Newly Independent State

OSS Operational Self-Sufficiency

RBI Reserve Bank of India

RoA Return on Assets

RoE Return on Equity

SHG Self-Help Group

SIDBI Small Industries Development Bank of India

SKS Swayam Krishi Sangam

SPA Social Performance Assessment

VP Vice President


APPENDIX 2List of Stakeholders Interacted with

Name of Organisation Place Name of PersonInteracted with

MFIs

1. SKS Hyderabad Jennifer Leonard, Vice President,Finance

2. Ujjivan Bangalore Ajit GrewalDirector

3. Mahila Abhivruddhi Society Hyderabad S. Rama LakshmiAssociate VP,Andhra Pradesh (APMAS) Quality Assessment

4. Ankuram-Sangamam- Secunderabad J. NeelaiahCEOPoram (ASP)

5. Sharada’s Women’s Secunderabad Ramamurthy S.GeneralAssociation ForWeaker Section Manager

6. Grameen Koota Bangalore Suresh K. K.CEO

7. Bharatha Swamukti Bangalore G. C. Swamy Project ExecutiveSamsthe (BSS)

8. Outreach Bangalore Radhakrishnan A. C.ProjectManager, MF Activities

BanksUNITUS Bangalore Abhijit RayCapital MarketsNABARD Mumbai Krishnan Jindal Deputy

General Manager

Factors Affecting Emotional Intelligence:AnEmpirical Study for Students of Secondary

School and Professional Colleges*

Shamira Malekar1 & R.P.Mohanty 2

Abstract

Researchers and human resource management professionals across the world are actively engaged instudying emotional intelligence (EI) and its applications in various organizational settings to improvemanagerial performance. It is found from literature that a very few studies are available relating to theapplication of EI among the school and management students. This paper is an attempt in that directionto make a comparative empirical study to identify important determinants of EI in students of professionalcolleges and secondary certificate schools in the metro city of Mumbai. Such a study has the potential tocontribute in providing feedback to the parents, academicians and other authorities to better meet thefuture needs of the society.

* Received November 11, 2007; Revised February 18, 20081. Research Scholar, Institute for Technology and Management (ITM) Group of Institutions,

Mumbai, email: [email protected]. Dean and Adviser, Institute for Technology and Management (ITM) Group of Institutions,

Mumbai, email: [email protected]

1.0 INTRODUCTION

Emotional intelligence (EI) has emergedas an important subject of researchinvestigation during the last severalyears. Some of the pioneeringresearchers have defined EI as follows:

“Emotional intelligence is the capacityfor recognizing our own feelings andthose of others, for motivatingourselves, and for managing emotionswell in ourselves and in ourrelationships. Emotional intelligence

describes abilities distinct from, butcomplementary to, academic intelligenceor the purely cognitive capacitiesmeasured by IQ” (Goleman, 1998).“Emotional intelligence is the ability toperceive emotions, to access andgenerate emotions so as to assistthought, to understand emotions andemotional knowledge, and toreflectively regulate emotions so as topromote emotional and intellectualgrowth” (Mayer and Salovey, 1997).“Emotional intelligence reflects one’s




ability to deal with daily environmentchallenges and helps predict one’s successin life, including professional andpersonal pursuits”(Bar-On, 1997).“Emotional intelligence is a way ofrecognizing, understanding andchoosing how we think, feel and act. Itshapes our interaction with others andour understanding of ourselves. Itdefines how and what we learn, it allowsus to set priorities, it determines themajority of our daily actions” (Freedman,1998).

All these pioneering definitions lead usto conclude that EI is important inshaping one’s personality, behaviour,style and abilities. EI has been studiedscientifically in the past decade.Goleman’s 1995 book “EmotionalIntelligence” substantially added to thepopular interests in accumulatingknowledge regarding EI.

Business organizations have used EI fororganizational development and forenhancing organization effectiveness(Lowe, Kroek, and Sivasubramaniam,1996). EI improves managerial practicesas well as helps in leadershipdevelopment (Druskat and Wolff, 2001).EI is often used to motivate employeesand to create a culture of highperforming work place. Huy (1999)introduced the concept of emotionalcapability to capture an organization’sability to acknowledge, recognize,monitor, discriminate, and attend to itsmembers’ emotions, and it is manifested

in the organization’s norms androutines related to the feeling.

Further, EI has been used as a predictorof ability by parents as it has been foundto be a predictor of life satisfaction,healthy psychological adaptation,positive interactions with peers andfamily, and higher parental warmth(Warwick and Nettelbeck, 2004).

EI has also been used in education tolay the foundations to bu ild thecul ture of a school committed tolearning (Parker 2004). Every childenters the world wi th a uniquecombination of components ofemotional inte ll igence such as:emotional sensit ivity, emotionalmemory, emotional processing andproblem solving ability, emotionallearning ability (Mayer, 2000). Theway a child is raised can dramaticallyaffect what happens to the potentialin each of these components. Forexample, if a child is born with a highpotential for the arts, but is nevergiven a chance to develop thatpotential, the world may miss out onthis person’s special gift. Childrenraised in an emotionally abusive homeor from a lower economic strata homemay use their emotional potential indestructive ways later in their lives.

We have observed from an extensivesurvey of literature that a lot of studieshave been conducted to measure EI andtesting its validity with business

25

organizations. We find a very littleevidence of EI application for schoolstudents and students of B- schools.There are studies that demonstrate thelink between EI and academicachievement in students makingtransition from high school to a postsecondary environment (Parker et al.2004). A finding by Newsome, Day andCatano (2000) and Van der Zee et al(2002) proves that EI is uncorrelated tocognitive ability relating to academicperformance (cited in Petrides et al2004). Another study by Reiff et al 2001showed that students with learningdisabilities had lower EI scores thantheir non disabled counterparts. Wecould find that no study is available todemonstrate the importantdeterminants of EI amongst the schoolstudents of age group 9-14 years.Therefore, we attempt here to measureEI by modifying Bar – On and Parkar’sEmotional Quotient Inventory YouthVersion questionnaire (EQi YV). Wealso compare the EI levels of schoolstudents with professional student’sage group 22 - 27 years whosemeasurement is done with Bar – On’s(1997) Emotional Quotient Inventory(EQi)

We attempt here to measure EI of schooland professional college students comingfrom different socio-economicbackgrounds and a large metro city likeMumbai. We intend to understand theimportant determinants of EI and

evaluate the strength of each factor. Wealso intend to develop a normativeempirical relationship of EI with keyfactors with a comparative study ofstudents of professional colleges andsecondary certificate school.

2.0 FACTORS AFFECTING EI

Salovey and Caruso (2000a) categorizedmodels of EI into two types; namelyability model (Mayer and Salovey 1997)and mixed trait ability (or personality)model (Bar-On 2001; Goleman 1995, 1998;Petrides and Furnham, 2001).

According to ability models, EI is aform of intelligence involving cognitiveprocessing of emotional informationand is defined as a set of cognitiveabilities in emotional functioning.Ability models conceptualizeintell igence that involves emotion(cited in Goldenberg et.al 2006). Suchmodels define EI in a traditional sense(e.g. Mayer and Salovey 1997). They area conceptually related set of mentalabilities with emotions and processingof emotional information. Emotionalperception and expression, emotionalfacil itation of thinking, emotionalunderstanding and emotionalregulation are the essential elements ofthe ability model. They contribute tological thought and intelligence ingeneral. Ability model proposes thatemotions can make thinking moreintelligent and can intelligently handleemotions. EI has a number of

Malekar et.al, Factors affecting emotional ...


similarities to other types ofintelligences and abilities and developwith age and experience.

In comparison, mixed trait abil itymodels have EI as partly or wholly apersonality-like trait, or behaviouraldisposition. They define EI as amixture of emotion relatedcompetencies and personality traits.Mixed trait ability models also makereferences to abilities in the processingand use of emotional information butcombine these abilities with other traitsand characteristics such as optimism,motivation and social relationships(Bar-On, 2000, 2001; Goleman 1995,1998). Mixed trait ability models areimportant as they acknowledge theimportance of multiple aspects ofpersonality that may pertain toemotion. They do not relate to theconcept of emotion specif ically(Matthews, Roberts and Zeidner, 2004).

Bar- On (2000) has identified 5 factors,such as intrapersonal abil ity,interpersonal abil ity, stressmanagement, adaptability and generalmood. Here we are using factorsoutlined by Bar-On to find out therelationship of emotional intelligencewith interpersonal abil ity,intrapersonal abil ity, stressmanagement, adaptability and generalmood tested with students ofprofessional colleges and secondarycertificate schools.

Intrapersonal ability

Shearer (2006) defined intrapersonalability as an ability to think about andunderstand one’s self, to be aware ofone’s strengths and weaknesses and toplan effectively to achieve personalgoals, reflecting on and monitoringone’s thoughts and feelings andregulating them effectively. It’s theability to monitor one’s self ininterpersonal relationships, be aware ofand understand one’s emotions,feelings, and ideas and to act withpersonal efficacy. It consists of relatedabilities like recognizing and labelingone’s feelings. Intrapersonal abilityincludes emotional awareness and theability to identify them correctly.Individuals scoring high onintrapersonal ability tend to understandtheir emotions and are able to expressand communicate their feeling andneeds.

Interpersonal ability

It is defined by Shearer (2006) as theability to recognize the feelings of otherpeople that are facilitated by linguisticskill. It’s the ability to be aware of andunderstand others’ emotions andfeelings. Skill in managing relationshipswith other people is also a factor inone’s overall mood and emotional well-being. It consists of related abilities likeidentifying emotions in others andhaving empathy towards others.Interpersonal ability deals with therelationship with peers, subordinates

27

and superiors. High on theinterpersonal ability are likely to havesatisfying interpersonal relationships,are good listeners and are able tounderstand and appreciate the feelingsof others.

Stress Management

It is defined as the ability to be flexibleand alter one’s feelings with changingsituations (Day and Livingstone 2005).It consists of abilities like delaying orresisting an impulse. Those with highstress management are generally calmand work well under pressure; they arerarely impulsive and can usually respondto a stressful event without an emotionaloutburst.

Adaptability

Day and Livingstone (2005) definedadaptability as the abi l ity to beflexible and alter one’s feelings withchanging situations. It consists ofabilities like being to adjust one’semotions and behaviuor to changingsituations or conditions. Adaptabilityinvolves skills related to managementof change. Managing change involvesthe abil ity to manage stressfulsituations in a relatively calm andproactive manner. Individuals whoscore high on this d imension areimpulsive rarely and work well underpressure (Bar –On, 1997, 2000, 2002).Individuals with high adaptabilityscores are f lex ible , realis tic andeffective in managing change; good at

finding positive ways of dealing witheveryday problems.

General mood

It is defined as the ability to feel andexpress positive emotions and remainoptimistic (Bar –On, 1997). It representsthe ability to enjoy life and maintain apositive disposition. Higher levels ongeneral mood feel satisfied with theirlives and maintain a positive outlook.Happiness and Optimism are two aspectsof general mood including maintenanceof positive aspects and brighter side oflife.

Measures of EI

A number of assessment devicespurporting to measure EI have beendeveloped. The devises differ in twosignificant ways:

1. They are based on differentconceptual frameworks.

2. They use different measurementapproaches including performancetests, self report inventories orobserver ratings.

Thus, there has been a lot of debateconcerning the most suitable method tobe used for measuring EI. Some haveargued that measurement approachrather than the theoretical approachultimately determines the nature of EImodel being assessed (Matthews et al2004; Petrides and Furnham 2000). It isargued that performance measures aremore valid if EI is a type of ability,



whereas self-report instruments can beused if EI is viewed of comprising anumber of non ability related traits orattributes (Goldenberg et al 2006).

Thus, the measures of EI for the agegroup 8 - 18 years similar to ability andmixed trait ability models are classifiedas: a. performance based measure of EIb. self-report measures of EI.

a. Performance based measures of EIpertain to ability models for instanceMayer, Salovey, Caruso EmotionalIntelligence Test (MSCEIT YV) byMayer, Salovey and Caruso (2006) whichis yet in the sampling stage.

b. Self-report measures are pertaining tomixed models of EI. They aredetermined to assess emotions within thepersonality framework and to assesscross - situational consistencies inbehaviour (Petrides and Furnham 2000)for instance Emotional quotientinventory: Youth Version (EQ-i YV) byBar-On and Parker (2000)

For adults above 18 years performancebased report measures of EI were:

• The instrument most stronglymodeled on this theory is theperformance-based Mayer-Salovey-Caruso EmotionalIntelligence Test (MSCEIT; Mayeret al., 2002a).

• The EARS - Emotional AccuracyResearch Scale by Mayer andGeher, (1996) modified by Geher,

et al . , (2001) assesses a singleconstruct rather than the fourbranches.

Similarly, adult self-report measures ofEI were:

• Personal excellence inventory(PEI)of Nelson and Low (2003). Ana-priori self-report instrumentintended to extend the educationmodel of emotional intelligence.

• Robert Cooper’s (2000) EQ mapdivides EI into 5 attributes -emotional literacy, emotionalcompetency, EQ values, EQattitudes and EQ outcomes.

• Schutte et al. (1998) developed a 33– item Emotional Intelligence Scale(EI scale) for use with olderadolescents and adults. Thequestionnaire was derived from theSalovey and Mayer (1990) model ofEI, but is often referred to as ameasure of trait EI because it reliesupon self-perceptions of ability(MacCann et al., 2003).

• A measure of workplace EI is theSwinburne University EmotionalIntelligence Test (SUEIT) of Palmerand Stough (2001) (cited in Palmeret al 2002). The SUEIT gives scoreson five facets of EI: emotionalrecognition and expression,understanding emotions, emotionsdirect cognition, emotionalmanagement and emotional control.

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• The Benchmark of OrganizationalEmotional Intelligence (BOEI) is apowerful organizational survey – aself report measure designed byStein (2006). BOEI analyses jobhappiness, compensation, work / lifestress management, organizationalcohesiveness supervisoryleadership, Diversity and angermanagement and organizationalresponsiveness.

• Assessing emotions scale (AES) isalso a measure to test EI devised bySchutte et al (1998). (cross validationof a modifies version by Austin et al2004) It contains 33 items measuringappraisal and expression of emotion,utilization of emotion and regulationof emotions.

3.0 REVIEW OF LITERATURE

EI has attracted a lot of interest inacademic literature (cited in Petrides2004). The roots of EI can be traced backto the concept of ‘social intelligence’coined by Thorndike (1920) to refer tothe ability to understand, manage andact wisely in human relations. Gardner(1983) introduced the concepts ofintrapersonal and interpersonalintelligence. EI as a concept has beenincluded in literature by Salovey andMayer (1990). Along with Goleman’s1995 best selling book, there has been alead article in the same year by Gibbsin TIME magazine. Thereafter articleson EI began to appear with increasingfrequency with empirical work on the

construct along with scientif ictheoretical literature.

Proponents of mixed models of EI (e.g.,Bar-On, 1997, Cooper and Sawaf, 1997,Goleman, 1995; 1998) have typicallybeen the most vocal in making claimsabout the predictive promise of EI andwhat EI means in terms of ‘life success’.These models have generally appearedto assume that just about any variableother than IQ that has been found toshow propensity towards predictingsome degree of success (i.e., higherincome, more frequent promotions,higher academic achievement, highertertiary attainment, more satisfyinginterpersonal relationships and betterphysical and psychological health) isrepresentative of EI. The field of EI,however, is still relatively new andthus many of these claims have notbeen substantiated. Furthermore,many such claims appear to beunrealistic and to extend beyond whatcould be reasonably attributed to theEI construct.

On the basis of this research on schoolstudents in the western context, EI hasbeen found, among other things, to bepositively correlated with relations withothers, perceived parental support andfewer negative interactions with closefriends (Lopes et al., 2003); pro-socialbehaviour, parental warmth andpositive peer and family relations(Mayer et al., 1999); more optimism(Schutte et al., 1998); higher empathic



perspective taking and self-monitoringin social situations, higher social skills(Schutte et al., 2001). Additionally,negative correlations have been reportedwith illegal drug and alcohol use, defiantbehaviour and poor relationships withfriends (Brackett et al., 2004),unauthorised absences and exclusionsfrom school (Petrides et al., 2004) anddepression (Dawda and Hart, 2000;Schutte et al., 1998).

EI proponents also claim that familysocialization practices determine thedevelopment of EI in children (Saarni1999,2000; Salovey and Sluter 1997)Parental socializations has been found toimpact directly child’s social andemotional competency as well as workindirectly on the understanding ofemotions and gaining social knowledge(Cited in Zeidner et al 2002). Parentalsocializations take effect through explicitlessons or informal conversations aboutregulation of emotion. Parentalinfluences also occur through the child’sobservational capacity. The basicassumption is that a child whose parentdisplays constructive EI relatedbehaviour in everyday life is most likelyto implement it as a part of its ownbehaviour. In addition to parents, schoolsetting is one of the most importantcontexts for learning emotional skills andcompetencies (Mayer and Salovey 1997).In the process of emotional learning theindividual develops the aptitudes, skills,attitudes and values necessary to acquire

higher emotional intelligence. Mayer andGeher (1996) hypothesized that thosewho are low in emotional intelligencecould be educated to recognize, expressand regulate their feelings better. In thispaper, we have tested Bar–On andParker’s questionnaire of EI in the Indianschool students and differentiated theEQ levels of school students (9-14 yrs)primarily focusing upon to provide arelationship between its factors. We haveattempted to identify these factors,which could be implemented fordirecting students to attain higher EI. Wehave also attempted to compare EQ levelof school and professional collegestudents and assert that similarrelationship exists between EI and itsfactors for professional students in theage group of 22 - 27 years. To achieveour final aim, we have tested Bar–On’s(1997) questionnaire of EI in the Indianprofessional college students and alsodifferentiated the EQ levels.

4.0 DESIGN OF EXPERIMENT

This statistical experiment designed inthe study involves the use of correlationcoefficients determination followed bymultiple regression analysis. It helps inassessing the individual and thecombined effect of independentvariables (factors) on the dependentvariable (EQ).

4.1 Participants

The sample consisted of a total numberof 948 students of Anjuman Islam’sAllana High School (Muslim Trustees

31

Board), Sir Jacob Sassoon High School(Jewish Trustees Board), Sharon HighSchool (Christian Trustees Board) andGandhi Shikshan (Hindu TrusteesBoard). The sample also consisted of atotal number of 319 professional collegestudents of Institute of Technology andManagement (1st year Post GraduateDiploma in Business Administration) andInstitute for Management and Computerstudies (1st year Master in Managementstudies and 1st year Master in ComputerApplication).

4.2 Procedure

Participants were asked if they wouldvolunteer to study on “emotionalintelligence”. Participants completed theBar-On Emotional quotient inventory:Youth Version (EQi YV) (Bar - On andParker, 2000) or the Bar-On’s (2000)Emotional quotient inventory (EQi) inJuly and August 2005 depending on theirage.

School students who participatedcompleted the EQi:YV during a zeroperiod in the premises of their school. Inexchange for their participation,individuals were provided with aconfidential feedback report on theirresults of the instrument. Similarly,professional college students were alsoasked to complete the EQi after theirlecturing hours in the premises of theirinstitute. In exchange for theirparticipation, individuals were providedwith a confidential feedback report ontheir results of the instrument.

4.3 Measures

The EQ-i;YV is a 60 item self-reportmeasure of EI developed by Bar-On andParker (2000).Children and adolescentsbetween the ages of 9 and 14 are askedto respond to the statements which bestdescribe the way they feel, think, or actin most situations. Responses are ratedby the participant on four-point Likertscales, ranging from 1 for ‘’very seldomor not true of me,’’ to 4 for ‘’very oftentrue or true of me.’’ The instrument hasa 6-item intrapersonal scale, a 12-iteminterpersonal scale, a 12-item stressmanagement scale, and a 10-itemadaptability scale. Along with a total EIscale (the sum of the four previousscales), the EQ-i;YV also has a 14-itemgeneral mood scale and a 6-itempositive impression validity scale. Ahigh score on any individual ability scale(or the total score) reflects a high levelof social and emotional competency.Bar-On and Parker (2000) report thatthe EQ-i;YV has a replicable factorstructure (developed with a normativesample of 9172 school-aged children andadolescents); the various scales on theinstrument correlate highly withcomparable scales on the adult versionof the inventory (the EmotionalQuotient Inventory; Bar-On,1997).

The EQ-i is a 133 item self-reportmeasure of EI developed by Bar-On(1997). Professionals between the agesof 22 and 27 are asked to respond tothe statements which best describe theway they feel, think, or act in most



situations. Responses are rated by theparticipant on five-point Likert scales,ranging from 1 for ‘’very seldom or nottrue of me,’’ to 5 for ‘’very often trueor true of me.’’ The instrument similarto its YV has an intrapersonal scale,interpersonal scale, stress managementscale, adaptability scale and generalmood scale.

4.4 Computation of EI scores.

We computed the scores with the aid ofSPSS statistical package and Excel worksheets. EI scores of school students hadto be calculated by the methodologydeveloped by Bar –On and Parker (2000)for his youth version of the test. EI scoresof professional college students had tobe calculated by the methodologydeveloped by Bar –On (1997).

The sample size consisted of a totalnumber of 1062 students of 4 different

schools.115 students did not completethe main battery of measures andtherefore could not be considered.Hence, the main sample size got reducedto 948 students – all of them belongingto age groups 9- 14 years. 616 (64.97%)of respondents were male and 332(35.03%) female. Table-1 shows thedescriptive statistics of the individualswith its EI and its factors scoring sheetscores.

Table-1: Statistics for School students

Male Female Male Female Male Female Male Female

AGE 9 9 14 14 12.34 12.57 1.550 1.630

EQ 65 65 130 130 91.18 90.9 14.968 13.95General mood 65 65 122 122 87.92 88.54 15.094 15.876Adaptability 65 65 130 130 95.22 97.73 16.434 16.783Stress 65 65 126 126 88.31 87.55 13.474 12.543ManagementInterpersonal 65 65 125 125 90.06 90.88 16.949 17.989ability

Intrapersonal 65 65 130 130 97.85 96.32 14.425 14.025ability

Minimum Maximum Mean StandardDeviation

Table-1 denotes descriptive statistics ofEQ along with its factors having 65 aslowest score and 130 as maximum. Schoolstudents ranged from 9-14 years of age;the mean age was 12.34 years (SD1.55)for males and 12.57 years (SD1.63) forfemales.

The sample size of professional collegestudents consisted of a total number of356 students of 4 different schools. Thirty

33Malekar et.al, Factors affecting emotional ...

eight students did not complete the mainbattery of measures and therefore couldnot be considered. Hence the main samplesize got reduced to 318 students – all ofthem belonging to age groups 22- 27 yrs.195 (61.32%) of respondents were maleand 123 (38.679%) female.

Table-2 denotes descriptive statistics ofEQ along with it factors has 3 as lowestscore and 130 as maximum.

Professional college students rangedfrom 22 - 27 years of age; the meanag e was 2 5 .4 y ear s (SD 1. 25) f ormales and 24.57 years (SD1.36) forfemales.

5.0 RESULTS

A confirmatory Pearson’s Correlation isconducted as seen in Table-3 for Schoolstudents.

Table-2: Statistics for professional college students

Male Female Male Female Male Female Male Female

AGE 22 22 27 26 25.4 24.57 1.25 1.360

EQ 3 3 130 130 90.8 94.7 14.67 13.50General mood 2 2 75 75 62.92 61.4 15.94 15.86Adaptability 3 3 112 112 95.22 97.73 16.31 16.83Stress Management 2 2 81 81 68.31 67.55 13.44 12.43Interpersonal ability 3 3 124 124 90.6 90.8 15.49 13.99Intrapersonal ability 5 5 167 167 121.85 126.32 11.26 12.05

Minimum Maximum Mean StandardDeviation

Table-3: Correlations of EI and its factors for school studentsFactors*** 1 2 3 4 5 6

1 1 0.593(**) 0.660(**) 0.530(**) 0.707(**) 0.540(**)2 0.203(**) 0.368(**) 0.262(**) 0.245(**)3 0.135(**) 0.601(**) 0.639(**)4 0.209(**) 0.099(**)5 0.554(**)6 1

** Correlation is significant at the 0.01 level (2-tailed).*** 1 = EQ

2 = Intrapersonal ability3 = Interpersonal ability,4 = Stress management5 = Adaptability6 = General mood


As shown in Table-4 of correlations of EIand its factors for professional collegestudents, Intrapersonal ability hashighest correlation with EQ followed bygeneral mood similar to the studyconducted by Bar-On (2000). This is incontrast to correlations obtained forschool students in which adaptability hasthe highest correlation coefficient.

As the objective of this paper is toidentify and assess the effect of factors

on EI, the method of multiple regressionanalysis has been chosen, as it helps inassessing the individual and thecombined effect of independentvariables (interpersonal, intrapersonal,adaptability, stress management,general mood) on the dependentvariable (EQ).

The steps used in conducting theregression analysis on the above sampleof school students are as follows:

There is a range of correlation coefficientsbetween the factors as described below:

1. Adaptability realm has highestcorrelation with EQ followed byinterpersonal ability compared to thestudy conducted by Parker et al (2004)where r = 0.707 for adaptability and0.660 for interpersonal ability. In that

study the former correlates highestwith EQ.

2. Intra-personal ability correlatesmoderately with EQ and the extentto which stress management andgeneral mood correlate is nearly thesame similar to the study conductedby Parker et al (2004)

Table-4: Correlations of EI and its factors (Professional college students)

Factors# 1 2 3 4 5 6

1 1 0.869(**) 0.653(**) 0.850(**) 0.708(**) 0.863(**)

2 0.553(**) 0.766(**) 0.558(**) 0.755(**)

3 0.522(**) 0.308(**) 0.604(**)

4 0.679(**) 0.589(**)

5 0.751(**)

6 1** Correlation is significant at the 0.01 level (2-tailed).*** 1 = EQ

2 = Intrapersonal ability3 = Interpersonal ability,4 = Stress management5 = Adaptability6 = General mood

# Factors here are same as in Table - 3.

35

Firstly, School wise analysis with 5 factors(as explanatory variables) of EQ wasdone. The regression equation for schoolwise analysis with 5 factors is as follows:

Y = A + B1X1 + B2 X2 + B3 X3+ B4 X4 + B5 X5.......... + Ui (1)

Y = dependent variable representing theemotional intelligence

B1, B2, B3, B4 and B5 are the coefficients ofthe regression equation

X1 = Intrapersonal ability

X2 = Interpersonal ability

X3 = Stress management

X4 = Adaptability

X5 = General mood

Ui = Disturbance term

A = Constant term

The regression was then tested for itssignificance using F-test for theregression as a whole, ( i.e. to testwhether the EI is dependent on theIntrapersonal ability, Interpersonalabil ity, Stress management,adaptability and general mood at 5%level of significance. This was followedby t-test to test the significance of eachof the drivers at 5% level ofsignificance. The F-test results showedthat the regression as a whole wassignificant for the first 4 factors. Hence,in order to improve and get moresignificant results it was essential toomit the factors that were not

significant. From the t-ratios in theabove regressions, it could be seen thatgeneral mood was not a significantfactor of EI. Further the overall impactof General mood can be overcome byusing and calculating EI as a functionof the intrapersonal abil ity,Interpersonal abil ity, stressmanagement and adaptability byomitting general mood. So, regressionanalysis with 4 factors (as explanatoryvariables) of EI was carried out withthe following equation.

Y = A + B1X1 + B2 X2 + B3 X3+ B4X4 + ……… + Ui(2)

Table-5 summarizes the results of theregression analysis for 4 factors of EI.The following points are worthmentioning:

• The results were found to besignificant in the data of 948 schoolstudents.

• Four explanatory variables -intrapersonal ability, Interpersonalability, stress management andadaptability are significant factorsaffecting EQ. General mood does notseem to impact EI.

• General mood is not significantlyaffecting EQ and hence cannot beconsidered as a factor for schoolstudents.

The steps used in conducting theregression analysis on the sample ofprofessional college students are asfollows:



Firstly, Institute wise analysis with 5factors (as explanatory variables) of EQwas done. The regression equation forschool wise analysis with 5 factors is asfollows:

Y = A + B1X1 + B2 X2 + B3 X3+ B4 X4 + B5 X5 +.......... + Ui (3)

The regression was then tested for itssignificance using F-test for the

Table-6: Descriptive statistics with regression analysis for 5 factors of EI for professionalcollege students

Independent Unstandardized Standardized t Sig. F R SquareCoefficients Coefficients

Variables B Std. Error Beta 675.602 0.914(Constant) 7.492 1.612 4.646 .000*Intrapersonal .195 .016 .346 12.164 .000*Interpersonal .118 .015 .162 7.631 .000* Stress .200 .024 .195 8.490 .000Management* Adaptability .145 .026 .172 5.590 .000*General Mood ,311 .035 .260 8.827 .000

Dependent Variable: EQ

regression as a whole, (i.e. to testwhether the EI is dependent on theIntrapersonal ability, Interpersonalability, Stress management, adaptabilityand general mood at 5% level ofsignificance. This was followed by t-testto test the significance of each of thedrivers at 5% level of significance. TheF-test results showed that the regressionas a whole was significant for all 5 factors.

Dependent Variable: EQ

Table-5: Results of the regression analysis using four independent variables (4 factorsof EI for school students)

Independent Unstandardized Standardized t Sig. F R SquareCoefficients Coefficients

Variables B Std. Error Beta 1092.927 0.823(Constant) -28.151 1.874 -15.019 .000* Intrapersonal .336 .016 .324 21.444 .000* Interpersonal .301 .015 .341 19.826 .000* Stress .322 .017 .290 19.504 .000 Management* Adaptability .325 .016 .356 20.298 .000

37

Table-6 denotes the descriptive statisticsfor professional college students withregression analysis for 4 factors of EI.The following points are worthmentioning:

• The results were found to besignificant in the data of 318professional students.

• All the five explanatory variables -intrapersonal ability, interpersonalability, stress management,adaptability and general mood aresignificant factors affecting EQ.

6.0 CONCLUSION

In this paper, we have attempted todecompose EI into its factors and theyhave been statistically validated to testthe significance of each of the factorin 4 school students and 2 professionalinstitutes. The objective was to derivesignificant and consistent factors of EI.This paper also reviews theapplicabil ity of EI for the schoolchildren in Mumbai (age 9- 14 years)and arranges the factors affecting EIin descending manner. A comparativestudy is also done with studentsstudying for professional courses (age22 -27 years).

The following remarks are worthmentioning:

1. Results of the present study suggestthat adaptability, interpersonalability and intrapersonal ability areimportant factors affecting EQ forschool students.

a. Adaptability was found to be veryhighly significant with EQ withcorrelation coefficient of 0.707.

b. Secondly, interpersonal ability wasfound to be highly significant withEQ with correlation coefficient of0.660.

c. Intrapersonal ability was found to besignificant moderately with EQ withcorrelation coefficient of 0.593.

d. The EQ of students can be enhancedif the 4 factors identified in theregression model are strengthenedwith the help of inputs and trainingimparted to them.

e. General mood and stressmanagement were found to bemoderately significant with EQ withcorrelation coefficient of 0.540 and0.530 respectively.

2. Comparatively results ofprofessional students suggest thatadaptability, interpersonal ability,intrapersonal ability, stressmanagement and general mood areimportant factors affecting EQ incontrast to 4 factors for schoolstudents.

a. Intrapersonal ability was found tobe very highly significant with EQwith correlation coefficient (r) of0.869.

b. Secondly, general mood was foundto be highly significant with EQ withcorrelation coefficient of 0.863.



c. Stress Management was found to behighly significant with EQ withcorrelation coefficient of 0.850.

d. Adaptability has r = 0.708 andinterpersonal ability has r = 0.653 incontrast to school students whereinthese two factors have the highestcorrelation.

7.0 KEY LEARNINGS

This study is a guiding study insuggesting that without the measure ofmore intrinsic and complex humanbehaviour, setting up a correlation modelfor emotional intelligence with stronglyinfluencing factors can actually be alonger journey involving a study of theevolution of human values as we growphysically and mentally.

There is some scope as to whetheremotional intelligence in children can bedeveloped or it is innate – for if it is theformer, there is real hope in literallycatching them young as far as EI / EQ isconcerned.

In this study we have only identifiedfactors affecting EI of students andmeasured them at aggregate level.However, each factor can bedisaggregated or factored intoattributes at operational level. Suchstudies are available for adults (Bar-on1997) by following the samemethodology depicted in the self-report.

We have denoted that EI depends onthese 4 factors and if we implement it

in the form of training the future ofIndia, our students will be bright. Theemotionally intelligent leader evolvesinto someone with the ability to moveseamlessly from one approach or styleto another, allowing the requirementsof the situation and the resources athand to dictate what he or she needsto do.

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Singh, D. (2006), “Emotional Intelligence atWork”, Sage Publications, 3rd edition, pp 72,New Delhi.

Stein, S. (2006), as seen on the Multi healthsystems website – http://www.mhs.com/


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Exchange Rate, FII and Stock IndexRelationship in India*

Ajaysingh Rajput1 & Keyur Thaker2

Abstract

In globalized world, exchange rate, FII and Stock Index are important economy variable and reflectunderlying strength and stability of business and an economy. Earlier study findings reveals positive,negative and mixed relationship amongst those variables. We measure the relationship and its predictivepower for the period from January 2000 to December, 2005, contemporary to third generation reformsin India. Using simple correlation and regression analysis it is found that no long run positivecorrelation exists between exchange rate and Stock Index except for year 2002 and 2005. FII and StockIndex show positive correlation, but fail to predict the future value.

* Received May 6, 2007; Revised February 23, 20081. Management Consultant, Mott MacDonald, Ahmedabad, e mail: [email protected]. Assistant Professor, Indian Institute of Management, Indore , email: [email protected]

1.0 INTRODUCTION

For a global and liberal economy,Exchange rate is increasingly importanteconomy metric as it reflects underlyingstrength and competitiveness with worldeconomies. Adoption of floatingexchange rate system leads to freedetermination of the Exchange ratechanges by market forces. Such changesaffect the business transactions andcompetitiveness and ultimately cashflows and market value. Firm level andindustry- level share values are thusinfluenced by exchange rate.(Dominguez, 2001)

Stock Index reflects underlying stabilityand growth of economy and strength ofbusinesses in an economy. Foreign

investments in stock market is driven bythe valuations of the stocks andunderlying growth and profitability ofthe business in an economy. The flowof foreign investments affects theexchange rate and the stock marketperformance.

Researches support prevalence ofrelationship, though evidences of causalrelationship are mixed. Substantialresearch is found in context of developedeconomies, but studies for emergingmarket are rare. Classical economictheory suggests a relationship betweenthe stock market performance and theexchange rate behaviour. For example,“flow oriented” models of exchange ratedetermination affirm that currency




movements affect internationalcompetitiveness and the balance of tradeposition, and consequently the realoutput of the country, which in turnaffects current and future cash flows ofcompanies and their stock prices(Dornbusch and Fisher, 1980).Movements in the stock market may alsoaffect exchange rates. Equities, being partof wealth, may affect the behaviour ofexchange rates through the demand formoney according to the monetaristmodels of exchange rate determination(Gavin, 1989). Money supplies anddemand theory emphasise therelationship of exchange rate and FIIinvestment.

2.0 REVIEW OF LITERATURE

In the context of a developed economythe research studies on this relationshipcan be traced back to 1970s. The earliestcontribution was found from Frank andYoung (1972), investigating therelationship between stock prices andexchange rates. Six different exchangerates were analyzed to find that thereexisted no relationship between thesetwo variables. Similar work by Solnik(1987), employing regression analysis onmonthly and quarterly data for eightindustrialized countries from 1973 to1983, concluded a negative relationshipbetween real domestic stock returns andreal exchange rate movements.However, for monthly data over 1979–83, he observed a weak but positiverelation between the two variables.Jorion (1988) attempted to analyze and

compare the empirical distribution ofreturns in the stock market and in theforeign exchange market by using themaximum likelihood estimationprocedure and ARCH model in dailydata of exchange rates and stock returnsspanning from June 1973 to December1985. The study found that exchangerates display significant jumpcomponents, which are more manifestthan in the stock market. The statisticalanalysis of the study for the foreignexchange market and stock marketsuggests important differences in thestructures of these markets. Taylor andTonks (1989) studied the impact of theabolition of the UK exchange control onthe degree of integration of the UK andits overseas stock markets such as WestGermany, the Netherlands, Japan andthe US. By employing the GrangerCausality and Engel Granger co-integration tests over the two subperiods, spanning from April 1973 toSeptember 1979 and October 1979 to June1986 respectively, the study concludedthat there was no significant increase inthe correlation of stock market returnsas a result of the abolition of exchangecontrol. The co-integration testconfirmed that the UK and foreign (non-US) stock-market indices were co-integrated in post-1979 period but notbefore that. Ma and Kao (1990), usingthe monthly data from 1973 to 1983 onsix major industrialized countries, foundthat domestic currency appreciationnegatively affected the domestic stock

45

price movements for an export-dominant economy and positivelyaffected an import-dominant economy.However, study was silent on exchangerate effect on stock index. Bahmani-Oskooe and Sohrabian (1992) employedco-integration analysis and the Grangercausality test on stock prices andeffective exchange rate of the dollar onthe US economy from July, 1973 toDecember, 1998. They found a bi-directional causality between stockprices and the effective exchange rate ofthe dollar, at least in the short run. Theco-integration analysis revealed thatthere is no long-run relationshipbetween these two variables. Bartov andBodnar (1994) concluded thatcontemporaneous changes in the dollarhave little power in explaining abnormalstock returns. They also found that alagged change in the dollar is negativelyassociated with abnormal stock returns.The regression results showed that alagged change in the dollar hasexplanatory power with respect toerrors in analysts’ forecasts of quarterlyearnings. Ajayi and Mougoue (1996)examined the inter-temporal relationbetween stock indices and exchangerates for a sample of eight advancedcountries during the period April, 1985to June, 1991. By employing the co-integration and causality tests on dailyclosing stock market indices andexchange rates, the study found that (a)an increase in aggregate domestic-stockprice has a negative short run effect ondomestic currency values, (b) sustained

increase in domestic stock prices willinduce domestic currency appreciationin the long run, and (c) currencydepreciation has negative short-run andlong-run effects on the stock market.Abdalla and Murinde (1997) observedthe interaction between exchange ratesand stock prices in the cases of India,Korea, Pakistan and the Philippines byapplying bi-variate Vector AutoRegressive models on monthlyobservations of stock price index andthe real effective exchange rate overJanuary, 1985 to July, 1994. The studyfound the unidirectional causality fromexchange rate to stock prices in all thecountries except in the Philippines. Thisfinding suggests policy implications,that the respective governments shouldbe cautious in their implementations ofexchange rate policies in such a way thatthese policies have ramifications in theirstock markets. Ong and Izan (1999)employed the Non-linear Least Squaremethod to examine the associationbetween stock prices and exchange rates.They found that US share price returnsfully reflected the information conveyedby movements in both the Japanese Yenand the French Franc after four weeks.However, this result suggests a veryweak relationship between the USequity market and exchange rates. Theyconcluded that depreciation in acountry’s currency would cause its sharemarket returns to rise, while anappreciation would have the oppositeeffect. Ibrahim (2000) investigated

Rajput et.al, Exchange Rate, FII and ...


interactions between stock prices andexchange rates in Malaysia using bi-variate and multivariate cointegrationand the Granger Causality test. Multiplevariables such as stock price, threeexchange rate measures viz., the realeffective exchange rate, the nominaleffective exchange rate and RM/US$,money supply, and reserves during theperiod January, 1979 to June, 1996 wereanalyzed. The results from bi-variatemodels indicate that there is no long-run relationship between the stockmarket and any of the exchange rates.However, there is some evidence of co-integration, when the models areextended to include money supply andreserves. This finding indicates that inthe short run, a concerted stance onmonetary policy, exchange rate andreserve policy is vital for stock marketstability and that there is informationalinefficiency in the Malaysian stockmarket. The multivariate test suggeststhat (a) there is unidirectional causalityfrom stock market to exchange rate, (b)both the exchange rates and the stockindex are Granger-caused by the moneysupply and reserves, (c) there is bi-directional causality between variablesonly in the case of nominal effectiveexchange rate. Bodart and Reding (2001)investigated the impact of foreignexchange markets on the conditionaldistribution of industry stock returns fora set of European countries by using thebi-variate GARCH model over theperiod January 5, 1990 to November 12,

1998. The analysis of the studyconfirmed that industries from tradedsectors are usually more sensitive toexchange rates than industries from non-traded sectors, both in mean andvolatility. Regarding the volatil ityspillovers, the study concluded that theinfluence of the foreign exchange marketon the mean and to a lesser extent onthe volatility of industry stock returnsis modified when exchange rateinnovations are abnormally large.

Fang and Miller (2002) attempted toinvestigate empirically the effects of dailycurrency depreciation on Korean stockmarket returns during the Koreanfinancial turmoil of 1997 to 2000. Byemploying the Granger causality test andan unrestrictive bi-variate GARCH-Mmodel over the period spanning fromJanuary 3, 1997 to December 21, 2000,the study found that (a) there exists a bi-directional causality between the Koreanexchange market and the Korean stockmarket, (b) currency depreciation hasstatistically significant effects on stockmarket returns through three channelssuch as, first, the level of exchange ratedepreciation which negatively affectsstock market returns; second, exchangerate depreciation volatility positivelyaffects stock market returns; and third,stock market returns volatility respondsto exchange rate depreciation volatility.

In Indian context, Apte (2001)investigated the relationship between thevolatility of the stock market and the

47

nominal exchange rate of India by usingthe EGARCH specifications on the dailyclosing USD/INR exchange rate, BSE 30(Sensex) and NIFTY-50 over the period1991 to 2000. The study suggests thatthere appears to be a spillover from theforeign exchange market to the stockmarket but not the reverse.

Bhattacharya and Mukharjee (2002)studied the nature of causal relationbetween the stock market, exchangerate, foreign exchange reserves andvalue of trade balance in India from 1990to 2001 by applying the co-integrationand long-run Granger Non-causalitytests. The study suggests that there isno causal linkage between stock pricesand the three variables underconsideration.

To examine the dynamic linkagesbetween the foreign exchange and stockmarkets for India, Nath and Samanta(2003) employed the Granger causalitytest on daily data during the periodMarch 1993 to December 2002. Theempirical finding of the study suggeststhat these two markets did not have anycausal relationship. When the studyextended its analysis to verify ifliberalization in both the marketsbrought them together, it found nosignificant causal relationship betweenthe exchange rate and stock pricemovements, except for the years 1993,2001 and 2002 during when aunidirectional causal influence fromstock index return to return in forex

market is detected and a very mildcausal influence in the reverse directionis found in some years such as 1997 and2002.

A gap analysis of FII investment in Indianstock market, on closing data of S & PCNX NIFTY 500 of September 30, 2004,shows that the FIIs investments arehighly concentrated in terms of theirmarket value in a very small number ofcompanies and there is a wide gapbetween the actual investments by FIIsand the investments allowed as per thecap, Sharma (2004).

Panda (2005) found that the returns onIndian stock market indices such as BSEsensex and NSE nifty are relatively moreaffected by mutual fund investmentsthan FIIs investments. In fact, FIIsinvestments do not affect BSE sensexrather it is affected by the latter. FIIsare found to follow positive feedbackstrategy and to have return chasingtendency. However, he does not find aclear causality between FIIs and NSEnifty. So researcher sum up with theview that domestic investors like mutualfund affect Indian stock markets to agreater extent than FIIs and the recentboom in Indian stock market could notbe mainly because of larger FII inflows.

Narayan and Smyth (2005) examine thelong run relationship and granger Ftests to examine any causal relationshipbetween exchange rates and stock pricein four South Asian Countries, (India,



Pakistan, Sri lanka and Bangladesh).The study finds that there is no longrun equilibrium relationship betweenthese two financial variables in three ofthe four countries studied. Exchangerates, Granger cause stock prices inIndia in both the long run and short runand in Pakistan in the short run.

Badhani (2005) examines the long termand short-term relationship amongstock prices, Dollar –Rupee exchangerate and net FII investment in Indiausing monthly data from April 1993 toMarch 2004. Study finds long termrelationship between FII investmentflow and stock prices and between FIIinvestment flow and exchange rate.However no long-term relationshipwas found between exchange rate andstock prices. Study also shows thatexchange rate long term granger causesFII investments flow and vice versa.It sugges ts that FII use positivefeedback trading in respect toexchange rate. BI-directional long-termcausal ity was found between FIIinvestment flow and stock prices.However, no short-term causalitycould be traced between above twopairs of variables using monthly data.Study shows that the short termcausality runs from change in exchangerate to stock returns, not vice versa.

3.0 RESEARCH METHOD

This study reexamines the relationshipbetween two fundamental economicvariables, exchange rate and stock

price over a long period coinciding 3rdgeneration reforms in India. FIIinvestment in stock market was alsostudied along. Causal research to findout correlation between exchange rateand stock price is performed. Samecausal research is adopted to f indcorrelation between FII investmentand stock market index. Regressionanalys is is used to develop theregression model to find predictionpower of relationship between thevariables.

Hypotheses

Exchange rate has positive correlationwith stock price i.e. stock market indexnifty.

FII investment has positive correlationwith NIFTY.

Each Relationship predicts the futurevalue of Stock Index.

Data and Sample

Data for six-year period consisting oftotal 1564 daily closing data of NIFTYand daily data of exchange rate fromJanuary 2000 to December 2005 werecollected. Also, 72 monthly data NIFTYperformance and FII investment fromJanuary, 2000 to December, 2005collected.

4.0 ANALYSES AND INTERPRETATION

a. Data analysis of Year 2000-2005

The select descriptive statistics ofregression analysis is given inTable -1.

49Rajput et.al, Exchange Rate, FII and ...

8 0 0

1 3 0 0

1 8 0 0

2 3 0 0

2 8 0 0

4 3 .5 4 5 4 6 .4 4 7 .1 4 8 .7 4 8 .4 4 7 .4 4 5 .3 4 5 .3 4 4 .5 4 3 .5

EX C HA NG E R A T E

NIF

TY

CL

OS

ING

Table-1: Descriptive statistic of NIFTY Closing and Daily Exchange Rate

NIFTY CLOSING

Mean 1475.54936

Standard Error 11.70637494

Median 1349.35

Mode 1067

Standard Deviation 462.8091312

Sample Variance 214192.2919

Kurtosis -0.053507729

Skew ness 0.884290224

Range 1988.4

Minimum 854.2

Maximum 2842.6

Sum 2306283.65

Count 1563

Largest (1) 2842.6

Smallest (1) 854.2

Confidence level (95.0%) 22.96187284

EXCHANGE RATE

Mean 46.11912494


Median 46.1269

Mode 47.125



Kurtosis -1.145765392

Skew ness -0.027592925

Range 5.7413

Minimum 43.3175

Maximum 49.0588

Sum 72130.3114

Count 1564

Largest (1) 49.0588

Smallest (1) 43.3175

Confidence level (95.0%) 0.084991417

Table-2 contains the correlation statisticsbetween Nifty and Exchange rate whileFigure-1 is the graphical representationof regression relationships and Table -3contains regressing analysis.

Table- 2: Correlation ship betweenNIFTY Closing and Daily Exchange Rate

n 1563

r statistic -0.76

95% CI -0.78 To -0.74

2-tailed p <0.0001 (t approximation)Fig. - 1: Relationship of NIFTY CI with

Exchange rate


Table -3 : Regression analysis of NIFTY Closing and Daily Exchange Rate

n 1563

R2 0.58Adjusted R2 0.58SE 300.5655

Term Coefficient SE P 95% CI of Coefficient

Intercept 10946.5767 204.75 <0.0001 10544.9467 to 11348.2Slope -205.3590 4.4367 <0.0001 -214.0615 to -196.65Source of variation SSq DF MSq F PDue to regression 193548207.276 1 193548207.276 2142.45 <0.0001About regression 141020152.748 1561 90339.624Total 334568360.024 1562

0 200 400 600-4.5

-3.5

-2.5

-1.5

-0.5

0.5

1.5

2.5

3.5

4.5

43 45 47 49

EXCHANGE RATE

Stan

dard

ized

res

idua

ls

y = - 2 0 5 . 3 6 x + 1 0 9 4 7

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

3 0 0 0

4 3 4 5 4 7 4 9

E X C H A N G E R A T E

NIF

TY

CL

OS

ING

Fig. - 2 : Relationship Between NIFTY closing& Daily Exchange Rate

Fig. - 3 : Histogram showing relationship ofNIFTY with Exchange Rate

There is a negative correlation betweenNIFTY Closing and Daily ExchangeRate as depicted in Figure-2 over thesix years. Figure-3 gives the Histogramof the NIFTY and Exchange raterelationship. It means upwardmovement in one variable whiledownward movement in the othervariable. The correlation is – 0.76. Basedon this correlation, the regressionmodel Y = -205.36X+10947, fails topredict any future trend in dependentvariable Y based on independentvariable X.

The Tables 4 and 5 and figures depictvarious statistics and graphical view ofregression analysis output on FII andNIFTY relationships for 6-year period.Table - 4 gives the descriptive statisticsof regression results while Table-5gives the correlation and the testresults.

51Rajput et.al, Exchange Rate, FII and ...

Table - 4: Descriptive statistic analysis of FII and NIFTY (based on monthly data)

FII

Mean 1939.027778


Median 1161.5

Mode #N/A



Kurtosis 0.692289239

Skew ness 0.898835174

Range 13423

Minimum -3808

Maximum 9615

Sum 139610

Count 72

Largest (1) 9615

Smallest (1) -3808

Confidence Level (95.0%) 633.2334363

NIFTY

Mean 1477.994485


Median 1359.634

Mode 1132.1



Kurtosis 0.027968328

Skew ness 0.906903156

Range 1823.181

Minimum 949.43

Maximum 2772.611

Sum 106415.6029

Count 72

Largest (1) 2772.611

Smallest (1) 949.43

Confidence Level (95.0%) 107.9904098

Table-5:Correlation between NIFTY and FII

N 72

r statistic 0.53

95% CI 0.34 To 0.68

2-tailed p <0.0001 (t approximation)

Similarly the Table-6 shows relationshipbetween Nifty and FII. Regressionresults show a low predictive power.Figure- 4 depicts the graphicalmanifestation of the relationship andslope.

8 0 0

1 0 0 0

1 2 0 0

1 4 0 0

1 6 0 0

1 8 0 0

2 0 0 0

2 2 0 0

2 4 0 0

2 6 0 0

2 8 0 0

1 8 4 -4 2 4 1 0 3 1 3 7 0 4 2 2 1 2 3 3 2 4 9 3 2 8 1 6 -5 8 7

FI I

NIF

TY

Fig. - 4 : Relationship Between NIFTY & FII

NA

FTY


Table-6 : Regression analysis of NIFTY and FII

A positive correlation is found betweenNIFTY and FII investment over the sixyears of data. By looking at Figure-5 onecan observe the graphic depiction of the

Source of variation SSq DF MSq F pDue to regression 4196643.639 1 4196643.639 27.21 <0.0001About regression 10797965.732 70 154256.653Total 14994609.371 71

Term Coefficient SE P 95% CI of CoefficientIntercept 1303.0546 57.1609 <0.0001 1189.0508 to 1417.0584Slope 0.0902 0.0173 <0.0001 0.0557 to 0.1247

R2 0.28Adjusted R2 0.27SE 392.7552

y = 0 .0 9 0 2 x + 1 3 0 3 . 1

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

3 0 0 0

3 5 0 0

- 4 0 0 0 1 0 0 0 6 0 0 0

FII

NIF

TY

Fig. - 5 : Representation of Regression Slope

NIF

TY

-4

-3

-2

-1

0

1

2

3

4

-4000 1000 6000

FII

Stan

dard

ized

res

idua

ls

0 10 20 30

Fig. - 6 : FII and Standardised Residuals

regression slope, while Figure-6 showsthe histogram of the relationship. Itmeans nifty increases as FII investmentincreases in nifty. The correlation statisticis 0.53. Based on this correlation theregression model Y = -0.0902X+1303.1 isdeveloped. This fails to predict anyfuture trend in dependent variable Ybased on independent variable X.

b. Yearly data analysis andinterpretation of 2000-2005

Over six-years period the Exchange rateand stock price has negative correlationand they this is not helpful to predictfuture trend. While FII and NIFTY showa positive relation, the regression modelis not able to predict the future trend.The data used in this analysis is variedlargely (as shown in descriptivestatistics) because of long time periodtaken for study. For better result, ananalysis on yearly data is performed. Theyear wise correlation statistic betweenNIFTY and FX Rate can be viewed inTable-7. Table-8 shows the correlationstatistic between FII and Nifty.

53

Table - 7 : Correlation between DAILYCLOSING NIFTY and DAILY EXCHANGERATE

YEAR CORRELATION

2000 -0.780370385

2001 -0.812194488

2002 0.38007965

2003 -0.839731013

2004 -0.627766231

2005 0.745564413

2000-05 -0.760592682

Out of six years four years show negativecorrelation between NIFTY andExchange Rate, while only two yearsshow positive correlation between thesetwo variables. The entire regressionmodel is not able to predict the futuretrend.

Table-8 : Correlation between FIIinvestment and NIFTY

YEAR CORRELATION

2000 0.351061

2001 0.780056

2002 0.416388

2003 0.826445

2004 0.599925

2005 0.228477

2000-05 0.53


FII and NIFTY show continuous positivecorrelation over six years. But theregression model is not able to predictthe future trend.

The positive correlation between FIIand NIFTY implies a causal relationshipbetween these two variables. It meansFII is affecting the NIFTY performance.While no continuous relationshipbetween NIFTY and Exchange Rateprovide a very weak relationshipbetween both the variables. But 0.76correlation in year 2005 between NIFTYand Exchange Rate, and heavyinvestment of FII in Indian stock marketduring this time, provide the evidenceof correlation ship between thesevariables.

5.0 CONCLUSION AND LIMITATIONS

Stock market and exchange rate areimportant factors in the economy and FIIflow affects both the variables. Researchfindings differ and lack consensus. Ourstudy found no long run positivecorrelation between Exchange Rate andNIFTY. Over the six years it showsnegative trend but in year 2002 and 2005a positive correlation between these twovariables is found.

From the analysis of FII investmentand NIFTY performance, one can findthat the FII significantly affects theNIFTY performance and is one of theimportant driving forces of the stockmarket. Continuous positivecorrelationship exists between thesetwo variables.

Positive correlation found between FIIand NIFTY tempts one to think aboutthe relationship between Exchange


Rate and NIFTY. If we consider recentboom in Indian stock market andmovement in exchange rate, a positivecorrelated movement is observed.This is because in last two years 2004-05 and 2005-06, FII invested heavily inmarket and their investmentinfluenced the supply and demandposition of Indian rupee.

FII flows fails to predict the future valueof NIFTY. This result provides evidencethat FII is one of the important factors,but not only one significant factoraffecting NIFTY.

We hope this study will provide a goodwork to carry out more vigorousanalysis in this field with more effectivestatistical tool and with latest data ofboom period.

For the analysis of financial market andwith voluminous data to predict theinterrelation ship between variables,more effective tools such as GARCH,Vector Auto Regression and GrangerCasualty are warranted. We wish toextend the research with those tools.

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Attribute Based Perceptual Mapping ofCement Brands: an Empirical Study*

Shahida P.1, Rajendra Nargundkar2 & Gaurav Hiremath3

Abstract

The Indian cement industry has seen an explosive growth backed by heavy investment in Infrastructuredevelopment in the last decade. By 2008, the domestic demand will be 140 million tonnes. The industryis expected to grow by 12 % every year. There are some established brands in the market, namely, ACC,Grasim, Gujarat Ambuja, Ultratech Chemco, Birla etc. Multinational companies such as Holcim(Switzerland), Lafarge (France), Italicementi (Italy) have invested 10-50% in Indian Companies. Thisstudy is an attempt to find out the factors, which influence the choice of cement brand. The relativeimportance of various brand attributes is studied. The consumers’ perception towards the leadingbrands of cement is analyzed through an attribute based perceptual map. The managerial implicationsand directions for future research are discussed.

* Received January 29, 2008 ; Revised February 13, 20081. Assistant Professor, Dept. of MBA, PESIT, Bangalore, email: [email protected]. Director, Dept. of MBA, PESIT, Bangalore, email: [email protected]. Area Sales Manager, Reliance Communications, Bangalore, email:[email protected]

1.0 INTRODUCTION

A brand is a strategically potent weapon.The Brand helps a company todifferentiate itself from competition. Itdefines to the stakeholders, customersand partners what the company believesin and what to expect from the company.Brand management has been extensivelyresearched in the western countries andseveral research papers have been writtenon different aspects of branding. Formany industries, branding offers the bestopportunity for creating growth.

Branding is applicable to all categoriesand industries and even applies tocommodities. Research in brandmanagement has gained prominence inIndia in the last decade. Brandpositioning is a crucial decision for acompany.

A brand’s positioning is designed tooccupy a unique and distinctive place inthe consumer’s mind. The objective is todevelop a sustainable competitiveadvantage on product attribute(s) in theconsumer’s mind. Kotler (2002) defines





brand positioning as “the act ofdesigning the company’s offer and imageso that it occupies a distinct and valuedplace in the target customer’s mind.”

Brand positioning involves establishingkey brand associations in the minds ofcustomers and other importantconstituents to differentiate the brandand establish (to the extent possible)competitive superiority (Keller et al.2002). Keller (2003) defines brandpositioning as all about creating theoptimal location in the minds of existingand potential customers so that theythink of the brand in the “right way.”Brand positioning requires thoughtfulanalysis of competitors and consumers todetermine the desired image for thebrand to maximize its chances for success.Although a number of differentapproaches and methodologies forpositioning are possible, they all typicallydefine the nature of the target marketand relevant competitors and the meansby which the brand should be seen assimilar as well as distinct from thosecompetitors.

According to Perreault and Mc Carthy(1999) positioning refers to howcustomers think about proposed and /or present brands in a market.Developing an effective positioningstrategy, which is sustainable, unique andcompetitive, is not easy.

Schnedler (1996) states “Positioningproducts in a complex market can be oneof a company’s most difficult decisions.”

The result of positioning is the successfulcreation of a customer focused valueproposition. Brand positioning sets thedirection of marketing activities andprograms—what the brand should andshould not do with its marketing.

2.0 OVERVIEW OF INDIAN CEMENTINDUSTRY

The Indian Cement industry is the secondlargest cement producer in the world,with an installed capacity of around 157million tonnes per annum (mtpa) at end-March 2006. The Indian cement industryis a mixture of mini and large capacitycement plants, ranging in unit capacityper kiln as low as 10 tpd to as high as7500 tpd. Majority of the production ofcement in the country (94%) is by largeplants, which are defined as plants havingcapacity of more than 600 tpd. At presentthere are 124 large rotary kiln plants inthe country. (IBEF, 2007).

The Ordinary Portland Cement (OPC)enjoys the major share (56%) of the totalcement production in India followed byPortland Pozzolana Cement (PPC) andPortland Slag Cement (PSC). A positivetrend towards the increased use ofblended cement can be seen with theshare of blended cement increasing to43%.

As on March 2006, ACC was the largestplayer with a capacity of 18.64 mtpa.UltraTech CemCo Ltd occupied thesecond slot with a capacity of 17 mtpa(now a part of Aditya Birla corp.). TheGujarat Ambuja group has emerged as

59

the third largest player with a capacityof 14.86 mtpa. Grasim ranks fourth witha capacity of 14.12 mtpa. Other leadingplayers include India Cements, Jaypeegroup, Century Textiles, MadrasCements, Lafarge, and Aditya Birla Corp.Multinational players have invested inIndian companies and the PlanningCommission’s Working Group onCement Industry predicts cementproduction in India to grow at a rate of10% during the Tenth Five-Year Plan(2002-2007). By comparison, the cementindustry is expected to grow at around8-10% during the 2003-07 periods.Growth of 9% per annum from FY2006-10 would result in cement productionincreasing to around 196 mt in FY2010.

According to Cement ManufacturersAssociation (CMA), the average monthlycapacity utilisation during fiscal 2006-07was 94 per cent. And due to the sustaineddemand levels, the growth in capacityutilization has continued in the currentfiscal 2007-08, with 94 per cent capacityutilization for the period April-September as against 90 per cent duringthe corresponding period quarter lastfiscal (vBulletin, 2007)

Simultaneously, cement dispatches in2007 were at an all-time high of 155million tonnes (mt), up from 142 mt inthe previous fiscal, thereby recording agrowth of 10 per cent. During the firsthalf of 2007, dispatches (includingexports) have also jumped by 8.19 percent to reach 80.24 mt. Net sales of

cement companies went up by 50.5 percent during 2007 while profits zoomedby 183.4 per cent. According to the latestICRA Industry Monitor report, installedcapacity of the cement industry isexpected to increase to 186 milliontonnes per annum (mtpa) by end of 2007-08, 219 mtpa by end of 2008-09, and upto 241 mtpa by end of 2009-10 (IBEF,2007)

3.0 SIGNIFICANCE OF BRAND POSITIONING

Rising noise levels in the media andextensive advertising by differentcompanies lead to a clutter in theconsumer’s mind. If brand awarenessand recognition is good, the brand willfall in the consideration set of theconsumer but may fail to buildcustomer loyalty without a uniquebrand position. According to Aaker andShansby (1982), the positioning decisionis often a crucial decision for a companyor brand because the position can becentral to consumer’s perception andchoice decisions. A clear positioningstrategy can ensure that the elementsof the marketing program areconsistent and supportive. According toGwin and Gwin (2003), whiledeveloping a positioning, a marketerneeds to consider four things: thetarget market, how the product isdifferent or better than competitors,the value of this difference to the targetmarket and the ability to demonstrateor communicate this difference to thetarget market.

Shahida et.al, Attribute Based Perceptual ...


According to Aaker (1996) brandposition is the part of the brand identityand value proposition that is to beactively communicated to the targetaudience and that demonstrates anadvantage over competing brands.Positioning and segmentation aretreated as different concepts in practiceand in literature. Positioning has novalue unless it is appropriate for thetarget segment (Rao and Steckhel, 1998).Aaker (1996) in the brand identityplanning model suggests that a brandposition has to be built on f iveparameters- look to the core identity,identify points of leverage, create thevalue proposition: benefits that driverelationships, target audience and activecommunication. Brand position isextremely important to create a definedidentity for the brand.

Aaker and Shansby (1982), propose sixapproaches to positioning strategy, whichare: positioning by 1) Attributes 2) price-quality 3) use or applications 4) product-user 5) the product class and 6) thecompetitors. The following were ourresearch questions:

4.0 RESEARCH QUESTIONS

R1. To find out the relative importanceof various attributes of cementconsidered while purchasing brandedcement.

R2. To find out the brand positioning ofdifferent brands with attribute basedperceptual mapping using discriminantanalysis.

5.0 RESEARCH METHODOLOGY

A questionnaire was administeredpersonally to collect primary data fromdealers and consumers. A seven pointrating scale with 1 being “Worst” and 7being “The Best” was used for rating theattributes on different brands of cement.Non-probability judgmental samplingtechnique was used. The sample size was30 retailers, 20 dealers and 10 consumers,covering major commercial andresidential areas in Bangalore city.

6.0 ANALYSIS AND DISCUSSION

Keon (1983) has described four methodsfor measuring and evaluating a brand’scurrent or potential positioning. Themethods are Multi dimensional scaling,factor analysis; discriminant analysis andmulti attribute compositional models. Inthis study we have used discriminantanalysis; discriminant analysisdetermines the linear combinations ofattributes that best discriminate amongbrands. The ratings of brands onattributes are used to develop theperceptual map. Perceptual maps providea visual picture of the brand positioningactivity and help brand managersunderstand the position of the brand incomparison to competing brands.

R1. To find out the relative importanceof various attributes of cementconsidered while purchasing a brandedcement. Table 1 shows the relativeimportance of different attributes basedon their mean scores.

61Shahida et.al, Attribute Based Perceptual ...

The most important attributes of cementare strength of the cement (mean; 6.9),followed by price (mean; 5.38) andavailabil ity (mean; 5.10) . Next inimportance is colour (mean; 4.6). Theleast important attributes are, settingtime (mean; 4.28) and sand-cement-water ratio (mean; 3.4). The strengthand price of the cement appear to bethe most important attributes thatcustomers will focus on while choosinga cement brand. This finding indicatesthat cement brands need to focus theirmarketing communicationspredominantly on “Strength” of thecement, as strength is the mostimportant attribute of cement.

Table 2: Standardized CanonicalDiscriminant Function Coefficients

Attributes Function

1 2

Price of The Brand .823 .027

Setting Time -.954 .225

Strength of the cement .109 1.121

Availability of Cement .787 .045

Sang Cement Water Ratio -.091 -.302

Colour of the Cement -.096 -.647

From the standardized discriminantfunction coefficients (table 2); it appearsthat there are two different functionsbased on five attributes. Function 1consists of price of the brand, settingtime and availability. Function 2consists of strength and colour of thecement.

R2. To find out the brand positioning ofdifferent brands with attribute basedperceptual mapping using discriminantanalysis.

We performed discriminant analysis andfound significant differences betweenthree leading brands of cement inBangalore- ACC (Associated CementCompany), Ultratech ( Aditya Birla Corp)and Zuari (Italicimenti group). The Wilkslambda test revealed, two functions (1and 2) both are statistically significant.The Chi square value for function 1 is171.572 at 12 degrees of freedom withsignificance of 0.000 and Chi square offunction 2 is 18.98 at 5 degrees of freedomwith significance of 0.002

Table 1: Relative Importance of DifferentAttributes

Sl No Attribute Mean

1 Price 5.382 Setting time 4.283 Strength 6.904 Availability 5.105 Sand-cement-water ratio 3.446 colour 4.60

Chart 1: Relative Importance of DifferentAttributes

Color

Sand-cement-waterratio

Avaliability

Strength

Setting time

Price0 2 4 6

4.6

3.44

5.1

6.9

4.28

5.38


Table 3: Functions at Group Centriods

Brand Name Function

1 2

Ultratech -1.916 -.013

ACC .918 .460

Zuari .998 -.448

A perceptual map is drawn using thestandardized canonical discriminantfunction coefficients (table 2) and thefunctions at group centroids (table3).

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

-3 -2 -1 0 1 2

Function 1

Function 2

Attributes Brands

STRENGTH

SETTING TIME

AVAILABILITY PRICE ULTRA TECH

ACC

ZUARI

S-C-W RATIO

COLOUR

Chart 2: Attribute based Perceptual Map ofCement Brands

7.0 INTERPRETATION

The above graph represents the vectorsfor each of the attributes- strength,price, availability, setting time, sand-cement-water ratio, and colour. Thesevectors represent the effect ofdiscriminating on each dimension.Longer arrows pointing more closelytowards a given group centroid,represents variables most stronglyassociated with that particular group

(or Brand, in this case) . Vec torspointing in the opposite direction froma given group centroid representlower association with the concernedgroup.

Variables with longer vectors in a givendimension, and those closer to a givenaxis are contributing more to theinterpretation of that dimension.Looking at all variables that contributeto a given axis (dimension), we can labelthe dimension as a combination of thosevariables.

As seen from the graph (chart 2)Ultratech (Birla Plus before October2007), ACC and Zuari have their uniqueposition on the map. In addition on themap we have values of the attributes onthe same two dimensions (eachdiscriminant function represents adimension). From the figure we can seethat dimension 1 seems to be acombination of Availability and Price(closest to the x-axis). Dimension 2 seemsto comprise Strength, Sand-Cement-Water ratio and colour.

8.0 BRANDS AND THEIR ASSOCIATION

ACC seems to be stronger in bothDimension 1 (Availability) andDimension 2 (strength). Ultratech seemsto be strong in dimension 2 (strength, incomparison to Zuari). Zuari seems to beweak in both the dimensions ascompared to its competitors.

Aaker (1996) defines brand position asfollows: Brand position is part of thebrand identity and value proposition

63

that is to be actively communicated tothe target audience and thatdemonstrates an advantage overcompeting brands.

The respondents in our survey associateACC brand as strong cement which iseasily available in the market. Ultratechis perceived to be high on strengthcompared to Zuari.

The brand Ultratech was known bymany other brand names in the past. In2004, Grasim bought 51% stake in L&Tcement and named L&T cement asUltratech Cement. According to O.P.Puranmalka, Group executivepresident, Grasim Industries and chiefmarketing officer, UltraTech CementLtd, “The name UltraTech was theoutcome of an in-depth researchconducted throughout the country. Theresearch study indicated that in thecustomers’ mind, L&T stood forquality, technology and expertise. Thename UltraTech with the signature line‘the engineer’s choice’ admirablycaptured the premium nature of thebrand and its salience.” In October 2007Birla Plus brands was rechristened asUltratech. Though regional brandswere retained such as Vikram Cementin the north zone and Birla Super inBangalore, Pune and Mysore, andRajashree Cement in the west and southzone (Business India, 2008). Ultratechbecame the national brand. The recentname change from Birla Plus toUltratech may have had an influence onthe brand positioning of the same.

9.0 LIMITATIONS

The study confines itself to Bangalorecity only. Though eight or more brandswere researched for brand awareness,we considered only three regionalbrands for attribute based perceptualmapping.

10. MANAGERIAL IMPLICATIONS

From this study we can conclude thatCustomer considers Strength of thecement as the most important attributeof the cement. Second is Price of thecement and the third is Availability ofthe cement brand. Cementmanufacturing companies need to focuson these attributes. From the perceptualmap, we can conclude that ACC ishaving an edge over Ultratech on Priceand Availability, which is a seriousconcern for Ultratech as it may lose itsmarket share to ACC due to nonavailability of cement in the market.Both Ultratech and Zuari cements arenot perceived highly on both dimensions.With the entry of global giants such asHolcim, Lafarge, the current positioningof Indian brands may have to bereconsidered. From this study, we caninterpret that except for ACC, otherbrands do not have good attribute basedpositioning. Aaker (1996) and Keller(2003) have emphasized on theimportance of not only selecting asuitable positioning strategy for a targetsegment but also on the importance ofupdating the brand over a period oftime, to ensure that the brand staysrelevant at all times.

Shahida et.al, Attribute Based Perceptual ...


REFERENCES

Aaker, A. David (1996). Building Strong Brands.The Free Press, New York.

Aaker, A. David and Shansby, Gary (1982).Positioning your Product. Business Horizons,May-June, 56-62.

Cement: A report for Crisil by IBEF, India BrandEquity Fund. www.ibef.org, accessed on 1201-2008.

Cement –Industry profile, updated on December31, 2007, www.ibef.org (2007), accessed on12 February 2008.

Cement Industry (2007), v Bulletin, Jelsoftenterprises, www.management paradise.com, accessed on 12 February 2008.

Cement: Industry Profile (2007), IBEF India BrandEquity Fund. www.ibef.org, accessed on 1201-2008.

Mohan, Devendra (2008), Grasim Press release,Business India, 13 January 2008.

Gwin, F. Carol and Gwin, R. Carl (2003 ). ProductAttributes Model: A Tool for EvaluatingBrand Positioning. Journal of Marketing: Theoryand Practice, 30-42

Keller, K. L. (2002). Branding and brand equity,Bart Weitz, Robin Wensley, eds. Handbook ofMarketing. Sage Publications, 151-178,London, UK.

Keller, K. L. 2003. Strategic Brand Management:Building, Measuring, and Managing BrandEquity, 2d ed. Prentice Hall, Upper SaddleRiver, NJ.

Keon, John. W.(1983). Product Positioning:Trinodal Mapping of Brand Images, AdImages and Consumer Preference. Journalof Marketing Research, 20, 380-392.

Kotler, P. (2002). Marketing Management.Prentice Hall. New Jersey.

Perreault, William D., Jr and E. Jerome McCarthy (1999). Basic Marketing: A GlobalManagerial Approach, Boston, MA: IrwinMcGraw-hill.

Rao and Steckel (1998). Analysis for StrategicMarketing. Reading, MA: Addison-Wesley.

Schnedler, David E. (1996). Use Strategic MarketModels to Predict Consumer Behavior. SloanManagement Review, 37(3), 85-94.

The Indian Cement Industry: ICRA SectorAnalysis (2006). www.icra.in. accessed on10/ 01/ 2008.

http://www.ibef.org

http://www.ibef.org

http://www.ibef.org

http://www.icra.in

Work Role Characteristics as Determinantsof Job Satisfaction: An empirical analysis*

J. Reeves Wesley1 & P.R. Muthuswamy2

Abstract

In this article, we have developed a model based on prior literature and examined the relationshipbetween work role characteristics and job satisfaction. Data was collected from 230 faculty membersfrom self-financing Engineering colleges in and around Coimbatore city. Using multiple regressionanalysis it was found that work conflict, supervisory support, and job involvement influence jobsatisfaction. The results are discussed and implications to the institutions as well as to the individualsare suggested.

* Received November 11, 2005; Revised January 17, 20081 Associate Professor, Karunya University, Coimbatore, email: [email protected] Dean, KMCH Institute of Health and Hospital Administration, Coimbatore,

email: [email protected]

1.0 INTRODUCTION

Work is deemed as an unavoidableaspect of human being. All socialrelationships are built around work.Human beings by working alsocontribute to the work world with theirintellectual stimulation, seek personalgrowth, relish the challenge of work, andget the financial benefit it provides(Gordon and Whelan, 1998). It is a sourceof life’s purpose, self-esteem and avalidating experience for men andwomen (Kanter, 1977). Work lendsmeaning to one’s lives and fulfils it(Rifkin, 1995). So, it may be seen thateconomic survival, satisfying the interestof the unremunerated work domain

(family) of an individual’s life and self-interest stimulates an individual to work(Meda, 1996). However, there is nodenying the fact that the most importantreason why an individual works is inorder to survive, since work is the onlymeans of meeting the end i.e., thefinancial stability of the family (Pratt andRosa, 2003).

Unfortunately, work which is deemedto be a source of l i fe-giving toindividuals and in turn to families withwhich an individual is attached isworking just in opposite direction.Organisations put pressure, explicitand implicit, on employees to put moretime, stay late at night, come in on




weekends, take work home and so onto help the f irm improve itscompetitive position (Hall, 1990). Thenorm of a 35-44 hour/week has givenway to longer hours in the full-timeworking week. With the dawn of anew century, the information age israpidly replacing the industrial age,bringing with it new norms of workand longer hours of work involvingharder and more challenging tasks andthe need to be multi-skil led. Theglobal isation process which hasresulted in increased and intensecompetition has brought in significantchanges in the workplace. By andlarge, it is believed that humankindspends a major portion of his or hertime and energy in this realm due tothe changing nature of work inresponse to new demands andenvironmental pressures. Therefore,assessing the characteristics of workrole (hereafter referred to as WorkRole Characteristics, labeled as WRC,becomes essential because of its verynature of being a factor influencingreactions to job related outcomes likejob satisfaction. Researchers earlierhave studied the relationship betweenWRC and job satisfaction, however,have often captured only one or twoWRC. Keeping this in the backgroundand after a careful investigation ofprior literature (Aryee, Fields and Luk,1999; Carlson and Perrewe, 1999) theresearcher examines four suchcharacteristics: Work demand (WD),

Work Conflict (WC), Job involvement(JI) and supervisor support (SS) andtheir impact on job satisfaction (JS).Accordingly, the researcher attemptsto study the following objectives.

1) To study the relationship betweenwork demand and job satisfaction

2) To study the relationship betweenwork conflict and job satisfaction

3) To study the relationship betweenjob involvement and job satisfaction

4) To study the relationship betweenSupervisor support and jobsatisfaction.

Organisations put tremendous pressureon employees resulting in longer hoursof work and increase of the work load.They affect the level of controlindividuals exert, when faced withincreasing role demand and timepressures. This results in incompatibilitywithin the work role as well as life’s otherdomain. A review of the extant literature(Aryee, Fields and Luk, 1999; Carlsonand Kacmar, 2000) shows that suchincompatibility result in increase in workdemand thus, affecting job satisfaction.Accordingly, the researcher hypothesizesas follows:

H1: Work demand is negatively relatedjob satisfaction

Higher work overload - which is referredto as a condition where an individual isexpected to do too many things within alimited time, as part of the daily routine

67

(Sekaran, 2004), could also lead toconflict within the work domain, in whichall the work demands cannot be met inthe available span of time. Moreover, aninsightful investigation into the roletheory (Katz and Kahn, 1978) reveals thatincompatible expectations from thesupervisors would leave the individualunable to influence the supervisor’sactions, thus experiencing conflict atwork. Subsequently, a review of priorliterature (Aryee, Fields and Luk,1999;Carlson and Kacmar, 2000; Higgins andDuxbury, 1992) reveals that an increasein demand in the work role results inconflict affecting job satisfaction.Accordingly, the researcher hypothesizesas follows:

H2: Work conflict is negatively related tojob satisfaction

Studies have reported that jobinvolvement represents an internal orself-induced source of pressure (Frone,Russell and Cooper, 1992a,b;Parasuraman, Purohit, Godhalk andBeutell, 1996) to achieve a desired need.The most important inference that couldbe made from the above definitions isthat job involvement refers to theindividual’s mental and emotionalinvolvement in the job in an attempt tofulfill its demands, leading to increaseddevotion of time and energy in the workrole. It includes identifying with the job,actively participating in it, and perceivingjob performance to be important to self-worth (Blau, 1985; Rabinowitz and Hall,

1977) resulting in incompatibility with theexpectations of the job thus, affecting jobsatisfaction (Aryee, Fields and Luk,1999;Parasuraman and Simmers, 2001).Accordingly, the researcher,hypothesizes as follows:.

H3: Job involvement is negatively relatedto job satisfaction

Supervisor support involves theinterpersonal transaction that takes placebetween the members of the organisationand the supervisor, seeking support onissues related to work and affecting theindividuals. The issues that could affectthe individual might be workenvironment stressors, such as timepressure which is a characteristic of thework (Kickul and Posig 2001) and rolepressure which is a combination ofexpectations and demands thatindividuals either place upon themselvesor have placed upon them by otherpeople such as the supervisors (Mattesonand Ivancevich 1987). The time pressureand role pressure at workplace mayinhibit the individual’s requirements tosatisfy the obligations of the job.Therefore, it is imperative that whenemployees experience role pressure ortime pressure, supervisors shouldattempt to provide emotional support(Kickul and Posig, 2001). Accordingly,the researcher hypothesizes as follows:

H4: Supervisor support is positivelyrelated to job satisfaction.

The model describing this relationship isdepicted in figure. 1

Wesley et.al, Work Role Characteristics as...


2.0 METHODS

Measurement of the Variables under study

A questionnaire consisting of itemscapturing the work role characteristicsand job satisfaction was used to collectdata.

Independent variables: The work rolecharacteristics are the independentvariables. The various factorsconstituting the work role characteristicswere measured as follows: Work demandscale Cronbach α = 0.65) consisted of fouritems adopted from Williams and Alliger(1994); work conflict (Cronbach α = 0.77)adopted from Higgins, & Duxbury,(1992) consisted of 8 items; jobinvolvement (Cronbach α = 0.66) was ashortened form of Lodahl and Kejner(1965) scale, quoted in Lobel and Clair,(1992) consisted of 4 items and supervisorsupport (Cronbach α = 0.61) originallydeveloped by Shinn, Wong, Simko andOrtiz-Torres (1989) and adopted fromBatt and Valcour (2003) consisted of 6items. The items were measured on afive point Scale (5 = Strongly agree to 1 =Strongly disagree).

Dependent Variable: The dependentvariable is job satisfaction. 8 items areused to measure the job satisfaction(Cronbach α = 0.78). These items werequoted in Wesley, Oomen, Sumithra andVarkey, (2003). It is measured on a 5point scale (eg, 5 = Strongly agree to 1 =Strongly Disagree).

Sample and Data Collection

The data for this article were collectedin course of doctoral work. Accordingly,the questionnaire was administered to403 faculty members working inEngineering Colleges in and aroundCoimbatore city. Almost half of thequestionnaires were administered inperson and the remaining by choosing acontact person in each college, throughwhom the questionnaires weredistributed. However, the researcherpersonally met the respondents orcontacted them over phone, to solicittheir kind cooperation in filling up thequestionnaire. They were given theassurance that their responses would beused only for academic purpose and wereassured absolute confidentiality andanonymity on the information will bemaintained. This was done based on thesuggestions given by the respondents inthe pilot study, in order to encourage andsolicit the kind cooperation of therespondents, in giving complete andaccurate information. A thorough follow-up was done in person and overtelephone to expedite the process offilling up the questionnaire. Yet some ofthe questionnaires were not returned and

- - - +

Work demand

Work conflict

Job involvement

Supervisor

Job Satisfaction

Figure - 1 Model depicting the relationshipbetween work role characteristics and job

satisfaction

69Wesley et.al, Work Role Characteristics as...

some were unusable and incomplete,yielding a response rate of 57.1% (230usable questionnaires).

The justification for choosing engineeringcollege teaching faculty as therespondents, was based on the patternof reasons given by Suppal, Roopnarine,Buesig and Bennett, (1996). It was seenthat they are educated and economicallystable because of the even salary structureprescribed by their governing body (i.e.,All India Council for TechnicalEducation). Further, the respondentsfrom academia are appropriate becauseof the likelihood of experiencing higherwork role characteristics such as workdemand (Wesley and Muthuswamy,2004). Moreover, academic realm holdsunique challenges, especially for womenwho often report greater demands in life(Dressel and Clark, 1990; Piotrkowski,Rapoport, and Rapoport, 1987).

3.0 RESULTS

Data were analyzed using SPSS Version11. Table-1 presents the means, the

standard deviations and theintercorrelations among the studyvariables. It is found that the meansrange from a moderate (2.69 for SS) to ahigh score (3.83 for WD). The standarddeviation of the variables measured on a5-point scale appears to be slightly higherwith factors like SS reporting 0.98. Theinter-correlations range from very low(e.g., 0.00 between WD and JS) tomoderate values (0.30 between WD andJI). Theoretically, there is no evidenceof multicollinearity. Correlations aremeaningful within the conceptualframework of the study, reachingstatistical significance. The coefficientsprovide support for the suggestedlinkages between the work rolecharacteristics and JS when viewed assimple associations. However, the resultsof the multiple regression analyses istaken for discussing the model in the nextchapter because of its advantage overcorrelation in explaining the simultaneouseffects of two or more variables in themodel.

Mean (& Standard 1 2 3 4 5Deviation)

Work demand 3.83 (0.65)Work conflict 2.86 (0.68) .15*Supervisory Support 2.69(0.98) .11 .18**Job involvement 3.38(0.70) .30** .15* .17**Job Satisfaction 3.78(0.60) -.00 -.22** .24** .23**

Table -1: Matrix of inter correlations among study variables

* Correlation is significant at the 0.05 level (2-tailed).** Correlation is significant at the 0.01 level (2-tailed).Standard deviations given in parenthesis


Table-2 presents the results of theregression analysis examining theantecedents of job satisfaction. The R²= 0.184 indicates that the regressionmodel explains 18.4% of the variance inthe dependent variable and R² seem tobe significant as indicated by the F-value. The adjusted R² = 0.170 showsthat any time another independentvariable is added to this model, the R²will increase (even if only slightly). Thedecline in the adjusted R² and smallerdifference between R² and adjusted R²are due to the relatively larger numberof observations compared to thenumber of predictors. The decline inthe adjusted R² may also be due to theless contribution to the explaineddeviation by the additional variable tothe degrees of freedom. On examinationof the standardized beta coefficients, itis found that WC (β = -0.29, p < 0.05) issignificant negatively supportinghypothesis H2 and SS (β = 0.25, p < 0.05)and JI (0.26, p < 0.05) are positivelyrelated to job satisfaction supportinghypothesis H3 reversely and H4respectively. Work demand is non-

significant predicting and hence,hypothesis H1 is not supported. Workconflict is the strongest predictor of JSfollowed by JI and SS. The slopes givenby the B values quantify the steepnessof the regression line. It equals thechange in job satisfaction for any levelof change in the predictor variables. Itindicates that any change in workconflict would affect change in jobsatisfaction in the reverse direction.Similarly, any change in job involvementand supervisor support result in changein the positive direction.

4.0 DISCUSSION

The goal of this study was to examinerelationship between work rolecharacteristics and job satisfactionoccurring as a function of the work rolecharacteristics, by evaluating ahypothesized model.

This study reported a smaller R², in spiteof the model being fit. In order toincrease R², work role characteristics maybe expanded to include variables such aswork role ambiguity and include life’sother role characteristic variable such as

Table- 2: Regression results predicting job satisfaction

Dependent Variable: Job satisfaction; R² = 0.184; adjusted R² = 0.170; F = 12.70(p < 0.05); constant (y intercept) = 3.588

Unstandardised B Beta Coefficients (β) t Sig.

Work demand -.0572 -.06 -.99 .33

Work conflict -.258 -.29 -4.74 .00

Supervisory Support .153 .25 4.07 .00

Job involvement .219 .26 3.97 .00


family role characteristics. Moreover, theresearchers assert that job satisfaction isan universal and pervasive phenomenonpredicted by many other organizationalfactors such organisation culture andclimate and work role characteristics isone of those many significant others thataccount for variance in the dependentvariable thus, resulting in a smaller R².

The results report that all the work rolecharacteristics, but work demand, predictjob satisfaction. The strongest predictionof JS by WC indicates that the facultymembers are subjected to multiple roleswithin the work role. The multiple rolesmay be in the form of conducting extracoaching for weak students,administrative work such as attendancemaintenance of the students andinforming parents about the performanceof the students, doing research,consultancy and publishing papers injournals. Going by the number ofinstitutions offering higher educations,increasing competition and the indicationof foreign universities making forays intothe Indian soil this year, quality isdeemed to be the focal point for survivalfor both the faculty and the institution.In view of this, they experienceincompatible expectations from two ormore significant others in the work role(e.g., students and management) leadingto dissatisfaction in their job.

The reward value of the SS is evidencedin its prediction of job satisfaction.Although SS is found to be lowest asreported by the mean value, it has

significance as its prevalence increases jobsatisfaction. This suggests that thesupervisors in educational institutions areempathetic whose support could be usedas a coping mechanism aimed ataccommodating the faculty’s multiplerole pressures (WC), thus increasing jobsatisfaction. Further, the SS - JSrelationship indicates in general, thegenre of supportive climate that exists ineducational institutions. It suggests theperceptions of supportive leadershippractices that influence feelings ofpersonal emotional state of the facultiesdirectly.

Job Involvement’s (JI) positiverelationship with JS is a notable finding.It points to the benefits associated witha workforce where faculty membersappear psychologically involved in theirwork efforts are satisfied with their jobs.

5.0 IMPLICATIONS, LIMITATIONS AND FUR-THER RESEARCH

This study has important implications forboth organizations and individuals as ithas the potential to benefit both of them.In the context of WC affecting JS,institutions can help increase jobsatisfaction by making adjustments in thework role through sufficient supervisorysupport. While multi-skilling and multi-tasking are present day phenomena, rolesinterfering with each other can bereduced by applying unity of commandprinciple, combined with clear jobdescription and supervisor support. Thismay also help to enhance the effective flowof communication from the superiors to


the faculty members, eliminating dualreporting relationships. Avoidance ofwork conflict would also to greaterextent enhance the faculty members’involvement in one particular job ratherthan sharing their psychologicalinvolvement with more than one job.However, institutions to induce multi-skilling and multi-tasking may resort tojob rotation rather than assigningsimultaneous multiple roles. This wouldto a greater extent make the faculty amulti-faceted personality. Further, it isseen that supervisory support may be amechanism, so effective, in givingsolution to reduce work conflict andenhance job satisfaction. Institutions canalso resort to newer initiatives, whichinclude the supervisors and the facultyjointly setting time and ethical standardsthat would meet the organizationsexpectations and match the faculties’abilities. This would also effectivelypromote two-way communicationbetween the supervisors and theirfaculty. In addition to this, they can alsojointly decide on the optimum numberof roles to be assigned to the faculty, theresources and support required fromtheir colleagues and supervisors tocomplete the tasks effectively.

Firstly, the sample is limited toCoimbatore city alone. Taking intoconsideration the number of engineeringcolleges spread over the state ofTamilnadu, this is a smaller sample.Therefore, future studies should focus onlarger samples across the state and lateracross India, which may reveal a better

picture on the work role characteristicsand their effect on job satisfaction.Secondly, the sampling focus is on theteaching faculty, which limits thegeneralisability of the findings of thestudy, given the structural andeducational differences in thecharacteristics of the employment ofother non-teaching professions. Hence,research should focus on occupationallyheterogeneous sample of individualspossessing diverse skills. Thirdly,researchers in the future shall have agendered approach while studying therelationship. Fourthly, realistically, thelink between the conflict arising out ofthe participation of men and women inmultiple roles and its impact on JS maybe complex. A structural equationmodelling may be applied to understandthe complex nature of this relationshipand thus eliminate measurement errors.Fifthly, although this study is conductedin a different culture (Indian), attemptwas not made to measure the culturalvalues and beliefs of Indians on work.Future studies shall focus on capturingthese factors too. Sixthly, future researchshall include other work-related factorssuch as age, years of experience etc., instudying this relationship.

6.0 CONCLUSION

This study is one among the pioneer testsgleaned from several literatures,providing insights into the importance ofjob satisfaction while understanding thework role characteristics. A majorcontribution of this study is that it


proposed and tested a composite model,thus establishing a relationship betweenthe various work role characteristics andjob satisfaction using a non-westernsample. For institutions concerned withthe retention and performance of theiremployees, this study suggests practicespainstakingly, that help enhance jobsatisfaction, supervisory support and jobinvolvement whereby, reducing workconflict. This facilitates institutions tocontinually gain competitive advantage.

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Empirical Examination of A Cost AllocationModel: Using the Theory of Planned

Behaviour*

Ajay Kumar Pillai1

Abstract

This study examines the behavioural, normative and control beliefs of managers related to cost allocation.The study is conducted in two phases. In the first phase, a procedure was used to determine the outcomebeliefs that underlie manager’s attitudes. Ajzen’s theory of planned behaviour provided the conceptualbasis for this study into manager’s attitude towards cost allocation.

Overall, the results of the study suggests that targeting identified underlying beliefs may serve tostrengthen the intentions of managers to participate in cost allocation. A major advantage of the TPB isits ability to identify the underlying beliefs that distinguish between individuals intending and notintending to perform a specified behaviour. It is proposed that the concepts of behavioural intentions,norms and perceived behavioural control can be adapted to the context of cost allocation.

* Received October 4, 2007; Revised February 26, 20081. Lecturer, SCMS School of Technology and Management, Muttom, Cochin,

email:[email protected]

1.0 INTRODUCTION

Attitude is an important concept that isoften used to understand and predictpeople’s reaction to an object or changeand how their behaviour can beinfluenced. Interest in this concept can beobserved not only among socialpsychologists but of late amongmanagement accounting scholars.

In cost allocations, literature revealsinterest in attitude generally andspecifically to certain techniques such as

Activity Based Costing (Kaplan, 1998).Not much research has been done on theattitude of managers in India towardscost allocation. Another factor that hasbeen neglected, but has a significantimpact on the performance of costallocation systems is the concept ofbehaviour.

The study of attitude’s influence onbehaviour began in 1872 with CharlesDarwin. Darwin defined attitude as thephysical expression of an emotion. In the



1930’s psychologists defined attitude asan emotion or thought with a behaviouralcomponent.

There are a number of psychologicaltheories that explain behaviouralintentions. Of special importance are thetheory of reasoned action (Fishbein andAjzen, 1975) and the theory of plannedbehavior (Ajzen, 1985, 1987, 1991). Thesetwo theories (reasoned action andplanned behaviour) have been appliedto predict behaviour in many settings,with considerable success (Baron et al.,2006).

The theory of planned behaviour (TPB)provides a conceptual vocabulary tohelp organize empirical observations,and indicates the important variablesin the attitude-formation process (Teoand Loosemore, 2001). Numerousstudies have conducted belief-basedanalyses using the TPB framework tounderstand behaviour. Most of theresearch, in this context, has been in thehealth area.

This paper is organized as follows: thenext section describes the Theory ofPlanned Behaviour and then the conceptof cost allocation is introduced. This isfollowed by the methodology and theanalysis and discussion of this study.Then, a model for cost allocation isproposed and recommendations aremade to help improve manager’sattitude towards cost allocation. Thepaper identifies areas for furtherresearch before concluding with a briefsummary.

2.0 THEORY OF PLANNED BEHAVIOUR (TPB)

Social psychologists theorized thatattitude included behaviour andcognition and that behaviour and attitudewere positively related. It wasconsidered that attitudes were multi-dimensional systems consisting of beliefsabout the attitude object and actiontendencies towards the object.

In 1934, the results of a study conductedby a leading psychologistdemonstrated that attitude was not agood predictor of behaviour. By thelate 1960’s, social psychologists nolonger believed that they had a theoryto explain the relationship betweenattitude and behaviour. It was in thisenvironment that Ajzen and Fishbeincreated the Theory of Reasoned Actionin 1967.

Ajzen and Fishbein (1973) proposed thata person’s behaviour was determinedby his intention to perform thebehaviour and that this intention was,in turn, a function of his attitudetowards the behaviour and subjectivenorms. Since then, there has beenconsiderable research and theorizingon attitude from diverse perspectives.The theory of reasoned action sufferedfrom a number of limitations whichmade Ajzen propose the Theory ofPlanned Behaviour.

The theory of planned behaviour modelsbehavioural intention as depending onthree factors: (1) attitude towards thebehaviour (AB); (2) subjective norms (SN)

77

and (3) perceived behaviour control(PBC). This theory is diagrammed inFigure 1:

Beliefs & Factual Knowledge

Social & Moral Values

Attitude (AB)

Subjective Norms (SN)

Perceived Behavioural Control (PBC)

Behavioural Intention

Actual Behaviour

(Figure 1: The Theory of Planned Behaviour)

Each of these determinants ofbehavioural intention (ie. AB, SN, PBC)is itself a function of an individual’ssalient belief (Ajzen, 1991). Managersmay hold certain beliefs and may formattitudes about cost allocation based onthese beliefs. In turn, intentions to complyor resist may relate to attitudes as wellas norms about these behaviours.

Attitudes relate to one’s own personalviews about the behaviour. Theantecedents of attitudes include bothbehavioural beliefs about the action andoutcome evaluations. Behavioural beliefsare the expected consequences of abehaviour (e.g., a belief that managersallocating costs will increase costconsciousness) and outcome evaluationsare the actor’s assessment of thoseconsequences (e.g., a belief that it is goodfor managers to be cost conscious).

Subjective norms are a function of anindividual’s perception that one or morerelevant people would approve of aparticular behaviour and the extent to

which the individual’s behaviour wouldbe influenced by that.

Perceived behavioural control refers toan individual’s perceptions regarding theextent of control he or she has over aparticular behaviour. This factor ismodelled as capable of influencingbehaviour directly as well as through it’seffects on intentions.

Although each determinant would havean impact on a person’s intentionstowards a behaviour, the relativeimportance of each determinant wouldvary based on the circumstances and thebehaviour studied. For example, twomanagers, each with a positive attitudetoward cost allocation, may engage indifferent behaviours if they face differentpressures in their environments.

3.0 COST ALLOCATION

Companies have to routinely allocatecosts of common corporate resources andfor this purpose they use a variety ofallocation methods reflecting differentattitudes concerning cost allocation. Abasic question often asked is: why costallocation?

Management accounting scholars haveattempted to offer different explanationsfor it. Cost allocation arises wheneverthere exists common resources which aredifficult to measure by the centralmanagement.

The important fact about common costwas recognized more than three quartersof a century ago, and reemphasizedmany times since then in leading

Pillai, Empirical Examination of A...


economic and accounting journals(Bonbright, 1961). However, theeconomic explanation was intertwinedwith the statistical reason why seriousproblem can arise with the allocation ofcommon costs.

There has been an everlasting debateabout cost allocation and manyarguments have been put forth to showwhy common costs cannot bemeaningfully allocated. Despite theseapprehensions, there is growing evidencethat companies do allocate costs for avariety of reasons and that there arearguably certain benefits associated withit (Modell, 2002).

Managerial accounting books (Horngrenet al., 2005; Blocher et al., 2006 andothers) and studies (Zimmermann 1979;Drury and El-Shishini, 2005 and others)on cost allocation have documented thewidespread practice of cost allocation.

The literature also states that there aretwo basic outcomes from allocating costs:better economic decisions (Snyder andDavenport, 1997) and a higher level ofmanagerial motivation (Morse andZimmermann, 1997)

Researchers exploring the adoption ofvarious cost allocation practices across awide range of companies provide supportfor behavioural considerations in costallocation systems. Since cost allocationmethods are components of the overallperformance evaluation system, it isimportant to identify the behaviouraldimensions before examining attitudes incost allocations.

3.1 Behavioural Considerations in CostAllocation

It was in 1977 that Bodnar and Lusk(Bodnar and Lusk, 1977) first introducedbehavioural considerations in costallocations. Their research addressed thestudy of cost allocation in terms of aspecific behavioural theory. Since thenmost management accounting scholarshave been guided by a behaviouralperspective while examining costallocation systems.

It has often been stated that one of thelikely explanation for the prevalence ofcost allocations within organization ismotivation and that cost allocation couldbe used to motivate managers toconsume less or more of the company’sresources. Another point made byresearchers was that managers mustconsider cost consciousness whileallocating costs.

Cost allocation must be done carefullybecause the motivational dimensionpresent in any allocation affects financialperformance (Bodnar and Lusk, 1977).Additionally, cost allocation serves as acommunication mechanism to letmanagers know how their actions wereaffecting costs in the rest of theorganization.

One of the commonly cited criticism ofcost allocation is its arbitrariness(Thomas, 1971). However, the positionthat all cost allocations are necessarilyarbitrary has been subject to debate.There was also suggestions that the

79

problem of arbitrariness has beencompounded by the institutionalizationof various allocation practices, such as theprevalent use of direct labour or othervolume-dependent bases for overheadallocations, but that the adoption of moresophisticated techniques such as activity-based costing might mitigate against this(Kaplan, 1999).

Critics of cost allocation interpret theword arbitrary to mean unfounded orwithout justification. They argue that costallocation could result in misleadinginformation that causes poor decisionsand therefore should be avoided (Hiltonet al., 2003). However, proponents ofcost allocation feel that it provides theright incentive for managers to makedecisions that were consistent with thegoals of top management (Blocher et al.,2006).

In addition to arbitrariness, it has alsobeen pointed out that poorly designedcost allocations could be the subject ofdisputes among departments and theirconstituents (Hilton et al., 2003). Thiscould lead to unnecessary tensions.

In spite of this, many managers allocatecosts to divisions and otherdepartments. Surveys conductedaround the world report that companiesallocate costs for a number of reasons.A recent survey conducted in UK foundthat companies allocated costs to remindmanagers that such costs exists and tostimulate them to economize in usage ofcorporate services (Drury and El-Shishini, 2005).

Building upon the behaviouralconsiderations, the literature identifiesthe following popular beliefs regardingcost allocation (See Table-1)

Table-1: Belief variables along with the related literature)

Zim

mer

man

n(1

979)

Abb

as a

nd A

bd-

Alla

h (1

999)

Hor

ngre

n et

al

(200

5)

Dru

ry a

nd E

l-Sh

ishi

ni (

2005

)

Thom

as (1

971)

Atk

inso

n at

al.,

(200

3)

Hilt

on e

t al

.,(2

003)

Cost allocation can lead to optimalutilization of resources × × ×

Cost allocation can lead to cost consciousness × ×

Cost allocation can lead to a highlevel of motivation × × ×

Cost allocation is not always accurate × ×

Cost allocation causes unnecessary tension × ×

Cost allocation often leads to conflict × ×



The literature on cost allocation identifiestwo types of intentions regarding costallocation. One group supports costallocation and can be called intenderswhile the other group considers costallocation arbitrary and do not want toallocate costs. This group can be callednon-intenders. The dependent andindependent variables are shown inFigure-2.

The intention to allocate or not to allocatecosts is the independent variable and eachof the three constructs identified earlier(personal, referents and control) in theTPB is the multiple dependent variablein the model.

4.0 METHODOLOGY

This study employs the theory ofplanned behaviour to identify beliefsthat comprise a manager’s attitudetowards cost allocation. An attitudemeasure based on these beliefs is testedto determine the influence of attitudeson specific behavioural intentions. Forthis reason, data are collected in twostages. The first stage identifies the

beliefs and the second stage developsthe attitude measure. Ajzen’s theory ofplanned behaviour provided theconceptual basis for this study intomanager’s attitude towards costallocation.

In the first phase, a procedure was usedto determine the outcome beliefs thatunderlie manager’s attitude towards costallocation. These beliefs wereincorporated into an attitude measureused in the second phase. The datacollected is further analyzed usingmultiple regression. In this way, acombination of qualitative andquantitative methods is used in thisstudy.

Ajzen and Fishbein (1980) argue that foran attitude measure to be useful atpredicting behaviour, it shouldcorrespond to the behavioural intentioncriterion in target, action, context andtime (TACT) variables. Accordingly, inthis study, attitudes are examined for costallocation keeping in mind the aboveargument.

Phase One – Belief Elicitation Procedure

In accordance with the proceduresoutlined by Ajzen and Fishbein (1980),an elicitation study was conducted toconfirm the identified beliefs that weresalient to the target population whenconfronted with cost allocation. AnElicitation study is a qualitativeinvestigation of a subset of a populationunder investigation, to discover the

Personal

Intentions Intenders Non Intenders (to allocate (not to costs) allocate costs)

Referents

Control

(Figure 2: Dependent and IndependentVariables)

81

salient behavioural, normative andcontrol beliefs about the behaviour(Ajzen, 1991).

Data for elicitation can be collected byarranging a focus group, or byindividual interview or by mailingquestionnaires (Ajzen, 1991). Thisstudy used a combination of focusgroups and individual interviews tocollect data for the belief elicitationstudy. The sample for the elicitationstudy was 22. Participants were fromboth industry and academicbackground. Table-2 shows theresponses by group.

Table-2: Responses for Belief ElicitationStudy

Respondent source Number ofSubjects (Response

rate)

Industry 15 (70%)

Academicians 7 (30%)

Total Respondents 22

The responses were independentlyanalysed by labelling the themes andlisting them in order of frequency foreach of the following:

• behavioural beliefs

• sources of social pressure (referenceindividuals or groups)

• control belief strength

The belief elicitation study consisted ofan open-ended questionnaire to elicitsalient behavioural, normative and

control beliefs for participationintentions. Respondents were asked tolist the advantages and disadvantages ofallocating costs. This part of the studywas conducted in conjunction with a focusgroup. Flexibility was ensured from theability to explore unexpected leads thatemerged from focus group discussion,enabling greater insights into people’sattitudes, beliefs and feelings about anysubject.

Careful management of the focus groupsessions was required because in caseof homogeneous groups, like the onesused in this study, there is a possibilitythat data could be biased. The focusgroups were carefully structured intotwo distinct groups of intenders andnon-intenders. Respondents were fromboth industry and academicbackground so that the focus sessionwas effective and there was adequaterepresentation.

Phase Two – Main Experiment

Although the elicitation study resultprovides information about the beliefvariables, they provide little insightabout associations between theattitude and behaviour variables.These were explored further in thesecond phase during which data werecollected using a questionnaire. Thevalue of qualitative data produced inthe first phase complemented andenriched this part of the researchenabling deeper explanations betweenthe variables.



After identifying the belief variables andfurther confirming them by the beliefelicitation study, data were collected onthe six outcome belief measures by twogroups based on their intention toallocate costs. The managers allocatingcosts formed a group (intenders) whilethe other group consisted of managerswho did not intend to allocate costs (non-intenders).

The response scale was a 1-5 Likert scalewith extremely likely on one end andextremely unlikely on the other.Referents included top management,other managers and staff. Five controlbeliefs were further identified.

Respondents for this part of study werefrom different industries. The sampleconsisted mainly of finance mangers whohave handled cost allocation.Questionnaires were sent to 75 managers,out of which ten were returnedincomplete. Another fifteen were notreturned so the total respondents werefifty. Table-3 provides the sampledemographics.

person’s behaviour, values, motives andbeliefs can be made from the content ofthe communication with others.

The three most frequently reportedadvantages of cost allocation (e.g.,optimal use of resources) and the threemost commonly reported disadvantage(e.g., causing unnecessary tension)formed the behavioural beliefs in themain questionnaire. Respondents wereasked to list the persons who wouldapprove or disapprove of cost allocation.The most common referents (e.g., topmanagement) were used as a measure ofnormative beliefs in the mainquestionnaire.

Elicitation Study

Content analysis based upon Ajzen’sTheory of Planned behaviour wasperformed. This technique is particularlyuseful for highly unstructured data, andinvolves categorizing communicationcontent into its component part andquantifying it (Berg, 1989). Theassumption is that inferences about a

Table-3: Sample Demographics

Sample

Age30 & Below 25%31-40 55%41-50 15%51 & Above 5%

GenderMale 57%Female 43%

IncomeBelow 2 lakhs 26%2-4 lakhs 54%Above 4 lakhs 20%

IndustryManufacturing 50%Service 45%Others 5%

83

Respondents were then asked to list anyfactors or circumstances that mightdiscourage or encourage them inallocating costs. The six most frequentlyreported barriers to allocating costs (e.g.,lack of awareness) formed the measureof control beliefs in the mainquestionnaire for the behaviour.

The main questionnaire assessed costallocation intentions and measuredbehavioural, normative and controlbeliefs for intentions to perform thebehaviour of allocation. Most belief itemswere positively worded with somenegatively worded items included toreduce participant response bias. All TPBitems were scored on 5-point Likertscales.

Intention: Two items were used to assessthe strength of participants’ intentions toperform the target behaviour (e.g., ‘Iintend to allocate costs’) ranging fromstrongly disagree [1] to strongly agree[5]).

Behavioural beliefs: The measure ofbehavioural belief comprised sixbehavioural belief items. Respondentswere asked to indicate how likely it wouldbe that three benefits and threedisadvantages obtained from theelicitation study, would result if theyparticipated in allocating costs, rangingfrom extremely unlikely [1] to extremelylikely [5]. To obtain an overall measure ofattitude belief, participants’ responses onthe behavioural items were averaged.

Normative belief: The measure ofnormative belief was assessed by fournormative items. Participants wereasked how likely they thought fourdifferent referents, identified from theelicitation study (e.g., top management)would think that they should allocatecosts and the answers varied fromextremely unlikely [1] to extremelylikely [5]. The participant’s scores on thenormative belief items were averagedto provide an indirect measure ofsubjective norm.

Control belief: The measure of controlbelief was obtained from six control beliefitems. Participants were asked to ratehow likely two external and three internalfactors obtained from the elicitationquestionnaire were to prevent them fromallocating costs from extremely unlikely[1] to extremely likely [5]. Participant’sscores on the control belief items wereaveraged to provide the indirect measureof PBC.

5.0 RESULTS

As stated previously, the beliefelicitation procedure was performed inconjunction with a focus-group study.Table-4 summarizes the mostcommonly mentioned advantages anddisadvantages for cost allocation.Based on these findings, the six beliefvariables identified by the literaturewere confirmed as the outcomevariables to be included in the mainquestionnaire.



On the basis of TPB research, threeseparate MANOVAs were performed toexamine the belief-based differencesbetween managers intending to allocatecosts and those not intending to allocate.In each analysis, the set of beliefs (i.e.,behavioural beliefs, normative beliefs orcontrol beliefs), were examined in anexploratory manner to identify thosebeliefs differentiating between managersintending and not intending to allocatecosts.

Three one-way multivariate analysesof variance (MANOVAs) wereconducted with intentions as theindependent variables and the belief-based measures as the dependentvariables. The distributions for thebehaviour was split into intenders andnon-intenders.

Overall, Wilk’s Lambdas were significantfor the three MANOVAs (p<.001) onmeasures of behavioural, normative andcontrol beliefs. To further explore the

differences between the groups, thedependent variables were examined atthe univariate level. Table-5 analysesexamining beliefs differentiatingintenders and non-intenders. The meanbeliefs for intenders and non-intendersare shown in the form of graph inFigure-3.

Table-4 : Summary of most FrequentResponses confirmed in the BeliefElicitation Procedure

Particulars Number ofresponses (%)

AdvantagesOptimum resource utilization 9 (40%)Motivates managers 8 (36%)Promotes cost consciousness 5 (24%)DisadvantagesIs not always accurate 10 (45%)Causes unnecessary tension 7 (31%)Often leads to conflict 5 (24%)

Behavioural beliefs

According to Wilk’s criterion, there wasa significant multivariate effect ofintentions on behavioural beliefs for costallocation, F (6,82) = 4.927, p < .001.Univariate analysis revealed thatintenders and non-intenders differedsignificantly on their assessment ofpositive and negative outcomes.

Managers allocating costs were morelikely to believe that optimum utilizationof resources (4.92) and cost consciousness(4.90) would result if they participatedin cost allocation. On the other hand,those managers who did not intend toallocate costs were more likely to feel thatconflicts (4.58) and the inaccurate resultsof cost allocation (4.53) would preventthem from allocating costs. As regardsmotivating managers, intenders (4.88)felt it is an important consideration andnon-intenders (4.00) considered it as notinfluencing cost allocation.

Normative beliefs

The second MANOVA examinednormative beliefs on allocationintentions. According to Wilk’scriterion, a significant multivariate effectwas found between groups for

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Table-5: Mean beliefs for non-intenders and intenders in allocating costs

Beliefs Non-Intenders Intenders(n=50) (n=52)

Mean SD Mean SD

Behavioural beliefOptimum resource utilization 4.15 0.80 4.92 0.77Motivating managers 4.00 1.41 4.88 0.99Promoting cost consciousness 3.66 1.03 4.90 0.68Not always accurate 4.53 0.51 3.83 0.70Causes unnecessary tension 4.30 0.63 4.04 0.86Often leads to conflict 4.58 0.58 4.25 0.44Normative beliefTop management 2.50 2.21 4.25 0.50Other managers 3.33 1.50 4.08 0.71Staff 3.10 0.51 4.20 0.41Control beliefLack of awareness 3.95 0.84 4.00 0.44Inability to allocate 3.50 0.81 3.49 0.95Arbitrary 4.25 0.96 3.85 0.85Type of Industry 4.50 0.70 4.34 0.52Time restraints 4.69 0.88 4.25 0.83

Intenders

0

1

2

3

4

5

6

Cost consciousness Optimum use of

resources Motivating managers Not always

accurate Causes unnecessary

tension Often results in

conflict

Inte

ntio

ns

I intend to allocate costs I do not intend to allocate costs

Figure 3: Graph Showing Mean Beliefs for Intenders and Non- Intenders



Table-6: Multiple regression analysis predicting allocation intentions

Variable R R2 F df β

Prediction of intentions .65 .42 27.06 3, 166

Behavioural beliefs .52***

Normative beliefs .39**

Control beliefs -.21

*** denotes very strongly significant** denotes strongly significant

6.0 DISCUSSION

The aim of this research was todetermine the beliefs differentiatingmanagers who intended to allocate(intenders) and managers who did notintend to allocate (non-intenders). Thefindings of this study suggests thatintenders and non-intenders differed

significantly on measures ofbehavioural, normative and controlbeliefs.

The most important predictor ofallocation intentions was behaviouralbeliefs. Therefore, the results of thisstudy provide information regardingbeliefs to target in formulating

normative beliefs, F (3,92) = 2.568, p <.001. Univariate analysis revealed thatintenders and non-intenders differedsignificantly in their perceptions ofpeople who would influence them inallocating costs as shown in Table-5.Managers allocating costs were morelikely to be influenced than those notallocating costs.

Control beliefs

Finally, a significant multivariate effectwas found between the groups forcontrol beliefs, F (5,91) = 1.56, p < .001.Univariate analysis revealed thatintenders and non-intenders differedsignificantly on some of the controlbeliefs, as shown in Table-5. Non-intenders were more likely than

intenders to report that arbitrariness ofcost allocation would prevent them fromallocating costs.

Regression analysis examining the roleof beliefs in allocation intentions

While the MANOVA analysisdetermined the beliefs thatdifferentiated between those managersintending to and those not intending toallocate costs, the belief’s predictingintentions were not identified. Therefore,a multiple regression analysis wasconducted to determine which of thebehavioural, normative and controlbelief sets contributed most to theprediction of intentions. The results ofmultiple regression analysis is shown inTable-6.

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strategies to increase allocation amongthose currently not intending to allocatecosts in their organizations.

For behavioural beliefs, intenders andnon-intenders differed significantly onbeliefs regarding both the advantagesand disadvantages of cost allocation.Intenders were more likely to believethat cost allocation will result inoptimum utilization of resources and atthe same time promote costconsciousness whereas non-intenderswere more likely to focus on thenegative belief (causing conflict). Thisfinding is in accordance with previousresearch suggesting that both costs andbenefits influence allocation(Zimmerman, 1979).

The findings that behavioural beliefspredicted allocation intentions suggeststhat, to shift the perceptions ofmanagers not intending to allocatecosts, future strategies should considerthe costs and benefits of cost allocation.A primary focus should be to decreaseperception of the costs ( i.e timerestraints, lack of awareness) andincrease the perceived benefits ofallocating (e.g. , promoting costconsciousness).

Examination of normative beliefsidentified in the study revealed thatdifferent sources of perceived normativepressures were apparent. Intenderswere more likely to be influenced by thetop management, other managers andstaff while allocating costs. Thus, a

potential strategy is to encourageparticipation in cost allocation involvingboth the top management and theemployees.

Examination of control beliefs revealeda significant difference betweenintenders and non-intenders. However,results from MANOVA revealed thatonly few control variables distinguishedbetween intenders and non-intenders.For control belief, non-intenders weremore likely to report that lack ofawareness and arbitrariness ofinformation would prevent them fromallocating costs.

Therefore, to increase participation incost allocation, it may be useful to developstrategies to combat the impact ofconflicts on cost allocation (e.g., costs canbe distinguished into controllable oruncontrollable to reduce unnecessaryconflicts).

When considering the appliedimplications of the findings of the presentstudy, it should be noted that failure toallocate costs is often attributed to thefact that often managers have no controlover certain costs and that they object tocharges they cannot influence andcontrol.

If cost allocations in an organization areunrelated to either the use of resourcesor influencing desired behaviour, thenit is difficult to justify any reason for costallocation. However, if costs areallocated in an efficient manner then



organizations can achieve the desiredoutcomes.

The manager should formulate a costallocation system that results in optimaldecision making and encourages alllevels of management to make decisionsthat are optimal from the organizationalperspective. The notion of beliefs andattitudes are an importantconsideration in constructing a costallocation system for performanceevaluation purpose.

7.0 A MODEL FOR COST ALLOCATION

A major advantage of the TPB is itsability to identify the underlyingbehavioural, normative and controlbeliefs that distinguish betweenindividuals intending and not intendingto perform a specified behaviour. Thisstudy uses this ability of the TPB modelto identify the beliefs regarding costallocation that distinguish betweenmanagers intending and not intendingto allocate costs.

Figure 4: Schematic Presentation of Conceptual Framework relating beliefs, attitudes, intentionsand behaviours with respect to Cost Allocation

(Source: Adapted from Ajzen's Theory of Planned Behaviour)

Beliefs about cost Allocation 1. Cost allocation can lead to optimum utilization of resources 2. Cost allocation can motivate managers 3. Cost allocation promotes cost consciousness 4. Cost allocation is not always accurate 5. Cost allocation causes unnecessary tension 6. Cost allocation often leads to conflict

Attitude towards Cost Allocation

Intention with respect to Cost Allocation

I intend to

allocate costs

Behaviours with respect to Cost Allocation

A

B

Influence

Feedback

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The Figure-4 shows that beliefs aboutcost allocation leads to formation ofattitude towards allocating costs whichin turn leads to a set of intentions thatindicates intention and non-intention toallocate costs. Each of these intentionsrelates to a certain behaviour. Forinstance, A leads to the behaviour that:“I will allocate costs as it will lead tooptimum utilization of resources and a higherlevel of motivation which will ultimately leadto cost consciousness”.

The second intention leads tobehaviour B which is :”I will notallocate costs as it will not always beaccurate and causes unnecessary tensionwhich will finally lead to conflict”.

Ajzen (1991) and other researchers havedescribed attitude as a learnedpredisposition to respond in aconsistently favourable or unfavourablemanner with respect to a given object.However, since a person’s attitude isassumed to be related to the total affectassociated with his beliefs, intentionsand behaviours, Ajzen (1991) viewsattitude as leading to a set of intentionsthat indicate a certain amount of affecttowards the object in question.

Each of these intentions is related to aspecific behaviour and thus, the overallaffect expressed by the pattern of aperson’s actions with respect to theobject also corresponds to his attitudetowards the object. The factorsinfluencing intentions and behaviourfor cost allocation is illustrated inFigure-5.

Based on the literature reviewed andthe findings which have emerged fromthis study, a model for cost allocationis proposed. This model relates thebehavioural beliefs identified earlier inthis study, with the attitudes formedas a result of the beliefs. This has ledto two different set of intentionspopularly associated with costallocation systems. Finally, the modelidentifies the actual behaviour whichwill occur as a result of the beliefs,attitudes and intentions.

The core propositions of this model arederived from the theory of plannedbehaviour. It is proposed that theconcepts of behavioural intentions,norms and perceived behaviouralcontrol can be adapted to the context ofcost allocation.

8.0 LIMITATIONS OF STUDY AND SCOPE FORFURTHER RESEARCH

The strength of this study has alreadybeen highlighted. The limitation of thisstudy should also be kept in mind. It isfor the first time that the theory ofplanned behaviour has been used in costallocation, so care should be exercisedwhile generalizing the result. This studyis the first effort to consider beliefs,attitudes, intentions and behaviour in costallocation.

The findings of the present study, alongwith the limitations noted above,highlight several areas for future



research. Replication of this study witha greater representation of managersfrom across industries would improvethe generaliability of findings. Futurereseach can further consider theantecedents to attitudes and behaviourand determine how they can be besttargeted to improve cost allocation.

While the focus of the present study wasonly on specific beliefs of cost allocation,more insights is needed into theperspectives of other beliefs whichinfluence managers to allocate or not toallocate costs.

Figure-5: Schematic Presentation of Conceptual Framework for the Prediction of SpecificIntentions and behaviours

9. 0 CONCLUSION

In conclusion, results of the presentresearch highlight important knowledge,deficits and provide support for the useof the theory of planned behaviour modelas a framework for understandingdifferences in underlying beliefs thatdistinguish between individuals whointend and do not intend to allocate costs.

Overall, the results of the present studysuggests that targeting identifiedunderlying beliefs may serve tostrengthen the intentions of managers toparticipate in cost allocation.

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Snyder, H. and Davenport, E. (1997), “What doesit really cost? Allocating indirect costs,”Asian Libraries, 6(3), 206-240.

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54(3), 504-521

Valuation of Intellectual Capital: The caseof Financial Services Industry in India*

Nikhil R. Nayak1, Munmun Mohanty2 & B. B. Mishra3

Abstract

It is well understood that in today’s economy which is more knowledge based, the source of competitiveadvantage lies in channeling the intellectual capital towards achieving the organization goals. Since it isa fact that, what cannot be measured cannot be controlled and hence cannot be channeled, the importanceof valuing intellectual capital cannot be overemphasized. This paper is a preliminary attempt at measuringthe value of intellectual capital of firms belonging to the financial services sector of India. The dataconsists of information collected from the financial statements of companies over a three-year period, thatis 2003-2006.

* Received April 19, 2007; Revised January 10, 20081. Research scholar, Department of Business administration, Utkal University, Bhubaeswar,

email: [email protected]. Assistant professor, Finance, Institute of Business and Computer Studies, Bhubaneswar,

email: [email protected]. Reader, Department of Business administration, Utkal University, Bhubaneswar,

email: [email protected].

1.0 INTRODUCTION

In today’s knowledge based economy,intellectual capital is being considered thehidden treasure of most businesses. Alsoknown as intangibles or knowledgeassets, these are now increasinglybecoming important factors in innovation,productivity, growth, businesscompetitiveness and economicperformance. These assets aredistinguished from physical assets suchas property, plant and equipment (PPE)or stock and financial assets such asreceivables, investments and cash. In the

past, businesses primarily invested in thetangible means of production likebuildings and machines. Hence, the valueof company was at least somewhatrelated to the value of its physical capital.But in today’s turbulent and complexbusiness environment where companiesare required to be flexible, highlyinnovative and be able to developproactive strategic approaches, there isan increasing realization that knowledgerepresents the most important factor increating value that underpins a firm’svalue creation performance (Nonaka and





Takeuchi, 1995). Hence, we arewitnessing an era where there is a lot ofinvestment in intangibles. However,although most companies acknowledgethat intellectual capital (IC) is their mostvaluable asset; conventional accountingsystems have no capacity to incorporateit on balance sheets. Indeed, manyaccounting standard setters oppose therecognition of it on balance sheets. Theyclaim that even if intangible assets areidentifiable, measures of it are highlysubjective and lack sufficient reliability.This confusion gives rise to problems ofvaluation in two different dimensions(Sudarsanam, Sorwar and Marr, 2003).

On one hand, companies that invest inintangibles may reap the benefit withoutany additional investment. For example,once the company designs a chip or writesa code for a new operating system, nofurther investment is needed to ship theproduct to yet another customer. Thisintangibility of a company’s mostimportant asset makes it extremely hardto figure out what company is reallyworth, thus leading to under or overvaluation of a company.

On the other hand, this difficulty invaluation gives rise to increased volatilityof the stock prices. This reflects in thephenomenal growth of market value ofsome knowledge driven internetcompanies in the second half of 1990s andthe subsequent crash in 2000. The ascentof stock markets around the world drivenby dotcom companies was as spectacularas the crash. This experience is a potent

reminder of the perils of overvaluationof knowledge rich companies.

Hence, under these circumstances theimportance of valuation of intellectualcapital can hardly be overstressed. Thefact that all the stakeholders of theorganization are now interested in thevalue of intellectual capital has increasedthe importance of valuation. The questionof classifying and measuring intangibleassets remains an important unresolvedissue in finance, economics and thepractice of management. That a firm ismore than the sum of its equipments andtangible assets is not in doubt. But howto measure the intangible part is aproblem that continues to vex academics,accountants, M&A advisors, intellectualproperty lawyers and joint venture andlicensing negotiators.

We have attempted to address thedifficult area of valuing the IC of theIndian companies belonging to thevarious financial services sectors by usinga suitable methodology. Definitions of ICand its various components, the needsof measuring IC, the difficulties normallyfaced during the valuation of IC, availablemethods of intangible valuation and theirpros and cons, the research method withmodel, the results and the summary andconclusion have been presented in thefollowing sections.

2.0 INTELLECTUAL CAPITAL DEFINED

Intellectual capital covers a multitude ofareas and economists, accountants andstandard setters are yet to agree on a

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global definition. During the last fewdecades we have witnessed anunprecedented increase in the use of theterms intangibles, intellectual capital orknowledge in reference to a set of factorsthat represent sources of corporateearnings. However, these terms arefrequently employed indifferently andoften applied to different concepts. Forthis reason it is essential to agree uponcommon definitions. The terms Intangiblesand Intellectual Capital are used to referto the same concept. Both are applied tonon-physical sources of future economicbenefits that may or may not appear incorporate financial reports. However,these two terms tend to be useddifferently: Intangibles is an accountingterm, whereas the Intellectual Capital wascoined in the human resources literatureand is mainly used in this field. However,our focus here is on the IntellectualCapital. Intellectual capital (IC) can bedescribed simply as knowledge that canbe converted into profits. There is,however, a multitude of other definitionsand experts have yet to reach a consensuson a commonly accepted definition. Someother definitions used in practice are :

‘Intellectual capital is the intellectualmaterial- knowledge, information,intellectual property, experience that canbe put to use to create wealth’ (Stewart,1998)

‘Knowledge that can be converted intovalue’ (Edvinsson, 1996)

‘Intellectual material that has beenformalized, captured and leveraged to

produce a higher valued asset’ (Klein andPrusak, 1994).

In this paper we use the termsintangibles, IC, intellectual assets andknowledge assets interchangeably.Intellectual property (IP) is a subset ofIC and it comprises assets such as patents,copyrights and trademarks and itsproperty rights are established under thelaw and ownership of IP may betransferred. Often there may be asecondary market in IP. In contrast, otherintangibles such as goodwill, R&D,organizational capital may be tooembedded within organizations to betraded separately. Their ownership may,however, be transferred as part of theorganization in which they areembedded.

2.1 Components of IC

In order to arrive at the objective ofvaluing and measuring IC, it is necessaryto understand the different componentsthat make up for intellectual capital.Intellectual capital includes orencompasses inventions, ideas, generalknow-how, design approaches, computerprogrammes, processes and publications.One of the most popular models ofclassifying IC is the Hubert Saint-Ongemodel (1996) which is largely based onSveiby’s (1997). This model developed inthe early 1990s, divides IC into threeparts: human capital, structural capitaland customer capital. A slight variant ofthis model devised by Nick Bontis (1999),restates customer capital as relationalcapital to include relationship with

Nayak et.al, Valuation of Intellectual ...


suppliers and other strategic partners andstakeholders. These are discussed ingreater details below and are depictedin figure-1.

Human capital is defined as theknowledge that employees take withthem when they leave the firm. It includesthe knowledge, skills, experiences andabilities of people. Some of thisknowledge are unique to the individual,some may be generic. Examples areinnovation capacity, creativity, know-how and previous experience, teamworkcapacity, employee flexibility, tolerancefor ambiguity, motivation, satisfaction,learning capacity, loyalty, formal trainingand education.

Structural capital is defined as theknowledge that stays within the firm atthe end of the working day. It comprisesthe organizational routines, procedures,systems, cultures, databases, etc.

Examples are organizational flexibility,a documentation service, the existence ofa knowledge centre, the general use ofInformation Technologies, organizationallearning capacity, etc. Some of them maybe legally protected and becomeIntellectual Property Rights, legallyowned by the firm under separate title.

Relational capital is defined as allresources linked to the externalrelationships of the firm, with customers,suppliers or R&D partners. It comprisesthat part of Human and Structural Capitalwhich is involved with the company’srelations with stakeholders (investors,creditors, customers, suppliers, etc.), plusthe perceptions that they hold about thecompany. Examples of this category areimage, customers’ loyalty, customersatisfaction, linkages with suppliers,commercial power, negotiating capacitywith financial entities, environmentalactivities, etc.

Figure- 1 Classification of Intellectual capital

INTELLECTUAL CAPITAL

Human Capital

1. Knowledge,Competence,skills andexperienceofemployees.

2. Training

3. Networks

Structural Capital

1. Organisational processes2. Databases and Software3. Manuals and Trademarks4. Laboratories and Market Intelligence5. Leadership6. Organisational learning capacity7. Leaseholds8. Franchises9. Licenses and patents10. Mineral rights

Relational Capital

1. Customerrelationship

2. Customer loyaltyand satisfaction

3. Distributionrelationships andagreements

4. Relationships withother partners andother stakeholders

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3.0 WHY MEASURE IC?

To gain a complete picture of theoperational performance and value of anorganisation, public or private, allaspects of the organisation must beconsidered. In order for an organisationto attain its full potential for valuecreation the intellectual capitalcomponents must not only be measuredbut also utilized effectively andefficiently (Contractor, 2000). Thespecific reasons for which companies areinterested in measuring intellectualcapital are as follows:

1. Young knowledge intensiveorganizations encounter greatdifficulty in attracting externalfinanciers because of the lack ofsufficiently large physical asset baseand hence need to develop a way toquantify their IC so as to be able toraise finance.

2. Alignment of IC resources withstrategic vision i.e. to support theimplementation of a specific strategyvia a general upgrading of the workwith the company’s human resources.

3. To place a value on separableintangible assets such as brands,patents, copyrights, databases andtechnology in the event of their sale,purchase and licensing.

4. During the sale, merger oracquisition of one company by theother, the actual value needs to becalculated because it is not just thephysical assets that are transferred

but there is a cost of knowledgetransfer over the years.

5. In case of lawsuits involvingintellectual property infringement,proper value must be calculated todetermine the infringement costsand penalties.

6. To influence stock prices, by makingseveral competencies visible tocurrent and potential customers.

3.1 Difficulty in Valuing IC

The first reason is historical. Accountingrules, although revised on a regularbasis, were initially designed for assetssuch as plant or machinery – tangiblethings that represented a source ofwealth during the industrial age. Second,some intangibles are hard to measure.Creativity, for example, is at the heart ofa knowledge-generation process yet isessentially an unpredictable process withunpredictable outcomes. It can manifestitself in many ways. For companies suchas Sony and 3M, product and processinnovation play a key role in marketdifferentiation. This leads us to the thirdproblem: the idiosyncratic nature of IC.What is valuable for one company maybe worthless for another. This hasresulted in diverse measuring systemsthat make comparability acrosscompanies and sectors difficult. Finally,intellectual capital can have twodimensions: the stock dimension (thestock of IC) and the flow dimension (theintellectual activities). The intangibleresources of a company, a static notion,



can be measured at any given time. Thusworker competencies (human capital),intellectual property rights (structuralcapital), customer satisfaction oragreements with suppliers (relationalcapital) would be considered under thiscategory. Intangible resources can also beanalysed in a dynamic sense. Companiesare undertaking activities to acquire orinternally produce intangible resources,to sustain and improve existing ones andto measure and monitor them. Thesedynamic activities thus imply anallocation and use of resources that aresometimes not expressed in financialterms and, consequently, may or may notappear in the corporate financial reports.This dynamic nature of IC means that itsindividual components are often notvaluable by themselves but work only asa system. In other words, it is theintellectual capital elements interactingthat generate value for companies. Forexample, a company may have goodprogramming skills that enable it to buildsoftware. However, they might be worthlittle unless accompanied by a strongdistribution network, loyalty andcommitment from its employees and apowerful brand name. This dynamiccombination of intangibles is often therecipe for success in companies such asMicrosoft, where the value of itsintellectual capital is more than the sumof its individual parts. So as a concludingremark on the difficulty of valuing thestock and flow aspects of IC, we wouldlike to quote Roos, “There is nocorrelation between how much you know

and how good you are at transformingthat knowledge into something useful forsomebody else” (Chatzkel, 2002).

4.0 A REVIEW OF AVAILABLE IC VALUATIONMODELS

Conventional accounting systems weredeveloped for manufacturing economiesand measure the value of financial andphysical assets- tangibles that can bequantified. These include plant,equipment, laboratories, land and naturalresources- assets that are easilyidentifiable and can be sold for an agreedprice. The global transition to knowledgebased economies has made this cost-based accounting of assets increasinglyirrelevant. For accountants andaccounting standard setters, the problemwith intangibles is that it is difficult toaccount for the rate of change. It is almostimpossible to match investments andcosts in one period with profits in anotherperiod. Conventional accounting treatstangibles, such as computers, land andequipments as assets. But investment inintangibles is treated as a cost.

There are currently no widely acceptedmethods for accounting for intangibleassets. Historically, the ‘goodwill’ line onthe balance sheet provided a convenientaccounting place for intangibles. But theincreasing complexity of business andfinance mean that this is no longerappropriate. Accordingly severalresearchers and practitioners haveattempted to put a value on theintangibles of a company. Some of thesemethods are suitable to be applied with

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the help of lot of internal informationabout the company, whereas, some othermethods can be applied by using publiclyavailable knowledge about a company.Accordingly we have segregated themodels into the internal measures and theexternal measures. We will also bediscussing a newer approach to valuingIC- the real option based approach (Luu,Wykes, Williams and Weir, 2001).

4.1 Internal Measures

Companies that have a deepunderstanding of the role of knowledgein their business treat it as an asset.Measuring and reporting information ontheir intangibles has the potential toimprove their management and decisionmaking and creates significant businessopportunities. The most common internalmeasures of intellectual capital focus onbudgeting, training and human resources.The four most popular internal measuresof intellectual capital are: Human resourceaccounting, the intangible asset monitor,the Skandia navigator and the balancedscorecard.

Human Resource Accounting: Humanresource accounting (HRA) is anaccounting method that describes themanagement of a company’s staff(Hermanson, 1964). It aims at improvingthe management of human resources froman organizational perspective i.e. byincreasing the transparency of humanresource costs, investments and outcomesin traditional financial statements. Itattempts to improve the basis forinvestors’ valuation of the company. It

focuses on employees’ education,competence and remuneration(Sackmann et al, 1989). HRA supportsaccounting for investments in staff, thusenabling the design of human resourcemanagement system to follow andevaluate the consequences of various HRmanagement principles. There are fourbasic HRA models: Anticipated financialvalue of individuals to the company,Financial value of groups, Staffreplacement cost and Human resourceaccounting and balancing. However, thedifficulties associated with several majorhuman resource evaluation methods castdoubt on HRA’s accuracy. The difficultiesfor any model of human resourceevaluation include input measurement,output measurement and replacementvalues.

The Intangible Asset Monitor: Karl-ErikSveiby developed the intangible assetsmonitor (IAM) as a management toolfor organizations wanting to track andvalue their intangible assets ,particularly accounting for thedifference between market and bookvalue. According to IAM, the intangiblepart of a company’s balance sheetconsists of three parts:

• External structure- a company’srelationships with its customers andsuppliers, brand names, trademarksand organizational reputation orimage.

• Internal structure- a company’sorganizational assets i.e. patents,processes, systems, concepts and



computer and administrativesystems.

• Individual competence- a person’sability to act in various situations i.eskills, education, experience andvalues.

The IAM is based on the assumption thatpeople are an organisation’s only profitgenerators. All assets and structures,whether tangible physical products orintangibles, are the result of humanaction and depend ultimately on peoplefor their continued existence.

The Skandia Navigator: The Skandianavigator is perhaps the best knownbusiness model developed to identifyintangible assets. A feature of thenavigator is its definition of intellectualcapital. In addition to the skills andexpertise of i ts workforce, i t alsoincludes the systems and processes thatit has put in place to capture and exploitall the knowledge it can (Edvinsson andMalone, 1997). It is designed to providea balanced picture of financial andintellectual capital. Consequently, itincorporates measures in categoriessimilar to those of the balancescorecard. The focus on financial results,capital and monetary f lows iscomplemented by a description ofintellectual capital and its development.The navigator framework has at its topend a series of measures about financialfocus. But it also has below the linemeasures of intellectual capital. Theseinvolve four areas and two dimensions.These are:

• Customer focus- how theorganization views its customers;

• Process focus-key aspects oforganisation’s process performance;

• Renewal and development focus-what is being done to renew anddevelop the intellectual asset base;and

• Human focus- the virtual bindingforce of customer, process, renewaland development and finance.

The Balanced Scorecard: The balancedscorecard (BSC) is an organizationalframework for implementing andmanaging a strategy at all levels of anenterprise by linking objectives,initiatives and measures to anorganisation’s vision and strategy(Kaplan and Norton, 1996). The BSCtranslates a business’s vision andstrategy into objectives and measuresacross four balanced perspectivesnamely, financial performance,customers, internal business processesand organizational growth, learning andinnovation. It is a structured way ofcommunicating measurements andtargets. It is used as a tool for managing,measuring and communicating acompany’s financial and non-financialinformation. The BSC allows anorganization to monitor its currentperformance- financial, customersatisfaction and business processes- andits effort to improve processes, motivateand educate employees and enhance itsability to learn and improve.

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4.2 External Measures

The growing influence of intangibles incompany performance is perceived as amajor factor in explaining theexceptionally large differences betweenthe market and book values currentlyseen in our capital markets. Thedevelopment of measurement andreporting models enables comparisons tobe made between firms in the sameindustry. By reporting on its IC, acompany can give itself a marketadvantage, attract investment capitalmore easily and improve its stock priceby giving market and potential customersa more accurate picture of its assets.Market-to-book values, Tobin’s Q andCalculated Intangible Value (CIV) are themost common intra industry measures.

Market-to Book Values: The value ofintellectual capital is commonlyexpressed as the difference between themarket value (MV) of the company,calculated by the market capitalization ofthe firm, and its book value (BV), alsoknown as equity value. Recentacquisitions show that price paid for anacquired company is invariably higherthan its book value. Conventionalaccounting practices incorporate thisdifference as goodwill on the balancesheets. The growing disparity betweenmarket value and book value is largelybased on the intangibles of the businessproviding the foundation for futuregrowth. The largest disparity occurs inhigh-tech and knowledge-intensiveindustries where investment is heavily

concentrated in intangible assets such asR&D and brands. From an internalperspective, differences between MV andBV are primarily due to assets that arenot currently included in the conventionalbalance sheets such as knowledge,relationships and image. The externalperspective on the gap between the MVand the BV is primarily due to thecompany’s future opportunities and theseare currently not valued in theconventional balance sheet. The market-to-book value is limited as a tool formeasuring intellectual capital for threereasons:

1. The stock market is volatile and canreact strongly to factors outside thecontrol of management.

2. There is evidence that market valueand book value are usuallyincorrectly stated.

3. Market-to-book value valuations canbe affected by timing inconsistencies.Market value is determined andrevised constantly whereas bookvalues are only updated periodically.

Tobin’s Q: Tobin’s Q compares acompany’s market value with thereplacement cost of its assets. It uses theratio to analyse dynamic firm behaviour,independent of macroeconomicconditions such as interest rates. Thereplacement cost of fixed assets can becalculated by adding the reported valueof a company’s fixed assets to itsaccumulated depreciation and adjustingthe result for inflation. It can be a useful



measure of IC because it can reflect thevalue market places on assets which arenot typically reported in conventionalbalance sheets. By making intra-industrycomparisons between a firm’s primarycompetitors, these indicators can act asperformance benchmarks and be used toimprove a company’s internalmanagement or corporate strategy. Theinformation provided by these ratiosfacilitates internal benchmarking andenables the organization to track itsprogress in an area it defines as integralto its success.

Tobin’s Q and market-to-book ratios aremost revealing when like companies arecompared over several years. They arebest suited to comparing the value ofintangible assets of firms within the sameindustry, supplying the same markets,with similar tangible assets, over anumber of years. When the ratios of acompany fall over time, it is a goodindicator that a firm’s intangible assetsare depreciating. It might tell investorsthat a particular company is notmanaging its intangible assets effectivelyand lead them to adjust their investmentportfolios towards companies withclimbing or stable Qs.

Calculated Intangible Value: Calculatedintangible value (CIV) is a model forcalculating a fair dollar value forintangible assets. It assigns a value tointangible assets by comparing the firm’sperformance with an average businesscompetitor with similar tangible assets.This approach is similar to that used to

evaluate brand equity. An advantage ofCIV approach is that it allows firm-to-firm comparisons using audited financialdata and, as such, can be used as abenchmarking tool. It can help assesswhether an organization is fading orindicate value not reflected in traditionalfinancial measures or whether thecompany is generating the capacity toproduce wealth in the future. However,this method has several limitations. Itrelies on averages to determine value andthis means that it lacks the precisionprovided by balance sheet numbers. It isalso applicable to only those industriesor sectors that are not dominated by asmall number of companies.

4.3 Real Option Based Approach

A real option is a recent approach whichuses the methodology and the theory offinancial options to value intangibleassets. A financial option is the right, butnot the obligation, to buy or sell anunderlying asset at a fixed price for apredetermined period of time. A realoption is an option that is based on non-financial assets. Real options can beapplied to determine the value toproceed, defer, expand or abandoninvestment. By drawing on financialmarket techniques, benchmarks andinformation, businesses can disciplinetheir investment decisions and align themwith the investment decisions of themarket. Unlike the previous methods, thereal option provides an approach whichvalues the opportunities arising fromintellectual capital. Deciding on how

103

much to spend on R&D, or the kind ofR&D to invest in, translates to thevaluation of opportunities. Companieswith new technologies, productdevelopment ideas, defensible positionsin fast growing markets, or access topotential new markets own valuableopportunities. For some companies,opportunities are the most valuablethings they own. The challenge for thecompanies is converting opportunity toreality. For the investor the challenge isto quantify the opportunity.

The real option approach is still in itsinfancy and there are limits to itsusefulness. Natural resources companieshave been the early experimenters in theuse of real options. This is largely a resultof their ability to link the future value oftheir assets to traded commodities, forwhich market information is readilyavailable. However, despite theattractiveness of this method, there aresignificant drawbacks. Determining thevalue of real options remains an inexactscience. Substantial difficulties remain invaluing non-financial assets accurately atthe firm level. As most businessopportunities are unique, the likelihoodof finding the similar option is low. Theonly reliable way to finding a similaroption is to construct one. Furthermore,real option pricing is often too complexto be worthwhile for minor decisions.The use of real options presents twofundamental problems: one ofquantifying real option value and thesecond one is of persuading anorganization to change the way it

traditionally thinks about valuation andinvestment.

5. 0 RESEARCH METHOD

A discussion of the available models forvaluation of IC reveals that all the modelshave inherent advantages and limitations.There is not a single model that is free ofproblems normally faced during valuingthe IC. The problem with the internalmeasures is that, to value the IC of acompany a lot of internal information hasto be collected about a company. Themeasurer has to be very closely associatedwith the company to understand theinternal dynamics and the way thecomponents interact in the organization.This proves to be difficult since most ofthe people have reservations regardingsharing intimate details of theirorganization, which can be used againstthem by their competitors. The problemof real options has been discussed indetails in the previous sections and hencehas been overlooked as a possibleresearch method. That leaves us with theexternal measures of IC valuation. Thesemethods are suitable for our purposesince it needs the audited financialstatement and share price data of therespective companies, which are readilyand publicly available. The market-to-book value method has a major limitationthat since market value is stock marketdependent, its tends to fluctuate to factorsthat are outside the control of themanagement and hence is very volatile.Tobin’s Q is quite similar to the market-to-book value method with the only



difference that instead of book value, thereplacement cost of assets is considered.This method is very useful since it readilylends itself to comparison across thecompanies in an industry. However thecalculation of replacement cost of assetsis a very tedious job. That leaves thecalculated intangible value (CIV) methodas the only suitable tool that can be easilyapplied by someone external to thecompany without company specific(internal) information. Hence theavailability of genuine data hasmotivated us to pick the CIV method asour model of IC valuation.

5.1 Calculated Intangible Value (CIV)

CIV is designed for valuing a company’sIC. It was originally developed forincreasing the interest of lenders towardsknowledge-intensive business in whichmajority of assets consists of intangibleones (Stewart, 1997). The method isbased on the assumption that a company’spremium earnings i.e. the earningsgreater than the average companieswithin the industry, result from thecompany’s IC. That is to say by utilizingtangible assets, a company can reach onlyan average level of earnings whereas thepremium is generated by the IC. The CIVof a company can be calculated asfollows:

1. Calculate the Company’s averagepretax earnings for the past threeyears (a).

2. Calculate the average year-endtangible assets of the company forthe past three years (b).

3. Calculate the company’s return onassets (ROA) denoted as ‘c’ asfollows c = a / b

4. Calculate the industry average ROA(d) for the same three-year periodas in Step 3.

5. Calculate excess ROA by multiplyingthe industry average ROA by theaverage tangible assets (b). Subtractthe excess return from the pretaxearnings from Step (a) i. e. excessreturn =a – (d * b)

6. Calculate the three-year averagecorporate tax rate and multiply bythe excess return. Deduct the resultfrom the excess return.

7. Calculate the net present value(NPV) of the after-tax excess returnby using the company’s cost ofcapital as a discount rate. For thesake of simplicity the samepercentage (10 %) has been used forall the industries.

The result of executing the seven stepcalculation is the calculated intangiblevalue (CIV). The value is a measure ofcompany’s ability to use its IC to succeedbetter than the other companies withinthe industry.

5.2 Data

The data covers the entire Indianfinancial services sector. According toRBI the service industry is divided intothe finance sector and the other sector.In the financial service sector we haveselected the Banking services (134

105

banks), Financial institutions (37companies), Non-banking financecorporations (270 companies) and theSecurity houses and Stock brokerssegment (782 companies) as our data set.The focus is to find out the IC of all thesecompanies and also find out whichcompanies in a particular sector has beenable to create more value as comparedto the average ones.

The financial information of the saidcompanies and the industryclassification has been obtained fromthe PROWESS database compiled bythe Center for Monitoring IndianEconomy (CMIE). The period forwhich data has been collected coversa three year period from March 2003to March 2006.

6.0 RESULTS AND ANALYSIS

As we have already discussed in thecalculation of CIV, it is a method whichdepends upon the industry averageROI and only those firms that havehigher ROI than the industry ROI areeligible for this method. Hence, in thisfiltering process a good number ofcompanies have been eliminated fromour original data set of 1223companies. We will discuss each of thesectors separately and compare thefirms within each sector to find outwhich company has the highest valueof IC.

6.1 Banking Services

The CMIE database lists a total of 134companies in banking sector. This

includes both government and privatebanks. The industry ROI of the bankingsector was found to be 37.38 percent.However, only 53 banks were found tohave a higher ROI than the industryaverage ROI. These banks and theircorresponding ROI and CIV are listedin Table-1.

It can be seen from the above table thatthe highest ROI have been reported bymostly the co-operative banks, leadingamong them are South Indian Co-operative bank Ltd, Mumbai districtcentral Co-operative bank Ltd, ModelCo-operative bank Ltd and City Co-operative bank Ltd. There are six bankswhich have ROI in excess of 100.However, none of these are the big andpopular banks. A look at the thirdcolumn of table reflects that the oneshaving very high ROI have very lowCIV. In fact the highest CIV have beenreported in case of all public sectorbanks which do not have astoundinglyhigh ROI. The highest CIV is reportedin case of State Bank of India(Rs.13572.21 Crores) followed byCanara Bank (17189.7 Crores) andAllahabad Bank (8823.8 Crores).

The CIV only represents an absoluteamount and it does not take into accountthe size (balance sheet value) of thecompany. Hence we have tried tocalculate the relative value of IC bydividing the value of IC by the value oftangible assets (TA) and are presentedin the last column of table1. This shows



that the banks reporting the higher ROIare also the ones having highest CIV toTA ratio. The highest ratio is reportedin case of South Indian Co-operativebank which incidentally also had the

Table-1: CIV of banking companies

Sl. No. Company Name ROI CIV CIV / TA

1 Allahabad Bank 87.87 8823.802 2.091856

2 Andhra Bank 53.7 3073.996 0.722939

3 Bank Of Baroda 39.86 5910.17 0.39652

4 Bank Of India 39.97 915.666 0.0657

5 Bank Of Madura Ltd. [Merged] 81.16 1146.513 2.871595

6 Bank Of Maharashtra 58.66 3210.534 1.11847

7 Bank Of Rajasthan Ltd. 54.18 418.0522 0.672715

8 Bharat Co-Op. Bank (Mumbai) Ltd. 54.68 143.3506 0.853989

9 Canara Bank 68.5 17189.7 1.629467

10 Catholic Syrian Bank Ltd. 79.1 733.2527 2.334828

11 Citizen credit Co-Op. Bank Ltd. 43.09 26.0805 0.236408

12 City Co-Op. Bank Ltd. 109.88 47.51328 3.86916

13 City Union Bank Ltd. 94.12 876.5526 3.33404

14 Corporation Bank 40.29 281.804 0.05285

15 Deccan Merchants Co-Op. Bank Ltd. 55.84 19.68279 0.969118

16 Dena Bank 58.6 1774.845 0.872224

17 Dhanalakshmi Bank Ltd. 47.54 120.3686 0.647004

18 Federal Bank Ltd. 71.73 2553.127 2.26317

19 H D F C Bank Ltd. 43.25 337.9875 0.039227

20 Indian Overseas Bank 67.09 7531.212 1.28205

21 Jain Sahakari Bank Ltd. 63.71 10.7199 1.395821

22 Janakalyan Sahakari Bank Ltd. 56.21 175.6009 1.526699

23 Janata Sahakari Bank Ltd. 83.99 454.7678 2.827279

24 Karur Vysya Bank Ltd. 57.24 982.3616 0.924541

highest ROI. The banks having thehighest CIV have reported average CIVto TA ratio of about 2, indicating thattheir IC twice as much as that of thephysical assets of the company.

107Nayak et.al, Valuation of Intellectual ...

25 Lakshmi Vilas Bank Ltd. 43.05 65.23872 0.159613

26 Mahanagar Co-Op. Bank Ltd. 45.86 30.9972 0.418881

27 Maratha Sahakari Bank Ltd. 68.24 32.14059 1.485926

28 Model Co-Op. Bank Ltd. 110.44 48.91814 4.391216

29 Mumbai District Central Co-Op. Bank Ltd. 128.7 2028.103 5.521351

30 N K G S B Co-Op. Bank Ltd. 59.43 179.1767 1.260033

31 Oriental Bank Of Commerce 59.17 5387.906 0.843941

32 Patan Co-Operative Bank Ltd. 46.69 4.178798 0.48254

33 Pinakini Grameena Bank 48.08 32.42292 0.33285

34 Punjab & Maharashtra Co-Op Bank Ltd. 65.48 202.9767 1.212163

35 Punjab & Sind Bank 88.01 2176.912 3.197485

36 Ratnakar Bank Ltd. 111.88 215.2236 4.047077

37 Sangli Bank Ltd. 160.45 484.8154 7.55635

38 Shamrao Vithal Co-Op. Bank Ltd. 54.02 276.6837 0.86415

39 Shree Suvarna Sahakari Bank Ltd. 96 293.9271 2.831668

40 South Indian Bank Ltd. 74.34 1455.06 1.73242

41 South Indian Co-Op. Bank Ltd. 236.57 62.36047 10.2063

42 State Bank Of India 46.54 13572.21 0.217953

43 State Bank Of Indore 46.14 960.1907 0.424722

44 State Bank Of Mysore 52.58 870.8464 0.422848

45 State Bank Of Travancore 65.01 2701.681 0.821664

46 Syndicate Bank 71.33 6326.435 1.344808

47 Tamilnadu Mercantile Bank Ltd. 91.57 1673.661 3.312344

48 U T I Bank Ltd. 44.7 666.0038 0.102665

49 Uco Bank 75.08 7379.788 1.485049

50 United Western Bank Ltd. 55.39 705.2736 1.968773

51 Veerashaiva Co-Op. Bank Ltd. 66.63 29.1522 1.649813

52 Vijaya Bank 57.8 3536.477 1.357088

53 Zoroastrian Co-Op. Bank Ltd. 55.95 42.54318 0.926463


A perusal of Table-2 reveals that all thefirms have ROI in the similar range unlikethe banking sector where there weremany extreme values of ROI. The highestCIV has been reported in case of HUDCOfollowed by Power finance Corporationand Indian railway finance Corporation.The CIV to TA ratio is highest in case ofKarnataka state financial Corporation.which also reported highest ROI in thesegment.

6.3 Non-Banking Finance Corporations(NBFC)

According to CMIE there are 270 firmsin this sector and the industry ROI wascalculated to be 11.58 percent. There areonly 11 firms reporting higher than

industry ROI and these are presented inTable-3.

The table reflects that the highest CIV isreflected in case of Ashok LeylandFinance (714.65 Crores) followed closelyby Reliance Capital Ltd. (699.89 Crores).Again the same peculiarity in case of CIVto TA ratio has been observed here i.e.the firm reporting highest ROI in thegroup, Dhandapani Finance Ltd., (30.31Percent) is also showing the highest CIV/TA ratio (1.25).

6.4 Security Houses and Stock Brokers

There is a whooping 782 firms listed inthis sector in the CMIE database and theindustry ROI was calculated to be a very

Table- 2: CIV of Financial Institutions


1 Andhra Pradesh State Financial Corporation. 11.09 98.79587 0.105279

2 Housing & Urban Development Corporation Ltd. 10.86 2100.55 0.091001

3 Indian Railway Finance Corporation Ltd. 10.53 1155.301 0.062284

4 Karnataka State Financial Corporation. 13.6 356.9523 0.287327

5 Power Finance Corporation Ltd. 11.43 1893.733 0.069658

6 Rural Electrification Corporation Ltd. 11.17 658.2568 0.02926

7 Tamil Nadu Power Finance & Infrastructure 11.54 131.4231 0.07126

Development Corporation Ltd.

8 Tourism Finance Corporation Of India Ltd. 11.22 97.22813 0.17792

6.2 Financial Institutions

There were originally 37 firms in thissector and the industry average ROI wascalculated to be 9.58 percent. Only eight

firms were found to be having higherROI than the industry average. Thesefirms and their corresponding values arepresented in Table-2.

109Nayak et.al, Valuation of Intellectual ...

Table-4 reveals that the highest CIV isreported by DSP Merrill Lynch(Rs.1554.83 Crores) having a ROI of 50.9

Table-3: CIV of NBFCs


1 Ashok Leyland Finance Ltd. [Merged] 20.22 714.65 0.481187

2 Bajaj Auto Finance Ltd. 20.15 185.9067 0.218162

3 Dhandapani Finance Ltd. 30.31 92.53375 1.257081

4 Mafatlal Finance Co. Ltd. 17.32 36.3884 0.458928

5 Magma Leasing Ltd. 25.66 134.6426 0.59361

6 Manappuram General Finance & Leasing Ltd. 16.27 15.6797 0.208757

7 Reliance Capital Ltd. 17.09 699.8949 0.166788

8 S R E I Infrastructure Finance Ltd. 14.68 143.5741 0.221084

9 Shriram Investments Ltd. [Merged] 19.11 452.3215 0.308325

10 Shriram Transport Finance Co. Ltd. 18.5 349.1698 0.209262

11 Tata Finance Ltd. [Merged] 11.9 35.07513 0.044205

modest 8.64 percent. After analysis it wasfound that only 9 firms have higher ROIthan the industry ROI. This means that

the industry is dominated by few playersand the average is affected by theextreme values of ROI.

Table -4: CIV of Security Houses and Stock Brokers

Sl.No. Company Name ROI CIV CIV / TA

1 Arihant Capital Markets Ltd. 32.12 9.13536 1.373738

2 B L B Ltd. 19.76 64.48863 0.808838

3 D S P Merrill Lynch Ltd. 50.9 1554.83 2.800134

4 Emkay Share & Stock Brokers Ltd. 86.75 146.3285 4.003516

5 Indbank Merchant Banking Services Ltd. 13.61 3.591952 0.270478

6 J R G Securities Ltd. 61.46 20.9769 2.315332

7 N P R Finance Ltd. 15.22 13.47029 0.356168

8 Networth Stock Broking Ltd. 15.52 4.184752 0.362945

9 S B I Capital Markets Ltd. 29.99 582.4622 1.303397

percent followed by SBI capital markets(Rs.582.5 Crores) having a ROI of 30percent. The highest ROI is reported in


It is quite apparent from the table thatfirms have a very low correlationbetween their ROI and their IC value,meaning that a firm having high ROIdoes not necessarily have high value ofintellectual capital, Whereas, firms areshowing very high correlation betweenROI and CIV to TA ratio. The reason isobvious. The higher ROI reported byfirms can be assigned to either higherpre-tax earnings or lower tangibleassets. The firms having higher ROI dueto the first reason are considered to becreating value whereas; the same is notnecessarily true for the second reason.

Hence they are segregated in thecorrelation test. The firms adding valuedue to higher earnings are showing highCIV and low correlation to ROI. Thefirms showing high ROI due to lowtangible assets are not adding value asevident from their low values of CIVand hence high correlation to CIV to TAratio.

7.0 CONCLUSION

The CIV method has a lot of practicalutility because the data needed forcalculation is readily found from thefinancial statement of a company.However, this can sometimes act as adouble edged sword. On the one hand,data are relatively easy to access andthe results of different organizations arecomparable with each other at leastwithin the same industry. On the otherhand, the financial statement is notnecessarily the best source ofinformation regarding the valuation ofIC due to the fact that only a minor partof IC is included in the f inancialstatement. In addition, the CIV alsosuffers from the limitations like it usesaverage industry ROA as a basis ofdetermining excess return. By nature,average values suffer from outlierproblems and could result in excessivelyhigh or low ROA. However, CIV is aquantitative method, which gives somekind of estimate of the monetary valueof IC (Antola et al., 2005). There is notmuch of evidence about utilizing CIVin practice. Stewart (1995) has

case of Emkay Share and Stock Brokersat 86.75 percent and also has the highestCIV to TA ratio at 4.

After observing the peculiarity of thebehavior of ROI in relation to the CIVand CIV/TA ratio, we decided to run thecorrelation test on both the series. Theresults are presented in Table-5.

Table-5: The Coefficients of Correlation

Sector Correlation Correlationbetween between ROIROI and and

CIV CIV/TA

Banking -0.026 0.86

Financial -0.314 0.81Institutions

NBFC 0.011 0.89

Security 0.25 0.97Houses andStock Brokers

111

calculated the value of Merck’s IC ($1.1billion).

In the present study, we have tried toput a monetary value on the intellectualcapital of an organization. We haveconsidered the Indian Financial ServicesSector as our data set. The sectors thatwe have selected for our study are thebanking service, the financialinstitutions, the non-banking financecorporations and the security housesand stock brokers. We have used thecalculated intangible value method(CIV) for valuing the IC. It was seenthat the firms having highest ROI werenot the ones having the highest CIV.The reason is simple. ROI is a ratio thatis dependent on tangible assets andearnings of a company. The company’stangible assets do not affect theintellectual value of the company.

REFERENCES

Antola, J., Kujansivu, P., Lonnqvist, A. (2005),Management Accounting for Intellectual Capital.Proceedings of the 7 th Conference onManufacturing Accounting Research, May30– June 1, Finland

Bontis, N. (1999), “Managing OrganisationalKnowledge by Diagnosing IntellectualCapital: Framing and Advancing the Stateof the Field”, International journal of TechnologyManagement, Vol.18, No.5/6/7/8.

Chazkel, J. (2002), “A Conversation With GoranRoos”, Journal of Intellectual Capital, Vol.3, No. 2

Contractor, F. J. (2000), “Valuing CorporateKnowledge and Intangible Assets”: Some

General Principles, Knowledge and ProcessManagement, Vo. 7, No. 4, pp. 242-255.

Edvinsson, L. (1996), Skandia, Pat Sullivan,European Management Journal, Vol. 14.

Edvinsson, L. and Malone, M. S. (1997),“Intellectual Capital: Realizing yourCompany’s True Value by Finding itsHidden Brainpower”, Harper Business Press,New York.

Hermanson, R. (1964), “Accounting for HumanAssets,” Bureau of Business and EconomicResearch, Occasional paper No.14, MichiganState University.

Kaplan, R.S. and Norton, D. P. (1996) “TheBalanced Scorecard: Translating Strategyinto Action,” Boston: Harvard Business SchoolPress.

Klein, D.A. and Prusak, L. (1994),“Characterizing intellectual capital,”Working Paper, center for Businessinnovation, Ernst and Young LLP, March.

Luu, N., Wykes, J., Williams, P. and Weir,T., (2001), “Invisible Value: The Case forMeasuring and Reporting IntellectualCapital,” ISR New Economy Issues, Paper no.1, July.

Nonaka, I. and Takeuchi, H. (1995), “TheKnowledge creating Compay,” OxfordUniversity press, New-York.

Roberts, H. (1999) “The Control of Intangiblesin the Knowledge-intensive Firm.” Paperpresented to the 22nd Annual Congress ofthe European Accounting Association,Bordeaux.

Roberts, H. (2000) “Classification of intellectualcapital.” In: J.E. Gröjer and H Stolowy (Eds)Classification of Intangibles. Groupe HEC, Jouy-en Josas, France, pp. 197-205.



Sackmann, S., Flamholtz, E. and Bullen, M. (1989),“Human Resource Accounting: A State-of-the-Art Review,” Journal of AccountingLiterature, No.8, pp.328-340.

Saint-Onge, H. (1996), “Tacit Knowledge: the Keyto the Strategic Alignment of Intellectualcapital”, Strategy and leadership, April.

Stewart, T.A. (1995), “Trying to Grasp theIntagible”, Fortune, Vol. 132, Issue 7.

Stewart, T.A. (1997), “Intellectual Capital: The NewWealth of Organisations,” Doubleday, NewYork.

Stewart, T.A. (1998), “Intellectual Capital Vs.Knowledge Management”, Presentation atthe DCI Knowledge ManagementConference, Boston, June.

Sudarsanam, S., Sorwar, G. and Marr, B. (2003),“Valuation of Intellectual Capital and Realoption Models,” Paper presented to PMAIntellectual Capital Symposium, October,Cranfield University.

Sveiby, K. E. (1997), “The New OrganisationalWealth: Managing and Measuring knowledgebased Assets,” Berrett -Koehler: New York

1.0 INTRODUCTION

India’s gross domestic product rising at9 percent this year reflects the goodeconomic health of the country. Thisgrowing economy has to be supportedby continuous supply of energy. The percapita energy consumption in Indiaremains low in comparison to countries

like the United States and China. ButIndia, the world’s fifth biggest energyconsumer, is projected to surpass Japanand Russia to take the third place by 2030.[1] This situation will lead to continuousand growing reliance on fossil fuel – coaland greater energy imports. In India,generally half of the energy is produced

Measuring Technical Efficiency of CoalMines using Data Envelopment Analysis – A

Case Study of Mahanadi Coal Field Ltd.*

Sreekumar1, Rohita Kumar Mishra2 & Debendra Kumar Mahalik3

Abstract

Coal Industry in India plays a significant role for socio-economic growth and industrial development, aspower generation in the country is mostly through coal. The extraction of coal from the coal mines dependsupon the peoples and technology involved in that particular site. The quality of the coal not only dependsupon the nature but also the efficient utilization of people, process and technology. This paper attempts toexamine the efficiency of various collieries of a leading Government owned Indian Coal Company - MahanadiCoal Field Ltd (MCL). The data collected shows that there is no significant difference between both inputand output factors over the periods considered. A non-parametric method called Data Envelopment Analysisis used for calculating the efficiency score of collieries or decision making units (DMUs). Two scale ofassumptions CRS (Constant Return to Scale) and VRS (Variable Return to Scale) of DEA are used tocompare the relative efficiency of collieries. The results obtained through application of DEA shows thatmany of the DMUs are performing consistently over the periods considered.

* Received March 19, 2007; Revised December 24, 20071. Associate Professor, Rourkela Institute of Management Studies, Rourkela, email:

[email protected]. Assistant Professor, Institute of Management and Information Science, Bhuabneswar, email:

[email protected]. Lecturer, Department of Business Administration, Sambalpur University, Burla, Sambalpur,

email:[email protected]





through coal. The Brookings reportestimates that India’s coal reserves couldrun out in forty years. Power generationaccounts for most of the coal consumedin India, with heavy industry a distantsecond. Beside power generation, the useof beneficiated coal has gainedacceptance in steel plants. The followingtable shows a comparison between twocountries, India and China, whoseindustrial development is powered byenergy consumption [2].

Table-1: Comparison of India and Chinaon coal production and consumption

China India

Recoverable 126,214.7 101,903.2Coal million millionReserves short tons short tons

Coal 2,156.4 million 403.1 millionProduction short tons short tons

per year per year

Coal 2,062.4 million 430.6 millionConsump- short tons short tonstion per year per year

Source: Forbes magazine, Nov. 20061 Short ton = 907.2 Kilograms

The Table-1 shows clearly a wide gapbetween the coal production andconsumption between the two countries,while there is not much of difference inrecoverable coal reserves between twocountries. The use of coal accounts for anumber of problems, such as high ash,pollution and low efficiency. TheGovernment is encouraging industries toswitch over from coal based powergeneration to natural gas based powergeneration, but such switch over is

happening at a slow pace due to thehindrance of reliable supply fromoverseas and the presence of India’s ownnatural gas field under deep seas.Besides, coal price being lower than theequivalent natural petroleum productprices, Indian coal industry shall continueand operate, but such continuance has tobe more efficient with improved qualityand through adoption of latest availabletechnology.

This paper attempts to evaluate theefficiency of twelve collieries ofgovernment owned coal company,Mahanadi Coal Field Ltd (MCL). A non-parametric method called DataEnvelopment Analysis (DEA) is used tomeasure the efficiency of each colliery.The paper is organized as follows. First,a brief overview of Indian coal Industryand MCL is presented and then themethod, DEA, is presented andexplained. After that it elucidates, howthe DEA approach can be used to measureefficiency of individual collieries. Theslack analysis is also done for betterinsight.

2.0 INDIAN COAL INDUSTRY AN OVERVIEW

India is the third largest producer of coalin the world. Coal mining in India datesback to the 18th century. The regulatoryframework for this industry wasconceived in 1923. In 1972-73, the Indiangovernment nationalised the coalindustry, primarily to develop the sector,since it was considered of strategicimportance for rapid industrialdevelopment. Coal India Ltd (CIL) was

115

incorporated as a holding company forseven coal producing subsidiaries and afocused institute for planning anddesign. It is engaged in mining of coalfrom a total of 495 working coal mineswhich account for nearly 88 percent oftotal production [3]. In India coal is usedfor power generation to meet theindustry and domestic needs. The coal

based electricity generation capacitysharply increased from 8000 MW in 1970to 51000 MW in 1995. This is expected togo up to 140000 MW by 2009-10.However, at present, the country facesan average energy shortage of about 15%and peak shortage of 30%. The coaldemand and availability over a periodof time is shown in Table-2 below [4].

Table-2: Demand and Availability of coal in India

Demand Availability

Year Steel Electricity Cement Others Total Availability Imports Gap(From Existing

Coal Companies)

1997-98 41.4 222.0 18.2 41.78 323.38 298 10 10

2001-02 51.6 287.8 21.4 51.4 412.2 371 19 22

2006-07 - - - 563 443 19 101

2009-10 68.0 500.0 37.0 85.0 690 530 - 160

All data are in Million Tonnes

The wide projected gap in the comingyears call for efficient use of coals in theyears to come.

2.1 Mahanadi Coal Field Ltd (MCL)

The state of Orissa has two coalfields viz.IB and Talcher under MCL. The estimatedshare in the reserve is around 24.48% (62.00Billion Tonnes) of total of 253.30 billiontonnes of coal reserves as estimated by GSIas on 1.1.2006[5]. The coal discovered goesback to the year 1900. The earliest coalmining started in 1909 by private parties.In the year 1973, after nationalization ofCoal Industry it became part of WesternCoalfields Limited (WCL). Then in the year

1986, it came under South Eastern CoalfieldsLimited (SECL). In the year 1992 it cameunder Mahanadi Coalfields Limited (MCL)having headquarters (HQ) at Sambalpur inOrissa. There are 33 sanctioned miningprojects in MCL with a capacity of 103.31million tonnes per year (MTY) of coal. Thetotal capital outlay of 33 projects is Rs3436.92 crore and out of this 16 (capacity=43.23 MTY) have been completed with asanctioned capital investment ofRs. 1714.49 crore. Mahanadi Coalfields Ltd.produces non-cooking coal of Gr. B LF, Gr.C LF, Gr. D LF, Gr. E & Gr.F at Talcherfield and IB field, in Orissa. For marketingof their products, MCL put sustained

Sreekumar et.al, Measuring Technical Efficiency...


efforts and customer satisfaction is giventop priority. The three factors, which aretaken care, are quality, quantity and sizeof coal. The major customers at presentare: Orissa Power GenerationCorporation, Tamil Nadu ElectricityBoard, Maharastra Electricity Board andWest Bengal Power DevelopmentCorporation Ltd. It has been seen thatduring the last three years the companyhas shown growing PAT (Profit after tax),and a sound financial health.

3.0 CONCEPTS OF TECHNICAL EFFICIENCY

Modern efficiency measurement beganwith Farrell (1957) who drew upon thework of Debru (1951) and Koopmans(1951) to define a simple measure of firmefficiency, which account for multipleinputs. Koopmans (1951) defines adecision making unit as technicallyefficient if – (i)an increase in any outputrequires a reduction in atleast one otheroutput or an increase in at least one input(ii) reduction in any input requires anincrease in at least one other input or elseit results in a reduction of atleast oneouput. This definition is not sufficient todetermine the absolute efficiency frontier(Sahoo and Mohapatra, 2001). Farrell(1957) took motivation from thedefinition put forward by Koopmans(1951) and treated technical efficiencyrelative to best practices in the groupunder consideration. But this approachfails to give information regarding thedegree of inefficiency of an inefficientDMU. Debreu addressed this issue.Debreu and Farrell defined technical

efficiency as one minus maximum feasibleequiproportionate reduction in all inputsthat still allows the continued productionof given outputs. A score of unityindicates technical efficiency and anyscore less than unity indicates technicalinefficiency. This concept wasreformulated as a mathematicalprogramming problem called DataEnvelopment Analysis (Charnes, Cooperand Rhodes, 1978).

4.0 DATA ENVELOPMENT ANALYSIS

The application of Data EnvelopmentAnalysis (DEA) was initiated after theseminal work by Charnes, Cooper, andRhodes (1978) and subsequent evidencecan be found in Banker, Charnes andCooper (1984); Ramanathan (2001); Taluri(2000); Despotis, Dimitris and Smirlis,(2002) and Seiford and Thrall (1990).DEA can be used to evaluate theefficiency of a number of producers,generally referred as decision-makingunit. DEA compares each producer withonly the “best” DMU in the group, whichis better than the comparison withaverage of the group. In DEA, we canconsider number of DMUs, each of themconsuming similar inputs to varying levelto produce. A fundamental assumptionbehind this method is that if a givenDMU, "" A , is capable of producing

)(AY units of output with )(AX inputs,then other DMUs shall also be able to dothe same if they were to operateefficiently. Similarly, if DMU B is capableof producing )(BY units of output with

)(BX inputs, then other DMUs should

117

also be capable of the same. DMUs BA , ,and others can then be combined to forma composite producer i.e. virtualproducer with composite inputs andcomposite outputs. The emphasis of DEAis on finding the “best” virtual producerfor each real producer. If the virtualproducer is better than the originalproducer by either making more outputwith the same input or making the sameoutput with less input then the originalproducer is inefficient

To develop the DEA model we definethe following notations.

Notations

To develop the DEA model, we use thefollowing parameters and variables:

n = Number of DMU },...,2,1{ nj =

s = Number of outputs },...,2,1{ sr =

m = Number of inputs },...,2,1{ mi =

rjy = Quantity of thr output of thjDMU

ijx = Quantity of thi input of thj DMU

ru = weight of output

iv = weight of input

DEA Model

The relative efficiency score of 0j DMUis given by

∑

∑

=

== m

iiji

s

rrjr

j

xv

yuvuh

1

1

0

0

0),(max


∑ ∑= =

=≤−s

r

m

iijirjr njxvyutosubject

1 1.,..,2,10

irvu ir ,0, ∀≥ (1)

The decision variables are respectively uuuuu sr ),...,,...,,( 21=

and ),...,,...,,( 21 mi vvvvv =

the weights given to the s outputs and tothe m inputs. To obtain the relativeefficiencies of all the units, the model issolved n times, for one unit at a time.

The fractional program (1) can be reducedto Linear Programming Problem (LPP) asfollows:

∑=

=s

rrjrj yuh

100

max

11

0=∑

=

m

iiji xvtosubject (2)

∑ ∑= =

=≤−s

r

m

iijirjr njxvyu

1 1

.,..,2,10

irvu ir ,0, ∀≥

This model is called CCR outputmaximization DEA model (Charnes,Cooper, Rhodes 1978).

The routine computation of DEA can beperformed using generalized LPsoftware or specialized DEA software.The non-computational aspects are alsoimportant in the application procedure ofDEA.


5.0 CASE OF MCL

The vision of MCL states consumer’sdelight as its ultimate goal, while at thesametime improving the quality of coalproduced and fulfilling socialresponsibility like using the mined outland for afforestation, orchard,pisciculture etc. to make the post-miningland more useful than the pre-miningland. To achieve this, company shalloperate efficiently. We have taken datafrom twelve collieries and used DEA tocalculate the technical efficiency.

5.1 Selection of DMUs

According to Ramanathan (2003), thereare two factors which influence theselection of DMUs for the study –homogeneity and number of DMUs. Byhomogeneity we mean the DMUs musthave same objectives and perform thesame task. The number of DMUs to beselected depends on the objective of theDEA study. The thumb rule to find thenumber of DMUs is that the number ofDMUs shall be larger than the productof number of inputs and number ofoutputs. We have taken twelve units of

MCL, Sambalpur for efficiency calculation.These units are Talcher, Deulbera,Nandira, Lingaraj OCP, Belpahar,Lakhanpur, Lilari, Lajkura,Balanda,Jagannath, Bharatpur, Kalinga OCP.

5.2 Input-Output Definition andDescriptive Analysis

For our analysis the data are classifiedinto two categories viz. inputs andoutputs. The criteria of selection ofinputs and outputs are quite subjective.Ramanathan (2003) indicates that thereis no specific rule in determining theprocedure for selection of inputs andoutputs. In general any factor used asthe resources by the DMUs forproducing something of value and also,any environmental factor that bears astrong effect on how the resources areconsumed can be considered as theinput. Similarly, any factor, whichdescribes the amount of goods, services,or any other outcomes obtained as aresult of the processing of resources canbe taken as output. The inputs andoutputs taken along with notations areshown in Table -3.

Table- 3: The inputs and outputs taken and notations

Input for thj DMU Output for thj DMU

.)(:1 Rsshiftmanperearningu .)(:1 Rstonneperpricesalesreliazablenetv)(:2 LKWHnconsumptioyelectricitu )(:2 tonnemanshiftperoutputtyproductiviv −

.)(:3 ltrsnconsumptiodiselu

.)(exp:4 Kgusedlosiveu

119Sreekumar et.al, Measuring Technical Efficiency...

.)(:1 Rsshiftmanperearningu : It is theaverage wage paid to the workers

)(:2 LKWHnconsumptioyelectricitu :Amount of electricity consumed for coalextraction.

.)(:3 ltrsnconsumptiodiselu : Amount ofdiesel consumed for coal extraction.

.)(exp:4 Kgusedlosiveu : Amount ofexplosive used for blasting the hard stoneshaped coal.

.)(:1 Rstonneperpricesalesrealizablenetv :The selling price of coal per tonne; it

generally depends upon the quality ofcoal.

)(:2 tonnemanshiftperoutputtyproductiviv − :The amount of coal produced per manshift.

The data collected from the collieries overthree-year period i.e. 2002-03, 2003-04and 2004-05 is shown in appendix. Thedata collected is subjected to descriptivestatistics; the results are tabulated inTable-4 below.

We have used paired sample t-test toknow the difference between the mean

and median across the years. The resultsare tabulated in Table-5 below.

Table-5: Results of the t –tests

Mean t = -1.41, p = 0.2169 t = -1.50, p = 0.1949 t = -1.50, p = 0.1949

Median t = -0.70, p = 0.5159 t = -1.18, p = 0.2895 t = -1.35, p = 0.2352

It is observed that there is no significantdifference between both input and outputfactors over the period considered. Next

the correlation analysis is done betweenthe parameters; the results are tabulatedin Table-6 below.

Table-4: Descriptive Statistics

2002-2003 2003-2004 2004-2005

Mean Median IQR Mean Median IQR Mean Median IQR

594.149 595.920 73.903 647.453 647.415 77.735 824.016 801.825 123.333

119.515 127.545 61.055 125.286 118.441 49.259 126.122 118.933 96.592

25.980 25.010 43.435 25.626 19.904 47.183 25.604 19.289 42.050

13.297 14.799 19.169 14.345 13.953 22.398 14.345 13.953 22.398

537.573 373.900 455.023 550.354 376.780 492.170 648.987 428.645 627.048

12.603 12.345 19.568 12.172 11.480 21.185 12.066 11.435 18.455


1u 2u 3u 4u 1v 2v

Table -6: Correlation Matrix

1u 1 -0.06 (a) -0.10(a) 0.11(a) -0.22(a) -0.05(a)

0.24 (b) 0.04(b) 0.14(b) -0.36(b) 0.02(b)

-0.06 (c) -0.27(c) -0.18(c) -0.10(c) -0.13(c)

2u 1 0.49(a) 0.38(a) -0.02(a) 0.15(a)

0.47(b) 0.43(b) -0.13(b) 0.31(b)

0.69*(c) 0.72*(c) -0.40(c) 0.50(c)

3u 1 0.80*(a) -0.72*(a) 0.90*(a)

0.94*(b) -0.70*(b) 0.90*(b)

0.96*(c) -0.74*(c) 0.85*(c)

4u 1 -0.64*(a) 0.60*(a)

-0.75*(b) 0.84*(b)

-0.79*(c) 0.80*(c)

1v 1 -0.83*(a)

-0.78*(b)

-0.75*(c)

2v 1

*indicates p is significant at 0.05, (a) for year 2002-03, (b) for year 2003-04,( c) for year 2004-05

The Table-6 indicates that there is a highdegree of significant positive correlationbetween the variable 2v and 3u , 4u overall the periods. But there is a low degreeof insignificant positive correlationbetween 2v and 2u , and low degree ofinsignificant negative correlationbetween 2v and 1u . Moreover it isinteresting to observe many of thenegative correlation occurring in thecolumn 1v .

5.3 Efficiency Analysis of Collieries underMCL

We have used both the scaleassumptions i.e. constant return to scaleand variable return to scale to calculatethe efficiency of collieries over threeperiods. For calculating the efficiencyscores of each DMUs we have used asoftware Frontier Analyst [6]. Theefficiency scores of both the scales aretabulated in Table-7 below.

121

Table -7: Efficiency scores of DMUs and their Peers for CRS and VRS.

2002-2003 2003-2004 2004-2005

CRS VRS CRS VRS CRS VRS

DMUs Eff. peer Eff. peer Eff. peers Eff. peer Eff. Peer Eff. peer

1 1 - 1 - 1 - 1 - 1 - 1 -

2 1 - 1 - 1 - 1 - 1 - 1 -

3 1 - 1 - 1 - 1 - 1 - 1 -

4 1 - 1 - 1 - 1 - 1 - 1 -

5 0.612 3,4,6 0.653 2,4,6 0.574 2,4,6 0.626 2,4,6 0.582 1,6,12 0.651 2,6

6 1 - 1 - 1 - 1 - 1 - 1 -

7 1 - 1 - 1 - 1 - 1 - 1 -

8 0.734 3,6,7 0.734 1,3,6,7 0.556 3,4,6,7 0.5938 3,4,6,7 0.508 2,6,7 1 -

9 0.733 1,3,4 0.883 2,4 0.734 2,3,4 0.867 2,3,4 0.638 1,2,6 0.765 2,6

10 0.908 3,4,6 0.820 2,4,6 0.839 2,6,7 0.862 2,6,7 0.643 2,6,7 0.650 2,6,7

11 1 - 1 - 0.884 2,4,6 0.954 2,4,6 0.811 1,6,12 0.815 1,4,6

12 0.781 1,4 0.781 1,2,4 0.798 2,4,6 0.813 3,4,6 1 - 1 -

It is observed that DMU1, DMU2,DMU3, DMU4, DMU6 and DMU7 arecoming out to be efficient over threeperiods under both the scales. So theseunits are utilizing their resources in aright way to produce the outputs.DMU11, which was operating efficientlyin the year 2002-03, has becomeinefficient in the subsequent period.DMU8 with efficiency score less thanunity in all the periods is getting a scoreof unity in the year 2004-05 under VRS.The inefficient DMUs can refer theirpeers for improvement and becomingefficient units e.g. DMU5 for the year2002-03 shall refer DMU3, DMU4 and

DMU6. The efficiency trend plot overthree periods under CRS assumption isshown in Figure -1.

Figure-1 : Efficiency trend under CRS



The figure makes it clear that some ofthe DMUs namely, DMU1 to DMU7 areperforming consistently over threeperiods. Some kind of variation isobserved in the rest DMUs. Theperformance of these DMUs has gonedown with increasing period with the

exception of DMU12 whoseperformance has gone up in the year2004-05.

Next, the potential improvement for theinefficient units is calculated for the year2002-2003 under CRS assumption, and isshown in Table-8.

Table- 8: Potential Improvement on various parameters for the year 2002-2003

Ineff.DMUs

Improv.Required 1u 2u 3u 4u 1v 2v

DMU5 Actual 634.29 178.75 34.15 24.05 370.88 12.12

Target 634.29 103.54 34.15 13.4 607.83 19.86

Pot. Imprv. 0 -42.08 0 -44.26 63.89 63.89

DMU8 Actual 605.72 82.67 14.16 16.84 355.62 9.29

Target 605.72 55.44 14.16 5.77 484.26 12.65

Pot. Imprv. 0 -32.93 0 -65.74 36.17 36.17

DMU9 Actual 676.13 131.91 15.87 17.72 798.39 2.61

Target 676.13 131.91 4.97 3.64 1088.7 3.56

Pot. Imprv. 0 0 -68.68 -79.47 36.36 36.36

DMU10 Actual 601.54 137.01 36.99 15.99 368.9 17.73

Target 601.54 98.9 36.99 12.63 459.47 22.08

Pot. Imprv. 0 -27.82 0 -21.03 24.55 24.55

DMU12 Actual 552.93 159.21 56.28 28.09 371.83 18.38

Target 552.93 102.02 44.46 20.71 476.14 23.54

Pot. Imprv. 0 -35.92 -20.99 -26.28 28.05 28.05

It is observed that (Table-8) the target ofinputs i.e. earning per man shift (u1),electricity consumption (u2), dieselconsumption (u3), explosive used (u4) for

DMU-5 should be 634.29, 103.54, 34.15and 13.4 respectively. The target ofoutputs for DMU-5 will be 607.83 and19.86 respectively. Hence the

123

management should decrease the inputu2 by 42.08 units and u4 by 44.26 unitsand increase the outputs v1 and v2 by63.89 units each for the DMU- 5. Thevalue of stock, wages, and floor space forDMU-1 should be 30.63, 9.63, and 248.33respectively. Similarly, other DMU’starget inputs and outputs are mentionedin Table-8.

6.0 CONCLUSION

In this paper, a methodology based onDEA is discussed to find the technicalefficiency of various collieries of anIndian coal company. The methodologyfacilitates to identify the benchmarkingcollieries which can be referred byinefficient units to become efficientunits. Two approaches of DEA viz;Constant Return to Scale (CRS) andVariable Return to Scale (VRS) areconsidered to obtain effic iency ofDMUs. From the perusal of the aboveanalyses and results, it is evident thatthe efficiency of coal mines dependsupon the performance in everyparameter which is directly orindirectly linked with the system. DMU1, DMU 2, DMU 3, DMU 4, DMU 6, andDMU 7 are relatively efficient. Otherunits are relatively inefficient. So inorder to maintain their efficiency theyhave to formulate proper strategies byproper utilization of inputs to producedesired outputs. It is interesting toobserve here that no inefficient DMUdemands for potential improvement ininput u1 which is earning per man shiftbut all the inefficient units has scope for

potential improvement regarding theinput u4 i.e. explosive used. There is ascope for improvement in both theoutputs for all the inefficient DMUs.The study will be more interesting ifone would take the non-discretionaryaspects like the location, quality ofmanpower, experience etc.

REFERENCES

Banker R.D, Charnes.A , Cooper W.W. (1984).“Some models for estimating technical andscale efficiencies in Data EnvelopmentAnalysis”, Management Science, 301078-1092.

Charnes.A , Cooper W.W and Rhodes.E. (1978).“Measuring efficiency of decision makingunits”, European journal of OperationalResearch, 2, 429-444.

Debreu, G. (1951),”The Coeffcient of ResourceUtilization”, Econometrica, 19, 273-292.

Despotis.K. Dimitris, Smirlis.G.Yiannis. (2002).“Data envelopment analysis with imprecisedata, European Journal of OperationalResearch, 140, 24-36.

Farrell, M.J. (1957).”The measurement ofproductive efficiency”, Journal of RoyalStatistical Society, 120(3), 254 - 290.

Koopmans, T. C., (1951). “Analysis of Productionas an Efficient Combination of

Activities” in T. C. Koopmans (ed.) ActivityAnalysis of Production andAllocation:Proceedings of a Conference. NewHaven: Yale University Press.

Ramanathan, R. (2001). “A Data EnvelopmentAnalysis of comparative performance ofschools in Netherland” Opsearch, 38 (2),160-182



Ramanathan, R. (2003), “An Introduction to DataEnvelopment Analysis: A tool forPerformance Measurement”, SagePublication, New Delhi.

Sahoo, K Biresh and Mohapatara, K J Pratap.(2001) “Measuring Technical efficiency inData Envelopment Analysis”, Opsearch, 38,(.5), 456-482.

Seiford, L.M. and R.M. Thrall. (1990), “Recentdevelopments in DEA: the mathematicalprogramming approach to frontieranalysis.” Journal of Econometrics,46, 7-38.

Taluri, Srinivas. (2000). “Data Envelopmentanalysis –Model and Extension” DecisionLine 8-11.

END NOTES[1] Zissis Carin , “India’s Energy Crunch” ,

Council on Foreign Relations, A Resourcefor Nonpartisan information and Analysis,December 8, 2006.

[2] Energy and Environment, Forbes magazine,27 November 2006.

[3] Coal Industry (diehardindian.com), http://www.diehardindian.com/infra/coal.htm,accessed on 09-02-07 at 7.00pm.

[4] Coal in India, Chowdhary S.K., FormerChairman, Coal India Limited, India, http://w w w . w o r l d e n e r g y . o r g /w e c g e i s /p ubl ica t i o ns /de fa u l t / te ch_ p ap e rs /17th_congress/2_1_20.asp

[5] h t t p : / / m a h a n a d i c o a l . n i c . i n /egocoalfield.htm

[6] www.banxia.com

http://www.diehardindian.com/infra/coal.htm

http://www.worldenergy.org/wecgeis/

http://www.banxia.com

Perspective

Beyond Whistleblowing: A Study onSocrates, Satyendra and Manjunath*

Bibhu Prasan Patra1

Abstract

Business ethics text books trivialize the concept of whistleblowing by stating some morally justifiablecriteria for whistleblowing. Business ethicists state that the act of whistleblowing should be based onwhat is desirable, permissible and obligatory for an individual manager to do in a business situation. Theargument is that following these standards makes our action morally defensible (See appendix-1-DeGeorge, 2006). The basic purpose of this paper is to analyze the other side of the notion and highlight thatwhistleblowing reflects the finer element of our moral life. It goes beyond the ordinary question of whatis morally defensible. In this paper an attempt has been made to look at the issues that are more valuablethan life itself. At every point of our life we encounter the dilemma that deals with the finer question ofour living. Living a moral life is not just what is morally defensible or justifiable. Whistleblower’scommitment to justice, fairness, and duty at times transcends the ordinary criteria of whistle blowing.As Elaine Sternberg (1994) points out the efficacy of whistleblowing is not just its moral justification.Individual decision makers as moral agents at times decide -which way to walk off- which ditch they wantto die. This obviously is not like resolving simple, ordinary dilemma of the whistleblower i.e. betweenloyalty and free speech. An insight into leading a moral life and addressing issues in business ethics, arenot poles apart; rather one is the part of the other.

* Received February, 27, 2008; Revised February 29, 2008.1. Associate Professor, Xavier Institute of Management, Bhubaneswar; email: [email protected]

1.0 INTRODUCTION

Whistleblowers are just like umpires ortraffic police who blow the whistlewhen they observe a foul beingcommitted on the field or some onerushing through, violating the trafficrule. Business ethicists definewhistleblowing as an act of disclosuremade by a person about some wrongdoings by a corporation to an external

agency which is difficult for the publicto know otherwise. Their act is basedon the inside information and thedocumented evidence they have as amember of the organization (see DeGeorge, 2006, Velasquez, 2006, Jubb,1999). For example Cynthia Cooper isthe whistleblower who exposedmassive accounting fraud at WorldComin 2002. Sherron Watkins the “Enron



whistleblower”, laments, “We’re sucha crooked company.” Thesewhistleblowers mainly inform thesociety about the different types offraud, trickery and profit maximizationachieved by corrupt means. The act ofwhistleblowing is valued for its moraldesirabil ity. Whistleblowers aregenerally hardworking people whobelieve in the social, political, and legalsystem and have loyalty to theirorganization.

The aim in this paper is to discuss theconcept of whistleblowing which goesbeyond the ordinary morallydefensible act of whistleblowing.These whistleblowers often travel thedifficult path and make the hard choiceof adopting the path of truth. Theirlives are guided by principle, and theygo beyond what is just e thicallydefensible. The basic point of theirmoral chart is based on a clearunderstanding of virtues that areessential for living a life which is worthliving.

Their strong faith in the system, justiceand reason force them to speak out whenthey see something wrong. They areaware that fighting against corruptionand injustice may deprive them from theordinary materialistic pleasure. Peoplethink that they take unnecessary liabilityand invite injury to themselves. But thesewhistleblowers do not agree with thisthesis and are ready to face even deathfor an ideal.

2.0 THE DEATH OF SOCRATES

The death of Socrates, ‘the wisest andmost just of all men’ in 399 BC hasshown the unreliabil ity andundesirability of the democratic rule ofAthens. Socrates is seen as a wise andbenevolent citizen martyred for raisinghis voice against injustice andcorruption. The false charge against himis that he is corrupting the youths ofAthens and instigating them against therulers. The jury voted for death as thepenalty and Socrates carried out hisown execution by drinking the poisoncalled Hemlock given to him. He accepted the verdict and decided todie, helds on to his intellectual andmoral beliefs, when other options likeescaping from prison, begging apologyto the jury and living in exile elsewherewere available to him. But he chose todie as a law abiding citizen and becauseof his respect for the system.

Common men ridicule Socrates forundermining human pleasure andcriticize him as an impractical man. People see him neglecting life andignoring the most pragmatic aspect ofhuman l ivings. The commonunderstanding of justice and right isthat who are deprived anddisadvantaged in society struggle hardfor thei r right and the rich andpowerful extract what they want. Inequality is inbuilt in the social systemand people reject the Socratic pursuitfor justice and equality. For them his

127

f ight was a futi le effort. It isunnecessary to bring life to an untimelyend like Socrates did.

But Socrates is well aware of these facts,which the common men thought that hedoes not know. On the other hand,people seem to ignore the truths aboutthe deeper aspect human living andhuman desires. They lack theknowledge that there is something morethan living well with wealth and power.In fact, proper use of the wealth andpower should be based on rationaljudgment and moral virtues. Socrateswas worried about what our prioritiesought to be if our lives are to really gowell. He was struggling hard toconvince people that in order to live agood life attachment to virtue isessential. Living well for Socrates is tohave an understanding of virtue andtranscends what is just ethicallydefensible. That is the wisdomnecessary to comprehend the value ofvirtue in human life. Socratesargument for his acceptance ofexecution reveals his commitment totruth and deep sense of moral virtue. In his explanation he says:

“I have concealed nothing I havedissembled nothing. I know, that I amspeaking the truth…they hate mebecause I am speaking the truth and thereason of their slender of me…. Hegoes on and says… the greatest goodfor man in daily life is to converse aboutvirtue… and the life which is

unexamined is not worth living. A lifewhich is worth living is also worthdying for (Apology- Plato,1957).”

The above account of Socrates explainsthe value of moral virtues and how theyare essential for our living well. Thesevirtues are traits of character that arecentral for everyone everywhere toobtain. Moral virtues are allencompassing and necessary for livingwell. He highlights the deeper aspectsof living well and the limits of theshallow understanding of the commonmen. Virtues matter in every aspect ofour life. Every person and everyprofession should start from theunderstanding of virtue and why theymatter in our lives.

This Socratic wisdom is still alive andasserted by the two young Indianprofessional who defy the commonmen’s understanding of living welland adopt the path of virtue anddecided not to compromise withprinciple. Mere surviving and living alife with ordinary pleasure failed toallure them. Like Socrates they spokeout when saw something wrong. Theylaid down their lives fighting againstcorruption and injustice. They facedthe ultimate end for holding on to their‘ideal’. Their commitment to virtue andliving a life that is worth living wasunequivocal. Those who put them todeath by unjust means really confer onthem the honor of immortality. What

Patra, Beyond Whistleblowing: A ...


is better?; an ordinary l ife withpleasure, without any ideal or a lifewith an ideal? This is what “Socratessays just before his death…. the hourdeparture has arrived, and we go ourways – I to die and you to live, whichis better, God only knows” (Apology –Plato, 1957).

3.0 SATYENDRA DUBEY ANDS. MANJUNATH

In what follows I shall elaborate thecases of these two martyrs referredabove. Both of them died in the mothof November. Satyendra Dubey, a 31year old civil engineering graduatefrom IIT, Kanpur, was gunned downby unidentified assailant (Gaya Bihar,India) on November 27, 2003. He wasworking with the National HighwayAuthority of India and assigned to theGolden Quadrilateral project thatconnects the four corners of India. Hewas posted at Koderma, Jharkhand. Hewas trying to expose the poorimplementation of work and rampantcorruption and irregularities to PM’soffice. Just after two years inNovember 19, 2005, S Manjunath wasgunned down by Pawan Kumar Mittal(alias Monu) the son of a Petrol pumpowner in Lakhmipur Kheri in UttarPradesh. He was working for IndianOil Corporation as an area salesmanager. Manjunath was 27 years oldand an MBA from IIM – Lucknow. Hewas trying to prevent adulteration ofpetrol.

3.1 Satyendra Dubey

Golden Quadrilateral, the state of theart infrastructure project, of nationalHighways Authority of Indian (NHAI)was considered as the dream project forevery Indian. The construction work ofthis project was taking place under thedirect supervision of the office of thePrime Minister (PMO). SatyendraDubey was working as an engineerwith the NHAI Bihar and assigned tothis pet project of the then PrimeMinister Atal Bihari Vajpayee. Dubeyhad written a letter to the PrimeMinister Atal Bihari Vajpayee exposingthe low quality work and otherirregularities in the construction of thefour-lane road. He wrote a letter tothe PM’s office which was received onNovember 11, 2002. Dubey hadrequested to keep his name secret. ButPM’s office circulated his letter alongwith the file among the bureaucracy.Noting on the file, bears witness to this.None of the officers of the PM’s officerealized the gravity of the situation andthe danger to which Dubey wasexposed to by the movement of the filethat contained his letter. The honestofficer who was working with all goodintention and dedicated to the cause ofnation building lost his life for blowingthe whistle against the offender. Thefact finding team of Indian Expressrevealed another fact which is morepuzzling that the young engineer wrotea second letter to PMO expressing his

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concern that his first letter was leakedand he was exposed to wrath of theoffender. He was afraid, because thecontent of his letter containedinformation about wrong doings of thecontractors and NHAI officials. He wasanticipating some troubles and thinkingthat the mischief makers may causephysical harm to him (The IndianExpress, Nov. 30. 2003).

The letter said:

“The NHAI officials showed greathurry in giving mobilization advance toselected contractors for f inancialconsideration. In some cases thecontractors have been givenmobilization advance just a day aftersigning the contract agreement. The bigcontractors have been able to get allsorts of help and secret information anddocuments from NHAI officials andeven note sheets carrying approval ofchairman have been given. The entiremobilization advance of 10% of contractvalue, which goes up to 40 crore incertain cases are paid to contractorswithin a few weeks. But there is littlefollow up to ensure that they areactually mobilized at the same pace, andthe result is that the advance remainslying with contractors or siphoned totheir other activities”.

Dubey also highlighted the problems ofsub-contracting by the primarycontractors. “Though the NHAI isgoing for international competitivebidding to procure the most competent

civil contractors for execution of itsprojects , when it came to actualexecution, it was found that most of theworks, (sometimes even up to 100percent) were subcontracted to pettycontractors who did not have sufficientexpertise of executing such bigprojects,” he said Everyone in theNHAI is aware of the phenomenon ofsubcontracting but turned the otherway.

“I have written all these in myindividual capacity. However, I willkeep on addressing these issues in myofficial capacity in the limited domainwithin the powers delegated to me,”he clarified. In another letter to theProject Director, NHAI, Koderma,Jharkhand, on July 26, two days beforehe was to take over as Project Managerin Gaya, Bihar, Dubey expresseddispleasure over the transfer saying itwas baffling and would not serve theinterest of the project in Jharkhand.Inhis letter also, he had drawn theattention of the Project Director to some‘irregularities’ committed bycontractors and consultant for theproject. Authorities of NHAI closedtheir eyes to the ways in which thework of the prestigious project wasprogressing which forced Dubey to dothe right thing by alerting the PMO.

A patriot with strong commitment toduty believed the project was of“unparalleled importance to thenation”. Dubey categorically put the



whole activity in black and white thatexplained the gravity of the situationand the rots that needs be cleaned infrom this big project. The tragicuntimely demise of the youngIIT,Kanpur engineer put the entirenation to reflect on the kind of risk onehas to take to fight against corruption.In a handwritten letter to his friend, thehero of this story had written: “Myconscience is my biggest virtue, mywealthiest treasure and my best guideor friend. I always do what myconscience tells or compel me to do. Iwant to keep this candle of humanityever glowing in my heart.’’ The hero’sstory was a shocking one with a sobending.

After effects

The National Human Rights Commissionissued notices to the Bihar police and theNational Highways Authority of India inconnection with the Satyendra Dubeymurder case. The commission has askedNHAI why Dubey’s identity was notprotected. Santosh Kumar, directorgeneral, Investigations, was asked toconduct an inquiry and submit the reportwithin three weeks .The prime ministerimmediately asked the CBI to investigatethe case ( rediff.com.). Media reporters

exposed the lapses of the Bihar police andthe NHAI’s for their failure to act onDubey’s complaints.

IITians ganged together to generatesupport for one of their dearest fearlessfriends who laid down his life fornational interest. They questioned theresponsibility of the police and the PrimeMinister’s office, and the level oftransparency in the CBI probe.

The entire alumnae raised their generalvoice of concern that “as law abidingcitizens and having faith on the systemwhen one files a complaint or bringssome wrong doing before the localpolice; he believes that the lawenforcement authorities will protect him.The minimum expectation of a citizenfrom the State is a reasonable level ofsafety and protection for his life andproperty. The State ought to ensure thisat all level (personal and professionallife)”. Dubey got national andinternational attention as a whistleblower. Satyendra K. Dubey MemorialAward was instituted by IIT Kanpur inthe memory of Mr. Satyendra K. Dubey(BT/CE/1994/IITK) for his exemplarylife and supreme sacrifice. The sequenceof events leading to Satyendra Dubeymurder is given in Table-1

Table-1: Sequence of Events of Satyendra Dubey Murder Case

November 2002 Satyendra Dubey sent a letter to the PMO detailing system in the NationalHighway Authority of India. He named four contractors and theirmisdeeds. In order to protect himself, he also made a special request tobe kept secret when the PMO investigated the matter.

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Satyendra’s name was not protected and the file containing his complaintwas circulated among various offices. This was like issuing a publiccontract for his life.

November 27, 2003 Satyendra was murdered in Gaya, the place where he lived and workedfor NHAI.

News reports about Satyendra’s murder stirred the Nation andunleashed the outrage.

Within days the Prime Minister’s Office and NHAI issued statementsdefending and trivializing Satyendra’s death.

December 5, 2003 Bihar govt. wakes up to IITian’s murder.

December 9, 2003 CBI to probe Dubey Case: PM Narayana Murthy calls for probe intoSatyendra Dubey’s murder. Dubey murder figures in Parliament.

December 10, 2003 Why was not Dubey protected: NHRC.

December 11, 2003 Govt. denies leaking Dubey’s identity. Bihar submits highway securityplan. How will you ensure smooth completion of Golden QuadrilateralProject?

December 12, 2003 Hearing of PIL on Satyendra Dubey on January 5.

December 14th, 2003 The case was handed over to the CBI.

December 16, 2003 CBI team in Gaya to probe Dubey’s murder.

December 18, 2003 Patna High Court to monitor security on highway project in Bihar.

December, 26, 2003 The CBI said that according to the evidence given by Mr. PradeepKumar, Satyendra had been killed when resisting thieves who weretrying to kill him. Most people refused to believe this and the CBI’sexplanation further intensified the outrage.

December 28, 2003 CBI detains one person in Dubey murder case.

January 5, 2004 SC notice to PMO, Centre, Bihar govt. on Dubey.

January 6, 2004 Satyendra Dubey killed for resisting robbers. Accused.

January, 2004 key witness, Pradeep Kumar, “disappeared”.

Two other witnesses, who were interrogated by the CBI in this case,allegedly committed suicide within a day in the end of January.

February 02, 2004 Dubey case: FIR against CBI officials. Dubey case: CBI denies hand insuicides.

February 04, 2004 Dubey Case: ‘Suicides hampering CBI probe”.

February 05, 2004 Dubey Case: CBI rules out change of officials.



Key Issues Raised by Satyendra Dubeyare Still Unanswered

Dubey’s letter contained the namesCentrodosity of Russia, China Coal ofChina, and Pioneer Constructions Ltd.as being guilty of taking the contractsby means of bribing and subsequentlygiving it away to subcontractors andmaking enormous profit without doingany value adding work. He also talksof up to Rs. 40 crores being given tocontractors as mobilization advance,which is evidently diverted; partly to payequipment advances. There is nojustification for giving advances tocontractors if they do not have capacityto do the jobs. The corrupt practiceshighlighted by Dubey are routine inmost of the infrastructure projects of theGovernment of India. Whyinvestigation has not been done on thedetailed allegations made by Dubey?

Shailesh Gandhi, an aggrieved citizenexpressed his worries and says:

“The minimum ethical standard is thatwhen as Institutions, Organizations, orMedia, we do not compromise ourhonesty, whenever these Institutionsdeviate, others must challenge them. Itadmits mistakes than to pretend we areinfallible. To refuse to admit errors isthe characteristic of our entire leadershipfrom the political, bureaucratic andbusiness class. If all the institutions whichhonoured Satyendra’s memory raise theirvoice for the sake of their own credibility,the truth will come out. Honesty is avalue, which is basic to the well being ofa society. As individual society, we haveto bring it to the centre stage of ourNational agenda and debate five decadesof the last century, Satyendra was theprime mover of our nation reason for theaffluence of the Developed nations is also

March 03, 2004 Centre Okays security plan for Golden Quadrilateral Project.

March 12, 2004 Dubey Case: SC notice to CBI, Centre, Bihar government.

There was no investigation of these murky happenings or the CBI’s rolein these deaths. After keeping quiet for about six months, the CBI againrepeated the investigation in June, 2004.

September 03, 2004 CBI files charge sheet in Dubey murder case.

September 29, 2004 Case against NHAI project director named by Satyendra Dubey.

October 27, 2004 Bihar College named after Satyendra Dubey.

There has been no public investigation of the alleged corruption withinthe NHAI to attempt to set things right.

January 13, 2005 Charges filed in Satyendra Dubey murder case.

September 13, 2005 Dubey murder accused escapes.

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an insistence on home and publicly. Theorganized workers have alternatives todefend their own turf. Who will defendSatya? And without Satya can there be abetter India?” (Shailesh Gandhi,Http”//s a t y a m e v a j a y a t e . i n f o /Satyendra_Dubey.htm. ,dated: 11/3/2007).

The fundamental duty of any democraticgovernment is to protect its citizens fromthe evil force of the society andencourage them to travel the path oftruth. In India “Satyameva Jayate”is thebasic principle we adopt to regulate ourconduct in public and private life. Inorder to accomplish truth one needslegal and moral support from the system.Satyendra Kumar Dubey was killed fortelling the truth .He could have chosento keep quiet, like the majority of youngprofessionals of this country. He couldhave continued doing his job as a deputygeneral manager in the Centre’sNational Highway Authority of India(NHAI) and shut his eyes to all thewrong doings taking place in theprestigious project .But Dubey optedto travel on the path of truth did theright thing by alerting the PMO(IndianExpress). Government promised toprotect future Dubeys but we allwitnessed another Dubey just after twoyears.

3.2 S. Manjunath Case

The 27-year-old young engineeringgraduate asked his teacher a month

before he was gunned down onNovember 19, 2005, for standing upagainst corruption .”Sir, tell me whatlife is this, if we have nothing to diefor?” Manjunath’s question regardingthe finer aspect of human living dig upvalues that goes beyond ordinary,monotonous way of living. ProfessorDebashis Chatterjee of IIM-Ldedicating his book, ‘Break Free(2007),to his former student, states“Manjunath -a man who broke free.”In the preface of his book he writesthat: “Manju was not the typicalbusiness school wonder boy who hada way with cold statistics and fuzzylogics. He was passionate to a fault.He would often visit me with questionsbeyond personal success or career……… He was like a wild bird lookingbeyond the nest for an adventure inthe wilderness,” Manjunath was anupright and honest man – an idealistand passionate about values, and aboutmaking a difference to Society. It wasthis passion, this standing up for whathe believed was right, that cost himhis life. In premium Business Schools“the job you get at the end of theplacement process determines yourworth in the peer group. At anunglamorous location in LakhimpurKheri, supervising distribution ofpetrol and diesel in several fil lingstations, Manjunath had a very modestbeginning, unlike his classmates whohad cushy marketing jobs in MNCs.But he took his work rather seriously.”



He had outdone his classmates becauseof what he died for.

The Scam

On September 13, the day he sealed theMittal outlet (the owner’s son MonuMittal is prime accused in his murder),Manjunath had sealed another petrolpump in the area— Mitauli’s L D ServiceStation, owned by one Dinesh Seth. Likethe Mittal pump, the L D Service Stationwas also allowed to open a month later,on October 15, with a warning fromManjunath that a second offence wouldinvite permanent shutdown.

Rajendra Singh, manager of the L DService Station, said their samples “werefound clean, so we were allowed to startwork.” Incidentally, Seth also owns thesole kerosene depot which serves the 2lakh population of the surrounding 132villages. Every month, the depot receivesabout 1.20 lakh litres of kerosene. Andgoing by the fair price shop owners ofthe area, a great deal of it is notdistributed.

For example, the sole fair price shopcatering to Mainhan Gram Sabha—comprising Khotena, Ranibehr andMainhan villages—which should get1,000 litres of kerosene per month, isgiven only 800 litres.

The shop owner, Mahesh Kumar, said heis not given any receipt. “The rest, a 200-litre drum of kerosene, has to besurrendered,” he said. The siphoning ofkerosene is supported by a PDS scam on

the sidelines. PDS kerosene which shouldsell for Rs. 10 a litre fetches Rs. 40 a litrein the black market.

“No one in Lakhimpur gets more thantwo litres of kerosene a month eventhough the official entitlement is fivelitres.” The district supplies inspector hasalleged involvement in the racket,

Predictably, Manjunath’s drive wasacquiring an avalanche of support fromvillagers across Lakhimpur Kheri. TheIOC officer was alerted by a local youth,one of the many whom he had organizedas informants.

In fact, it was a young customer whoblew the whistle on the L D ServiceStation. Manjunath had cultivated cordialrelations with the locals in order todevelop a network of informants. Andthe youth had called on Manjunath’s cellphone to alert him about the L D ServiceStation.

Said Devendra Prasad Misra in Udehravillage: “Everyone cheats us. We don’teven get our due of two liters a month.Don’t you know about that IOC officerManjunath? The one who was murderedbecause he cracked down on petrolpumps? We have heard he refused a Rs.4.50 lakh bribe from the petrolmafia”(The Indian Express).

The Plot to Kill

“Manjunath was staying at a hotel inGola on November 19. Around 4 pm, hewent to check the samples at the Mittal

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Petrol Pump and started watching theIndia-South Africa cricket match on a TVset there. He saw the entire first sessiontill almost 6 pm. Unfortunately he forgotthe measuring instrument on MonuMittal’s table and left the Pump. Monuknew that Manju would definitely comeback to get it. He decided to kill himthen”.

Monu locked the instrument in hisalmirah. “He knew that Manjunathwould have to meet him to get theinstrument back. He alerted his otheraccomplice to be ready for his phone call.Monu waited till 8 pm but Manjunath didnot turn up. Monu then left the pump.”However, on his way back home, hecalled Manjunath on his cell phone andreminded him that he had forgotten hismeasuring instrument.

The trick worked. Manjunath turned upat the pump around 9.30 pm and theemployees told him that the keys of thealmirah were with Monu. One of theemployees called Monu and he arrivedin 10 minutes. “But Monu didn’t comealone. He was accompanied by DeveshAgnihotri, a criminal with 10 casesagainst his name. They talked toManjunath and even treated him to tea.Then, around 10 pm, they executed theplan.”

As Monu and Agnihotri accompaniedManjunath back to his car, one of hisemployees rushed to turn off thegenerator. “We have checked thegenerator and it has a problem.

Whenever it is switched off, it givesout a sequence of loud bursting soundsfor some 5-8 seconds. So as thegenerator started booming and thelights went off , both Monu andAgnihotri pulled out their guns andshot Manjunath. Then they pushed himinto the rear seat and asked two oftheir employees to dispose of thebody.” “The accused even threwManjunath’s spectacles into a nullahand planned to throw his body in theKatna River—the river f lows intoBarabanki district. They had drivenalmost 50 km before being caught.”

He was killed for doing his duty for IOCand Satyendra Dubey—the IIT engineerand NHAI official was killed in Gayaafter he complained of corruption on theGolden Quadrilateral.

Reaction from Family and Friends

Manjunath, the eldest of three children,had told his father about the risks, andthe father had advised him “to let go ofsome things” because he was all alone.

“He was killed for doing his duty,” saida tearful Shanmugham after thecremation. “He told me many times thathe was working in an area with manymafia gangs and that anything couldhappen to him. I never thought it couldhappen,” he said, fighting to regain hiscomposure. “He used to tell me about thelack of proper controlling systems andofficial support when it came to stoppingadulteration and booking wrongdoers in



UP. He said it is a lawless world and forsurvival, one has to keep mum even ifthere are irregularities,” saidShanmugham. “He wanted the dealers tofollow all norms, but his father used totell him ‘you are alone, don’t get workedup, let some things go’. He was aresponsible manager and committed tohis company and its sales. He loved thechallenge.”

Manjunath’s death has shocked andoutraged all those who knew him. “Hewas such a free spirit. He had noenemies and yet he suffered such aheinous fate. Just because he was doinghis duty,” his IIM classmate Sunit Saprawrote in an e-mail to The IndianExpress. “The case is no less than thekill ing of Satyendra Dubey. Thecriminals must be brought to justice andManju’s sacrifice must be given therespect it deserves.”

“He would always keep his mind on thesilver lining of a dark cloud, alwayslaughing and joking around. You foughtthe odds real hard. Goodbye Machan,”wrote Karthik Parthasarathy, IIM-LBatch of 2003. “He sang from the bottomof his heart, and with a catchingenthusiasm. He is one of those singerswho made the listeners experience thesong.

A Great relief

After an anxious wait for theShanmugham family, Monday turnedinto a great relief when the news trickled

from Uttar Pradesh that the main accusedin the murder was sentenced to death.”Ithas been a long and anxious day for uswaiting to know the quantum ofsentence- We are relieved to learn thatat least the main accused has been givendeath sentence and the other accused are,condemned to jail for life,”(Manjunath’sfather M. Shanmugham told IANS onphone from Kolar Gold Fields (KGF),about 100 km from here).

Expressing satisfaction at the pace thecase was taken up with and justicedelivered, Manjunath’s father said hisfamily compares Lakhimpur KheriDistrict Judge S.M.A. Abidi to god forconducting a fair trial, finding theaccused guilty and convicting them onmerit.

“Justice Abidi is like god for us. He hasdone a great justice to my brave sonManju. Though all the accused deserveddeath for the heinous crime, he ensuredthe main killer (Pawan Kumar Mittal) didnot escape capital punishment. It is a greatrelief the case was handled in a recordtime and the judgment delivered soonafter conviction.”

Lauding Manju’s friends, especially hisfriends from the Indian Institute ofManagement (IIM), Lucknow, the districtpolice, public prosecutor and thecompany’s counsel (D.P. Singh) for theirmoral and financial support in fightingthe case, Manjunath’s family was readyto fight the accused in the high court oreven in the Supreme Court.

137Patra, Beyond Whistleblowing: A ...

Table: 2- Sequence of Events Relating to Death of Manjunath

November 22, 2005 Samples fail test, pump owners kill fuel inspector

An Indian Oil Corporation sales manager was shot dead last Saturday by theowners of an Uttar Pradesh petrol pump whose operations were suspendedfor a month in September after its fuel samples failed quality tests.

November 24, 2005 ‘My son told me about the mafia, he was killed for doing his duty for IOC’

Adulterated Fuel Father of IIM graduate killed for shutting down petrolpump says he knew of danger; batchmates say can’t let him vanish intothe night

November 25, 2005 Manjunath had evidence to close pump down, owner’s son called him tohis murder

IOC Dealer whose son prime suspect in murder had been fined Rs 75,000,first time in 29 years

Pall of gloom at IIM-L

Had it not been for prior commitments made to corporate houses, theIndian Institute of Management-Lucknow would have cancelled its annualfestival, INDEX ’05, to mourn the death of its alumnus, S Manjunath.

Manjunath killing: angry IOC demands action against mafia

Anger and frustration were the two overriding emotions at the meetingof 100-odd Indian Oil Corporation officials held today, in the wake of themurder of S Manjunath — their area sales manager in Lakhimpur Kheridistrict.

‘Where do we see such courage’

We have received an outpouring of letters from readers in India andoverseas, many of them former classmates of the slain Manjunath

This system of ours

Wanted: bright, young, honest Indians willing to die in vain

“We will fight it out till the last to ensureManju’s soul rests in peace,” saidShanmugham, an employee of the state-owned Bharat Earth Movers Ltd (BEML)at KGF.

Giving full credit to the ManjunathMemorial Trust, set up by his lifelongfriends, batch mates and well wishers.

Shanmugham hoped the sacrifice his sonmade and the judgment in his murder casewould ensure honesty, integrity and fightagainst corruption carried on as a crusadeto cleanse the system and the countryfrom such evils ( March 26 IANS). Thesequence of events relating to death ofManjunath is given in Table-2.


November 26, 2005 Murder most foul was also murder most plannedManjunath They called him back to collect measuring instrument, maskedsound of gunshots with generator‘The last such sacrifice’Letters continue to come in to The Indian Express, condemning Manjunath’smurder, commiserating with his bereaved family, and calling for justice

November 27, 2005 ‘My poor sales officers are helpless...it’s very dangerous to raid’Three months before IIM graduate Manjunath was hired by IOC as salesofficer, his chairman had told a Parliamentary committee:State wakes up, orders raids on petrol pumpsDistrict officials to crack down on all petrol pumps; police searchManjunath’s house in Kheri, take his computer, official files

November 28, 2005 Local youth helped Manjunath seal third violating pump in LakhimpurKheriL D Service Station owner also sole kerosene supplier for 132 villagesIOC shuts down Mittal pumps in LakhimpurThe Indian Oil Corporation has terminated the retail dealerships of thetwo pumps owned by the Mittals in Lakhimpur Kheri. The fuel tankmachines at both pumps are in the process of being dismantled.Monu’s phone records evidence enough: PoliceThe Lakhimpur Kheri police will move court to seek remand of MonuMittal, main accused in the murder of Indian Oil Corporation official SManjunath — a graduate from IIM-Lucknow.

November 29, 2005 Manjunath has one debt after death: his IIM MBA loanWhile the oil mafia tried to entice him with bribes to turn a blind eye tofuel adulteration, murdered IOC sales manager S Manjunath refused towaver in the line of duty, despite his own financial constraints.

November, 30, 2005 To loosen cartel hold, Manjunath okayed seven new pumps in LakhimpurKheriThe young sales manager might have thought he was killing two birdswith one stone. When S Manjunath, the murdered IOC executive,recommended increasing the number of petrol pumps in LakhimpurKheri district, he would not only have addressed the sliding diesel salesfigures but also loosened the grip of the cartel that controlled oil businessin the region.PMO steps in, Govt for 2 kerosene ratesProposal: Rs 10/l for BPL, Rs 20/l for rest to reduce price gap with diesel,lower ‘adulteration’ incentive

December 1, 2005 We can only direct states, says PatilRajya Sabha debate: Members demand security for PSU officials on dutyOne life, two prices


Distorted pricing is the lifeblood of economic crime. Even a tragic deathcan’t drive this home

December 2, 2005 IOC, PNB to pay off Manjunath’s MBA debt

Consolation, if any, for murdered IOC officer S Manjunath’s family cameyesterday when Indian Oil Corporation chairman S Behuria handed overa cheque of Rs 26 lakh to his father M Shanmugham.

December 09, 2005 Manjunath’s death reaches the Prime Minister’s desk

Murder Singh calls special meeting to discuss pricing, security; NSA willattend, Chief Secys will meet today

December 10, 2005 States, Centre begin talks on how to check doctored diesel

Manjunath All states agree on more security, many oppose 2 kerosenerates, say make income criterion

December 12, 2005 Role of Cong leader’s son alleged in petrol racket

A young IAS officer caught two oil tankers allegedly involved in oiladulteration in Haridwar. A son of a Congress party leader holdingministerial status is alleged to be involved in the racket.

December 16, 2005 Five days before Manjunath’s murder, Govt issued an SOS

Just five days before IIM graduate S Manjunath was shot dead for blowingthe whistle on kerosene adulteration in a petrol pump, the PetroleumMinistry had ordered oil companies, including Manjunath’s Indian OilCorporation, to test a series of stringent measures meant to curbadulteration.

December 17, 2005 Manjunath murder: ‘pricing is key’

Oil Either 2 kerosene rates or give cash/coupons to BPL customers: Aiyar

January 1, 2006 At Mumbai marathon, he runs for friend Manjunath

IIM batchmate and football team mate Dharmendra comes all the wayfrom Bangalore

February 16, 2006 Manjunath murder: Forensic tests confirm police stand

It’s official now: S Manjunath, the Indian Oil Corporation LakhimpurKheri sales manager who died on the job last year, was murdered.

February 22, 2006 Chargesheet against 8 in Manjunath murder case

We feel the case would reach its logical end, say cops

March 27, 2007 Manjunath’s father relieved, compares judge with God

Source: The Indian Express


4.0 BEYOND WHISTLEBLOWING

Satyendra Dubey – who had reportedthe wrong doing to the PMO in theNational Highway Authority of Indiaproject, is still alive. Law Ministry iscoming up with whistleblowerprotection act (see Appendix-2).SManjunath will continue to live for everfor cleaning up the mess. Like Socratesthese two young martyrs were guidedby their wisdom and have the shownhighest form of professionalism,commitment to ethics and dedication forthe common good. They were notmerely whistleblowers, but muchbeyond .

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The Indian Express, 12 December 2005The Indian Express, 16 December 2005The Indian Express, 16 February 2006The Indian Express, 16 January 2006The Indian Express, 17 December 2005The Indian Express, 22 February 2006The Indian Express, 22 November 2005The Indian Express, 24 November 2005The Indian Express, 25 November 2005The Indian Express, 26 November 2005


The Indian Express, 27 November 2005The Indian Express, 28 November 2005The Indian Express, 29November 2005The Indian Express, 30 November 2005

Valasquez, Manuel, (2006) Business Ethics:Concept and Cases, Pearson Education, NewDelhi.

Whitbeck, C. (1998), Ethics in EngineeringPractice and Research, CambridgeUniversity Press, Cambridge.


APPENDIX 1Criteria For Justifiable Whistleblowing

According to Richard T De George (2006) there are three conditions thatmust hold for whistle-blowing to be morally permissible, and twoadditional conditions that must hold for it to be morally obligatory. Thethree conditions that must hold for it to be morally permissible are:

The firm through its product or policy will do serious and considerableharm to the public, whether in the person of the user of its product, aninnocent bystander, or the general public. Once an employee identifies aserious threat to the user of a product or to the general public, he or sheshould report it to his or her immediate superior and make his or hermoral concern known. Unless he or she does so, the act of Whistleblowing is not justifiable.

The two additional conditions for Whistle blowing to be morallyobligatory: Whistleblower must have accessible documented evidencethat would convince a reasonable, impartial observer that one’s view ofthe situation is correct, and that the company’s product or practice possesa serious and likely danger to the public or to the user of the product.

The employee must have good reason to believe that by going public thenecessary changes will be brought about. The chance of being successfulmust be worth the risk one takes and danger to which one is exposed.


APPENDIX 2

Government Action; Protecting future Dubeys

The full text of the government resolution, issued on April 21, empowering theCentral Vigilance Commission to act on the complaints of whistle-blowers andto protect them:

(Ministry of Personnel, Public Grievances and Pensions (Department ofPersonnel and Training Resolution New Delhi, the 21st April, 2004).

No.371/12/2002-AVD-III: Whereas while hearing Writ Petition © No.539/2003 regarding the murder of Shri Satyendra Dubey, the Supreme Courtdesired that pending enactment of a suitable legislation, suitable machineryshould be put in place for acting on complaints from “whistle-blowers”.

The Public Interest Disclosure and Protection of Informers’ Bill, 2002, draftedby the Law Commission is under examination.

Now, therefore, the Central Government hereby resolves as under:

1. The Central Vigilance Commission (CVC) is hereby authorized as thedesignated agency to receive written complaints or disclosures on anyallegation of corruption or of misuse of office by any employee of theCentral Government or of any corporation established by or under anyCentral Act, government companies, societies or local authorities ownedor controlled by the Central Government. The disclosure or complaintshall contain as full particulars as possible and shall be accompanied bysupporting documents or other material.

2. The designated agency may, if it deems fit call for further informationor particulars from the persons making the disclosure. If the complaintis anonymous, the designated agency shall not take any action in thematter.

3. Notwithstanding anything contained in the Official Secrets Act, 1923,any public servant other than those referred to in clauses (a) to (d) ofArticle 33 of the Constitution, or any other person including any non-governmental organisation, may make a written disclosure to thedesignated agency.


4. If the complaint is accompanied by particulars of the person making thecomplaint, the designated agency shall take the following steps: Thedesignated agency will ascertain from the complainant whether he wasthe person who made the complaint or not.

5. The identity of the complainant will not be revealed unless the complainanthimself has made the details of the complaint either public or disclosed hisidentity to any other office or authority.

6. After concealing the identity of the complainant, the designated agencyshall make, in the first instance, discreet inquiries to ascertain if there isany basis of proceeding further with the complaint. For this purpose, thedesignated agency shall devise an appropriate machinery.

7. Either as a result of the discreet inquiry, or on the basis of the complaintitself without any inquiry, if the designated agency is of the opinion thatthe matter requires to be investigated further, the designated agencyshall officially seek comments or explanations from the head of thedepartment of the concerned organisation or office. While doing so, thedesignated agency shall not disclose the identity of the informant andalso shall request the concerned head of the organisation to keep theidentity of the informant secret, if for any reason, the concerned headcomes to know the identity.

8. After obtaining the response of the concerned organisation, if thedesignated agency is of the opinion that the investigations reveal eithermisuse of office or substantiate allegations of corruption, thedesignated agency shall recommend appropriate action to theconcerned government department or organisation. These shall, interalia, include following:

a) Appropriate proceedings to be initiated against the concerned governmentservant.

b) Appropriate administrative steps for redressing the loss caused to theGovernment as a result of the corrupt act or misuse of office, as the casemay be.

145

c) Recommend to the appropriate authority/agency initiation of criminalproceedings in suitable cases, if warranted by the facts and circumstancesof the case.

d) Recommend taking of corrective measures to prevent recurrence of suchevents in future.

9. For the purpose of making discreet inquiry or obtaining information fromthe concerned organization, the designated agency shall be authorized tocall upon the CBI or the police authorities, as considered necessary, torender all assistance to complete the investigation pursuant to the complaintreceived.

10. If any person is aggrieved by any action on the ground, that he is beingvictimized due to the fact that he had filed a complaint or disclosure, hemay file an application before the designated agency seeking redress inthe matter, who shall take such action, as deemed fit. The designatedagency may give suitable directions to the concerned public servant or thepublic authority as the case may be.

11. Either on the application or the complainant, or on the basis of theinformation gathered, if the designated agency is of the opinion thateither the complainant or the witnesses need protection, the designatedagency shall issue appropriate directions to the concerned governmentauthorities.

12. The machinery evolved herein shall be in addition to the existingmechanisms in place. However, secrecy of identity shall be observed,only if the complaint is received under this machinery.

13. In case the designated agency finds the complaint to be motivated orvexatious, the designated agency shall be at liberty to take appropriatesteps.

14. The designated agency shall not entertain or inquire into any disclosure:

(a) In respect of which a formal and public inquiry has been ordered underthe Public Servants Inquiries Act, 1850; or



(b) In respect of a matter which has been referred for inquiry under theCommissions of Inquiry Act, 1952.

15. In the event of the identity of the informant being disclosed in spite of thedesignated agency’s directions to the country, the designated agency isauthorized to initiate appropriate action as per extant regulations againstthe person or agency making such disclosure.

16. The machinery created herein shall operate till Parliament passes a law onthe subject.

Private Equity — Gaining Momentum*

Naliniprava Tripathy1

Abstract

Indian financial markets have progressively become more attuned to the international market forces. Atpresent both foreign and domestic companies look to expand into the emerging markets in Asia andglobally integrate a business plan across a broad spectrum of cultures, languages, markets and laws. Inthis process the private equity firms and private equity funds have played key roles in providing accessto funding, resources, operational expertise, expansion, etc. Private equity funds are the pools of capitalinvested by private equity firms. In the present environment of competition many companies need helpof PE firms to increase their market competence and value of brand for strengthening market ability. PEfirms usually have long experience and they are able to help immensely with the business strategy,corporate governance and organizational development by generally bringing in best practices. Keepingthese in view, this paper highlights major role played by the PE firms for improving the efficiency ofcompanies in the business world of India. Secondly, this paper also throws some light on how the PEfirms are facing challenges in India in form of bureaucracy norms, regulatory limits in certain sectors,poor infrastructure, etc. This paper concludes that there is a high potential in terms of more mature andconvenient environment for private equity in India.

* Received August 3, 2007; Revised February 23, 20081. Associate Professor, Indian Institute of Management, Indore, email: [email protected]

1.0 INTRODUCTION

The robust financial markets of India arenow experiencing a strong growth,encouraged by domestic andinternational investments. At present,sophisticated investors are looking outfor more localized investment andalliance opportunities for new targetsand markets for investing in innovativeasset classes. They believe thatpartnering with the right team can

improve company’s presence andcompetitive edge by providing insightinto the local decision-making process,overcoming cultural barriers,interpreting laws and, mostimportantly, maintaining importantrelationships that will add value to acompany’s expansion strategy. Anotherbenefit of partnering with locals is thatthey will know how to approach and talkto promising entrepreneurs, who might

Perspective



be reluctant to bring in outside capitaland foreign advice to enable growth oftheir young company. One of them isprivate equity. Private equity hasarrived as a major component of thealternative investment universe and isnow broadly accepted as an establishedasset class within many institutionalportfolios. Private equity investment istypically a transformational, value-added, active investment strategy.Private equity funds typically controlmanagement of the companies in whichthey invest, and often bring in newmanagement teams that focus on makingthe company more valuable. Privateequity executives face increasingprofessional and personal liability forthe performance of their funds andPortfolio Company.

2.0 WHAT IS PRIVATE EQUITY?

Private equity is a broad term thatrefers to any type of equity where theequity is not freely tradeable on thepublic market. It refers to the mannerin which the funds have been raised,namely on the private markets, as

opposed to the public markets. It is themode of financing private companiesby third parties,who are high networthinvestors seeking higher rates ofreturn. Passive institutional investorsmay invest in private equity funds,which are in turn used by privateequity firms for investment in targetcompanies.Categories of private equityinvestment include leveraged buyout,venture capital, growth capital, angelinvesting, mezzanine capital andothers.

Private Equity falls into two broadgroups: venture capital and other privateequity. Private equity investing is oftendivided into the categories described inFig-1. Private equity is the universe ofall venture and buyout investing,whether such investments are madethrough funds, funds of funds orsecondary investments. Most otherprivate equity is invested in more matureor later-stage companies. Private equityis generally part of an LP’s(LimitedPartners ) overall investment strategy thatmay include real estate, bonds, andpublicly traded company stock.

Fig-1

Source: http://venturechoice.com/articles/why_n_how_to_inv_in_priv_equity.htm

http://venturechoice.com/articles/why_n_how_to_inv_in_priv_equity.htm

149Tripathy, Private Equity Gaining ...

3.0 IS PRIVATE EQUITY A SENSIBLE INVEST-MENT FOR THE AVERAGE INVESTOR?

Private equity is a favoured asset classfor professional managers because it hashistorically produced superior returns.Private-equity deals are making investorsrich. The Economist reported recently thatduring 1980 – 2001 the top quartile ofprivate-equity funds produced an annualrate of return of 23 percent. Accordingto Thomson Financial, buyout fundsaveraged gains of 25.5 percent for theyear ended March 31, 2006 and 17.6percent for the past three years. (FortuneMagazine, October 24, 2006). Over thepast ten years, the score is 11.4 percent ayear vs. 6.6 percent; over the past 20years, 14.2 percent vs. 9.8 percent(Fortune Magazine, November 27, 2006).Its investment risk is spreading over longtime periods, in multiple industry sectors,and in a large number of investments.Professional money managers know howto do so, that is why private equity has aprominent place in large investmentportfolios, even in conservative ones likethose of pension funds.

4.0 HOW PRIVATE EQUITY GROUPS WORK?

In many ways, private equity groupsoperate just like house buyers. They arelooking for bargains. They usually stumpup a bit of money, a deposit; up front,and then rely on the bank to lend themthe rest. They are looking for a quick,profitable sale, usually within three toseven years. And they do things inrelative privacy, often de-listing theiracquisitions if they were quoted on any

stock market. This means they can maketough or controversial decisions withouthaving considered the shareholderswithout releasing sensitive information.Hence they are accountable only to smallgroups of private investors and lenders,rather than to stock market investors andcompany employees. They do not evenrelease information to outside peopleand journalists to interfere and makingenquiries into their personal businessaffairs.

5.0 INTERNATIONAL SCENARIO

In the U.S. many private equity firmsrecently have been gobbling up retailbusinesses, which usually perform wellin market downturns. After a historic forprivate equity professionals in year 2006,there are no signs that 2007 will be anydifferent. The first quarter’s $44 billionmark signals a 67% increase from the 46funds that raised $26.6 billion in the firstquarter of 2006.The Private EquityAnalyst study found that on top of thefirst quarter another 400 other funds aretrying to raise another $130 billion. Theamount of money private-equity firmshave spent buying companies totals justover $900 billion in 2006 according tofinancial data provider Dealogic.

The Dow Jones Private Equity Analystrecently reported that U.S. private equityshops have raised $44.3 billion out of 68funds in the first quarter of 2007. In 2007,industry magazine Private EquityInternational launched a ranking of thelargest 50 private equity firms in theworld called the PEI 50. The Carlyle


Group ranked at the top, followed byKKR and then Goldman Sachs. The PEI50 found that the largest 50 firms in theworld had raised $551 billion over fiveyears. The top 10 constituent firms in PEI50’s (Private Equity International) 2007rankings are shown in Table 1.

On February 07, 2007, the global Privateequity market observed the biggest everdeal as Blackstone, a (PE) firm, tookover the control of Equity off iceproperties trust, the largest Real estateInvestment Trust (REIT) in USA for$38.9bn, beating the Vornado RealtyTrust. The numbers of such high profiledeals are ever-rising, thus adding to theindustry’s prestige. The Table-2 depicts the top 10 deals of

all-time

Table-1: PEI 50’s (Private EquityInternational)

1. The Carlyle Group2 Kohlberg Kravis Roberts3 Goldman Sachs Principal

Investment Area4 The Blackstone Group5 TPG6 Permira7 Apax Partners8 Bain Capital9 Providence Equity Partners10 CVC Capital Partners

Source: www.privateequityinternational.com

Table-2: Top 10 deals of All-timeCompany Value ($bn) Acquirer Year

Equity office Properties trust 38.90 Blackstone 2007

Hospital Corp.Of America 32.7 Bain, KKR. Merrill Lynch 2006

RJR Nabisco 31.1 KKR 1989

Harrah’s entertainment 27.4 Apolo, Texas pacific 2006

Clear channel communications 25.7 Caryle, Riverstone, 2006Goldman sahs

Kinder Morgan 21.6 Black stone, Carlye,permira, 2006Texas pacific

Free scale Semiconductor 17.6 Cerberus 2006

Albertson’s 17.4 Caryle, Clayton Bubillier 2006and Rice, Merrill Lynch

Hertz 15 Apax, Blackstone,KKR, 2005Permira,Providence

TDC 13.9 2005

SOURCE: http://money.cnn.com/magazines/fortune/fortune_archive/2007

http://www.privateequityinternational.com

http://money.cnn.com/magazines/fortune/fortune_archive/2007


6.0 INDIAN SCENARIO

Global PE firms are exploringopportunities of investment in India dueto expanding consumer market in India,reforms and slowdown of US market.The last three years have seenunprecedented private equity inflowsinto India. Mostly PE firms are improvingtheir presence in the real estate and alsoin infrastructure and telecom business.India Inc. has witnessed strategic M&Adeals worth of $24.06 billion in the first11 months of 2006, both within thecountry as well as overseas. Apart from

this, PE investments to the tune of $6.62billion have taken place till November2006. Out of the total 299 deals of theyear 2006, 26 deals were worth morethan $50 million compared to just ninesuch deals of its previous year. Privateequity deals rose 230% to $7.46 billionin 2006 in India, compared with $2.26billion in 2005. M&As involving Indiancompanies, in the same period, rose by150% from $20 billion in 2005 to $50billion. Table-3 provides the dataregarding the top PE investments inIndian market.

Table-3: Top PE investments (July-Sept 2006) ($ mn)

Company Amount Investors

Quattro BPO Solutions 100 Olympus Capital

Centurion bank of Punjab 90.7 Bank Muscat,ICICI Venture

UTI bank 80 Chrys capital

Aryan Coal Beneficiations 66 Warburg Pincus

Gujarat Pipavav port 65.2 Others

Source: The economics Times, October11, 2006

Today, there are more than 150 privateequity players in the local ring and all ofthem have carted in corpulent corpuses.They need to invest fast and they needthe people to help them do it. Privateequity firms have made lucrative returnsfrom early bets on companies. TheBusiness Process Outsourcing (BPO)industry, which grew by 37 per cent to$6.3 billion in FY06 and touched $8 - 8.5billion by the end of FY07, has actuallybeen a runaway success. And now, lured

by the massive opportunity and highreturns, private equity (PE) is forayinginto Indian real estate in a big way. While2006 saw private equity investmentsworth $500 million (Rs 2,080 crore), thefirst six months of 2007 have already seendeals worth about $755 million (Rs 3,145crore) announced.

Warburg Pincus, the largest privateequity investor in India,has investedin Amtec Auto, Kotak mahindra,Moser


Baer,max India and NicholasPiramal.Nearly $135 billion of privateequity was invested globally in 2005.Buyouts by private equity playersaccounted for 8% of the total M&Aactivity in India during the year2007.Finance sector has been thebiggest recipient and has attracted $2bill ion with 11 deals , followed byconstruction $418 million with 9 deals,textiles $309 million in 7 deals. Today,the private equity funds are interestedin different sectors in economy and areholding diverse types of companies intheir portfolio. PE funds are showinggreater interest in Indian companies inthe major cities which is depicted inTable- 4.

Table-4:Top Cities attracting PEInvestments in 2006.

City Number Valueof Deals (US$M)

Mumbai 69 1,780

Delhi/NCR* 41 395

Bangalore 40 1,525

Chennai 22 354

Hyderabad 17 492

Pune 10 1,114

*National Capital Region

Source: TSJ Venture Intelligence India October2007

With regard to growth in PE/VC in Indiaduring 2000 – 07, the data relating toseries 1 and series 2 are given inFigure -1.

Growth of PE/VC in India 2000 - 1H2007 (US$ millions)

1160 937591 470

16502200

7500

5648280

11078

5671

146

299

161

0

1000

2000

3000

4000

5000

6000

7000

8000

0

50

100

150

200

250

300

350

Series2 Series1

Fig-1 Growth of PE/VC In India 2000-1H2007(US$ Millions)

Source: TSJ Venture Intelligence IndiaOctober 2007

PE deals are rising in India in varioussectors, ie., Information technology andIT- enabled services, banking, financialservices, insurance, engineering andconstruction, real estate and telecomamong other sectors. Financial servicessector continued to score as a favouritesector for PE firms in 2007 containing37percent followed by 16 percent by ITand ITES, 14 percent by shipping andlogistics as shown in Fig-2.

16%

7%

2%3%

37%

2%

7%

14%

5%2%1% 4%

Fig-2 PE Investments by Industry (First Halfof 2007)

Source: TSJ Venture Intelligence India October 2007

123456789101112


Table-5: PE Investments by Stage: 2007(First Half)

Stage of Company No. Of AmountDeals (US$M)

Early Stage 24 154

Growth Stage 25 1082

Late Stage 67 2162

PIPE (Private 34 1714investment inpublic equity)

Buyout 6 440

Others 6 47

Source: TSJ Venture Intelligence India October2007

Global private equity firms in the Indianmarket are continuously on the rise. PEinvestments have increased recently incomparison to investment in china, whichsaw investments of $2.6 billion as per

Table-6. India obtained the number twopositions only after Japan with respectto the receipts of private equity flowsaccording to Center for Asia’s privateequity research.

7.0 MAJOR GROWTH DRIVERS OF PE IN-VESTMENT IN INDIA

The performance of stock market,possibility of fast growth and maturingof the mergers and acquisitions activityhas played a key role in the developmentof private equity market in India. Thefollowing are some of the key points:

• India is rapidly turning out to be aninvestment driven economy due tosolid underpinnings for economicgrowth, democratic government, astrong education system,widespread knowledge of Englishand a deep pool of expatriatesexperienced in Western businesses.

• Annual GDP growth, averagingaround 9 % over the last three years,has made the country among thefastest developing major economiesin the world.

• Private equity deals in India is greatlyattributed to its strong corporateperformance, robust and transparentcapital markets, buoyant economy,and burgeoning middle-class.

• A rapidly growing economy with asuperior rate of Return on Equity(ROE) vis-à-vis other markets in theregion, low volatility in ROE, astrong financial system, and lowgearing are a few other reasons.

Table-6: Private Equity Inflows to Asia(USD Billion)

Destination 2005 2006 2007(July)

Japan 4.65 10.89 4.91

China 3.87 8.27 2.6

India 1.71 5.44 3.7

S o u r c e : h t t p : / / w w w . a s i a p e . c o m /?Publications:Asia_Private_Equity_Review:APER0706MY

Late-stage investments accounted for 67while PIPE (PE investments in PublicEquity or in listed companies) accountedfor 34 of the deals. Early-stageinvestments accounted for about 24 dealsduring first half of 2007 as shown inTable-5.


• One of the biggest triggers for therise of the Indian economy is the lowinterest rate regime. It has changedthe face of the Indian corporate thathave not only weathered globalcompetition, but also managed toinfluence the steep hike in fuel prices.

• IPO norms are stringent and SEBI isbringing in future reforms like IPOGrading and easier de-listing normsto make the investment climateattractive.

• India’s Sensex 30 — that country’sversion of the U.S. Dow-JonesIndustrial Index — broke through21,000 in 2007.The price-to-earningratio for India stocks is increasing,which is encouraging to foreignprivate equity firms to make theirIndia investment destination.

• India has firmly established itself asthe world’s IT super power withalmost all major softwaredevelopment companies having anIndian development centre. India isalso developing some retail financialservice businesses, which isattracting PE investments.

• The nature of entrepreneurship inIndia is different because largenumbers of Indian entrepreneurshave been able to work abroad asexpatriates in many roles. This, nodoubt, becomes manifest in the kindsof businesses they develop,particularly in informationtechnology. Again India has anadvantage in healthcare including

biotech, pharmaceuticals,telemedicine, banking, engineeringand construction which haveattracted a significant chunk of PEinvestments.

• In India, many listed companies actmore like privately held firmsbecause they are under tight control,usually by founders.

• India made an all-out push topromote itself as a business-friendlyenvironment for investment. Thegovernment has also decided to liftthe limit on foreign directinvestment for the development ofairports, mining for diamonds andother precious stones, and powertrading which leads to growth of PEinvestments in India.

• Main economic forces, which are fuelfor attractive private equity growthand investment opportunities inIndia, are combination of a growingIndian consumer class and anevolving set of differentiated Indianskills.

• The first generation of private equityplayers has significant success in lastseveral years.

• There are strong PE funds in Indialike HDFC PE, ICICI PE, KotakMahindra PE, UTI Venture, GVFLLtd etc. which provide genuineliquidity option.

• Competition in the market and thestrategy to improve cost effectivenesshas generated the feeling of security

155

and many companies seek the helpof private equity investment toimprove their performance.

This changed “growth focused”mindset of Indian entrepreneurs willgive rise to continued and growingdemand for PE in future.

8.0 PROBLEMS OF PE INVESTMENTS

Although India is an integral part of theglobal economic chain, its plan is notalways matched by its ability toimplement changes. Most of privateequity investors are now seriouslyconsidering China, because it hasprovided spectacular private-equityreturns in recent years (Source:Knowledge Wharton, Oct, 2006). Furthercheap labour and foreign directinvestment have made China the world’smanufacturing powerhouse. Chinesecompanies with good management aregrowing at a rate of 30% internally and30% globally and there are at least 3million privately owned companies inChina. Out of these China believes that300,000 would qualify to list onNASDAQ or NYSE. (Source: KnowledgeWharton, Oct 2006) Apart from this,there are more Internet users andengineers in China than any othercountry. China also has a strongentrepreneurial culture, thus China is adirect competitor of India. Most of theprivate equity investors draw acomparison across both the countries.

Secondly,there is no listed public marketavailable for the vast majority of privateequity investments in india.

Thirdly, the Indian public markets lackliquidity and many Indian companies arethinly traded in markets which arecontrolled by powerful local brokerages.

Fourthly, Mid-cap funds are oftenconstrained by several factors i.e. ininvestment circles. The equity purchasedby the fund is not freely tradable if theportfolio of the company is not listed inthe stock exchange. Liquidity of thestocks becomes a major issue.

Fifthly, India’s economy is largely beingbuilt by closely held family businesses,with minority private equity investorshaving less scope to hire and fire.

Lastly, The Indian market is already oneof the expensive markets in Asia today.This is resulting in high cost deals, whichmay in long run affect the return oninvestment of private equity companies.

9.0 EMERGING CHALLENGES

Indian corporate is by and large familyowned business. Hence it is animperative need for Indian business tounlock the value of their business andexpand for global competition. As thereare multiplayer authorities like RBI,SEBI, Finance Ministry, ForeignInvestment Board, Department ofIndustrial Policy and Promotion, it isadvisable to have separate regulatoryauthority for smooth growth of PE spacefor the development of the economy. Itis needed to target the beneficiaries of agrowing consumer class, forge key localrelationships, leverage global networks,and plot a flexible course to exit for the

Tripathy, Private Equity Gaining ...


growth of PE investments in India. Vastmajority of private equity investmentsin India involve minority control, somultinational private equity funds shouldleverage global networks to maximizetheir ‘network effect’ and influencemanagement teams. Apart from this, PEfirms are facing a few challenges in theform of bureaucracy norms; regulatorylimits in certain sectors, poorinfrastructure, etc.

10. CONCLUSION

There is a good potential for PE firms inIndia as a result of sustained economicgrowth drivers across sectors. Theeconomy’s size from $800 billion in 2005is estimated to increase to $5040 billionin 2020 (source: Evalueserve). Inaddition, Indian companies aresuccessfully integrating non-Indianentities and M&A are likely to grow at arapid pace. There is a huge demand-supply gap and there is increasingdemand for investment in infrastructure.In the near future PE funds will havedirect or indirect funding in theinfrastructure sector. India’s conducive-environment are the basis for privateequity to grow and this in turn is likelyto lead to a virtuous cycle of furtherimprovements in the economic andinfrastructure environment.

REFERENCE

Abe de Ramos “The Answer is Private” CFOAsia, February 2005

Business Development | Sub-SaharanAfricaOctober 05, 2006 - 09:00,

Deloitte, “Central Europe Private EquityConfidence Survey” (2007), July.

Evalueserve Research Publication, 2006.

Fortune Magazine, November 27, 2006

Fortune Magazine, October 24 2006

Heel, Joachim Kehoe, Conor, “Why SomePrivate Equity Firms do Better than others,”Mc Kinsey Quarterly, 2005, Issue 1.

http://allafrica.com

http://knowledge.warton.upenn.edu

http://money.cnn.com/magazines/fortune/fortune_archive/2006/11/27

http://money.cnn.com/magazines/fortune/fortune_archive/2007

http://n.wikipedia.org

h t t p : / / v e n t u r e c h o i c e . c o m / a r t i c l e s /why_n_how_to_inv_in_priv_equity.htm

http://www.altassets.net

h t t p : / / w w w . a s i a p e . c o m ?P u bl i ca t i o n s : A s i a _ P r i v a t e _ E q u i t y _Review:APER0706MY

http://www.illinoisvc.org

http://www.isb.edu

Just IN PRINT, vol. No.1, Issue no.3, October 1-15, 2007

Knowledge Wharton, Oct 2006

Price water house Coopers, November, 2004,“European Private Equity Tax Survey,”.

Private Equity: Capitalism’s New Kings, TheEconomist, November 25, 2004

TSJ Venture Intelligence India, October 2007.

www.incrementaladvantage.com

www.indiavca.org

www.privateequityinternational.com

www.ventureintelligence.in

http://allafrica.com

http://knowledge.warton.upenn.edu

http://money.cnn.com/magazines/fortune/

http://money.cnn.com/magazines/fortune/

http://n.wikipedia.org

http://venturechoice.com/articles/

http://www.altassets.net

http://www.illinoisvc.org

http://www.isb.edu

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http://www.indiavca.org

http://www.privateequityinternational.com

http://www.ventureintelligence.in

Fabindia Overseas Private Limited*

B. Mohanty1 & Rajeev Roy2

* Received January 29, 2008; Revised March 3, 2008; Both authors have contributed equally to thedevelopment of this case.

1. Professor, Xavier Institute of Management, Bhubaneswar, email: [email protected]. Associate Professor, Xavier Institute of Management, Bhubaneswar, email: [email protected]

1.0 INTRODUCTION

In July 2007, a TNN reporter broke thenews that a private investment fund ledby the former World Bank PresidentJames Wolfensohn, had picked up a 6%stake in Fabindia, an Indian ethnic wearcompany, for $11 million. That put thevalue of the company at around $183million or Rs.730 crore. Fabindia, in fact,was approached by a number of potentialinvestors but they chose to go with theinvestment vehicle promoted byWolfensohn because they were keen tochoose an investor who shared theirvalues.

Various reports mentioned that the fundsso raised by Fabindia would be used forfinancing the expansion plans of thecompany. The fund would also be usedto develop support structure particularlyfor providing advanced technology andtraining to the artisans, who were theprime suppliers of fabrics and other rawmaterials to the company.

2.0 ORIGIN

John Bissell who founded Fabindia wasborn in Hartford in Connecticut and was

educated at the Brooks School in NorthAndover, Massachusetts, and at Yale. Hewas introduced to India by his father,who told him stories of his time in Indiawhen he was posted there during theSecond World War.

John Bissell worked as a buyer for theAmerican departmental store, Macy’s. In1958, under a programme run by the FordFoundation, he came to India to advisethe Central Cottage IndustriesCorporation which was formed by theIndian government mainly to showcaseIndian handlooms and handicrafts. Hisrole was to advise on issues relating tomarketing Indian handicrafts.

He was new to India and he did not knowany Indian language. In spite of theseinconveniences, he travelled extensivelyover India and met several craftsmen. Hecame across a lot of skill, but he couldsee that the talented craftsmen had noidea about marketing their products andthey were in no position to access distanturban or international markets. He likedhis experiences in India and kept comingback.

Management case




His experience in the retail businessallowed him to recognize anentrepreneurial opportunity and hedecided to set up a business based onIndian crafts, particularly traditionalweaving and handlooms.

Initially his goal was to export to theUS and to other western countries.With that aim in mind, he incorporatedFabindia in 1960. The companyoperated from Bissell’s residence in theposh Golf Greens locality in New Delhi.The company was mainly intoexporting and initially its business wasconcentrated on upholstery fabrics,durries and rugs. Growth was slow forthe company and in 1965 the companymoved out of his house and into aproper office. By then, Fabindia had anannual turnover of rupees 20 lakh. Mostof this turnover was accounted for bya single buyer and a single supplier. A.S. Khera made durries and other homefurnishings in his workshop in Panipatand most of the output was purchasedby the UK based Habitat, which wasfounded by a famous interior designer,Sir Terence Conran.

On the personal front, Bissell marriedBimla Nanda, who served as the socialsecretary to the American Ambassadorin India. Soon, they had a daughter,Monsoon, and a son, William.

3.0 THE START OF RETAIL

Bissell’s business continued without muchof change in its approach till about 1976,when he opened the first Fabindia retail

outlet in the Greater Kailash market, anupmarket shopping area in South Delhi.During the early days, merchandisingwas not a planned activity. WheneverBissell saw something of interest, heprocured it for display at the store.Sometimes he would invite the craftsmenalso, to display the products and assistin the sale. This orientation of customerrelationship later became a part of theculture in the company.

Bissell’s Greater Kailash shop was asuccess and he attracted a distinct typeof visitors to his shop. But in spite ofsuch success in its direct retail business,Fabindia remained dependent onexporting and Habitat continued to betheir single major buyer. In the early80’s, Fabindia made a significantaddition to their range by adding readyto wear garments in their retailofferings. From late 70’s, Bissell hadthought of marketing readymadegarments. In an interview in 1977, hehad said, ‘’The greatest thing thathappened to our business was the movein Europe and America a few years backto the natural look - natural textures,natural fibres - and away from thingslike polyester and nylon’’. Similarly, inIndia, a distinct group was emerging likein Europe and America. Some of India’snew young politicians patronizedFabindia and were able to provideFabindia with nationwide exposure forits products. In spite of all that, theirdomestic retail business grew slowly andthey continued to focus their primaryefforts on their export business.

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4.0 BREAK-UP WITH HABITAT AND SUBSE-QUENT GROWTH

All that changed in 1992. An unexpecteddevelopment came as a shock to Bissell.Habitat, with whom a close businessrelationship had grown over the lastmore than 30 years, was acquired by alarger firm and the new entity abruptlyended the long buying arrangement withFabindia. Fabindia had not tried todevelop any strong relationships withother foreign buyers and even in the faceof such a crisis, it was unable to find anybulk buyer, who could provide analternative buying support.

One viable option was to aggressivelydevelop their domestic retail operations.But, before Bissell could come up with astrategy for his business, he suffered aparalytic stroke. This led to WilliamBissell, his son, to step in to run Fabindia.Very quickly, he was able to set Fabindiaon the path towards domestic expansion.Eighteen years after opening their firststore, Fabindia opened their second storein Delhi in 1994.

John Bissell’s bad health continued andin 1998, he succumbed to aneurism - adisease related to blood vessels. In 1999,at the age of 32, William formally tookover as the Managing Director ofFabindia. The Company’s domesticexpansion had been spectacular afterWilliam’s taking over. By 2001, Fabindiahad six stores concentrated in the metrocities. By the end of 2004, these hadincreased to 20, and the company wasseriously considering expanding its

stores into the tier-II and tier-III cities aswell as overseas. By the end of 2007Fabindia had 75 retail stores across Indiaand in addition stores in Dubai, Romeand Guangzhou in China.

5.0 PRODUCTS AND PRODUCT MIX

The products of Fabindia in the initialyears consisted of only upholstery fabricsfor export to overseas markets. Then inthe early part of 1980s readymadegarments were added to its product lineand in 2004 organic products were added.In 2006 body care products wereintroduced. Thus, the product mix ofFabindia could be divided into threebroad groups, namely Garments, HomeProducts and Organics.

Garments

Though Fabindia was the supplier ofupholstery fabrics initially, it gainedpopularity as a retailer of readymadegarments. It started with men’s wearwhich occupied a shelf in some selectstores. Gradually a whole corner wasoccupied with men’s wear, women’s wearand kid’s wear in all the stores. InOctober 2007 teen’s wear was alsolaunched which comprised camisoles inbeautiful prints, khadi salwar sets invibrant colours and kalamkari skirts. In2006 70% of the Fabindia’s revenue camefrom garments segment. Along withreadymade garments Fabindia storeshave a wide collection of accessories likedupattas in a variety of colours, weaves,fabrics and prints, scarves and stoles insilk and cotton ,neck ties and shawls.

Mohanty et.al, Fabindia Overseas Private ...


Fabindia’s garments were known fortheir ethnic look. These garments usedvegetable-based and other natural dyesand were generally in soft colours. Therewas a fine-tuned balance betweentradition and modernity. Hand blockprinted short kurtas, mix and matchchuridar kurta sets with or withoutdupattas, straight skirts in raw cotton,long crinkled skirts and white cotton orchanderi dupattas were some of the verypopular items among garments. SomeFabindia customers who used Fabindiagarments said that these were verycomfortable to wear and were finecombinations of Indian aesthetics andwestern design sensibility.

Home products

In India there were hardly any organizedoutlets for home furnishings be itupholstery, curtains, linens or homefurniture. Mostly the local carpenters dealtwith the local demand where furniturewas made as per customer specification.Similar was the case with curtains andlinens. There were local showrooms whichcatered to the need. Fabindia was one ofthe first retailers in India that offered a“complete home solution”. The Fabindiarange of home products comprisedupholstery, curtain fabric and readymadecurtains and bed linens. Home furnishingscomprised furniture made of only woodand metal, which went well with thephilosophy of Fabindia.

Fabindia was into almost all elementsof home décor and furnishing. A webstory on a website popular in the Middle

East rated Fabindia very highly, saying‘If I can tempt you away from the mallsfor just one visit – then I urge you toput Fabindia on your l ist’(www.7days.ae, 2007)

Organics

Fabindia entered into the Organicproduct market with full commitment in2004. Its product range comprised readyto eat items like dry fruits, cereals,honey, jams, pickles and coffee. In 2006it added a range of body care productsto its product mix. It included shampoos,soaps, hair oils, moisturizers, bodyscrubs, face packs, hair conditioners andskin care products.

Fabindia promoted its products, mostlythrough posters, word of mouth andevents. The youth leaders whopatronized Fabindia garments were likebrand ambassadors for Fabindia. Thenews reports also to a certain extentworked as advertisement for Fabindia.One such news item which described theorganic products is given in Box 1.

6.0 STORES AND THEIR MANAGEMENT

Most Fabindia stores are owned or leasedby Fabindia and Fabindia operated thestores. There are a few exceptions likethe joint venture in Rome and thefranchise outlet in China. The number ofFabindia stores has increased over theyears, particularly under William Bissell.From three stores in 1996 it has gone upto 75 stores in 2007. The growth can beseen from Figure-1. The growth in salesand profit are shown in Figure 2.

http://www.7days.ae

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Box 1: News Item on Fabindia Organic Products.

Saturday, March 5, 2005, The Indian Express.Fabindia has launched organic foodproducts after due certification as per the standards set by the International Federationof Organic Agriculture (IFOAM) and the National Programme for Organic Production(NPOP). This latest initiative by Fabindia, the pioneers in the field of promotion ofcottage industry on a mass scale, has made available organically grown and certifiedvarieties of rice, flour, pulses, beans, teas and coffees, sugar and jaggery, honey, cashew,groundnuts, walnuts, salts, peppers, and herbs at Fabindia stores across the country,including the Sector 9 outlet at Chandigarh. Organic food is better due to its nutritionallevels and exclusion of toxic chemicals and GMOs and contains higher levels of essentialminerals, vitamins and anti-oxidants. Worldwide, the demand for organic goods istremendous. Statistics are predicting that the global market was only $17 billion in theyear 2000, may touch the $31 billion mark by 2005 and India’s current share is only0.001 percent. In 2002, according to government statistics, from a total food productionof over 200 million tonnes, the country produced only 14,000 tonnes of organic foodproducts.According to Dilraj, manager, Fabindia, Chandigarh, “Through thecertification process, we have ensured that the customer actually gets organic food. Wehave worked to build relationships with farmers and farm cooperatives, ensuring thatour fair trade policy is maintained. From the pristine slopes of Himachal Pradesh andthe fertile valleys of Punjab, right across India to the natural forests of Coorg region inKarnataka and the plains of TamilNadu, farmers are supplying us with organic varietiesthat are ideally suited to their own local conditions. Our policy of fair trade makestraditional organic farming a viable modern economic option. We believe in givingfarmers a fair price for their produce, and in supplying the very highest quality food toour customers,” she added.

Figure 1: Growth of Stores since William tookover as MD

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Figure 2: Profit and Turnover in RupeesCrores (2002 to 2006)



Fabindia has primarily three differentkinds of stores, namely, premium stores,regular stores and concept stores. Bothpremium and regular stores carried thefull range of merchandise but in premiumstores, the proportion of high end goodsis much more than in the case of regularstores. Concept stores have been openedto test new markets. These are typicallysmall stores with very few types ofproducts in stock. Overall, Fabindia dealtin over 150,000 stock keeping units(SKU’s). However, no single store carriedall the items.

Fabindia stores focused on creating theright ambience. Many of these stores arelocated in famous historical landmarks,such as in Jeroo in Mumbai, Ilford Housein Chennai and Charles Correa’s housein Bangaluru. The stores themselves havedécor and layouts that highlight theirtraditional and natural focus. Even storepersonnel are encouraged to wear clothesthat reflect the Fabindia ethos oftraditional and natural look.

With regard to the management of stores,the managers are given a lot ofindependence in the way they operate.They are given budgets for buying andfor operational costs. Store budgets areset centrally after consultations with thestore managers. Budgets are determinedprimarily on the basis of previous year’ssales, next year’s forecasts and otherexternal factors.

Store managers interact continuouslywith merchandisers to stay abreast ofanticipated new styles and trends.

Managers regularly go for field visits toexplore new possibilities. They alsoattend regular training programmeswhere the accent is on learning modernmethods of retail management as well asremaining true to Bissell’s vision for thefirm. The ‘mystery shopper’ technique isused to keep a watch on operations instores.

7.0 DESIGN

Fabindia made its first foray towardsincorporating contemporary design in1977, when it invited the designer, RitenMazumdar, to design and make acalligraphy-based home furnishingscollection. This was a highly successfulendeavour and it encouraged thecompany to bring about new innovationsin its products. This practice of invitingdesigners has continued to this day. Veryoften, weavers and craftsmen are invitedto interact with the designers and to holddemonstrations and exhibitions inFabindia stores.

In a recent buyer-seller meet in Varanasi,representatives of Fabindia met localweavers and traders. A small display anddemonstration of local weaves and craftswas organized. The Fabindiarepresentatives gave inputs on currentmarket trends and emerging designs.They stressed on the importance ofproduct innovation and diversification.

Taking this further, Fabindia suggesteda prototype development project.Merchandisers from Fabindia indicatedtheir preferences and the local weavers’

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cooperative worked with a designer fromthe National Institute of Design (NID) todevelop samples as per Fabindia’sspecifications. The project was verysuccessful and Fabindia placed an initialorder for fabric worth Rs.24 lakh.

8.0 SUPPLY CHAIN

Fabindia’s supply chain is uniquelydesigned keeping in mind its uniquebusiness model and its ideology. Mostof its suppliers are based in rural India.For fabrics, the suppliers are mainlyweavers but there are also a few largerfabricators. Fabindia sourced its organicproducts from farmers, small scalemanufacturers and non governmentorganizations (NGO).

As many of its suppliers are uneducated,much of Fabindia’s purchasing is carriedout without written contracts. The systemoperates on trust and verbalcommitments.

On the other hand, Fabindia is far moreflexible and forgiving than many otherprocurers, especially from the West.Fabindia understands the limitations ofits weavers and small suppliers. So ifthere are some minor changes in theoriginally agreed upon design, the goodsare not rejected or returned. Theprocurement team talks with others inthe organization and tries to find someway to gainfully use the fabric.

Also a number of times the supplies aredelayed. This can play havoc withcentralized planning, especially whensales and demand patterns are heavily

dependent on the prevailing season.Getting a delayed supply of fabric, meantfor winter, could mean storing it foralmost a year, that is till the next winter.In spite of such issues, Fabindia does notturn away suppliers who deliver late.

Till recently, Fabindia used to make spotpayments for all deliveries. Now theypay within 15 days of delivery. Many oldemployees at Fabindia resented thismove and said that this is not in keepingwith the ideology of Fabindia. Williamwas able to convince them that for sucha large organization, business sensedictated a change in their establishedpractice. He reiterated that Fabindia wasa ‘for profit’ organization with socialmotives.

There are some practices in Fabindiawhich might seem like ad hoc procedures.Weavers sent their fabric in ‘thaans’. Athaan was a roll of fabric that could be20 to 25 metres long. The weaver’sstatement regarding the length wasgenerally accepted and only randomchecks were occasionally carried out tocross check the statements.

9.0 PHILOSOPHY

Fabindia believes that it does more thanjust collect and sell handicrafts. It seesitself as an enabler of a certain way oflife. By doing its business in a certainway, it is trying to demonstrate thatthe urban living model is not the onlypath to development for a society. It istrying to prove that old patterns ofliving do not have to be sacrificed for



the sake of modernization anddevelopment.

Gandhiji had a vision of an India builtaround its villages but the model ofdevelopment followed in India andelsewhere led to the growth of an urbancentric economy. Fabindia is trying topresent an alternate vision. Growth ofurban areas does not necessarily meanthe death of the village. One is notnecessarily better than the other. Bothneed each other. There exists a symbioticrelationship.

Long before corporate socialresponsibility and eco-friendly businesspractices were seriously talked about inmanagement, Fabindia practised theseconcepts. Production of organic products,bringing out the village based skillswhich were hitherto hidden from theworld, providing equitable employmentto traditional artisans and market fortheir products, enabling the ruralcraftsmen to form self sustainingcommunity based organizations andpromoting natural dyes, natural fabrics,etc, were some of its activities symbolicof its socially responsible and eco-friendly practices.

10.0 COMMUNITY-OWNED ENTERPRISE

Fabindia is trying to establish communityowned enterprises in which artisans willbe the shareholders of newly formedcompanies. The small and medium scaleartisans, who quite often run short of fundscould trade their shares to obtain funds forrunning their businesses in the times of need.

This is in line with the companyphilosophy and mission.

The company has tied up with ICICIBank’s Sandhi Craft Foundation, whichwill provide Rs.100 crores over five yearsto Artisans Micro Finance Private limited(AMFPL), which will help establish thesecommunity owned companies. Fabindiawill guarantee 8% of the 100 croresthrough a bank guarantee of 4% and anFDR for the other 4%.

The companies will be of varying sizesand 49 % of their equity will be held byAMFPL, 15% by outside investors andthe balance 36% by the local craftspersons.The companies will have access to amaximum investment of two croresrupees and they can avail a loan ofanother one crore rupees. AMFPL willalso work to establish a new tradingsystem, to enable shareholders to buy orsell their shares a few times a year.Providing a market for trading shareswill enhance the value of theirshareholding. A corporate structure willhelp artisans to raise funds for workingcapital.

AMFPL has a long term goal ofestablishing 100 community ownedenterprises. The first 20 are targeted tobe set up in the first 18 months itself.Within a few months of its launch in 2007,AMFPL had already established ninecompanies in Faridabad, Jodhpur, Jaipur,Bikaner and Bhuj.

Apart from finance, Fabindia also hopesto improve quality standards and supply

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technological know-how. A design panelwas to be set up to help artisans to createdesigns in sync with market demand.Also, heads of the companies were toundergo a course on businessadministration in a leading businessschool.

The inspiration to set up AMFPL camefrom the success of Delhi ArtisansHandicrafts Pvt. Ltd. It was establishedin the early 90’s and it currently has aturnover of Rs.10-15 crore. Artisans heldshares and the share prices had seen a25-fold increase over this period.

11.0 AWARDS AND ACCOLADES

Fabindia is very careful to maintain itsbrand and its brand has won a numberof accolades. Fabindia won the ‘BestIndian Retail Brand’ in 2005 and 2006. Ithas also won awards for ‘DesignerPromoting Indian Craft or Technique’ atthe Idea Zee Fashion Awards.

12.0 COMPETITION

Fabindia’s main competitors are theethnic wear retailers like Khadder, Wand Good Things, who are alsoexpanding at a rapid pace. W, forexample, has well over 30 exclusivestores now, in addition to being availableat some multi-brand outlets.. There isalso severe competition from the ethnicwear labels of modern Indian retailchains, such as Shoppers Stop andPantaloons. Stand alone stores like Shristiand Biba in Bangalore, Prapti in Kolkataand Sadka and Shoma in Delhi have been

doing well for a while and could pose achallenge by expanding.

New competition is expected fromoverseas retailers also. The governmenthas already permitted single brandretailers to set up shop and others likeCarrefour, Walmart and Metro havedevised ways to get into the Indianmarket. Powerful Indian business houseslike Tata, Reliance and Birla areexpanding their retail businesses.

13.0 FUTURE

From a turnover of 36 crore rupees in2000-01, Fabindia has grown to having aturnover of Rs.130 crore in 2005-06. Itregistered a CAGR of about 38% in theperiod 2002-06. Such phenomenal growthhas not come at the cost of profits. Theprofitability has been maintained at a rateof 6% for the entire period (See Figure-2). For Fabindia William Bissell has set avery ambitious target of reaching 250stores and a turnover of Rs.1000 croreby 2011.

The growth is expected to come from newstores as well as increase in sales fromexisting stores. That increase will beachieved by increased emphasis onpremium products. Also, Fabindia hasattempted to decrease its dependence onfabric based businesses by increasing itsother product lines. Currently organicfoods, body care products andhandicrafts form a significant part of itstotal sales.

Growth in locations was expected tocome from expansion in promising



overseas markets as well as a greaterpenetration of the markets in smallertowns in India. Fabindia planned toexpand significantly in tier-II and tier-IIIcities in India.

India has a flourishing retail business butmost of it is in the unorganized sector.There are estimated to be over 120 lakhstores in the country. Of this, organizedretail is only 3% but is growing at therate of 18%. This organized retail sectoris vying for a share of the spending ofIndia’s rapidly growing middle classwhose purchasing power is estimated tobe around Rs. 10 lakh crore. An estimatemade by a professional demandforecaster shows that out of the totalretail business potential, the Indianmarket for ethnic wear is likely to be aabout Rs. 9000 crore.

REFERENCES

Acharya, T. (1999) Weaving a new life. IndiaTogether, May

Bagchi, S. (2005) Be Indian, but Indian. TheTelegraph, 4 June

Bajaj, K. (2007) Fabindia’s fabulous march.Business Today, 3 October

Chakravarty, C. (2007) Wolfensohn’s privatefund picks 6% in Fabindia. Economic Times,9 July

Deshpande, T.A. (2007) Fabindia set to spawncommunity companies. SME World, BusinessStandard, 25 May

Fabindia (2007) 7 May 2007 www.7days.ae

Indian Express (2005) Fab food. Footloose, TheIndian Express, 5 March

Indian Handloom Cluster. Varanasi Handloomfabric marketing with Fab India- A newmarketing support to handloom weavers.May 2007 http://indianhandloomscluster-dchl.net

Kaimal, R. (2002) A school may be a harbingerof change in rural Rajasthan. Outlook India,4 November

Kale, R. (2007) Design: Retail. India Today, 26September

Rynne, G. The Fabindia Model: Ghandi Lives.27 November 2007 http://globalicity.blogspot.com

Singh, N. (2007) Fabindia charts out globalexpansion plan. The Times of India, 16August

Singh, U. (2005) Artisans, weavers happy overgood prospects. Hindustan Times, 20January

The Hindu Business Line (2007) Fabindia, ICICIstart fund for craft cos. The Hindu BusinessLine, 24 March

The Telegraph (2007) Store casts ethnic spell. TheTelegraph, 24 September

TNN (2002) Straight answers. Calcutta Times,The Times of India, 18 December

Varghese, N. (2005) Fabindia plans more outletsin South. The Hindu Business Line, 16September

http://www.7days.ae

BSNL – Making the Elephant Dance*

M. N. Tripathi1

In April 2003, Mr. Anil Sawant, ChiefGeneral Manager, BSNL had just comeout of a strategy meeting with some ofhis senior colleagues. His brow wascreased with anxiety at the prospect ofthe new developments in the telecomsector and the rapid strides thatcompetition had taken. He knew thatalthough there was still no cause forextreme alarm, the writing was on thewall as far as what the future held forthe organization. The monopolistic holdthat the company enjoyed all these years,was for ever, a thing of the past. In fact,his major concern now was what stepshe needed to take urgently to preventyielding any further space to competition.Even after a protracted meeting, therewas still no consensus on what shouldbe done to stem the rot.

1.0 THE INDUSTRY

Until the last decade, telecommunicationswas state run in India; the private sectorwas reluctant to invest in long gestationindustries like telecom. Learning from theexperience of developed countries, Indiamoved towards privatization of the

telecom industry by adopting theTelecom Policy of 1994.

In 2001, telephone penetration in Indiawas 3.5 % and cellular phone distributionwas a meagre 0.25%, compared to 85%in UK and almost 95% in someScandinavian countries. Mobile telephonygrew from 10 million subscribers in 2001to 150 million subscribers in 2007. BothGSM and CDMA technologiescontributed to this growth of the cellulartelephone sector.

The Indian Union Ministry ofCommunications oversees operations ofthis industry and determines policyguidelines. The Telecom Authority ofIndia (TRAI) is the regulatory bodywhich determines toll rates and acts asan arbitrator, wherever necessary. In1986, telecom operations for Delhi andMumbai were moved out of theDepartment of telecommunications (DoT)and given to Mahanagar TelephoneNigam Limited (MTLN), a public sectorcorporation. Following that, theGovernment launched Bharat SancharNigam Limited (BSNL) in an effort to

* Received November 28, 2007; Revised February 25, 2008This case has been prepared with the help of inputs provided by Mr. Alok Ranjan Mahapatra,Ex PGP 2001-2004 and Mr. Harsh Laad of Ex PGP 2005-2008. The author gratefully acknowledgesthis help.

1 Associate Professor, Xavier Institute of Management, Bhubaneswar, emali:[email protected]

Management case

mailto:emali:[email protected]


corporatize the remainder of DoT,empowering the new company to ventureinto new areas like basic, cellular andinternet services.

The Telecom Policy of 1994 sawliberalization of the sector. Since evenaverage telecom services were difficultfor the Government to provide, basic andvalue-added services were thrown opento private players. However, due toinexperience in dealing with suchdevelopments, some policy steps toregulate competition, led to confusion.The new Telecom Policy of 1999remedied the flaws in the earlier policyalong with opening up the bandwidthsegment for overseas communication tothe private sector.

The country now has a total capacity of29 million lines. The Long Distancetransmission network has 300,000 km ofterrestrial network, including 100,000 kmof optical fibre. Fully automatic nationaland international subscriber dialingservice is available almost everywhere inthe country. International communicationhas improved through use of satellitecommunication and submarine links. Thevoice and non-voice telecom servicesinclude data transmission, fax, mobile,radio, radio paging, V-SAT and leasedline facilities.

The Indian economy is on a path ofresurgence. The gradual opening up ofthe economy post-reforms ensuredsteady growth even at a time when othercountries were in the grip of a massive

slowdown. Progressive reforms such asthe removal of restrictions on foreigninvestment and industrial delicensing areresponsible for this growth (Exhibit I).Tailoring the EXIM policy to promoteexports and aligning the import dutiesto meet WTO commitments furthercontributed to this development. Thistrend is expected to continue in the nextfive years, driven by a favourablebusiness policy environment in terms oftax cuts, broadening tax base and a softinterest regime. The TRAI has earned agrowing reputation for independence,transparency and competence. Despitethe political interference, challenges to itsauthority, accusations of ineptitude byprivate players, this regulatory body hasbeen able to weather the storms and hascarved out the road map for the telecomsector.

Such structural changes have had apositive impact on thetelecommunication sector and a CAGRof 13% is estimated for the period 2002-2006. The future of the industry lies inthe mainline and cellular segments andconstant technological innovations suchas Internet Protocol (IP) based services.Revenues from voice services willexperience sustained growth even asthose from data services are expectedto increase sharply due to a surge inusage. As per a recent report from Frostand Sullivan, “In the last quarter of 2001,the number of cellular subscribers hadreached the 5 million mark due to thecontinuous fall in airtime rates, achieving

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0.5% mobile penetration in India.Revenues from cellular phones areexpected to grow at a CAGR of 37%during the period 2002-2006, with higherdata usage and multimedia services.”

2.0 THE COMPANY

BSNL was formed on 1st October 2000from the erstwhile Department ofTelecommunications. With revenues of Rs22000 crores (Exhibit II) in 2001-02,annual capital investment of over Rs 16000crores (Exhibit III) and a cumulativeinvestment in gross fixed assets (ExhibitIV) over Rs. 90000 crores (US $ 20.64billion), BSNL is the largest public sectorundertaking serving 34 millionconsumers. Cumulative fixed assets hasgrown at an average annual rate of over20% in the last 15 years, and is expectedto cross Rs. 100,000 crores (US $ 21.2billion) in 2001-02.

3.0 CORPORATE MISSION AND VISION

Mission – To provide world classtelecom services on demand using state-of-the-art technology for our valuedcustomers at affordable prices

Vision – BSNL would like to be a high-tech customer oriented company withemphasis on value addition.

Objectives

1. Provide telephone on demand byMarch 2003

2. Provide telephone in all villages ofIndia by Dec 2002

3. Raise telephone density from 3.5 to7 by 2005 and 15 by 2010

4. Provide bandwidth on demand

5. Build customer’s confidence throughquality and reliable service

6. Provide world class telecominfrastructure

4.0 THE CURRENT SITUATION

In the last few years thetelecommunications scenario had vastlychanged. BSNL had been at the forefrontof this revolution by ushering in changes,which until a few years ago would havebeen thought well nigh impossible.Technological advances had enabled thecompany to offer services such as fasteraccess to internet users as against the dial-up modem connections. Basic landlinetelephones double up as answeringmachines, alarm clocks, voice mail service,wake-up/reminder services and manymore.

With new technology such as CDMA,it was possible for mobile telephony toget a major fillip, because subscribershad the option to go mobile at localrates. Simultaneously, the reduction inmobile telephony rates encouragedcustomers to go mobile, which saw thecustomer base swell to giganticnumbers. BSNL, which was a pioneerin bringing these services, offered allthese services, apart from a host ofcorporate services.

However, the market meanwhile hadchanged in the last five years. BSNL

Tripathi, BSNL – Making the Elephant ...


through its predecessor, DoT was theonly player then, but now several playershad joined the fray. Earlier, BSNL wasthe monopoly operator offering a basketof products and services to customerswho had no choice but to select from thisbasket. But now BSNL was one amongmany others who offered consumers awide choice of products and services inthis over Rs 50000 crores telecom market.The company’s efforts to woo itscustomers is reflected in a minutes of avendor conference held in the corporateoffice at Delhi. (Exhibit V)

5.0 PRODUCTS

BSNL is present in almost all productcategories in the telecom market of India(Exhibit VI). In fact, it had launched mostof the products that dominate today inthe market except for cellular services,where it entered last and is today thesecond largest operator behind BhartiTelecom. The product range consistedof

• Basic services• Cellular services (Post paid and

prepaid)• National Long Distance• Internet service provider• Phone plus services• Answering machine services• ISDN• Centrex• Intelligent Network services• Leased Lines

• Managed Leased Lines Network• Webfone Services• DIAS• MPLS-VPN

• Broadband Services, etc

Exhibit VII indicates the companywisedistribution of revenues for the year2002-03.

6.0 BRANDING

During 2002, BSNL decided to go on abranding exercise to give its productand itself a distinct identity amongst theusing public. Being a governmentowned company, without the‘Navratna’ status it had constraints inchoosing the agency, since it had to gothrough a bidding process, with thecontract going to the lowest bidder.Soubhagya, a Delhi based agency gotthe contract to handle this brandingexercise. The advertising objectivescentred round the range of productsand services offered by the companywithout trying to get in anydifferentiation with competition. Thecampaign was sporadic since theterritorial circles were authorized tocarry the advertisements as per thelocal festivals and holidays in theirrespective circles. Owing to itsmonopoly status till late 2002, there hasnever been any serious attempt madeby the organization to identify anyparticular customer segments for itsrange of products. As a result all

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communication was directed ateverybody, thereby losing focus on theparticular customer segments thatneeded to be addressed. Whilepositioning its cellular services‘Cellone’, BSNL never cared to identifythe profitable customer segments, andpushed for its coverage and pricingonly, supposedly its strengths. Toattract numbers, the campaign had adistinct middle class slant, which keptaway the high-end customers. Exceptfor giving information, there was verylittle persuasion to bring in newcustomers. Since it was left to therespective circles to advertise as pertheir local needs, there was no commonmessage carried by different circles.Sometimes these advertisements fromdifferent circles, appeared in the samemedium, thereby confusing the public.

Lately, the company has been spendingmore on promotions with competitionhotting up. It has resorted to use of TVand radio apart from extensive outdooradvertising. In TV, prime time slotswere taken in BBC, CNBC and StarNews channels in the 9 – 10 pm slots.These campaigns were for specificperiods and the frequency was limitedto 2-3 runs during the course of theprogramme. Also, family serials andsports programmes were used to runthis campaign. Exhibits VIII - X.

7.0 PERSONNEL

Being a government department beforeit was corporatised, BSNL continued to

have a lot of baggage in terms ofinefficient, ill trained and demotivatedmanpower. To keep up with competitionthe organization needed to step upefficiency by using the latest technology,but the manpower was ill trained to takeadvantage of it. Training programmesdesigned to upgrade skills at the variouslevels in most cases, were shunned byemployees since morale had sunk in tosuch levels that they did not appreciatethe value of such programmes.Employees used to working lethargicallyfor years were unable to cope with thechanges that technology and competitionbrought in upon them. While the youngeremployees found it easier to learn andcope with the new changes it wasexceedingly difficult for the senioremployees who had fixed mind sets,lethargic working styles and werelooking forward to retirement, to managethis transformation.

8.0 THE ISSUES

Mr. Anil Sawant knew that there wereno easy solutions. Within theconstraints posed by the organizationhe had to bring this turnaround inBSNL. He knew it was possible, becauseBSNL had a lot of strengths, whichcould be leveraged to bring about thistransformation. However, he alsoknew that the service aspects of thebusiness and getting his employees toperform would be critical to the successof this venture. He was just not sure asto how to go about cl imbing thisseemingly steep mountain.



EXHIBIT I

Major Economic Indicators of the Indian economy(Year-on-year Percentage Changes)

Year GNP GDP Agri Foodgrains Industrial ElectricityProduction Index Production Index Production Index generation

90-91 5.5 5.6 3.8 3.2 8.2 7.891-92 1.1 1.3 -2.0 -4.5 0.6 9.192-93 5.1 5.1 4.2 6.6 2.3 5.093-94 5.9 5.9 3.8 2.7 6.0 7.394-95 7.2 7.3 5.0 3.8 9.1 8.195-96 7.5 7.3 -2.7 -5.8 13.0 8.696-97 8.2 7.8 9.3 10.5 6.1 4.397-98 4.9 4.8 -5.9 -3.6 6.7 6.698-99 6.4 6.5 7.6 5.9 4.1 6.599-00 6.2 6.1 -0.6 3.0 6.7 5.200-01 4.0 4.4 -6.0 -6.2 5.0 1.001-02 6.0 5.8 7.5 7.7 2.7 3.102-03 3.9 3.8 -14.9 -17.8 5.7 3.203-04 8.7 8.5 18.3 21.7 7.0 5.004-05 7.4 7.5 -25.8 -6.9 8.4 5.005-06 9.0 9.0 7.9 5.0 9.0 5.1

Source: Statistical Outline of India, Tata Services Ltd, Dept of Economics and Statistics, Mumbai

0

5000

10000

15000

20000

25000

86-87 94-95 95-96 96-97 97-98 98-99 99-00 00-01 2-Jan

EXHIBIT II

Bharat Sanchar Nigam LimitedRevenues (Rs crores)

173

EXHIBIT III

Bharat Sanchar Nigam LimitedAnnual Capital Investment (Rs crores)

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

86-87 94-95 95-96 96-97 97-98 98-99 99-00 00-01 2-Jan


EXHIBIT IV

Bharat Sanchar Nigam LimitedCumulative Gross Fixed assets (Rs crores)


EXHIBIT V

Minutes of the Vendor Conference held on 19.05.02 at 3.00 PM at BSNL Corporate Officeregarding Empanelment of Advertising Agencies for BSNL Corporate Office.

Posted on: 2006-05-23No. 12-4/05-Mktg.

Minutes of the Vendor Conference held on 19.05.02 at 3.00 PM at BSNL Corporate Officeregarding Empanelment of Advertising Agencies for BSNL Corporate Office.

A Vendor Conference was held on 19.05.02 at 3.00 PM regarding Empanelment of AdvertisingAgencies in BSNL Corporate Office in presence of DDG(Mktg.), DDG(BBF) & Jt. DDG(Mktg.I)in conference hall 9th floor, Statesman House, New Delhi. Following representatives ofAdvertising agencies were present:-

1. Shri Harish Sharma & Divendra Srivastava M/s Percept H2. Shri Subhash Gulati & Arjun Mukherjee M/s R.K. Swamy3. Shri Gopal Vyas & Ms. Shikha Jain M/s Pressman4. Shri Jhoy Roy & Subodh Pal Singh M/s Triton5. Shri Rajakumar M/s Grey Worldwide6. Shri Ashutosh & Ms Jaya M/s Lintas

2. The above mentioned representatives have taken participation in above mentionedVendor Conference. Following clarifications were made during the Conference in whichthe following issues were raised: -

(Ashok Maheshwari) Jt. DDG(Mktg.I)

Points Raised by Vendors

1. Section VIII – Bid Security Form : Whereas........................... (hereinafter called “the Bidder”)has submitted its bid dated.......……..for theAppointment of Advertising agencies & mediaHouse for BSNL Corporate office, new Delhi videTender No 12-4/2005-Mktg dated ....……….. Thewordings to be reworked.

2. Section II Clause 21.2 & Section XI clause 23.Clarification about the point 4, which is “Conceptnote on the creative or media brief given forbusiness brief given with the Tender Document.

Clarifications

Format is Ok.

Concept Note on the creative or Mediabrief given for Business brief given withthe Tender Document is uploaded onBSNL website. (Annexure ‘A’ please)

175

ANNEXURE ‘A’

No. 12-4/02-Mktg.

Sub : - Empanelment of Advertising Agencies for BSNL Corporate Office

Please refer to Section II Clause 21.2 & Section XI clause 23

Brief for Mobile services

BSNL is no. 2 GSM operator of India. After launch of GSM services BSNL was able to create anew market for its services. Most of the users who subscribed for BSNL services in 2002 werenew users of BSNL. Since launch BSNL had high demand for its GSM services and BSNL wasnot able to meet the demand except Punjab. However BSNL is facing following problems.

• The revenue from value added services is less in comparison of other operators.

• BSNL is facing declining demand in bigger cities.

• The high user and sec A customer segment prefers other service providers.

Now BSNL has planned 60 million capacity and already floated tender for the same. You arerequested to submit a concept note on advertising strategy for BSNL GSM services, so thatBSNL can utilize additional capacity to generate higher revenue and customer satisfaction.Further provide strategy to create distinct Brand image and generate higher revenue fromvalue added services.

Brief for Landline services

BSNL is facing problem of declining demand for BSNL landline services. In fact BSNL isloosing approximately 30 lakh customers every year. Problems are manifold ranging fromservice consideration to positioning of landline vis-a-vis mobile and FWP of CDMA providers.However landline offers distinct advantages like voice clarity and broadband services.

BSNL wants a answer to Aggressive marketing of competitor so that the slide of landlineservices can be stopped.

Brief for media

BSNL intends to spend approximately Rs 150 crores in next two years. Concept note on mediastrategy and planning is required to improve overall brand image and brand image of itsvarious services.



EXHIBIT VII

Company wise Telecom Revenues (2002-03)

Sl Company Revenue ShareNo. (Rs Cr) %1 BSNL 27500 552 MTLN 6022 123 VSNL 4183 84 Bharti 3083 65 Idea 1080 2.16 Hutchinson Max 711 1.47 Data Access 632 1.38 Spice 550 1.19 BPL Mobile 522 1.010 Hutchinson Essar 483 1.011 Others 5592 11

Total 50358

(Source: Business Standard: 8th National TelecomSurvey – 31 July, 2003)

EXHIBIT VI

Breakup of Telecom Revenues (2002-03)

Sl. Category Revenue % contri GrowthNo. (Rs Cr) bution rate (%)

1 Basic 28704 57 9Services

2 Cellular 8057 16 51Services

3 NLD 6043 12 (21)

4 ILD 5539 11

5 Internet 1285 2.6

6 Others 730 1.4

Total 50358

(Source: Business standard: 8th National TelecomSurvey - 31 July, 2003)

EXHIBIT VIII

177

EXHIBIT IX



EXHIBIT X

1.0 BACKGROUND

The Woodcarving profession has existedin Orissa since ancient times anddeveloped under the influence of Bengaland South India. In Orissa, the majorcentres of wooden handicrafts includeBhubaneswar, Barpali, Berhampur,Bhograi, Cuttack, Khalikote, Koraput,Mayurbhanj, Phulbani, Puri, andSambalpur among others.

Wood Carving in Orissa is broadlygrouped into plain woodcarvings andwooden items. Plain woodcarvings arelargely seen in Puri-Konark –Bhubaneswar clusters and Bargarhcluster. These items are made with lightvarieties of wood and painted withvegetable dye and mineral colours. Thewood and sculptors use the simplecarpentry tools like hammer, chisel etc.Mainly white teak and rosewood is usedfor plain woodcarvings. This art ispractised mainly in Bhubaneshwar, Puri,Konark, and Cuttack. Wood articles areusually made from harder and darkerwood and this craft is practised mainlyin Daspalla, Khandapara, Phulbani andNayagarh areas. Wood sculptures,

The Case of Raw Material Supply in theWood Carving Clusters of Orissa*

Debadutta Kumar Panda1

images of gods and goddesses, animalslike elephants, peacocks, and horses,masks, toys, boxes and bowls are allextremely well designed and thereexemplify the art of wood carving in thestate of Orissa.

Wood carvers as well as the woodcarving industry have been suffering dueto various reasons. Supply of the righttype of wood and at right time is one ofthe major reasons. In the present case,analysis of the supply chain has been theprime focus of the study. The objectiveis to find out the problems in the supplychain and possible approaches to alleviatethese problems.

2.0 METHODOLOGY INVOLVED IN THESTUDY

This study is based on both primary andsecondary information. In the first phase,wood carving clusters were identifiedfrom secondary sources. The mapping ofartisan clusters and the uses of differenttypes of raw materials were done throughcollection of information fromgovernment departments, non-government organizations, educational

* Received December 10, 2007; Revised January 19, 20081. Faculty, Xavier Institute of Social Service, Ranchi, email: [email protected]

Management case



institutions and development consultingfirms which are working on handicrafts.For the primary study, different clustersof woodcarving were chosen based on thetypes of raw material used. Threewoodcarving clusters namely, Puri-Bhubaneswar-Konark cluster, Cuttackcluster and Naygarh-Daspallha-Khandapada cluster were chosen for thestudy. In-depth personal discussions weremade with artisans. In-depth discussionswere carried out with the middlemen,involved in the supply of the rawmaterials, i.e., wood to the artisans.Personal discussions were held with thekey informants from various sources ofsupply of raw material for woodcarving.Consultations and discussions wereconducted with various governmentorganizations, non-governmentorganization, traders and educationalinstitutions. Government reports andpolicy documents were also reviewed tounderstand the policies and current statusof the craft.

3.0 METHODOLOGY FOR DEMAND ESTIMA-TION

The demand estimation was based on theannual potential of raw material use perartisan, type of raw material use, andnumber of artisans and their preferredkind of raw materials. The demandestimation was made by taking averagedemand of 25 artisans chosen randomlyfrom the three clusters. Then thecumulative average was taken and laterthe cumulative average was multipliedwith the number of artisans. The supplyof raw material is calculated based on the

total raw material chanellised from eachsource.

The Limitations in the Demand Estimation

1. Artisans kept on changing the typesof raw material based on the salesdemand.

2. The average uses of wood perartisans varied widely and arelargely dependent upon theintricacies and complexity of thecraft.

4.0 WOOD CARVING CLUSTERS IN ORISSA

The major wood carving clusters arelocated in Cuttack, Puri-Bhubaneswar-Konark, Khairapadar- Bhawanipatna-Rengalpalai- Narla- Kandargarh,Basudevpur -Chandabali – Thidi-Dhamnagar, Khandapada – Dasapalla-Nayagarh, Nawarangpur- Debugaon-Chandanhandi, Khallikote- Berhampur-Dharakote and Sambalpur. There are4795 artisans in the practice ofwoodcarving in Orissa. Moreover, theartisans of Puri-Bhubaneswar-Konarkcluster and Nayagarh-Khandapada-Dasapalla cluster, Khairapadar-Rengalapalli cluster are found to be themost active and the artisans/artisanfamilies are almost fully dedicated totheir profession.

5.0 RAW MATERIAL FOR WOOD CARVING

There are several types of wood used forcarving in Orissa. The major wood usedfor carving is white teak (locally knownas Gambhari) and the rose wood (locallyknown as Sisu). Other types of woodused for carving are sandal wood, neem

181

wood (Nimba), mango wood, Kurum(local), Katrang (local), Akasia and Kendu(local). The plain woodcarvings aremostly done on a soft creamish woodcalled Gambhari or white teak. Woodcarved articles using the creamishGambhari and the harder and darker Sisuor rose wood is a specialty of the artisansfrom Daspalla and Puri clusters.

7.0 SUPPLY CHAIN OF RAW MATERIAL INWOOD CARVING

Orissa Forest Development Corporationis responsible for cutting and selling ofthe timber. It is the sole authority to tradetimber both in round as well as in sawn

Panda, The case of raw material ...

forms in different dimensions from theirspecified depots. This process involves anumber of stages.

The Orissa Forest DevelopmentCorporation Limited (OFDC) permits theuse of only non-fruit bearing trees in theforest. Cutting of fruit bearing trees likemango, jack fruit etc can be done if theOFDC gets an order from thegovernment to cut the forest for a specificpurpose for example, construction of newhighways, development of industries etc.The supply chain of wood is shown inFigure – 1. The stages involved in theofficial supply chain in explained below:

Figure-1: Supply chain of Wood for Artisans

Official Supply Unofficial Supply

Felling of Wood by Forest Dept.

Setting Up of Interim Depot

Transportation of Logs/Wood to the Govt.

Depot/Saw Mills

Auction of Timber Timber Merchants

ARTISANS

Wood Felling by tribals, Villagers

and Others

Hardwood & Soft Wood

Private Sawmills

Wood Supply From Other States


Stage - I: During cutting of thetrees, the OFDC sets up an interimdepot where initially the timber isstored. Then the ‘lot’ formation iscollated based on species, and girthclass. If a particular species of woodfalls short for a lot, then a mixed lotis formed. After reaching a truckablepoint, each lot of wood is numberedand transported to the forestdepartment depot.

Stage – II: The forest departmentdepot sells the timber throughauction and retail selling. The auctionis conducted twice every month andthe buyers in the auction are usuallytimber merchants, as the auction isbased on a huge quantity and at leastnot less than one lot at a time.

In the retail selling, an individual goesto the Depot of the forest departmentand takes permission from the supervisorto get information about the availability,type, species and girth class of the wood.After that the individual places an orderfor the log/wood. Then permission isissued by the divisional manager andafter that a price is fixed for the selectedlog. After the payment, the log istransferred to the purchaser.

Stage – III: The purchased timber isthen transported to the Governmentpermitted sawmills by the purchaser.At the time of purchase a chalan isissued in the name of the personcontaining the number of the timberwhich he has purchased. The timberis transported to sawmill, which has

the permission to saw the timber andconvert it into different sizes. Thereagain before sawings the previouschalan is verified and another newchalan is issued.

Once every month there is a generalauction of round timbers from each depoton a pre-fixed date. The auction detailsare advertised in the local dailies both inOriya and English. Auction takes placeat the timber depot site where purchasersgather and bid the purchase price in thepresence of the Divisional Manager andthe subordinate staff of a particulardivision. Before announcing the auction,lots are formed comprising different girthclasses’ species wise. The prices quotedby the bidders are tabulated and sale isratified in favour of the highest bidder.

7.0 DRAWBACKS IN THE SUPPLY CHAIN

The artisan may buy timber from theforest depot through retail selling orfrom the timber merchant. Generally, theartisans buy the wood from the timbermerchants, as they cannot afford toparticipate in the auction due to lack offinance. Also the artisans prefer topurchase according to requirement ororder placed on the artifacts.

The price of the wood purchased by theartisans from the timber merchant is morethan the government price as it includescommission and profit of the merchantinvolved. For the direct purchase ofwood from the forest depot, first theartisan goes to the depot of the forestdepartment and takes the permission

183

from the supervisor to get informationabout the availability, type, species, sizeand shape of the wood. After that theartisans places an order for the log/wood. Permission is issued by thedivisional manager after a price is fixedon the selected log. After the payment,the log is transferred to the artisan. It isa time taking process as sometimes thedivisional manager is not available andthe permission process is delayed.

In order to participate in the auction, onehas to get registered and deposit a fixedpercentage of the security deposit in theform of Bank Draft. In case he fails tosucceed as the highest bidder, hissecurity amount is refunded and in caseof a successful bid, the security amountis adjusted from the sale price. But manytimes the carvers do not have enoughmoney to pay the security amount andbid for the highest price. Moreover thesculptors do not have enough time toenter into the legalities of bidding andformal transactions.

8.0 MAJOR BOTTLENECK IN TIMBER SALEAND SAW MILLS

Generally the wood used for carving i.e.,Rose Wood, Teak, Sal etc. remainunavailable with the forest depot orprivate timber merchants. The carveroften visits the forest depot and privatetimber merchants a number of times toget the desired wood. Most of the timethe carver has to wait for a month or evenlonger to get the wood and incurs hugeexpenses in repeated visits to forestdepot and timber merchants.

Among the total timber or woodproduced, a major chunk of wood istaken by the private parties, contractorsand individuals, who are basically non-artisans, for furniture, housework andother purpose. So these private parties,contractors and individuals like topurchase the wood/timber as soon aspossible and are ready to pay more. Sounofficially the cost of the wood isescalated, thus making it unaffordable forsmall artisans.

Now-a-days the White Teak (which ismostly used for carving purpose) is oftenused for furniture and other wood workthat leads to the diversion of wood fromthe artisans to non-artisans.

Supply chain (unofficial)

On an average 45 % of the total timberused for carving, is supplied unofficiallyfrom village areas (unofficial sources). Amajority of the clusters from Phulbanidistrict, Nayagarh district, Kalahandidistrict and Dhenkanal districts getwood (mostly Gambhari, Sisu and localwood like Katrang, Kurum etc.) fromlocal villagers and traders. On an average,40 cubic feet of wood is supplied everymonth to carvers of the above districtsunofficially by traders, villagers andforest dwellers.

Unofficial sources of wood supply werevery much appreciated by artisans as itensured timely supply, and supply at thedoorstep. At times, when artisans getgood orders, timely availability of rawmaterial is more important than highprice of wood.



9.0 PRODUCTION AND SALE OF TIMBERWOOD

Annual Timber Production and Sale

Year Production Sold(Cubic Meter) (Cubic Meter)

2000-01 34411 220432001-02 20503 210202002-03 22017 132032003-04 19047 98832004-05 5727 125942005-06 NA 10089

(Source: Orissa Forest DevelopmentCorporation Limited, Bhubaneswar, 2007)

The production of timber varied fromyear to year. Sometimes, the productionhas shown negative growth, which ledto a short supply in the market. Also theproduction and sale of timber were notin the same proportion. Though theproduction was high in 2001, 2003 and2004, the timber sale was much lowerthan the production. Often this happenedwhen all the timber cut in a year or seasonwas not fully sold as some of the timberremained as stock either due to badquality or remained unpurchased. Themerchants purchased the wood fromother neighbouring states (mostly fromChhattisgarh) and sold the timber at anescalated price in the market.

From the year 2000 to 2005, there was acontinuous decline (except slightvariation) in the production and sale oftimber. As the production and sale oftimber decreased, a price escalation in themarket was largely seen in private

sawmills. The shortage of raw materialwas due to high industrial uses i.e.,furniture and house construction, whichled to less raw material being availablefor woodcarving.

The major issue in timber was theavailability at a particular time atsawmills or forest godown. At aparticular time, even if timber wasavailable, carvers could not store it intheir work place or home due to legaldifficulties. Again, carvers were unableto purchase in bulk due to lack of financialstrength.

At a particular time, when there wastimber shortage in the market, whatevertimber was available it was chanellisedfor housing, furniture (by price escalationin the market) and other industrialpurposes. Sawmillers gave greaterpreference to furniture and houseconstruction as they were purchasing inbulk and they happened to be high valuecustomers.

10.0 ESTIMATION OF ANNUAL DEMAND OFWOOD FOR ARTISANS

The consumption of wood for carvingvaried depending on the size andintricacy of the work. At times even asmall size wood took a long time forcarving and vice versa, based on theamount and intricacy of the carvingwork. But assuming that the marketdemand is created properly for the saleof the wood carved product and thesupply is maintained properly, then thepotential consumption of wood per

185

carver per annum was about 40 cubicfeet and about 80% of this was in rosewood, white teak and local varieties.

As per the policy of Department ofForest, Government of Orissa, nosawmill could saw any wood unlesspermitted by the Government eventhough all sawmills could sell the timberafter fulfilling all legal formalities. Therewere 173 sawmills in Orissa but 156sawmills only had valid license.

The government had cancelled thelicense of 17 sawmills. There was nosawmill in Nayagarh division,Dhenkanal division, Phulbani division,and Kalahandi division, where most ofthe wood carvers were located. On theother hand 15 sawmills (10 %) werepresent in Baripada (Mayurbhanj) and66 sawmills (42 %) were located inRajnagar where there were no woodcarvers (According to the report ofOrissa Forest Development Corporation,Bhubaneswar, 2007). The distinctivedistribution of sawmills and carvers areshown in Figure -2.

Average demand for wood per carver/annum: 40 CftTotal No. of carvers: 4795Average demand for wood for carving/Annum: 1,91,800 CftAverage demand for Rose wood & White Teak (70%): 1,34,260 Cft1

Average demand for hard wood (Sal, Piasal, Teak) (23%): 44,114 CftAverage demand of other wood Neem, Kurum, Mango,Sandal, Kendu, Chakunda) (7 %) 13,426 CftThe average production of timber wood from OFDC: 20341 cubic meter

7, 18, 037 cubic feetThe average sale of timber wood from OFDC 14805 cubic meter

5, 22, 616 cubic feet

Figure-2: Distinctive Distribution of Sawmillsand Carves

Some details about the wood carvingindustry and wood supply are givenbelow:

The forest policy says that– “Forests arenot to be exploited, but are to be conservedfor soil and environment and meet thesubsistence requirement of the people”.

However, instead of supporting peoplefor subsistence requirement, timber issupplied mostly to big wood basedindustries and urban households. Thishampers the timber supply to povertystricken artisans who depend on woodcarving for a living.



The Land Ceiling Policy of governmenthas seriously affected the wood carverartisans, as they were unable to raiselarge-scale plantations for meeting theirraw material needs.

The farmers and community producerswere also affected by policies related toregulation of felling and transportationof forest produce, mostly the timberwood. Prior permission was needed forfelling of trees even on private land andspecial transit permission are needed totransport such timber. This led toinsufficient appreciation by the farmersand community producers. The majorsources of supply of raw materials to theartisans (where sawmills are not locatedor there is no institutional supplymechanism) remained out of the stockand to fill the gap wood were chanellisedillegally from the forest.

The 1988 National forest policy stated thatthe forestry enterprises should not besupplied with raw material from the stateforests and they should instead meettheir requirements through adoptingalternative raw materials, imports orfrom farmland. It further stated that nonew forestry enterprises are permittedexcept village and cottage levelenterprises. But unfortunately, the stategovernment did not have any record onthe end user (whether artisans orcommercial enterprises) of the foresttimber.

11.0 SOME OBSERVATIONS

Absolute scarcity, locational mismatchbetween availability and need, and lackof access were the principal constraints in

relation to wood availability for woodcarving artisans. The overarching rawmaterial constraints could be traced torapidly shrinking of stock at institutionalsources, poor geographical distributionand large scale supply to wood basedindustries. The competing demand forraw material (i.e., Timber Wood) kept thelarge wood based industries and urbanconsumer at higher end, and pushed downthe artisans at the lower end.

Three major issues remained as thebiggest hurdles in the provision of rawmaterial for wood carving, (1) Theregularity in supply of wood, (2)availability of a particular species ofwood, and (3) Availability of wood at aparticular place. The institutional andlegal framework in timber wood supplieswas in the favour of large wood basedindustries than poor artisans. The stategovernment retained almost all of thecontrol over timber wood management,regulation, monitoring, and timberharvesting and marketing. To someextent, the demand of wood was metfrom unofficial sources, as there was ahigh scarcity of wood in institutionalsources. The types of species of woodused for carving depended upon threefactors, (1) availability of the species, (2)choice and expertise of the carver, and(3) market demand or sales demand.

Moreover, there was no concrete policyin the state regarding supply of wood forartisans. Universal policy for large woodbased industry and small artisans hadincreased the gap. Also there was anunplanned exploitation of forest resourcesparticularly timber wood. Within the

187

forestry sector, most emphasis is given tolarge wood based industries even thoughthe “small wood carving sector” hademployed more number of people andkept on bringing huge revenue fromnational and international tourists.Though wood and timber aresymbolically related to rural areas andrural enterprises, there was a sharp declinein timber uses by rural households

12.0 PROPOSAL FOR CONSIDERATION

In the light of developments, the agencieswere considering several possibilities tohelp the wood carving industry and theartisans. Some of these are brieflynarrated below:

1. Establishment of Wood Banks inartisan clusters: With the Inter-departmental initiatives from thegovernment, wood banks could beset up in wood carving clusters.NGOs and cooperatives could beencouraged for establishment andmanagement of Wood Banks inartisan clusters. Government andfinancial institutions can extendfinancial support to Wood Banks forartisans, Department of forest couldensure supply of softwood to woodbanks and Department ofHandicrafts could play a supportiveand supervisory role in theprocurement and supply of woodthrough wood banks.

2. Provision of formal financialassistance: Financial assistance couldbe provided to wood carvingclusters. Financial institutions like

commercial banks, SIDBI andMicrofinance Institutions mayextend their arms to the artisans withcustomized repayment schedules.

3. Encouragement of Social Forestry,Farm Forestry and Village Forestry:These could be helpful to meet thegrowing demand of local wood likeKurum, Katrang, Keli Kadamba etc.(where there are less legalrestrictions) through social forestryand through trees grown on farmland.

4. Afforestation of Softwood Trees:Ground level survey with the helpof GIS technologies could be madeto identify large tract of wasteland,and government, private and non-government institutions/organiza-tions could be encouraged to affor-est species (Gambhari, Sisu andother locals) largely used for wood-carving.

5. Systematic Felling of Trees withProper Regenerating Measures: Seeingthe importance of wood carving sectorand social security of wood carvers,the department of forest couldconsider making provision in its policyfor systematic and planned felling ofsoftwood trees like Gambhari andRosewood with appropriateregenerating measures to meet theartisans’ raw material demand.

6. Use of Information andCommunication Technologies forForward and Backward Linkage: Amajor thrust could be given for



linking the wood carving clusterswith markets (raw material suppliersand carved product purchasers) withthe help of information andcommunication technologies.

7. Linking Artisan Clusters withTourism: Tourists haveinquisitiveness about seeing thecarving process and places ofproduction of wood carved products.Also, tourists might be able to buythe wood carved products from theartisans directly (No middleman willbe involved) and the tourists couldhave an impression and confidenceof buying the original products fromthe carvers. In the process, the touristinflow will be increased and theartisans concern for sale of carvedproducts will be solved. There willbe a regular flow of money fromtourists to artisan and it will enablethe artisans to purchase rawmaterials with minimum time gap.

8. Establishment for Wood SeasoningPlants: There could be initiations fromgovernment and private sectors forwood seasoning and woodpreservation plants. Entrepreneurscould be encouraged and governmentcould come out with appropriatemodalities for wood seasoning andwood preservation plants underpublic private partnerships. Apartfrom sawmill and godowns, OrissaForest Development Corporationcould come up with wood seasoningand wood preservation plants.

9. Minimum Time Period for Delivery:The forest policy possibly couldaddress the importance of raw material

for wood carvers and department offorest should tailor minimum timeperiod for delivery of wood to theartisans from forest godowns underretail sale. Stringent action should betaken in case there is an increase intransition period in wood supply toartisans from the forest godowns.

10. Forward Linkage and BackwardLinkage: Government and non-government organizations, who arecurrently engaged in forward linkageof wood carving products, should beengaged in backward linkage also.

The authorities, with the above facts andsuggestions were pondering over whatpolicy changes should be made and whatsteps should be taken to make the changeswork.

REFERENCESAction plan on self employment through

Development of Handicrafts in Orissa(2004-09), Directorate of Handicraft andCottage Industries, Orissa Bhubaneswar

Annual Report, 2001, 2002, 2003, 2004, 2005, 2006of Orissa Forest DevelopmentCorporation, Bhubaneswar

Handicraft and Cottage Industries of Orissa, 2003,Directorate of Handicraft and CottageIndustries, Orissa Bhubaneswar

Investment Climate for Handicraft Productionin Orissa, Shanghvi Presentations

National Forest Act, 1998 documentNational Forest Policy, 2002 documentOrissa Industrial Policy, 2001 documentReport on the State Level Workshop on craft

clusters development in Orissa, organizedby Development Commissioner ofHandicraft, March, 2003

The Indian Forest Act, 1927 documents

Book Review

Rastogi, P.N., (2003): Managing Creativity, Macmillan, New Delhi,pp. 166, Rs.198.00*

Reviewer: D. Chakraborty1

* Received November 11, 2007, Revised January 14, 20081. Lecturer, Kolkata Centre of BIT (Mesra), Kolkata, email: [email protected]

Managing Creativity, authored by Rastogi,is a meaningful contribution to the subjectof enhancing the creative talents of thepractising managers. The author admitsin the preface that since creativity doesnot come automatically, it needs to becultivated ‘in a systematic and sustainedmanner’ (p.v). Accordingly, the chaptershave been laid-out thoughtfully to enableeven a lay reader to follow the line ofthought developed by the author.

In Chapter 1 (Introduction) the authorlucidly explains the meaning of‘creativity’ thus,

“ Creative thinking involves the abilityto find solutions to problems bychanging one’s point of view when normalapproaches … fail to provide the neededanswers” (p. 3).

Thus, the creativity-instinct is believedto be triggered when the conventionalmethods for fixing problems arechallenged. However, it is equally truethat some individuals facing challengesuccumb to anxiety. Anotherfundamental aspect of creativity, of whichmost are ignoramous, has also beenhighlighted,

“Creativity is not restricted to thinking.Its scope and application extend to allfacets of human endeavour …imaginative exploration … testing theirsolutions … and implementing thesolutions by securing the willingcooperation of others” (p.3).

The author has made the intentions clearby not adhering to the commonly heldview of creativity for its sake only. Theprobable reason is that managers, and notartists, comprise the target audience ofthis book. It is true that so long as amanager cannot translate his thoughts/ideas into workable solutions, his inputswill not be considered valuable.

Chapter 2, with ‘Creativity as aCompetitive Resource’ as its title, bringsout a vital difference between ‘individualcreativity’ and ‘group creativity’ (pp.9 -11). Working in an organization impliesworking in group(s). Unless a groupleader takes an unilateral stance indecision-making, it is usually theculmination of a group effort. Therefore,the author remarks,

“ Most human beings are potentiallycreative in the areas of their strong



interest. Their creative potential can bebrought out and amplified, … in groupsettings” (p.10).

Hence, there is a word ofencouragement for those who feel thatthey are not creative. Creativity haseven been considered to be a ‘resource’because it adds to the competitive edgeof a company in terms of new productdevelopment, promotional strategy etc.(pp. 11-12). However, this view invitesa deeper question: is creativity a‘resource’ or a ‘source’? It will be taken-up later.

Chapter 3 on the Cultivation of Creativitythrows light on the ‘thought-skills’ (p.16)required for creativity. The authorelucidates two different types ofapproaches (pp. 16-20) to creativethinking:

(a) Convergent Thinking (a problemwith plural solutions)

(b) Divergent Thinking (uncommonthinking resulting in novel solutions)

Lack of corporate examples in explainingthe points (a and b) will cause a littledifficulty for a general reader tounderstand the ‘process’ of creativethinking. The concepts of ‘forcedrelationship’ and ‘visualizing futuresolution state’ (pp.21-2 and 24-5) theauthor suggests,

(i) ‘To get out of our automatic modeof thinking, … must discover, makeor seek out non-familiar and non-habitual linkages among unrelatedfacts and objects.”

(ii) “… try to create a vision of what asolution might look like.”

But a couple of questions remainunanswered: How do the skills ofrelating unrelated facts be ‘discovered’?How does a person ‘create a vision’?

The author offered a useful insight whenhe observed, ‘ The ability to find thepositive potential in a problem is a markof creative openness, receptivity, andflexibility” (p.22). Moreover, thedistinctions between ‘traditionalthinking’ and ‘creative thinking’ (pp.25-6) are quite helpful and relevant. Forexample, the former is orderly andsequential and the latter, disorderly andparallel. But the second difference, whichstates, ‘Traditional logical thinkingoperates in terms of dichotomies, polarcategories, and contradictions …Creative thinking, … embraces both sidesof a contradiction or dichotomy in orderto generate, … a new way forward’(p.25) is ambiguous. One fails to identifythe distinction between ‘ thinking interms of dichotomies’ and ‘embraces bothsides of a contradiction’.

‘Generating Creative Ideas inIndividuals’ (Chapter 4) has identifiedseven different ‘techniques’ (p.28) tofacilitate generation of creative ideas forsolving problems. The author has donea commendable job of lucidly explainingthe techniques. However, at timesreading has been a bit tedious due to lackof interesting examples e.g.. PMIApproach (pp. 36-7), ISA Perspective(p.38) etc. Even the example pertaining

191

to ‘Envisionment Approach’ (p.36) couldhave been enriched if the processinvolved in it had been highlighted.However, the examples, related to ‘UsingRandom Matching’ (pp.34-5), especiallythe idea of cotton buds that came to LeoGerstenzang when he noticed his wifewrapping cotton on toothpicks to cleantheir baby’s ear, were of immenselearning value.

In chapter 5 (Generating Creative Ideasin Groups) twelve different approachesfor generating ideas in groups have beendiscussed. Of all these approaches,barring only ‘Induced Dissociation’,have been explained adequately (p.47).The technique of induced dissociationinvolves keeping the mind in a blankstate. However, no effort was made toexplain what does the ‘blank state’ meanand how can it be achieved. This apart,it would have been of some help to anavid student of the subject had theauthor identified those techniques thatare presently popular. Some of thetechniques (like Morphological Method,Genetic Learning Approach etc.) beinga bit sketchy will remainincomprehensible to those who areunfamiliar with the subject.

Chapters 6 and 7 (Diagrammatic Methodsfor Creative Problem Exploration andCoping with Uncertainty inTechnovation) provide an outline to theprocess of creativity. The contents ofchapter 6 comprising the technicalprocesses for enhancing creativity aremore advanced and hence demand

rigorous mental discipline. However, allthe five techniques have been highlightedand explained in simple terms. The ‘Treeor Systems Flow Diagram’ has beenexplained as a, “… technique … tosystematically map out the full range ofpaths and tasks that need to beaccomplished for achieving an overallgoal” (pp.60-2). But is it not true thatsystematic charting-out of the options foraccomplishing a goal calls for adequateexperience? The author could havereferred to a positive correlation betweencreativity and experience. Anothertechnique involving ‘Ishikawa Diagrams’despite lucid exposition remains onlypartly comprehensible to a reader asthere is lack of any diagrammaticrepresentation (pp.62-4). However, thename of the technique suggests that thereshould have been diagrams. Deliberationon the ‘Matrix Diagrams’ (pp. 65-9) sansapplication in real life cases poses a similardrawback. Chapter 7 deals withuncertainties thrownup due totechnological innovations. The authorhimself admits, “ Technovation is amessy, disorderly, and highly uncertainprocess” (p.70). One feels that thetechniques discussed in the chaptercannot be appreciated in entirety unlesssomeone is a part of such creativeprocesses in any organization. Therefore,a person unless exceptionally interestedto know about creativity, or doing anyresearch work on it, may even skipreading the chapter.

‘Heuristics for Stimulating CreativeIdeas/Insights’ (Chapter 8) is a

Chakraborty, Managing Creativity ...


meaningful contribution towardsenriching the book. Heuristics are tacticalrules for guiding creativity along the lineof empirical experience (p.82). Themeaning assumes significance because,unlike the techniques mentioned earlier,creativity based on heuristics cannot besubjected to any defined process. Hence,there is a general perception that thecreative sparks based on such methods(like intuition, meditation, learning fromnature, idealizing etc.) occur at random.The mainstream scholars contend thatcreativity cannot be developed in thismanner because it then becomes a matterof chance. Despite these odds the authoradmits,

“ The individuals and groups may getlocked into older, conventional, andfamiliar modes of thought … . Undersuch conditions, some tactics, means orrules which may serve to stimulate theproduction of new and fresh ideas,insights, or viewpoints, may be veryuseful” (p. 82).

This indicates the possibility of gettingconfined to the conventional mode ofthinking by adhering to a predeterminedpath. Naturally this goes against the veryspirit of creativity.

The author has taken great pains to pendown thirty-five different methods tocreative problem solving. These methodshave been explained crisply in a reader-friendly manner with suitable examples.

Chapters 9 and 10 (Utilizing Creativityof Groups and Fostering Creativity and

Innovation in Organizations) essentiallyhighlight the relevance and importanceof formation of groups to facilitatecreativity. Emphasis has been added todepict the importance of sustainedtraining programmes with the objectiveof making creative problem solving ingroups a part of an organization’sculture (pp.108-9, 114). However, oneobserves that there has not been mucheffort by the author to outline themethods to encourage individualcreativity in the book. Throughout, thefocus has been on group. Such anapproach appears to be handicappedconsidering that a group is a sum totalof individuals. Therefore, the quality ofcreative output of a group should havedirect bearing on the quality of creativeoutput of an individual.

Chapter 11 (Creativity as the Core ofCompetitive Excellence) deals with theimportance of creatively handling newproblems, situations and demands toremain ahead of the competitors(p.121) . Therefore, i t has beensuggested that the employees be dealtwith in a more humane manner andnot just as labour inputs. The authoradds, “ …organizations view theiremployees as valuable resources …”(p.122). This observation sounds a bitjarring. So far, the line of argumentviewed human beings to be the sourceof creative ideas. Then how come theemployees be deemed as ‘valuableresources’ when they are in effectsources of creativity?

193

Appendices (I and II) essentiallydistinguish between the Japanese andAmerican approaches to managingcreativity. One of the fundamentaldistinctions between the Japanese andAmerican approaches is that throughcreativity the former aims at developingmotivation, job satisfaction andteamwork (p.129). The latter, on theother hand, encourages creativity to, ‘…sustain high level of innovation andcommercial success’ (p.140). This apart,the other unique feature of Japaneseapproach is that even, “… hierarchicallylower level employees are invited toparticipate in the problem finding phase”(p.130). Later the author adds, “ MostAmerican and Indian managers do notunderstand the importance of involvingemployees in early phases of problemfinding activities’ (p.130). That the Indiancompanies have been clubbed togetherwith American and not Japanesecompanies, although Indian and Japaneseare culturally more in tune with oneanother. The Indian companies adoptAmerican management concepts andtechniques instead of adapting them. Theauthor has not mentioned if monetaryrewards are doled out to the employeesserving American firms for generatingcreative ideas. The Japanese firmshowever offer negligible sum asincentives (p.132).

It is now appropriate to have a little moreof conceptual clarity on creativity whichhas so-far been ignored in this book.Associated with creativity are twophrases (Chakraborty, 1989):

(a) adaptive or incremental creativity(AC)

(b) break through or quantum creativity(BC)

It is felt that creativity techniquesapplied in business organizations aremostly of AC type and rarely of BCtype. For instance, the transition fromBoeing 707 to Boeing 747 represents ACwhereas shift from propeller plane tojet plane is BC. For the former whiletechnique like brain storming is crucialand for the latter brain sti ll ing isessential. Modern day managementpractices (borrowed heavily fromAmerica) hardly repose any faith inbrain stilling as a technique for creativeproblem-solving. Hence, it is arguedthat these two concepts represent acertain degree of culture-specificity –brain storming depicts the Western andbrain stilling the Eastern approaches.(Chakraborty, 1989).

The concept of brain stilling essentiallyinvolves different types of breathingtechniques to quieten the mind fromfleeting thoughts. This allows the rightlobe of the brain (which is the seat ofdirect intuition and synthesizedcomprehension) to become active. Thistechnique is not as unscientific as yet it ismade out to be. It is pertinent to listen toProf. M.H. Wilkins (Nobel Laureate in1962),

“The logical and rational is a veryimportant element in science. Butemphasis of that tends to make people

Chakraborty, Managing Creativity ...


not notice the absolutely essential role ofintuitive. In fact, in any creative activityyou can never analyze the wholeprocess completely becausepsychological and other dimensions areat work. Nobody understands thenature of creative process. Certainlynot the rational scientist” (Wilkins,1986).

Thus, the above statement from a NobelLaureate refutes the commonly heldnotion that since intuitive decisionscannot be objectively verified thereforethey are unreliable. Sri Aurobindo, theleading seer-philosopher of modernIndia, asserts,

“In … Yoga the whole principle is toopen oneself to the Divine influence. Itis there above you and, if you oncebecome conscious of it, you have thento call it down into you. … In the quiet

mind there will be a progressivepreparation for the experience. But youmust not become impatient”(Aurobindo, 1973).

Thus, it is evinced at once howsignificantly different the oriental temperis as compared to the occident at oneswhen it comes to problem solving byadopting creative techniques.

REFERENCES

Aurobindo, Sri (1973), On Self-Perfection, Part I(Pondicherry: Sri Aurobindo Society),pp.23-4.

Chakraborty, S.K. (1989), Foundations ofManagerial Work: Contributions from IndianThought, (New Delhi: Himalaya), pp.261-2,264-5

Wilikins, M.H. (1986), Interviews With NobelLaureates and Other Eminent Scholars(Bombay: Bhaktivedanta Institute), p.39

Paradigm shift in managementeducation is the need of today’s globalenvironment. A journey from Taylor’sscientific era to new age managementera highlighting Indian concept ofmanagement mantra and shaping thesein an integrated ‘new model’ ofmanagement by Professor SubhashSharma is a pioneering contribution inmanagement literature. It is pioneering, because he has penetrated into thestudies of Veda, Geeta, Panchtantrastories, Mahabharata, Ramayana,Kabir’s work etc. to develop theseideas with reference to management.He has worked towards ‘modelbuilding’ frameworks through a‘creative and meditative research’approach.

Sharma’s attempt in his recentlypublished integrated research work,New Mantras in Corporate Corridors:From Ancient Roots to Global Routesforces management intellectuals toraise following thought provokingissues.

Subhash Sharma (2007), New Mantras in Corporate Corridors, New AgeInternational, New Delhi, pp.558, Price Rs.295/-*

Reviewer: A.S. Abani1

1. Should management teachingmove from mind colonization toliberalization or extension ofmaster – master process of learningfrom each other? The integratedmodel presented in Fig 1.3 of NewMantras in Corporate Corridors,indicates how Indian concepts,thinkers and scholars (SulabhSutra, Buddha, Mahavir, Kautiya,Aryabhat, Bhaskaracharya, Kabir,Tulsi, Vivekanand, Aurobindo,Gandhi and others such as C VRaman, J C Bose, HargovindKhurana, Meghnad Shah,Chandrashekhar, Ramanuja, VinodDham of Pentium chips, , DeepakChopra of alternative medicine,Sabir Bhatia of free mail serviceetc .) have influenced andawakened western scholars andhow Indian scholars have gainedfrom this heritage as well as fromintellec tual interaction withwestern scholars and madesignificant achievements.

* Received March 3, 2008.1. Director, B.M. College of Management, Surat, email:[email protected]

Book Review



The proposed models with ancient rootshave global appeal. This is reflected inthe model of complementary approach ofHolistic Development ( Fig 2.4, p. 37),Indian model for corporate development(Fig. 4.3, p.77) as well as in Kautilaya’stheory of motivation (Sam, Dam, Bheda,Dand) approximating itself to theory Xand theory Y. The Kautilayan strategicmodel (p.106) has also been excellentlypresented.

The author has made efforts towards‘modulation’ of thoughts on EnlightenedLeadership (Fig. 9.2, p.177), Theory K(Kutumb), Y in trinity (Laxmi, Saraswati,Durga) model of leadership and OSHAmodel of self awareness and its relevanceto X,Y,Z theories. Model of ‘hierarchy ofmen’ representing HOPE (Higher OrderPurpose of Existence) is a model fortransformation to better world whichworks towards the self-actualizationparadigm.

The Human Quantity Development(HQD) model rotates around ‘manas’,vachan and karam with subset of sevencomponents, namely, ( i) Thought-Action analysis, (ii) Negergy- Synergygrid (iii) SO - SO window (iv) Stimulus-Vivek-Response (v) G/T Ratio (vi)Relationship analysis and (viii) E-N-UAction analysis . These are classicexamples of modulation for corporatemanagement.

BCG matrix model of strategy replacedby growth rate and value addition

with the help of plant life metaphorsby the author is a step towardssimplif ication of presentation ofcomplicated ideas for betterunderstanding (Fig. 18.5, p.301). Thereare a number of other importantmodels, such as KPCL, BEST, CINEMatrix, FATE Analys is , 9 Tframework of TRM yantra, EPIS(Enterprise Performance ImprovementSystems) based on value chain matrixand management control system.Using the brain metaphor, he has alsogone beyond McKinsey’s 7 Sframework and suggested acomprehensive framework of VSPyantra that suggests co-alignment ofnine elements represented by V vector(Vision, Vistas, Values) , S vector(Strategy, Structure, Systems) and Pvector (Purpose, Process, People) .Thus, the book is full of simple modelsfor easy learning and easy practice ofmanagement concepts.

The book reflects the type of changes thatare required in terms of revision ofcourses focusing on value basedinternalization of management ideas withroots in Subhasitani, Arthashastra, Vedaetc.

2. What strategies should be adoptedin teaching and practice by modernmanagers with greater intensity toagain re-institutionalize Indianmanagement mantras with roots in

197

wisdom and knowledge fromancient texts? In what ways re-surfing of ‘Indian Managementmantras’ can be achieved in the eraof Holistic Globalization orViswanisation?

The book suggests the need for aparadigm shift from Darwin to Dharma,Maslow to Moksha and Marx toMahatma. The totally different andunique work, presented in the book isbased on ‘Gap Analysis’ of managementideas and is the first step towardsrevolutionary thinking andcontribution in re-surfing and‘re-surfacing’ Indian management mantrasand its Viswanisation. This approachopens new vistas of researchopportunities based on Kabir Ke Dohe,principles followed in Mahabharat,Kautilaya’s Arthasastra, Geeta, Vedasand many folk stories of local civilizedsocieties (some are reflected in childrenliterature l ike old Chanda Mamamagazine ).

3. “Challenging with confidence” isanother issue which needs to drawsour attention. There is a need tochallenge and replace existingconcepts and thoughts andestablish new ones. Academiciansmust take the lead in this context.The author with great confidenceraised an issue based on Geeta. Hehas sharply contrasted, “Arrival of

the best to lead the rest” fromGeeta with Darwin’s “survival ofthe fittest to eliminate the rest”. Itcan be perceived that both viewsare correct but in Geeta it is saidwith a positive approach and inDarwin’s philosophy with negativeapproach. Geeta represents theDharma to protect the people andlead them. Quite often, we go forcritical analysis, we get divergentthoughts and ideas. We hesitateand demonstrate lack of confidenceand thus ideas remain in cell. Weneed to overcome this hesitationand the book amply demonstratesthat this can be achieved.

4. Towards A New ResearchApproach: The author’s workamply demonstrates a new researchapproach viz. approach of creativeand meditative research. Thisapproach can be used as asupplement to quantitative andqualitative research approaches.This approach leads to metasynthesis of ideas and opens newopportunities for creative synthesisfor development of newknowledge.

The metaphor of recent Hindi movie,‘Taare Jamin Pe’ applies to Sharma’screative and innovative work inmanagement education as well as inrelated social sciences. The bookproposes teaching through ‘corporate

Abani, New Mantras in Corporate ...


rhymes’. By raising certain issues formanagement education, as raised in thisbook, we can carry forward this newrevolution of India’s mind liberation andcreative churning in the field of

management. Then India’s contributionto management will become worldknown just as its knowledge workersand knowledge professionals are worldknown.

199

Xavier Institute of ManagementBhubaneswar

Xavier Institute of Management, Bhubaneswar (XIMB) has completed 20 years of purposefulexistence, offering management education “with a human face”. During this period, XIMBhas established an identity of its own and a consistent position among the best B-schools inthe country. It is known not only for its Post-Graduate Programmes but also for developmentalprojects. The institute owes its origin to a “Social Contract” between the Government ofOrissa and the OJS (Orissa Jesuit Society). The Management of the institute is in the hands ofa Board of Governors, consisting of Jesuit Fathers, senior representatives of the Governmentof India and Government of Orissa, eminent industrialists and educationists.

The institute offers three post graduate programmes, two certificate programmes and onedoctoral programme (known as Fellow Programme). These are :

l PGDM : Two-Year Full-Time Post-Graduate Diploma Programme in Management(Residential);

l PGDMCRMS : Two-Year Full-Time Post-Graduate Diploma Programme in RuralManagement (Residential);

l PGDM for Executives : Three-Year Post-Graduate Diploma Programme in Managementfor Working Executives. This is offered in two mode-one involves week-end classesand the other 15 days class in every term.

l PGCBM : One year Post-Graduate Certificate Programme in Business Managementusing Video Conferencing Technology.

l PGPMI : XIMB in collaboration with ICICI is offering a one year Certificate programmenamely, “Post Graduate Programme in Management and Insurance” to nurtureprofessionals for the emerging insurance industry.

l FPM : Fellow Programme in Management (Residential).

All PGDM courses along with the Fellowship Programme of the institute are approved bythe All India Council for Technical Education (AICTE), Government of India. Since XIMB isan autonomous institute not affiliated to any university, it does not grant degrees. The full-time PGDM of XIMB is recognised by the Association of Indian Universities (AIU) as equivalentto an MBA degree from an Indian University.

National Academic Recognition Information Centre for the United Kingdom (UK NARIC)recognises XIMB’s PGDBM as comparable to British Master’s degree standard.

XIMB has a tie-up with several European, American and Afrian Schools for student exchangeprogrammes.


MDP CALENDAR (2008-2009)

Sl. Programme Days Dates Programme Prog. FeesNo. Venue Cordinator Res Non-Res

1 MIS Skills for Competitive 3 May 20-22, 2008 Bhubaneswar Prof. Dipak Mishra 12000 9000Advantage of Business Managers Prof. Sanjay Mohapatra

2 Emotional Intelligence for 5 June 2-6 , 2008 Bangalore Fr. P.T. Joseph, SJ 28000 NAManagerial Effectiveness

3 Innovation as a tool for 3 June 24-26, 2008 Bhubaneswar Prof. Jacob D Vakkayil 12000 9000organizational effectiveness

4 Credit Risk Management 3 July 21-24, 2008 Bhubaneswar Prof. Sridhar Dash 12000 90005 Meeting Corporate Objectives 3 July28-30 Bhubaneswar Prof. Snigdha Pattnaik 12000 9000

through the Balanced Scorecard Prof. Sanjay Mohapatra6 Transnational Business Strategies 2 Aug. 12-13, 2008 Bhubaneswar Prof. Amar KJR Nayak 8000 60007 Personal Growth & 5 Sept. 1-5, 2008 Puri Fr. P.T. Joseph, SJ 30000 NA

Effectiveness Lab.8 Selling Skills 3 Sept. 04-06, 2008 Bhubaneswar Prof. M.N. Tripathi 12000 90009 Strategic Compensation 3 Sept. 8-10, 2008 Bhubaneswar Prof. S.S. Ganesh 12000 9000

Management10 Teamwork Competency for 3 Sept. 15-17, 2008 Bhubaneswar Fr. Tony Uvary 12000 9000

Star Performers Fr. George Joseph11 Business Analytics : Scoring & 6 Sept. 22-26, 2008 Bhubaneswar Prof. Sridhar Dash 24000 18000

Customer Segmentation Prof. Subhajyoti Ray12 Logistic & Supply Chain 3 Nov. 3-5,2008 Bhubaneswar Prof.S K Bishwal 12000 9000

Management13 Lab on Entrepreneurship 3 Nov. 11-13, 2008 Bhubaneswar Prof. Rajeev Roy 12000 900014 Marketing Research for Sales 3 Nov. 19-21, 2008 Bhubaneswar Prof. Sandip Anand 12000 9000

Professionals15 Journey towards excellence for 3 Nov. 3-5,2008 Bhubaneswar Prof. Snigdha Patnaik 12000 9000

professional women16 Customer Service Management 2 Nov. 21-22, 2008 Bhubaneswar Prof. M.N. Tripathi 8000 600017 Train the Trainers 6 Nov. 24-29, 2008 Bhubaneswar Prof. Saveeta Mohanty 24000 1800018 Counselling skills using Neuro – 5 Dec. 1-5, 2008 Bhubaneswar Fr. P.T. Joseph, SJ 20000 NA

Linguistic Programming techniques19 Demand Estimation, Forecasting 3 Jan. 08-10, 2009 Bhubaneswar Prof. P. Mishra 12000 9000

& Market Data Analysis20 Mentoring & Coaching for 5 Jan. 12-16, 2009 Bhubaneswar Fr. P.T. Joseph, SJ 20000 NA

Performance effectiveness21 Negotiation Skills 3 Jan. 15-17, 2009 Bhubaneswar Prof. M.N. Tripathi 12000 900022 Project Implementation 3 Jan. 19-21,2009 Bhubaneswar Prof. W.S. William 12000 9000

& Monitoring23 Effective Communication & 3 Jan. 20-22, 2009 Bhubaneswar Prof. I. Kumar 12000 9000

Presentation Skills24 Basic Leadership Skills 5 Jan. 20-24, 2009 Bhubaneswar Fr. George Joseph, Sj 20000 15000

Fr. Tony Uvary, SjProf. Jacob D Vakkayil

25 Developing Change Champions 5 Feb. 24-28, 2009 Bhubaneswar Prof. S. Peppin 20000 15000for Organizational Excellence Prof. Snigdha Pattnaik

26 Business Intelligence for 3 Mar. 2-4, 2009 Bhubaneswar Prof. P. K. Bala 12000 9000Managers

ILAKSHAN is a bi-annual journal. The paperspublished in the journal go through blind peer-review. It publishes original research-based articles,perspectives, cases on topics of current concernand book reviews in all areas of Management. Ageneral guideline for contributors is given below.1. Manuscripts should be of approximately 10,000

words (20 to 40 A-4 size pages, typed in doublespace). Manuscripts should be submitted alongwith a soft copy or by e-mail with the coverpage bearing only the title of the paper andauthor’s names, exact designation, officialaddress, e-mail and phone/fax numbers.

2. Article should accompany an abstract of about150 words.

3. Tables and Figures : Their location in the textshould be indicated as follows :

Table-1 about here

4. Endnotes : All notes should be indicated byserial numbers in the text and literature citedshould be detailed under reference inalphabetical order of the surnames followed byyear of publications immediately after theauthor’s name.

5. References :The list must mention those sourcesactually cited in the text or notes and to theextent other sources possible which are essentialfor understanding the topic. Author’s nameshould be the same as in the original source.

a) In the text, the references should appear asfollows : Dayal (2002) has shown.... or Recentstudies (Ramnarayan 2002; Murthy, 2001)indicate...

b) Journal references should be listed as follows:Khandwalla, P. N., (2001). “CreativeRestructuring,” Vikalpa, 26(4), 3-18.

c) Books should be referred to as follows :Sugandhi, R. K., (2002). Business to BusinessMarketing, New Age International, New Delhi.

d) References from Internet should be referred to asfollows : Hesterbrink, C., E-Business and ERP :Bringing two paradigms together, October 1999;Pricewaterhouse Coopers., www.pwc.com.

GUIDELINES FOR CONTRIBUTORS

For more than one publication by the sameauthor, list them in chronological order, with theolder item first. For more than one publicationin one year by the same author, use small (lowercase) letters to distinguish them (e.g., 1980a,1980b).

6. British spellings should be followed throughout(programme, not program) the manuscript.

7. Numerals should be used one to twelve in words,thirteen and above in figures, unless the referenceis to percentages (5 percent), distance (5 km), orage (10 years old). Use 1990s and 19th century.

8. No stop should be used after abbreviations (UK,MBA), but should be used after initials (K. S.Singh).

9. Double quotes should be used throughout. Theuse of single quotes is to be restricted for usewithin doubles quotes, e.g., “In the words of Szell,the ‘economic question’ is today....” Quotationsin excess of 45 words should be separated fromthe text with a line space above and below andindented on the left. Quotes should be citedaccurately from the original source, should notbe edited, and should give the page numbers ofthe original publication.

10.Capitalisation should be kept to the minimumand should be consistent.

11.An author will receive free of cost 10 offprintsand a copy of the issue in which his/her paperappears and in addition, one copy each of thethree subsequent issues.

12.Manuscripts not considered for publication willnot be sent back. Those submitting papers shouldalso certify that the paper has not been publishedor submitted for publication elsewhere and thatit represents author’(s) own work.

13.Every contribution for publication is providedwith a code number. The author is required toindicate the code number during all enquiries.

14.Manuscripts and all correspondence should beaddressed to : Editor, Vilakshan, Xavier Instituteof Management, Xavier Square, Bhubaneswar -751013, India, Ph.: 91 - 674 - 3983893, 3012345(Pilot No.) Fax : 91- 674-2300995,E-mail :[email protected]

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