A Journal of Management - Integral University · 2016-06-01 · Department of Business Management Faculty of Management and Research Lucknow-226026 U.P. (India) p-ISSN : 0974-8032

Department of Business ManagementFaculty of Management and Research

Lucknow-226026

U.P. (India)

p-ISSN : 0974-8032

e- ISSN : 2278 6120

A Journal of Management(Indexed at J-Gate and EBSCO)

Vol. 8 No.2 December -2015IRJM

SERV II TN Y,U L ULA C

R KG N

E OT WNI

Dr. Zahid Raza KhanDept. of Business ManagementIntegral University

Dr Yasir Arafat ElahiDept. of Business ManagementIntegral University

Dr. Gaurav Bisaria Dept. of Business ManagementIntegral Univerisity

Prof. Mirza S. SaiyadainDean Faculty of BusinessBSAS UniversityChennai, Tamilnadu

Prof. Ashfaq Ahmad ZilliDeanFaculty of EngineeringIntegral University

Prof. Serajul BhuiyanFaculty of Marketing communication & Media, University of AuburnMontgomery, USA

Prof. Shahid SiddquiMarketing & International BusinessLong Insland UniversityC.W. Post Campus, USA

A Journal of Management

Editor-in-chiefProf. Aftab Alam

Dean, Faculty of Management and Research, Integral University

Chief PatronProf. S.W. AkhtarVice ChancellorIntegral University

PatronProf. S.M. IqbalChief Academic ConsultantIntegral University

Sub-EditorDr. Adeel MaqboolAssociate ProfessorHead, Dept. of Business ManagementIntegral University

Managing EditorDr. Rizwana AtiqAssistant ProfessorDept. of Business ManagementIntegral University

Prof. I. A. KhanRegistrarIntegral University

Prof. Azhar KazmiCollege of Industrial ManagementKing Fahad Univ. of Petroleum & MineralsDhahran, Saudi Arabia

Advisory Board

Dr. Asma FarooqDept. of Business ManagementIntegral University

Associate Editors

December 2015, All Right ReservedNo part of this publication may be reproduced or copied in any form by any means without prior written permission. The

Faculty of Management and Research, Integral University, Lucknow press holds the copyright to all article contributed to its publication. In case of reprinted articles, the Faculty of Management and Research. Integral University, Lucknow press holds the copyright for the selection, presentation, and publication.

Dr. Tauhidur RahmanAssociate ProfessorDept of Agriculture and Resource EconomicsArizona University, Tucson, USA

Prof. T. UsmaniPro Vice ChancellorIntegral University

Prof. Kaleem Mohd. KhanFaculty of Mgmt. Studies & ResearchAMU, Aligarh

Prof. Abid HaleemFaculty of Engg & TechnologyJMI , New Delhi

Dr. Jabir AliAssociate ProfessorCentre for Food and AgribusinessManagement, IIM, Lucknow

Prof. D.C. ThaparAcademic ConsultantIntegral University

C O N T E N T S

Camille Paldi Kuwait finance house: A case-study in the issues andconcerns in the financial reporting of Islamic banks

Sanjeev Kumar Saxena Measuring organizational service orientation:Validating Serv*or scale in Indian context

Archana Aravindan Urban infrastructure investment & its relateddevelopmental status in Kerala - A study with specialreference to Kerala sustainable urban developmentproject

Shazia Parwez Liquidity and stock returns: A study of theValeed Ahmed Ansari Indian market

Navdeep Kumar Leveraging emotional intelligence for the enhancementof the organizational effectiveness – Paradigms and Paragons

Anu Kohli An empirical study of variations in critical successRam Singh factors of quality management practices

in Indian manufacturing industry

K.K. Garg Leadership in TQM context : A case studyPranav Mishra

Author(s) Research Papers Page No.

1-8

25-35

36-47

48-63

1-16

17-35

36-51

52-71

72-80

81-92

93-101

Editorial Note

Global economic growth, estimated at 3.1 percent in 2015, is currently projected at 3.4 percent in 2016 and 3.6 percent in 2017. The pickup in global activity is projected to be much more gradual than in October 2015 as per the World Economic Outlook (WEO), especially in emerging markets and developing economies. Similarly, while assessing India's economy from October to December period 2015, it has been found on track and so far it is a witness to being one of the fastest-growing economies in Asia. The core facts of the resilient domestic demand and a limited reliance on the external sectors, are expected to fuel a pickup in growth in the fiscal year 2015. However, the data for the final quarter are mixed. The reason behind this debacle is industrial production deterioration in January, although the manufacturing PMI was found stable in February. The Ministerial credibility in this regard has unveiled some credence to the tune of the budget for the upcoming fiscal year 2016. The overall budget continues in tune with the government's fiscal consolidation path , and introduces a number of measures to spur the rural economy and improve the business environment. At the advent of governmental treatise and understanding, what makes the government responsive to the needs of the citizens is a key issue of today's political economy. It is poignant in low-income countries, wherein the absence of market opportunities, vulnerable populations are being relied upon the state action for their survival. A key issue then is what institutions of economic, social and political change can be built to enhance the effectiveness of the state in social protection and preparing people to be vigilant over social change. It requires not just a grasp of the roots of both state and government, but also an understanding of its embeddedness in society, to restore specifically its relation with the economy.The overall gamut of such complexities can be reckoned positively if some authentic sources could be put forth under the ambit of research foray, which has become an order of the day.The Integral Review Vol 8 No. II issue in your hand reveals a combined essence of researches, with diverse ideas from different scholars. The first paper highlights the current unorganized state of financial reporting in Islamic bank and reveals a true picture of the negative effects of using conventional accounting standards in Islamic banks rather than Islamic accounting standards and shows how this leads to non-transparency and the provision of inaccurate and misleading information to the general public and investors. The second paper contemplates the unique scaling technique “Validating SERV *OR Scale in Indian context” and has proved how it fits in for measuring any organizational service and verified positively for its internal consistency. The third paper, a unique study on “Urban infrastructure investment & its related developmental status in Kerala” herein incorporated, is worth studying for its strategic plan. The fourth paper is devoted

Integral Review- A Journal of Management, Vol.8 No. 2, December 2015

Dr. Aftab Alam

Editor-in-chief


to “Liquidity and stock returns: A study of Indian market.” It examines the effect of liquidity on returns in the Indian stock market for the period between April 2000 and March 2012, and gives a lucrative result in the form of earning a premium of 4.50 per cent per month over liquid stocks. The Fifth paper “Leveraging emotional intelligence for the enhancement of the organizational effectiveness-paradigms and paragons” gives an insight into organizational effectiveness and concludes with suggestions to develop further scope of research in this domain. The sixth paper “An empirical study of variations in critical success factors of quality management practices in Indian manufacturing industry” is discussed with quantifications that an updated technology and leadership skills can create an edge over the variance of turnover. The last and the seventh paper envisages toward “Leadership in TQM Context: A case study” which on the whole contemplates a complete review of the practices of Leadership on Total Quality Management (TQM) in Indian automobile industry and gives a result of its incredible performance of TQM journey.

We conclude by saying that it has been our honor and pleasure to bring out this Journal. We are highly thankful to the authors who have published their research and the reviewers who have ensured the quality of IRJM. We have expanded our authorship to include more international contributions, as well as broadened the social science contributions.

Last but not the least we are greatly indebted to our chief patron Prof. Syed Waseem Akhtar, Hon'ble Vice Chancellor, Integral University, who has been our motivator and has always gone an extra mile in giving his invaluable guidance. His constant encouragement and support has given us the much needed boost to do even better.

1Integral Review- A Journal of Management, Vol.8 No. 2, December 2015

KUWAIT FINANCE HOUSE: A CASE-STUDY IN THE ISSUES ANDCONCERNS IN THE FINANCIAL REPORTING OF ISLAMIC BANKS

1Camille Paldi

Abstract

This paper aims to shed light on the current unorganized state of financial reporting in Islamic

banks. In this exercise, I illustrate the negative effects of using conventional accounting standards in

Islamic banks rather than Islamic accounting standards and show how this leads to non-transparency

and the provision of inaccurate and misleading information to the general public and investors. I also

reveal how Islamic banks are not disclosing much of the information available on the financial

statements of a conventional bank and are inadequately providing information about Shari'ah

compliancy and the activities of the Shari'ah boards. The current state of financial reporting in Islamic

banks allows Islamic banks to conduct operations secretively and to hide negative information and

losses. The non-transparency of the emerging Islamic banking system should be a major concern for the

industry as this may lead to corruption and scandals, which may lead to the demise of the industry. At the

end of the paper, I make several key conclusions and recommendations for financial reporting in Islamic

banks. The paper is limited in proportion to the amount of limited information available in the financial

statements of Kuwait Finance House.

Key Words: Islamic Accounting, Financial Reporting, Islamic Finance, Maqasid al Shari'ah.

Executive Summary

In this financial and non-financial analysis of Kuwait Finance House Group (KFH), I have

conducted a ratio analysis of key liquidity, profitability, and efficiency ratios including the current ratio,

EPS, return on equity (ROE), return on assets (ROA), and the debt-to-equity ratio and compared KFH to

one of its main competitors, Gulf Finance House (GFH) in order to illuminate the financial health of

KFH. In addition, I have examined KFH accounting, disclosure, and reporting practices and their

suitability for an Islamic bank, remuneration practice, corporate and Shari'ah governance, corporate

social responsibility, significant changes in policy and strategy and their possible financial impact, and

have discussed risk mitigation and capital structure in order to provide a snapshot of the financial and

non-financial health of the institution for the benefit of a potential investor/depositor. I have investigated

1. Prepared in accordance with the Central Bank of Bahrain's requirements outlined in its Public Disclosure Module, Section PD 3.1.6 Additional Requirements for Semi Annual Disclosures, CBB Rule Book, Volume II for Islamic banks.


various reasons for the performance of KFH and explored the profitability of the investment and real

estate segments of the KFH conglomerate. The comprehensive analysis is based on the 2009-2011

annual reports of KFH and GFH, the 2009-2011 KFH Corporate Sustainability Reports, and the 2011

Public Disclosure Report of KFH Bahrain. In addition, I have examined and discussed relevant industry

standards including IFRS, IFSB, and AAOIFI regulations regarding accounting and capital adequacy

and explored the work of several academics including Haniffa, Safiedinne, Ahmed, Khan, Epstein,

Archer, Simon, and Karim, Sarea, Shabbir, and Van Greuning and Iqbal as well as the work of industry

practitioners such as Mohammad Amin and Michael Gassner. I conclude with recommendations to

KFH and the industry for the best way forward in terms of financial reporting practice. This paper is

directed at the stakeholders as defined in the KFH 2011 CSR Report.

Introduction: KFH at a Glance

KFH is organized into three major business segments including treasury, investment, and

banking (KFH 2011: 78). In 2011, KFH had 54 branches and was ranked among the best Islamic banks

in the world. KFH activities are conducted in accordance with the Shari'ah as approved by the Bank's

Fatwa and Shari'ah Supervisory Board (SSB) (KFH 2011: 51).

Ratio Analysis

Kuwait Finance House (KFH) has a fairly consistent current ratio for 2009 (.73:1),

2010(.73:1), and 2011(.70:1). Although the ratio is below 1:1, this doesn't necessarily indicate that KFH

is headed for a financial disaster, however, it does mean that KFH is working with negative working

capital. The current ratio for Gulf Finance House (GFH) gives a gloomy outlook for this international

financial institution in 2009 (.48:1), 2010 (.08:1), and 2011 (.01:1). In 2011, GFH only had .01 cents of

assets for every $1 of liability. Both banks are relying heavily on the fact that depositors do not withdraw

their deposits, however, GFH seems to be in a more vulnerable position. In terms of Earnings Per Share

(EPS), initially, a potential investor may feel uncomfortable with KFH as KFH starts in 2009 with (18.1

cents), 2010 (15.4 cents), and ends in 2011 at (10.8 cents). However, the reason for the sudden decline in

EPS may be due to a bonus share issue. GFH starts out in 2009 with an EPS of 272.17 cents, 2010 (76.84

cents), and ends in 2011 with .04 cents. This is an alarming rapid decline and also means that for every 1$

invested, the return for GFH is only .04 cents, indicating very low profitability for GFH.

KFH has a debt- to- equity ratio of 5.9 in 2009, 6.5 in 2010, and 7.3 in 2011. GFH's debt-to-

equity ratio is 2009(2.7), 2010(7.7), and 2011(2.53). It seems that KFH has been more aggressive than

GFH in financing its growth with debt in 2011 and appears to be a credit risk. If the cost of debt-

financing becomes greater than the return, this could negatively impact KFH's business. Therefore,

1Camille Paldi


KFH should seek the right balance of debt and equity finance so as to leverage its assets correctly,

especially with a declining EPS and turbulent economic conditions. Return on equity for KFH amounts

to 2009(22%), 2010(4%), 2011(9%) and for GFH 2009(13%), 2010(7%), 2011(31%). It appears that in

2011, GFH has a better ROE than KFH. Furthermore, KFH's ROE steadily declined from 2009 to 2011.

This is a worrying signal for potential KFH investors. Return on assets for KFH in 2009 is 6.4%,

2010(5.7%), and 2011(.01%) and for GFH in 2009(.03%), 2010(7.96%), and 2011(.09%). Once again,

GFH is more efficient in terms of return on assets although GFH also has a low figure and KFH sees a

rapid decline in ROA from 2009 to 2011, possibly worrying investors. In fact, in 2011, Moody's was

reviewing a downgrade for KFH due to the fact that the overall coverage level of provisions to problem

loans remained relatively low, approximately 73%. Provisioning needs also continued to weigh down

KFH's profitability, with the bottom-line only stabilising through relatively volatile investment income.

Moody's cited inefficient reporting as one KFH's key problems in addition to weak asset quality,

financing, and loan books, and problems in management and internal controls. Moody's stated that the

poor asset quality was due to concentrated exposures to non-banking financial institutions, real estate,

and underperforming investments. In fact, in May 2013, Moody's downgraded KFH's long term ratings

by one notch to A1 from Aa3. Moody's also downgraded KFH's baseline credit assessment (BCA) and

bank financial strength rating (BFSR) by two notches to ba1/D+ from baa2/C- respectively. The Prime-1

short term rating was confirmed. All ratings assigned to KFH in 2013 carry a negative outlook. Moody's

reported that the rating actions reflect (1) continued asset quality pressures; (2) an increasing reliance on

volatile investment income; and (3) the current organisational complexity and overall risk profile

inconsistent with global peers.

The exposure from excessive derivatives trading most likely added to the poor asset quality. In

addition, the bank may be overextended in real estate and investment. In 2011, KFH launched a one

billion KD real estate portfolio in collaboration with the Kuwait Investment Authority and KFH initiated

several real estate and special purpose financial funds including a gold traded fund and introduced

investment portfolios. KFH also partnered with Grosvenor Fund Management to invest up to £380m in

US healthcare real estate, having a combined investment capacity of £900m (Gassner: 2011). Perhaps

KFH should redirect some of these efforts towards its banking section.

Strategy

KFH introduced new products such as the al-Khumasiya five -year deposit, the gold

investment account and offers a continuous investment deposit, a three-year investment deposit, Sudra

investment deposit, and investment deposits in US dollars, Sterling Pound, and Euro. KFH also

introduced Visa, Mastercard, and pre-paid cards, ranking number one in credit card ratings in Kuwait and

Kuwait finance house: A case-study in the issues andconcerns in the financial reporting of Islamic banks


the Middle East. KFH utilizes an e-banking platform incorporating online services in addition to

iPhone, iPodTouch and iPadApp banking, SMS, as well as phone service (Allo Baitak) and provides a

service where one can open an investment deposit account through ATM machines in Kuwait. KFH also

received accreditation from Purdue University for outstanding customer service. In 2011, KFH

implemented a new five-year strategy, upgraded its operations systems, completed the change to

automated systems, and secured approval for providing e-corporate services (KFH 2011). Furthermore,

in 2011, KFH embarked on an extensive restructuring exercise to improve efficiency and internal

controls and to remove legacy management processes with the aim of addressing the company's

organisational complexity (Moody's). The three pillars of KFH's five year strategy can be seen below.

The strategic pillars include (1) Improving KFH's performance in Kuwait, (2) Enhancing KFH's

investment business; and (3) Leveraging KFH's international presence more effectively, generating

synergies across KFH banking operations in Bahrain, Malaysia, and Turkey.

New KFH 5- Year Strategy

Pillar 1 Improve KFH’s performance in Kuwait.

Pillar 2 Enhance KFH’s investment business.

Pillar 3 Leverage KFH’s international presence

more effectively, generating synergies

across KFH banking operations in Bahrain,

Malaysia, and Turkey.

Change in Board Membership

New Members of the KFH Board in 2011 included Chairman Sameer Yaquob Al-Nafeesi, a

powerhouse corporate giant who serves on the Board of numerous institutions and with over 33 years of

experience in the real estate market and Board Member Iman Al-Humaidan (female), who has written

Women and Waqf. The addition of the new Chairman may positively affect the profitability of KFH

especially in the real estate and investment sections, however, potentially steering KFH in the wrong

direction, and the addition of a well-renowned female Islamic finance academic was a good move for the

overall structure and outlook of KFH.

Accounting Practices

Although an Islamic bank and an associate member of AAOIFI, KFH Group with the exception

of KFH Bahrain does not officially adhere to the AAOIFI standards in its financial reporting. KFH

1Camille Paldi


financial statements are prepared in accordance with IFRS, however, KFH selectively and unofficially

follows FAS guidelines in some areas of reporting. New additions to IFRS in 2011 and revenue

recognition can be seen in Appendix A.

IFRS does not equip KFH with the necessary degree of disclosure and transparency in light of

Islamic modes of finance, as risk exposures of assets vary according to different types of contracts and

the mode may be used for sale or finance, which would result in different reporting implications.

Furthermore, there are many rules in the Shari'ah, which the IFI must abide by, which may affect

reporting requirements. General disclosures unique to IFI's are information about the Shari'ah Advisory

Board, policies on zakat, policies of profit distribution with IAHs, disclosures on prohibited earnings and

disclosures of concentration of asset risks involving unrestricted investment accounts. Many gaps in

disclosure occur due to use of conflicting standards.

For example, in regards to investment accounts, some IFIs treat such accounts as equity or

liability, while others report them as off-balance sheet items. Jordan Islamic Bank, Bahrain Islamic Bank

and Qatar Islamic Bank treat investment accounts that are based on mudarabah contracts as liabilities

and report them on- balance sheet. Other banks treat investment accounts as fiduciary investments and

report them off-balance sheet (Al Rajhi Bank and Shamil Bank of Bahrain)(Sarea 2012:27). KFH

reports restricted investment accounts off-balance sheet and discloses joint financial assets and

percentages of funds involving unrestricted investment account funds, which mitigates agency risk

involved with the commingling of funds (FAS1). Furthermore, in terms of FAS1, KFH discloses

compensating balances as balances with banks and financial institutions – (exchange of deposits), both

on the assets and liabilities sides of the balance sheet (Shabbir 2012).

According to Abdel Karim, reporting off balance sheet allows IFI's to hide negative

information such as losses because of misconduct or negligence (Safiddiene 2007:144). Under

mudarabah investment management, the IFI is not liable for loss arising from investments according to

Shari'ah. In IFRS, this would be presented as a liability along with other deposits, however, under

AAOIFI, unrestricted investment funds are to be presented as a separate item between liabilities and

owners' equity. In terms of Ijarah, AAOIFI requires both operating ijarah and ijarah muntahia bittamleek

to be treated as an operating lease. In IFRS, both operating ijarah and ijarah muntahia bittamleek are

classified as finance leases. Due to Shari'ah requirements, Ijarah contracts cannot be accounted for as

finance leases. Therefore, the leased assets are recognized in the books of the bank and not capitalized in

the customers books. The leased assets are then depreciated in the books of the bank, contravening IAS

17 (Ibrahim 2007). The 2011 KFH Annual report states that capitalized leased assets are depreciated

over the estimated useful life of the asset (KFH 2011:54). Furthermore, it is required for leasing with

gradual sale that the inventory be valued at fair values, not lower of historical cost or net realizable value.



Hence, IAS2 cannot be followed (Ibrahim 2007). The 2011 KFH Annual report states that finance leases

are capitalized at inception of the lease at fair value, or if lower, the present value of the minimum lease

payments (2011:54). The special nature of Islamic banking requires tailored standards in order to

promote full disclosure and transparency of the IFI. In contrast to conventional standards, one can see in

the table below the AAOIFI disclosure requirements specifically tailored for Islamic finance.

Disclosure Requirements for Islamic Finance (AAOIFI)

Capital Based on trust, profit sharing contract with no executive involvement.

Performance of fund (net asset value) and/or dividend return.

State outstanding balance, change in value and profit distributed (FAS 6).

Commingling of

Funds

IFI can utilise the funds and pool for financing or investment.

Funds utilised are to be identified vis-à-vis shareholders and other deposit funds.

Disclose joint financial assets and percentages of funds involving unrestricted investment account funds (FAS 1).

Investment

Policy

IFI can adopt a flexi investment policy in utilising IAH funds.

Decisions should be taken in the interest of an IAH.

Provide adequate disclosure on basis of investment policy

when mobilising IAH funds.

Profit and Loss Distribution

Mutually agreed profit distribution ratio and basis to be specified.

Mechanisms are specified and effectively communicated.

State PSR, income determination method, allocation basis and reserve management policy (FAS 5).

Reasonable Return

Effective return to IAHs is realised.

Smoothing of rate of return to IAHs.

Report policies, amount, and movements within PER (FAS 11).

Capital Recovery

Fund is safeguarded by ensuring capital is recovered prior to profit distribution.

Accrued profit not distributed until assurance provided that capital is not depleted.

Report policies, amount and movements of Investment Risk Reserve IRR (FAS 11).

1Camille Paldi


Another area for concern in the financial reporting of Islamic banks includes using

conventional standards for capital adequacy. At Kuwait Finance House, capital adequacy and the use of

regulatory capital are governed by the Basel Committee on Banking Supervision (KFH 2011: 87) rather

than the standards issued by AAOIFI and the IFSB. However, Islamic finance standards are required to

regulate deposits based on Wadi'ah (guaranteed safe custody) or Qard Hassan (interest free loan)

contracts, which are reported as liabilities in the balance sheet. At 31 December 2011, the total Capital

Adequacy ratio for KFH was 13.73% and Tier (1) 13.51% (2010: 14.22% and Tier (1) 14.15%)

compared to the ratio required by the regulatory authorities of 12% (KFH 2011 Annual Report, 31).

However, as KFH does not use the IFSB and AAOIFI standards for capital adequacy, this may not truly

reflect KFH's capital structure and stakeholders cannot truly assess whether capital structure decisions

were made to maximize shareholder equity. The IFSB and AAOIFI Capital Adequacy Standards are

listed in the table below.

IFSB Capital Adequacy Standard The IFSB has issued a capital adequacy

standard, which is based on the Basel II

standardized approach with a similar

approach to risk weights. However, the

minimum capital adequacy requirements for

both credit and market risks are set out for

each of the Shari’ah

compliant financing

and investment instruments (Van Greuning

and Iqbal 2008:83).

AAOIFI Capital Adequacy Standard The AAOIFI Statement on the Purpose and

Calculation of the Capital Adequacy Ratio

for Islamic Banks takes into account the

differences between deposit accounts in

conventional banking and investment

accounts in Islamic banking (Van Greuning

and Iqbal, 2008:59) recommending not

including the risk-sharing account deposits

in capital (Van Greuning and Iqbal

2008:81).



The 2011 KFH Annual Report states that no changes were made in respect to capital

management objectives, policies, and processes from the previous years, however, the dividend pay- out

to shareholders significantly decreased from 2010 to 2011, while directors' salaries increased.

Furthermore, profits distributed to investment account holders (IAH's) decreased from 2010 to 2011 as

seen in the table below. The table below reveals that Mustamera profit distribution to IAH's decreased

from 2.378% in 2010 to 1.728% in 2011, Sedra profit distribution decreased from 1.850% in 2010 to

1.344% in 2011, and Tawfeer profit distribution decreased from 1.585% in 2010 to 1.152% in 2011.

Deposit Type

2011% of Profit Distribution

to IAH’s

2010 % of Profit Distribution

to IAH’s

Khumasia: 2011 (1.920%)

Mustamera: 2011(1.728%) 2010 (2.378%)

Sedra: 2011(1.344%) 2010(1.850)

Tawfeer :

2011(1.152%)

2010(1.585%)

Investment Accounts

The Bank receives deposits from customers as part of several unrestricted investment accounts

“On Balance Sheet” and restricted “Off Balance Sheet.” In Unrestricted Deposits, these are invested by

the bank as Mudarib investing funds for limited or renewable periods at various investment ratios.

Investment returns are distributed among the bank as a Mudarib and investment account holders on

proportionate basis for each type of these accounts and the elapsed investment period (KFH 2011).

Investors' capital is not guaranteed and they incur losses if the bank does (Van Greuning and Iqbal

2008:35). KFH acts as an investment agent in restricted deposits.

In terms of depositors' accounts, non-investment deposits in the form of current accounts are not entitled

to any profits nor do they bear any risk of loss as the Bank guarantees to pay the related balances on

demand. Accordingly, these deposits are considered Qard Hasan from depositors to the Bank under

Islamic Shari'ah. Investment deposits comprising of Khumasia, Mustamera, and Sedra deposits are for

an unlimited period, initially valid for one year, and are automatically renewable for the same period

unless notified to the contrary in writing by the depositor. The Tawfeer savings accounts are investment

savings accounts valid for an unlimited period. In all cases, the investment deposits receive a proportion

1Camille Paldi


of the profit as the board of directors of the Bank determines or bear a share of loss based on the results of

the financial year. The bank generally invests approximately 100% of investment deposits for an

unlimited period (Khumasia), 90% of investment deposits for an unlimited period (Mustamera), 70% of

investment deposits for an unlimited period (Sedra) and 60% of investment saving accounts (Tawfeer).

The bank guarantees to pay the remaining un-invested portion of these investment deposits.

Accordingly, this portion is considered Qard Hasan from depositors to the Bank under Islamic Shari'ah.

Investing such Qard Hasan is made at the discretion of the Board of Directors of the Bank, the results of

which are attributable to the equity-holders of the Bank (KFH 2011:71).

According to the AAOIFI Shari'ah Standard No. 40 Distribution of Profit in Mudarabah-based

Investment Accounts, section 4/1, the method of profit distribution should be well-known so that no

room is left for uncertainty and dispute. Distribution of profits should also be in terms of ratios and not at

all by specifying a lump sum amount or a percentage of the capital for any party or any other method that

could lead to avoidance of sharing of the profit between the two parties (2004: 723). KFH has not

specified in its annual report the method of profit distribution, however, has listed the concerned ratio.

According to section 5/1, Distribution of Profit, Application of Scoring Method of Profit

Distribution, the scoring method for distribution of profit among the participants of general investment

accounts should be used. From the 2011 report, we cannot deduce the method used, however, all we can

see is that the ratio of profit decreases from 2010 to 2011 due to a decision of the Board of Directors

(AAOIFI 2004: 723). The dilemma currently experienced in terms of the divergence of accounting

standards and their implementation poses a great threat to the sustainability of Islamic financial

institutions. Appropriate management of PSIA, with proper measurement, control, and disclosure of the

extent of risk sharing and IAH's can be a powerful risk mitigant in Islamic finance (Van Greuning and

Iqbal 2008:59). The AAOIFI and the Islamic Finance Supervisory Board recommend that Islamic banks

accurately disclose the returns on IAH and shareholder funds, the bases and the percentages for the

allocation of assets, and profits and expenses in a way to enhance transparency and enable investors to

monitor the performance of their investments (Safieddine 2009: 144).

Remuneration Committee

The Board of Directors of the Bank proposed a cash dividend of 15% for the year ended 31

December 2011 decreasing from 20% in 2010. At the same time, Directors' fees increased to KD 260

thousand in 2011 from KD 160,000 in 2010 (KFH 2011: 74). As the Annual Report does not contain a

remuneration committee report, we cannot see how and why these decisions were made.



Shari'ah Governance Board

A transparent financial institution would ideally reveal the duties, decision-making,

competence, and composition of the Shari'ah Board, as well as publish all fatwa issued by the Board.

However, in a one page report, KFH merely certifies that most decisions made were Shari'ah compliant

and for those that were not, the funds have been donated to charity and provides the names and pictures of

the members (Van Greuning and Iqbal, 2008:36). KFH unofficially adheres to FAS 1 in terms of zakat

and qard-hassan reporting. In 2011, zakat was calculated at 2.5777% and charged to the consolidated

statement of income (KFH 2011:59).

Corporate Governance

KFH lacks any meaningful corporate governance structure to address potential agency

problems concerning investment accounts nor for the organization as a whole, except through unofficial

compliance with minimal FAS standards.

Disclosure

Although the statements have been certified by Ernst and Young as a true and fair representation and

KFH compliance with capital adequacy regulations, if KFH does not adhere to the standards set out

specifically for Islamic banking, the statements may not in reality be a true and fair representation of the

position of KFH and the capital structure management may not have been carried out in a manner to truly

maximize shareholder's equity and this would remain unknown to the stakeholder.

Risk Mitigation

The table below illustrates the credit risk exposure, liquidity risk, and equity price on the

Kuwait Stock Exchange for KFH in 2010 and 2011.

KD000’s

2010

2011

Credit Risk

Exposure

KD11941780 KD12588420

Liquidity Risk 23% 22%

Equity Price on

Kuwait Stock

Exchange

KD2740 KD2920

1Camille Paldi


KFH slightly reduced liquidity risk even though credit risk increased, indicating effective capital

structure management in the advent of business expansion and a slightly increasing ability to meet

demand deposit withdrawals. One cause for concern is the use of derivatives by KFH, which is not

Shari'ah compliant and which exposes the assets of its business to a whole new set of risks, potentially

resulting in loss of profits in the long-run.

Notes to the Financial Statements

As KFH Group adheres to IFRS, gaps in disclosure may occur and there runs a risk of non-

Shari'ah compliance. The table below illustrates which AAOIFI standards KFH, with the exception of

KFH Bahrain, voluntarily adheres to in its financial statements.

Are AAOIFI Standards Addressed in the Notes to KFH's 2011 Statements?

Standard Yes No

FAS No.1 requires that restricted investment accounts should be reported off -balance sheet in the statement of the changes in restricted investments.

x

FAS No.3 disclosure should be made in the notes to the financial statements for a financial reporting period if the Islamic bank has made during that period a provision for decline in the value of Mudarabah

assets.

x

FAS No.4 disclosure should be made in the notes to the financial statements for a financial reporting period if the Islamic bank has made during that period a provision for a loss of its capital in Musharaka financing transactions.

x

FAS No.5 requires bank to disclose percentages for pr ofit-allocation between investment account holders and the bank.

x

FAS No.6 disclosure should be made, in the notes on significant accounts, of the percentage of the funds of unrestricted investment. Distinguishes reporting requirements of unrestricted (on balance sheet item) and restricted (off balance sheet item) investment accounts.

x

Fas No. 9 on Zakat x

FAS No.10 requires that the Islamic bank shall disclose in its financial statements revenues and profits of Istisna’a contracts recognized for the financial period.

x

FAS No.11 requires that the Islamic bank shall disclose in the notes any deductions, either as a percentage or an amount, from mudarabah income. Introduces the Profit Equalisation Reserve (PER) and Investment Risk Reserve (IRR) to protect IAHs’ interests

by ensuring stable distribution rate of return to

IAHs as well as ensuring capital recovery prior to realisation of distributable profit.

x



Fas No. 14 on Investment Funds

x

FAS No. 17 on Investments

x

FAS No.20 requires that the bank shall disclose in the notes to the financial statements the policy adopted in financing deferred payment sale transactions.

x

FAS No.21 require that disclosures shall be made of the accounting policies adopted in the transfer of assets from unrestricted investment accounts to restricted investment accounts.

x

FAS No.23 requires consolidated financial statements shall be prepa red by combining the financial statements of the IFI.

x

It appears that KFH follows the basic disclosure requirements of AAOIFI even though it

officially adheres to IFRS, however, there is a gap in relation to the more detailed requirements of the

AAOIFI standards. However, all of these requirements appear to have been met in the KFH (Bahrain)

B.S.C.(c) Public Disclosure Report,as AAOIFI standards are officially followed in Bahrain.

Corporate Sustainability Report

KFH was the first bank in the world to issue a corporate sustainability report in 2009, which

constitutes voluntary disclosure. In 2011, KFH won the Best CSR Programme in the Middle East by

EMEA Finance and donated approximately KD 9 million including KD 4 million paid to the Zakat

House and KD 5 million to alleviating the effects of famine and drought in the region of the Horn of

Africa (KFH 2011). KFH also has many programs related to Diabetes (KFH 2011: 24-25) and

introduced the Qu'ran App for iphone as well as an iphone application for monitoring Diabetes. In

addition, KFH offers the Jameati Saving Account for Higher Education, encouraging their employees to

save for their childrens' college educations (KFH 2011) and actively supports Islamic educational and

social events, especially pertaining to Qu'ran recitation. The CSR Report also indicates employee's

welfare, training and development, recruitment schemes, equal opportunity, reward to employees, and

special services for women (Haniffa 2007:101). In terms of voluntary disclosure and social support

activity, KFH ranks number one in the world.

Conclusion

Concerns for investors include the worrying debt-to-equity, ROE, and ROA ratios, overextension in the

real estate and investment businesses, the declining dividend pay-outs and increasing salaries along with

the decreasing percentage of profits to investment account holders, and the Moody's downgrade.

Another destabilizing factor could be the use of derivatives to hedge risk and/or speculate and the lack of

transparency in the reporting of the investment accounts, remuneration committee, Shari'ah Board, and

1Camille Paldi


the Group as a whole. Agency problems involving the investment accounts can be mitigated if KFH

Group opted to adopt the structure of the KFH Bahrain Public Disclosure Report in its financial

reporting, which adheres to AAOIFI standards. My recommendation to KFH is to utilize the Bahrain

Public Disclosure Report in the KFH Group consolidated financial statements either as a separate

additional report or included in the Notes to the Group consolidated financial statements. Furthermore, I

recommend KFH to issue a Remuneration Report and to develop a comprehensive corporate governance

structure as well as issue a more substantial Shari'ah Supervisory Board Report so as to ensure Shari'ah

compliance. KFH should also consider taking the lead as the first Islamic bank to introduce a system of

guaranteeing deposits in order to attract greater clientele and ensure industry-wide stability. Otherwise,

KFH remains the best Islamic bank in Kuwait and the Middle East and is the best Islamic bank in terms of

Corporate Social Responsibility (CSR).

Bibliography

lAAOIFI (2010).Shari'ahStandards for Islamic Financial Institutions. AAOIFI: Bahrain.

lAhmed, Habib (2011).Product Development in Islamic Banks.Edinburgh University Press:

Edinburgh.

lAhmed, Habib and Tariqullah Khan (2007).Risk Management in Islamic Banking. In M. Kabir

Hasan and Mervyn K. Lewis (Editors), Handbook of Islamic Banking (pp. 144-160). UK:

Edward Elgar.

lAmin, Mohammed (2011, 9 February). What is AAOIFI's Proper Accounting Role? Retrieved

from http://www.mohammedamin.com/Islamic_finance/AAOIFI-proper-accounting-

role.html.

lArcher, Simon and Rifaat Ahmed Abdel Karim (Editors)(2007). Islamic Finance: The

Regulatory Challenge. John Wiley & Sons (Asia) Party Limited: Singapore.

lEpstein, Lita (2012).Reading and Understanding Financial Statements, How to Budget,

Forecast, and Monitor Cash Flow for Better Decision-Making. John Wiley & Sons, Inc.: New

Jersey.

lGassner, Michael (2011, 3 October).Grosvenor Joins Up with Kuwait Finance House for

£ 3 8 0 m U S H e a l t h C a r e R e a l E s t a t e Ve n t u r e . R e t r i e v e d f r o m

http://www.islamicfinance.de/?q=node/2921.

lHaniffa, Roszaini (2007).Exploring the Ethical Identity of Islamic Banks via Communication

in Annual Reports. Journal of Business Ethics, 76, pp. 97-116.

lKuwait Finance House 2009, Annual Report 2009, Kuwait Finance House, Kuwait City,

Kuwait.



Kuwait Finance House 2010, Annual Report 2010, Kuwait Finance House, Kuwait City,

Kuwait.

lKuwait Finance House 2011, Annual Report 2011, Kuwait Finance House, Kuwait City,

Kuwait.

lKuwait Finance House 2009,Corporate Social Responsibility Report 2009, Kuwait Finance

House, Kuwait City, Kuwait.

lKuwait Finance House 2010,Corporate Social Responsibility Report 2010, Kuwait Finance


lKuwait Finance House 2011, Corporate Social Responsibility Report 2011, Kuwait Finance


lKuwait Finance House (Bahrain) B.S.C.(c) 2011, Public Disclosure Report 2011, Kuwait

Finance House, Manama, Bahrain.

lGulf Finance House 2009,Annual Report 2009, Manama, Bahrain.



lIFSB (2005).Guiding Principles of Risk Management for Institutions (Other than Insurance

Institutions) Offering only Islamic Financial Services. Islamic Financial Services Board:

Kuala Lumpur, [http:/www.ifsb.org/standard/ifsb1.pdf].

lIFSB (2005).Capital Adequacy Standard for Institutions (Other Than Insurance Institutions)

Offering Only Islamic Financial Services. Islamic Financial Services Board: Kuala Lumpur,

[http://www.ifsb.org/standard/ifsb2.pdf].

lIqbal, Munawar and Tariqullah Khan (2005).Financial Engineering and Islamic Contracts.

IRTI and the International Association of Islamic Economics: Jeddah.

lKhan, Tariqullah and Habib Ahmed (2001).Risk Management: An Analysis of Issues in

Islamic Financial Industry.IRTI: Jeddah.

lMoody's Announcement in Regards to KFH Downgrade. Retrieved from

http://www.moodys.com/research/Moodys-places-all-ratings-of-Kuwait-Finance-House-on-

r e v i e w - - P R _ 2 5 9 1 0 9 a n d

http://www.moodys.com/page/viewresearchdoc.aspx?docid=PR_273062&WT.mc_id=NLTI

TLE_YYYYMMDD_PR_273062%3C/p%3E.

lSafieddine, Assem (2009). Islamic Financial Institutions and Corporate Governance: New

Insights for Agency Theory.Corporate Governance: An International Review, 17(2), pp.142-

158.

l

1Camille Paldi


Sarea, Adel Mohammed (2012). The Level of Compliance with AAOIFI Accounting

Standards: Evidence from Bahrain. International Management Review, 8(2), pp. 27-32.

Shabbir, Muhammad (2012). Adequacy Disclosure in Islamic Financial Institutions.

Retrieved 14 May, 2013 from http://www.islamic-banking.com/iarticle_5.aspx.

lVan Greuning, Hennie and Zamir Iqbal (2008). Risk Analysis for Islamic Banks. World Bank:

Washington D.C.

Appendices

A Revenue Recognition for KFH 2011 Annual Report

Appendix A:

In terms of revenue recognition by KFH, financing income is income from murabahah,

istisna'a, and wakalah investments and is determined by using the effective profit method. The effective

profit method is a method of calculating the amortized cost of a financial asset and of allocating the

financing income over the relevant period; Income from leased assets is recognized on a pattern

reflecting a constant periodic return on the net investment outstanding and is included under financing

income; Operating lease income is recognized on a straight line basis in accordance with the lease

agreement; Rental income from investment properties is recognized on an accruals basis; Dividend

Income is recognized when the right to receive is established; and Fee and commission income is

recognized at the time the related services are provided (KFH 2011). The below table states the new

accounting standards for KFH in 2011.

l

l

New Accounting Standards for KFH in 2011

IAS24-

Related Party Disclosures (Amendment), effective 1 January 2011.

IAS32-

Financial Instruments: Presentation-Classification of Rights Issues (Amendment),

effective 1 February 2010.

IFRIC 14 -Prepayments of a Minimum Funding Requirement (Amendment), effective 1

January 2011.

IFRIC 19 - Extinguishing Financial Liabilities with Equity Instruments, effective 1 July

2010.

IAS1- Financial Statement Presentation – Presentation of Other Comprehensive Income.

IFRS7 - Financial Instruments: Disclosures – Enhanced De-recognition Disclosure

Requirements.

IFRS 9 - Financial Instruments: Classification and Measurement.



IFRS10 -

Consolidated Financial Statements.

IAS27-

Separate Financial Statements.

IFRS 11 -

Joint Arrangements.

IFRS 12 -

Disclosure of Involvement with Other Entities.

IFRS 13 -

Fair Value Measurement.

IAS28 - Investments in Associates and Joint-Ventures (as revised in 2011).

1Camille Paldi


MEASURING ORGANIZATIONAL SERVICE ORIENTATION:VALIDATING SERV*OR SCALE IN INDIAN CONTEXT

1Sanjeev Kumar Saxena

Abstract

Purpose/objectives: With advent of globalizations and openness of the Indian economy after

liberalization policies, Indian firms in lines with global competitors are becoming market & service

driven. Recent marketing literature has acknowledged the role of a firm's service orientation in

achieving a sustainable competitive advantage. Given this backdrop, this study has used improved

version of the widely accepted scale SERV*OR (Lytle et al., 1998), named as i-SERV*OR, for measuring

service orientation of the organization. i-SERV*OR is validated for its application to different types of

organizations (Service, Manufacturing & hybrid). The items of the scale have been factor analyzed and

verified for internal consistency. Variations of service orientation scores across sets of organizations

have been studied using one way ANOVA. The study is first of its kind, as far as using a common scale for

measurement of Organizational Service Orientation for all types of firms. Future research may be

carried out across countries of both developed and developing economies for wider acceptance of (i-

SERV*OR) scale.

Design and Methodology:

The questionnaire based on modified version of SERV*OR scale, covered wide variety of

service and manufacturing firms from both the private and public sector across India. The response rate

of 522 responses was around 85%. The Statistical Package for Social Sector (SPSS) version 22 and MS

excel has been used to analyze the given data. A reliability analysis was performed to investigate the

internal consistency of the survey instruments used in this study. Cronbach's alpha coefficients were

calculated to examine the reliability of the scales. Variations of service orientation scores across

organization have been studied using one way ANOVA.

Findings:

This study has improvised SERV*OR scale to a modified scale called i-SERV*OR to reflect 11

Dimensions, applicable to all sets of organizations (Service, Manufacturing & hybrid) for measuring

1. Sanjeev Kumar Saxena, Doctoral Programme Fellow, BITS, Pilani and Additional General Manager, Ordnance Factory Board, Ministry of Defence, Kolkata 700001 email: [email protected]


service orientation of Indian firms. 11 dimensions include: Customer Treatment, Employee

Empowerment, Service Technology, Service Failure Prevention, Service Vision, Service Standard

Communication, Service Failure Recovery, Service Rewards, Service Leadership, Service Training &

Real time Management Information System. The extent of organizational service orientation varies

across the three sets of industries i.e. service, manufacturing and hybrid organizations. The result reveals

that a significant share of variation is associated with “within group variation”, with a minor variation

existing “between groups”. The ANOVA results show that service orientation scores are statistically

different for the three sectors.

Originality/Value:

The study is first of its kind, as far as using a common i-SERV*OR scale for measurement of

Organizational Service Orientation for all sets of firms i.e. service, manufacturing and hybrid

organizations in Indian context.

Key Words: Organizational service orientation, i-SERV*OR scale, Indian context

Paper type: Research Paper

Introduction

The interest of researchers in service orientation dates back to 1972, when Adair (1972) first

used the concept and identified it as an important trait in librarians. One of the ? rst studies exploring the

service orientation concept was carried out by Parkington and Schneider (1979) who investigated

simultaneously employees' perceptions of organizational service orientation and individual employee

service orientation. Despite the strategic importance of examining this service orientation discrepancy,

the majority of studies either focused on the exploration of employees' perceptions of organizational

service orientation (e.g. Johnson, 1996; Lytle et al., 1998; Webster, 1993) or on individual service

orientation (e.g. Cran, 1994; Hogan et al., 1984).

Lytle and Schilling (1994) defined Service orientation as 'a collection of organizational

activities undertaken by service firms designed to secure the creation and delivery of excellent services

in strategic response to market information'. Lee et al (1999) defined service orientation as 'a strategic

response to market information which is designed to implement marketing concept within the overall

framework of customer oriented services'. Thus a service-oriented organization puts a strategic

emphasis on providing an excellent service on the belief that doing so will enable the organization to

promote its value as perceived by both customer and employee and to secure customer satisfaction which

results in competitive advantage and higher performance.

India is among the fastest growing economy of the World, with GDP growing steadily at 7.3%

Sanjeev Kumar Saxena1


(2014-15) which is higher than that of the other developing economies. Indian economy has also gone

for integration with the global economy to usher in global competition. This has brought in efficient

manufacturing with economic growth. As a result, the corporate landscape has witnessed major changes

in terms of competition from both imports and multinationals in the domestic markets (Aggarwal et al,

2004; Dangayach et al, 2001). Sapna Popli et al (2015) in recent study in specific context of the private

service sector organizations in India, found that Service orientation is found to be strongly correlated to

employee engagement and employee engagement is a strong predictor of service orientation.

It is observed from the available literature that most of the research studies on Organizational

Service Orientation and how it affects organizational performance have been undertaken in context of

US, Europe and few in Chinese & Korean Service industries. Further most of the studies have used

SERV*OR scale to measure Organizational Service orientation for Service Industries in above

countries. Not much research has been undertaken to test applicability of SERV*OR scale to

Manufacturing Organizations or to develop different and/or modified scale applicable to manufacturing

firms. It is also not attempted to develop universal scale for measurement of Organisational Service

Orientation for all types of organisations i.e. service, manufacturing and hybrid (having characteristics

of both service & manufacturing). This is important in today's context of manufacturing industry

individualization in regard of a combination of products and services offer a huge differentiation factor

and there is the need for a shift from a product-centric view towards a service-dominant perspective.

Given this backdrop, this study has developed a scale for measurement of service orientation of

the organization (named as i-SERV*OR), applicable to all types of organizations i.e. Service,

Manufacturing & Hybrid. The study has also examined the extent of similarity or difference between the

service orientations across the three types of organizations. Thus an attempt has been made to develop a

common Service Orientation measurement Scale suitable for all types of organizations in the Indian

context.

Theoretical Development

In literature, Service orientation construct has been researched with wide variety of

organizational perspectives. It is argued that the interaction between employees and customers is

influenced positively by the internal processes and systems that are invisible to the customers (Gronroos,

1990; Langeard et al, 1981). Internal services management practices and procedures are important for a

positive service delivery to customers as they have an impact on how employees perceive the service

orientation of the organization (Schneider et al., 1985). The service encounter is dependent on the

attitudes and behavior of customer facing staff, a concept that has been defined as individual service

Measuring Organizational Service Orientation:Validating Serv*or Scale in Indian Context


orientation (Hogan et al., 1984). It is observed that service orientation has been viewed from a wide

angled view from individual employee service orientation to 'the philosophy implied by (or attributed by

others to) the policies, procedures and goals of management', as one of the key elements of

organizational characteristics responsible for creating a culture, beliefs, values and behaviors of an

organization that influence employee performance and also as 'a strategic response to market

information'.

Recent marketing literature has acknowledged the role of a company's service orientation in

achieving a sustainable competitive advantage. The service orientation, the relationship and strategy

between the company and the customer, is arguably the most important area for a business to study. Over

the last decade, it has become crucial for businesses to fundamentally understand and satisfy consumer

needs in order to succeed in a highly competitive market environment (Keillor et al., 1999). These new

considerations, while extended in scope, clarify several points about service orientation. As a result, its

antecedents and consequences have been widely studied (Homburg et al., 2002; Kelley, 1992; Lytle et al,

2006; Marinova, Ye et al., 2008).

Measurement of Service Orientation

The major breakthrough in measurement of the extent of service orientation can be credited to

Lytle et al. (1998) for the development of the SERV*OR scale. Two fundamental positions are used to

define Organization's Service Orientation (OSO). First, OSO as a dimension of an organization's overall

climate (Schneider, et al 1996; Schneider et al., 1993; & 1995).Second, OSO as a measure by soliciting

employee's perceptions, beliefs, and opinions (Schneider et al., 1993; Brief et al., 1996; Schneider et al,

1992). These studies demonstrate that service orientation is dependent on Service leadership practices,

service encounter practices, human resource management practices and service systems practices. .

Lytle et al. (1998) developed a scale named as SERV*OR and identified four major components with 10

sub dimensions of service orientation - 1) Service leadership consisting of two sub dimensions: i)

Service leadership & ii) Service vision 2) Service encounter consisting of two sub dimensions: i)

Customer focus ii) Employee empowerment 3) Service system consisting of four sub dimensions: i)

Service failure prevention ii) Service failure recovery iii) Service technology iv) Standard

communication and 4) Human resource management consisting of two sub dimensions: i) Service

training ii) Service reward.

Service leadership practices comprises of service leadership and service vision. Leadership

is, most likely, the critical and integral ingredient necessary for creating and maintaining an effective and

positive service orientation (Heskett et al., 1997; Kotter et al., 1992; Schneider, 1990). A "top-down"

service vision is important and necessary to instil widespread aspirations of providing quality service



among organizational members (Albrecht et al., 1985; Heskett, 1986; Heskett, 1987; Heskett et al.,

1990).

Service encounter basically means “employee interaction with customer”. They are

important within the service orientation paradigm because often brief encounters with customers form

the basis of important customer service quality evaluations (Parasuraman et al., 1988; Zeithaml et al.,

1996; Rust et al., 1996). Two important dimensions of service within the service orientation model are

measures of actual customer treatment practices and measures of employee empowerment. How

customers are treated directly impacts their perceptions of service performance and customer

satisfaction (Berry et al., 1994; Bitner et al., 1990; Jones et al., 1995; Schneider et al., 1992).Thus,

organizations must consistently engage in practices enacting the "golden rule" during service encounters

to create positive customer perceptions of service performance thereby enhancing customer satisfaction.

Empowered employees have the responsibility and authority to meet customers' needs as quickly and

effectively as possible. Empowerment refers to a situation in which the manager gives employees the

discretion to make day-to-day decisions about job-related activities (Conger et al., 1988). They form an

integral part of service encounter.

An organizational service orientation requires service systems that include (1) service failure

prevention and recovery practices, (2) service standards communication practices, and (3) high levels of

service technology adaptation. At the heart of a service system are practices that (1) function to pro-

actively prevent service failures and (2) function to respond effectively to customer complaints or

service failures. Service failure prevention and recovery are important determinants of service quality

(Berry et al., 1994; Kelley et al., 1994; Johnston, 1994). The utilization of "cutting-edge” technology is

critical to creating a service system for the delivery of outstanding service quality (Bowen et al., 1989;

Heskett et al., 1997; Jones and Sasser, 1995; O'Connor et al., 1995;Zeithaml et al., 1996). In order for the

service system to work effectively, service standards or benchmarks must be understood by all members

of the organization (Benoy, 1996; Bowen et al., 1989; Chase and Bowen, 1991; Hallowell et al., 1996;

Heskett, 1986; Treacy et al.,, 1993).

Human resource management: An organizational service orientation would involve a focus

on service-oriented human resource management throughout the organization, a model of service

orientation must include measures of service training and service rewards practices (Lytle et.al. 1998).

Employee contact skills such as courtesy, attitude or helpfulness (Benoy, 1996) are instrumental in

provision of quality services to customers. Advanced quality-based team training, problem-solving

training, inter-personal skills training must be imparted to employees, as Schlesinger and Heskett (1991)

suggested that value investment in people is equally important as value investment in machines; the

authors further advocated for specific investment in service skill training so as to make employees



empowered to meet complex demands of customers. An important element of service quality is the link

between employee compensation/reward and service performance (Berry, Parasuraman, and Zeithaml,

1994; Heskett, Sasser, and Hart, 1990; Roach, 1991; Schlesinger and Heskett, 1991; Schneider and

Bower,, 1995). Specific compensation and rewards have found to been linked with service-related

employee behavior (Benoy, 1996; Hartline and Ferrell, 1996; O'Connor and Shewchuck, 1995). Works

of Schneider and Bowen (1993) also acknowledges the importance of service rewards and

compensation. Steve Macaulay Sarah Cook, (2001) stated that linking rewards to customer satisfaction

and taking account of the needs of internal customers, has a critical role in motivating groups and

individuals to keep the energy focused on customer; which in effect improves performance.

Management Information system: With recent technological advancements and application

of communication, internet and e-commerce other dimensions/constituents like Management

Information system (MIS), e-services & delivery etc. have also become relevant. In the context of

Management of Information Systems (MIS), Cherbakov et al (2005) argued that service oriented

enterprise is "an enterprise able to deal with the challenges of the emerging business environment".

Therefore real time management information system is also an important dimension of Service

Orientation, as it gives flexibility and faster decision making as per customers' changing requirements.

It is observed from the available literature that most of the researches focuses on Organizational Service

Orientation and how it affects organizational performance have been undertaken in the context of US,

Europe, Chinese & Korean Service industries. Further most of the studies have used SERV*OR scale to

measure Organizational Service orientation for Service Industries in above countries. Not much research

has been undertaken to test applicability of SERV*OR scale in manufacturing Organizations or to

develop suitable new and/or modified scale applicable to manufacturing firms. Further, there has been

no attempt to develop a common scale applicable for measurement of Organisational Service

Orientation for all types of organisations i.e. service, manufacturing and hybrid (having characteristics

of both service & manufacturing).

Methodology& Research framework

The research is designed to empirically validate and improvise, most widely service

orientation measurement scale SERV*OR in Indian context covering wide variety of Indian industries

from both Service sector and Manufacturing sector including hybrid organizations (having

characteristics of both service & manufacturing). This study intends to bridge the gap in research in

Indian context to develop a measure for organizational service orientation. The study also attempts to

examine the impact of organizational service orientation on the nature of the organization (i.e., whether it

is a manufacturing or service business firm). Whether a common measure of service orientation can be



used for both service firms and manufacturing firms has not been tested in the previous researches.

This study has been carried out in context of Indian business firms with an important feature of Cross-

sectional design. Cross-sectional design of research has been undertaken by many researchers to assess

the relations among the constructs so as to improve the precision of the theoretical structure connecting

the constructs (Lillis & Mundy, 2005). Hence, the time window is of no specific importance. It is known

that such a design is best suited to explore the variation in individual behavior, in our case of individual

firms, but not across time dimensions (Frethey-Bentham, 2011). To obtain the snapshot of the firms to

test the hypothesized model, this study used questionnaire-based surveys.

Sample Description

From a geographical perspective, this study is not limited to any city or region. All Business

firms in India having structure & functions like Operations/ manufacturing, marketing and Finance are

eligible for selection in this study. Convenience sampling has been resorted to covering wide variety of

Indian firms.

The profile of the firms selected in the final sample is given in Table 3.1. The table classifies the

firms into the industry sectors they are operating in at present, on the basis of the classifications provided

in the CMIE Prowess database. These firms belonged to both domestic and also to MNC categories as

well. The responses received have been classified into large corporate organizations and Mini, small and

medium enterprises (MSMEs). The table 3.1 clearly shows that the sample is heterogeneous.

Appendix

Table 3.1: Profile of the Respondent Firms (N = 174)

By industry type N

Automobile & Auto ancillaries 9

Bank & Financial services 61

Cement, Ceramics & Abrasives 3

Chemicals 16

Electrical & Electronics 7

Heavy Engineering & Equipment 59

Industrial Construction 21



ITES & Software 89

Logistics & Courier 6

Machine tools 1

Market research 2

Metals & Steel 37

Petroleum, Petrochem & Plastics 6

Services (including Communication services & Telecom) 131

Others* 74

By management pattern

Indian firms 480

MNCs operating in India 42

By turnover (in Rs. crores)

50-100 80

100-1000 372

1000-10000 70

More than 10000

*Others consist of Construction, Footwear, Media content, and Media printing



Schematic diagram of research methodology

Short-listing of dimensions of

Organizational Service Orientation

based on available Literature

Dimensions based on

recommendation of Expert group

Finalizing questionnaire for survey and distribution

Pilot Survey

Reliability check for pilot data

and re-examination by expert

Development of scale for Organizational Service

Orientation

Based on Literature available, dimensions of service orientation were shortlisted. These

dimensions were given to a Focus Group, consisting of 5 experts with different industry background, as

shown in Table 3.2.

Table 3.2: Formulation of expert group

No. of Experts Industry

1 Power sector

1 Petrochemicals

1 IT & Consulting

1 Financial Services

1 Academics

Development of measurement Instrument

For developing a scale for measuring Organizational Service Orientation following

methodology was adopted. The steps followed during research is presented below:



Based on recommendations of this Focus Group, 11 dimensions were identified for

measurement of Service Orientation. It was observed that 10 dimensions were similar to that of

SERV*OR scale Lytle et al (1998). One dimension was related to Management Information System

(MIS), (Cherbakov el at, 2005). Thus as per recommendation of Focus Group experts it was suggested

that 35 items to measure 10 Dimensions as per SERV*OR scale Lytle et al (1998) with additional two

items on Real time information and feedback system related to Dimension on real time Management

Information may be utilized in the survey Questionnaire to measure Organizational Service Orientation.

Thus survey Questionnaire includes 37 items to reflect 11 Dimensions. This scale may be termed as i-

SERV*OR. These 11 Dimensions of Organizational Service Orientation are listed below.

Table 3.3: Dimensions and items of i-SERV*OR scale

The questionnaire for this part of the survey is henceforth referred as i- SERV*OR scale Survey

is enclosed in appendix. The data for customer-based brand equity (CBBE) is received from the contacts

in the customer firms, as provided by the respondents to the Marketing Survey. We use the term

Customer Survey for this questionnaire. The data from the two surveys, Marketing and Customer needs

to be linked for the purpose of our study i.e. to test the relationships.

Analysis

The reliability construct was carried out separately for the service sector, the manufacturing

sector and the hybrid sector. The reliability analysis revealed that all the items of the scale have

converged with the respective constructs satisfactorily and with high degree of accuracy. Around 2000

questionnaires were dispatched to managers of medium and large industries. The questionnaires were

S. No. Dimension No. of items to measure the Dimension

1 Customer Treatment 4

2 Employee Empowerment 2

3 Service Technology 3

4 Service Failure Prevention 3

5 Service Vision 3

6 Service Standard Communication

5

7 Service Failure Recovery 4

8 Service Rewards 2

9 Service Leadership 6 10 Service Training 3

11 Real time MIS 2



randomizes along the cross-sectional unit of industries over space to capture the real scenario. The

questionnaires covered the service sector and the manufacturing sector as well. Further, both the private

and public sector undertakings were covered. The response rate was calculated to be around 28%. The

responses were examined and those with a near constant level of standard deviation were excluded. Thus

522 valid responses were considered to proceed with the study. The response rate for these 522

questionnaires was around 85%. The Statistical Package for Social Sector (SPSS) version 22 and MS

excel has been used to analyze the given data.

A reliability analysis was performed to investigate the internal consistency of the survey

instruments used in this study. Cronbach's alpha coefficients were calculated to examine the reliability of

the scales. Nunnally and Berstein (1994) suggested that a Cronbach's alpha coefficient greater than 0.70

is reasonably reliable. However, an alpha coefficient for a scale with less than six items can be much

smaller (0.60 or higher) and still be acceptable. Therefore, a Cronbach's alpha around 0.60 was

considered to be acceptable for this study. The tables below reveals the level of reliability for the service

sector, the manufacturing sector and the “hybrid” group of industries which exhibit characteristics of

manufacturing and service.

Table 4.1: Reliability Statistics

Service Industry

Manufacturing Industry

Hybrid Industry

Instrument

Factor

No of Items

Cronbach’s Alpha

Cronbach’s Alpha

Cronbach’s Alpha

Service Orientation

Customer Treatment

4

0.78

0.79

0.79Employee Empowerment

2

0.57

0.57

0.69

Service Technology

3

0.83

0.84

0.86Service Failure Prevention 3 0.69 0.8 0.78

Service Vision 3 0.69 0.79 0.75Service Standard Communication 5 0.76 0.8 0.84Service Failure Recovery

4

0.77

0.79

0.82

Service Rewards

2

0.58

0.72

0.58Management Information System

2

0.75

0.83

0.82

Service Leadership

6

0.87

0.9

0.88

Service Training

3

0.87

0.88

0.85

i-SERV*OR Scale 37 0.9 0.89 0.93



Descriptive Statistics of Factors

Descriptive statistics were calculated to show the mean and standard deviation of the factor

scores measured in this study. All the scales were five-point Likert scales (1= strongly disagree and 5=

strongly agree). The mean score of service orientation (M= 3.77) was highest for the service sector,

followed by “hybrid” and then by the manufacturing sector.

Table 4.2: Descriptive Statistics

A comparison between the 11 dimensions of i-SERV*OR and the service orientation score for

the three industrial segments have been carried out.

lIn the dimension of “customer treatment”, service sector leads followed by the “hybrid” sector

and then by “manufacturing”. The scores are in tally with reality in the sense that, customer

treatment forms a vital part in interaction with customers; it is a key step towards creating

business. The importance and emphasis of customer treatment in service industry has

highlighted its importance in industries.

lAverage score of the dimension “employee empowerment” in “hybrid” industry is the highest

followed by “service” and then by “manufacturing”. Indian manufacturing industry seems to

be lacking in this dimension, the reason to which can be traced to the fact that Indian

manufacturing industry is still in the nascent stage of progress.

lService technology has a significant impact in the service sector and hybrid sector. The reasons

Service Industry

Manufacturing Industry

Hybrid Industry

Instrument

Factor

Mean Std.

Dev.

Mean Std. Dev.

Mean

Std. Dev.

Service Orientation

Customer Treatment

4.01

0.66

3.84

0.68

3.95

0.69Employee Empowerment

3.17

0.97

3.1

0.87

3.2

0.98

Service Technology

3.95

0.76

3.62

0.79

3.93

0.74Service Failure Prevention 3.9 0.7 3.68 0.71 3.74 0.75

Service Vision 4.05 0.65 3.87 0.73 3.95 0.66Service Standard Communication 3.73 0.66 3.64 0.66 3.64 0.75Service Failure Recovery 3.71 0.69 3.62 0.67 3.53 0.77

Service Rewards 3.6 0.81 3.5 0.79 3.43 0.83Management Information System

3.74

0.76

3.73

0.69

3.57

0.79

Service Leadership

3.88

0.68

3.73

0.66

3.72

0.64

Service Training

3.68

0.87

3.52

0.83

3.56

0.84

i-SERV*OR Scale 3.77 0.54 3.62 0.56 3.66 0.6



being obvious that Indian Service sector being technology driven, a significant weightage is

placed in this aspect. The hybrid sector which is an amalgam of service and manufacturing also

exhibits high scores for service technology with obvious implications to that of the service

sector.

lService failure prevention scaled its highest figures for the service sector, which is not

surprising in the sense that quality emphasis is placed in this aspect for the service sector.

Competitive edge of any business is hampered if there are frequent failure and overrun of

deadlines, which further accelerates costs. The Indian service sector seems to be aware of this

fact, and is very keen in preserving this edge.

lFigures for service vision recorded a high of 4.05 for the service sector, followed by the hybrid

sector and then by the manufacturing sector. The results are quite natural because having

vision, to be precise, planning and having an idea of the future perspectives and scenario is a

pivotally important, thus the dimension has no doubt higher values for the service sector,

followed by the hybrid sector.

lService standard communication is a very important dimension of service orientation. The

service sector has quite a high magnitude of service standard communication, while that of the

manufacturing and hybrid sectors are at par with each other. The importance of this dimension

can be clearly seen by the fact that, business making is possible as an outcome of service

standard communication.

lThe probability of failure haunts every industrial segment, the picture clearly shows that the

figures for service failure recovery are highest for the service sector, followed by the

manufacturing sector, and then by the hybrid sector.

lRewards are nothing but incentives which are necessary to boost productivity. It is not

surprising that the value of service rewards have highest figures for the service sector, which

contributes about two-third of the Indian GDP.

lUse of real time information in modern business has enhanced over the years. Cutthroat

competition and the ever expanding satiety to capture markets has pushed in increased role of

information technology and enhanced the role of real time information. The Indian service

sector enjoys an edge in the world market, reasons to which can be attributed to the increased

use and accessibility of real time information. The manufacturing sector is catching behind in

this dimension, as quality thrust is being pressed in this sector recently.

lLeadership skills are very important for a headstrong organisation, form the face of an

organisation. Even in this dimension, the service sector leads, followed by the manufacturing

sector which is closely followed by the hybrid sector.



Training forms an important part in service delivery, it is through learning that an individual

learns and implements the ideas in reality. In tandem with theoretical logic, this dimension

scaled its highest figures for the service sector, followed by the hybrid sector, and then by the

manufacturing sector.

The overall score of service orientation as measured by i-SERV*OR scale shows that the

service industry is more service oriented, which is followed by the hybrid industry, further followed by

the manufacturing industry.

One way ANOVA was conducted to determine the difference in service orientation across the

service industry, the manufacturing industry and the “hybrid” industry. The one way ANOVA assumes

the null Research questions that the variance (or variation) of service orientation scores across the three

group of industries are same. The analysis of variability within the individual group and variability

among the group reveals that there is not much difference between service orientation scores between

groups (service, manufacturing and hybrid), but there exists significant variability within the groups

itself. Excerpts of the same are presented below.

Table4.3: Descriptive Statistics

Table 4.4: Test for Homogeneity of Variances

l

Descriptives

Score

N Mean Std.

Deviation Std.

Error 95% Confidence

Interval for Mean Minim

um Maxim

um

Lower

Bound Upper

Bound

1.0 212 3.355 .6363 .0437 3.269 3.441 2.0 5.0

2.0 237 3.438 .5950 .0387 3.361 3.514 1.4 5.0

3.0 68 3.715 .7381 .0895 3.536 3.893 2.0 5.0

Tot

al

517 3.440 .6412 .0282 3.385 3.495 1.4 5.0

1=Service sector, 2=Manufacturing sector, 3= “hybrid” sector.

Test of Homogeneity of Variances

Score

Levene Statistic df1 df2 Sig.

4.407 2 514 .013



Table 4.5: ANOVA results

The ANOVA results show that service orientation scores are statistically different for the three

sectors. The results also reveal that the variations of service orientation scores across the three groups are

not homogenous.

Conclusion, implication and limitations

This research with its findings and conclusion drawn has wider research and managerial

implications. The extent of organizational service orientation varies across the three sets of industries i.e.

service, manufacturing and hybrid organizations. The result reveals that a significant share of variation is

associated with “within group variation”, with a minor variation existing “between groups”. The results

give clear evidence of the extent of service orientation variation across the three sets of industries.

Despite of extensive work done for this research study, it has certain limitations given the constraints of

time, availability of complete information and finance. The final sample size was satisfactory for

carrying out the as-planned statistical analysis. However there are limitations in covering samples to

cover all geographical and types of firms in India. Further classification of the samples into different

groups was not possible given the distribution of the firms. Such analysis based on groups like MNC vis-

a-vis domestic firms, etc. would have provided a deeper picture of the wide variety of Indian firms as the

framework became more refined. From methodology perspective for the Survey, though we have

gathered responses from a limited number of respondents representing the firm, it could not be extended

to more managers. In spite of the few respondents from the middle and top level in the respective

function of the firms, a larger number of responses would have provided a more vivid picture of the firm

in respect of the extent of its service orientation.

Since this study is first of its kind, as far as developing & applying a universal scale is

concerned for measurement of Organizational Service Orientation for all types of firms i.e. service,

manufacturing and hybrid (having characteristics of both service and manufacturing) in Indian context,

future research may be carried out across countries of both developed and developing economies for

ANOVA

Score

Sum of

Squares df Mean

Square F Sig.

Between

Groups

6.675 2 3.337 8.348 .000

Within Groups 205.501 514 .400

Total 212.176 516



wider acceptance of i-SERV*OR scale. Further classification of the samples into different based on

groups like MNC vis-a-vis domestic firms, Large and medium size firms etc. may be conducted in

future for a deeper insight.

References:

lAdair, F. L. (1972). The development of a scale to measure the service orientation of librarians:

Preliminary investigations. University Microfilms.

lAlbrecht, K., &Zemke, R. (1985). Service America! Dow Jones-Irwin.

lBerry, L. L., Parasuraman, A., & Zeithaml, V. A. (1994). Improving service quality in America:

lessons learned. The Academy of Management Executive,8(2), 32-45.

lBitner, M. J. (1990). Evaluating service encounters: the effects of physical surroundings and

employee responses. The Journal of Marketing, 69-82.

lBitner, M. J. (1992). Servicescapes: the impact of physical surroundings on customers and

employees. The Journal of Marketing, 57-71.

lBitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: diagnosing

favorable and unfavorable incidents. The Journal of Marketing, 71-84.

lBowen, D. E., Siehl, C., & Schneider, B. (1989). A framework for analyzing customer service

orientations in manufacturing. Academy of Management Review, 14(1), 75-95.

lChase, R. B., & Bowen, D. E. (1991). Service quality and the service delivery system: A

diagnostic framework. Service Quality: Multidisciplinary and Multinational perspectives, SW

Brown, E. Gummesson, B. Edvardsson and B. Gustavsson (editors), Lexington Books, New

York, 157-78.

lCherbakov, L., Galambos, G., Harishankar, R., Kalyana, S., & Rackham, G. (2005). Impact of

service orientation at the business level. IBM Systems Journal, 44(4), 653-668.

lConger, J. A., & Kanungo, R. N. (1988). The empowerment process: Integrating theory and

practice. Academy of management review, 13(3), 471-482.

lCran, D. J. (1994). Towards validation of the service orientation construct. Service Industries

Journal, 14(1), 34-44.

lDeshpandé, R., Farley, J. U., & Webster Jr, F. E. (1993). Corporate culture, customer

orientation, and innovativeness in Japanese firms: a quadrad analysis. The journal of

Marketing, 23-37.

lFrethey-Bentham, C. (2011). Pseudo panels as an alternative study design. Australasian

Marketing Journal (AMJ), 19(4), 281-292.

lGrönroos, C. (1990). Service management and marketing: managing the moments of truth in



service competition. Jossey-Bass.

lHallowell, R., Schlesinger, L. A., & Zornitsky, J. (1996). Internal service quality, customer and

job satisfaction: Linkages and implications for management. Human Resource Planning, 19,

20-31.

lHartline, M. D., & Ferrell, O. C. (1996). The management of customer-contact service

employees: an empirical investigation. The Journal of Marketing, 52-70.

lHeskett, J. L. (1986). Managing in the service economy. Harvard Business Press.

lHeskett, J. L. (1987). Lessons in the service sector. Harvard Business Review, 65(2), 118-126.

lHeskett, J. L., &Kotter, J. P. (1992). Corporate culture and performance.Business Review. Vol,

2, 83-93.

lHeskett, James L., W. Earl Sasser, Jr., and Christopher W.L. Hart. (1990) - Service

Breakthroughs: Changing the Rules of the Game. New York: The Free Press.

lHogan, J., Hogan, R., & Busch, C. M. (1984). How to measure service orientation. Journal of

Applied Psychology, 69(1), 167.

lHomburg, C., Hoyer, W. D., & Fassnacht, M. (2002). Service orientation of a retailer's business

strategy: Dimensions, antecedents, and performance outcomes. Journal of Marketing, 66(4),

86-101.

lJohnson, J. W. (1996). Linking employee perceptions of service climate to customer

satisfaction. Personnel psychology, 49(4), 831

lJones, S. (2005). Del Sasser. WE (1995). Why Satisfied Customers Defect, Harvard Business

Review, Nov/Dec, 73, 88-99.

lKeillor, B. D., Parker, R. S., & Pettijohn, C. E. (1999). Sales force performance satisfaction and

aspects of relational selling: Implications for sales managers. Journal of Marketing Theory and

Practice, 101-115.

lKelley, S. W. (1992). Developing customer orientation among service employees. Journal of

the Academy of Marketing Science, 20(1), 27-36.

lLangeard, E., Bateson, J., Lovelock, C. H., &Eiglier, P. (1981). Marketing of services: New

insights from consumers and managers. Marketing Science Institute, Cambridge, MA, 81-104.

lLee, J. N., & Kim, Y. G. (1999). Effect of partnership quality on IS outsourcing success:

conceptual framework and empirical validation. Journal of Management information systems,

29-61.

lLillis, A. M., & Mundy, J. (2005). Cross-sectional field studies in management accounting

research-closing the gaps between surveys and case studies. Journal of management

accounting research, 17(1), 119-141.



Lytle, R. S. (1994) - Service orientation, market orientation, and performance: an

organizational culture perspective. Unpublished Doctoral Dissertation, Arizona State

University, Arizona

lLytle, R. S., & Timmerman, J. E. (2006). Service orientation and performance: an

organizational perspective. Journal of Services Marketing, 20(2), 136-147.

lLytle, R. S., Hom, P. W., & Mokwa, M. P. (1998). SERV* OR: A managerial measure of

organizational service-orientation. Journal of Retailing, 74(4), 455-489.

lMarinova, D., Ye, J., & Singh, J. (2008). Do frontline mechanisms matter? Impact of quality

and productivity orientations on unit revenue, efficiency, and customer satisfaction. Journal of

Marketing, 72(2), 28-45.

lParasuraman, A., Zeithaml, V. A., & Berry, L. L. (1994). Reassessment of expectations as a

comparison standard in measuring service quality: implications for further research. The

Journal of Marketing, 111-124.

lParkington, J. J., & Schneider, B. (1979). Some correlates of experienced job stress: A

boundary role study. Academy of Management Journal, 22(2), 270-281.

lRoach, S. S. (1990). Services under siege--the restructuring imperative.Harvard Business

Review, 69(5), 82-91.

lRust, R. T., Zahorik, A. J., & Keiningham, T. L. (1996). Service marketing. HarperCollins.

lSasser, W. E., Schlesinger, L. A., & Heskett, J. L. (1997). Service profit chain. Simon and

Schuster.

lSchlesinger, L. A., & Heskett, J. L. (1991). Breaking the cycle of failure in services. MIT Sloan

Management Review, 32(3), 17.

lSchneider, B. (1990). The climate for service: An application of the climate constructs.

Organizational climate and culture, 1, 383-412.

lSchneider, B., & Bowen, D. E. (1985). Employee and customer perceptions of service in

banks: Replication and extension. Journal of applied Psychology, 70(3), 423.

lSchneider, B., & Bowen, D. E. (1993). The service organization: Human resources

management is crucial. Organizational Dynamics, 21(4), 39-52

lSchneider, B., Brief, A. P., &Guzzo, R. A. (1996). Creating a climate and culture for sustainable

organizational change. Organizational dynamics, 24(4), 7-19.

lTreacy, M., & Wiersema, F. (1993). Customer intimacy and other value disciplines. Harvard

business review, 71(1), 84-93.

lAggarwal, N., & Singh, R. (2004). Market orientation in Indian organizations: an empirical

study. Marketing Intelligence & Planning, 22(7), 700-715.

l



Dangayach, G. S., & Deshmukh, S. G. (2001). Manufacturing strategy: literature review and

some issues. International Journal of Operations & Production Management, 21(7), 884-932.

Popli, S., & Rizvi, I. A. (2015). Exploring the relationship between service orientation,

employee engagement and perceived leadership style: a study of managers in the private service sector

organizations in India. Journal of Services Marketing, 29(1), 59-70.

l



URBAN INFRASTRUCTURE INVESTMENT & ITS RELATEDDEVELOPMENTAL STATUS IN KERALA - A STUDY WITH SPECIAL

REFERENCE TO KERALA SUSTAINABLE URBANDEVELOPMENT PROJECT

1Archana Aravindan

Abstract

The style of urban infrastructure provision that encourages more efficient pattern of resource

consumption is the basis for development of sustainable cities. Conventional approach to urban

infrastructure management was based on the premise 'Facilitating Infrastructure Supply.' But in new

built developments serviced within a supply-oriented framework, any explicit consideration of various

environmental and social effects is rare. The increased awareness towards environment and a

sustainable society coupled with a need to make our cities worth living, demand side interference in the

provision and management of urban infrastructure is being advocated. But the societal, political,

personnel factors etc adversely sum up and lead towards a state of limbo when it collectively reacts to the

planning and implementation pattern of urban infrastructure in India. The present paper however

encapsulates a critical analysis of the existing planning approach to the urban infrastructure system and

the multiple facets that affects for and against the implementation of urban infrastructure projects in the

state of Kerala with special reference to the Kerala Sustainable Urban Infrastructure Programme.

Key Words: Urbanization, Urban Infrastructure Planning, Facilitating Infrastructure Supply, Demand

for Urban Infrastructure

Introduction

Urbanization and growth go together: no country has ever reached middle income status

without a significant population shift into cities. Urbanization is necessary to sustain growth in

developing countries. But it is not painless or always welcomed by policymakers or the general public.

Managing urbanization is an important part of nurturing growth; neglecting cities— even in countries in

which the level of urbanization is low—can impose heavy costs.

In terms of Urbanization trend, India is falling under the second stage of accelerated shift

where basic restructuring of the economy and investments in social overhead capitals including

transportation, communication etc is taking place and therefore India is being addressed as a developing

nation. History of Indian urbanization reveals a slow progression when compared to many developing

1 Archana Aravindan M.Com, MBA, Pursuing M.Phil is an UGC Major Project Research Fellow assisting Dr. Suresh V.N of Maharajas College, Department of Commerce, Ernakulam. Having a teaching experience of 4 yrs her specialization is in Marketing Management, Human Resource Management and Database Management System. She has published 9 research peer reviewed national and international journals and has presented a number of research papers in National and International conferences.


countries. The percentage of annual exponential growth rate of urban population reveals that in India it

grew at faster pace from the decade 1921-31 to until 1951. Thereafter it registered a sharp drop during the

decade 1951-61. The decades 1961-71 and 1971-81 showed a significant improvement in the growth and

from thereafter it steadily dropped. This slowdown tempo attracted the attention of Indian Government

and it started paying to the urbanization factor. The 74th Constitution Amendment Act (CAA) in June,

1983 led to the formation of Urban local government institutions/municipalities which acted for the

maintenance and planned development of urban areas. (State of the World Population Report, 2007)

Presently it is evaluated that the pace of urbanization in India is being triggered when compared to the

rest of the world. By 2030, 40.76 per cent of India's population will be living in urban areas compared to

about 31 per cent now. But ironically the cities and towns of India are visibly deficient in the quality of

services provided, even to the existing population. As society progresses, the process of economic

development and resulting urbanization gets momentum which in turn creates demand for urban

services and infrastructure facilities. The gap between demand and supply of essential urban services

and infrastructure deteriorates the physical environment and quality of life in the urban areas. Across the

globe, urban planners have taken up the challenge of designing urban living in ways that leave a smaller

ecological footprint.

India being a federal union comprising of 28 states and 7 union territories, within which a

momentous active urbanization by over 20% growth has been reported in the 'Gods Own Country',

Kerala. Urbanization trend in the state of Kerala shows marked peculiarities. Generally, increase in

urban population growth rate is the result of over concentration in the existing cities especially

metropolitan cities. This is true in the case of urbanization in the other states of India. But in Kerala, the

main reason for urban population growth is the increase in the number of urban areas and also

urbanization of the peripheral areas of the existing major urban centres. The urban sector in Kerala

comprise of five Municipal Corporations and 53 Municipalities. 25.97% of the population lives in urban

areas. This is a little less than the National average. However unlike other parts of the country the

Urbanization in Kerala is not limited to the designated cities and towns. Barring a few Panchayaths in the

hilly tracts and a few isolated areas here and there, the entire state depicts the picture of an urban rural

continuum. The Kerala society by and large can be termed as urbanized.

Kerala posses the distinctive characteristics of dispersed settlement pattern, a liking for

homestead type development, comparatively developed infrastructure in urban and rural areas,

geographical grounds, availability of sub-soil water etc can be considered as a prospect. In terms of

investments in infrastructure development and social services sector presently the scarce resources are

spread thinly over the entire mat of Kerala, therefore the accruing benefit is also marginal. The urban

spread demands more investment in infrastructure development. The rural to urban migration which

Archana Aravindan1


accentuates urban problems and urban poverty is only marginally present in the urban scenario of the

state. Keeping the national perspectives of Urbanization requirements the Indian Government has

initialized nationwide developmental projects for the purpose of economical and social advancement as

well as to achieve urban rural progression towards raising their standard of living. For this very purpose it

launched a country wide reform-linked urban infrastructure investment project named Jawaharlal Nehru

Urban Renewal Mission (JNNURM) in 2005 with individual State level nodal agencies. This mission

initiated within individual states an urge towards the achievement of better urban infrastructure.

Kerala with increased room for better urban infrastructural development initiated a state wide

reform-linked urban infrastructure investment project named Kerala Sustainable Urban Development

Project (KSUDP) which owns a separate entity in the accomplishment of urban infrastructure

progression projects funded by Asian Development Bank as well as by separate state Municipal

Corporations other than that it is also the State-level nodal agency (SLNA) for the Urban Infrastructure

and Governance component of JNNURM.The Kerala Sustainable Urban Development Project

(KSUDP) has come up with urban infrastructure assisted projects. With an investment of US$ 315

million, the project focuses on urban infrastructure improvement, community upgrading, local

government infrastructure development, capacity building and implementation assistance and

expansion of existing urban environmental infrastructure facilities.

Despite of, the slow initialization of urban infrastructure development projects have been

depicted in the development scenario of Kerala's urban areas is mainly due to the lack of proper vision

and master schemes, which envisage long term and short term effects of urban infrastructure

improvements. Proper development strategy should cater to the development needs of urban society

ensuring modern comfort levels and standard of living while preserving natural, cultural and historical

entity of the city.

Considering the urbanization trends in Kerala, the urbanization strategy to be adopted for the

state needs a broad based assessment. Developing infrastructure projects in a commercially viable

format helps improve management efficiency, mitigate implementation risks, and attract commercial

investment. Project development is the process of turning broad planning concepts for infrastructure into

implementable designs. A commercially viable format (1) ensures that adequate revenues from project

services and from other dedicated sources will cover project capital costs and operations and

maintenance (O&M); (2) is socially inclusive and operates in a systemic and sustainable basis; (3) is

environmentally sustainable; and (4) has a regulatory framework to enforce quality of service,

preservation of public interest, and economic sustainability.

But the current scenario is far away from reality. The projects were scheduled to be completed

by June 2012 but an extension up to June 2014 has been approved. The delays and the cost overruns have

Urban Infrastructure Investment & Its Related Developmental Status In Kerala -A Study With Special Reference To Kerala Sustainable Urban Development Project


put the ADB in a state of distrust. The extensive delay in the project implementation is leading to

discontinuity in the flow of finance for the ongoing projects. This is one of the prime factors that has led

to the present hostile scenario of the KSUDP projects. Urban Infrastructural planning in Kerala has been

prescriptive, slow, and top-down from national and state-level agencies. As a consequence, informal

development is proliferating throughout cities—congesting public and environmental spaces, sprawling

out on the periphery, constructing unsafe buildings, and settling where no services exist adding to the

miseries. These reasons leading towards the improper implementation and planning of urban

infrastructure in Kerala became a research problem that attracted interest for an in depth analysis.

This paper is a comprehensive perspective on infrastructure development in the state of Kerala.

It provides a perspective on the inefficiencies in infrastructure implementation and the challenges that

drive these inefficiencies. The basic objective of this study is to ascertain the extent of progress made in

the various project components in the prime districts and to identify the reasons that are leading to the

slow implementation of the urbanization projects in the state of Kerala. The research problem

concentrates around the identification of bottlenecks in the phase of projects planning and their further

implementation resulting in delays during construction stages.

LITERATURE REVIEW

In terms of development and growth theory, urbanization occupies a puzzling position. On the

one hand, it is recognized as fundamental to the multidimensional structural transformation that low-

income rural societies undergo to modernize and to join the ranks of middle- and high-income countries.

Lucas's Model (2004, 2007), explicitly consider how urbanization affects the growth process primarily

through the enhanced flow of ideas and knowledge attributable to agglomeration in cities.

Landes (Williamson, 1988) suggests the scenario with an historical treatment and situates

urbanization as an essential ingredient in modernization:' Industrialization is at the heart of a larger, more

complex process often designated as modernization. Modernization comprises such developments as

urbanization; the so-called demographic transition; the establishment of an effective, fairly centralized

bureaucratic government; the creation of an educational system capable of training and socializing the

children of a society; and of course, the acquisition of the ability and means to use an up-to-date

technology. '

Burgess and Venables (2004) says urbanization is relatively a little-studied area of

development economics and policy note: Spatial concentration is most dramatically demonstrated by the

role of urbanization, and of mega-cities, in development. . Despite the massive diseconomies associated

with developing country mega-cities, there are even more powerful economies of scale making it

worthwhile for firms to locate in these cities. Urbanization is one of the clearest features of the

development of manufacturing and service activity in developing countries, yet discussion of

Archana Aravindan1


urbanization is strangely absent from economic analyses of growth and development.

Davis, (1965) suggests urbanisation is an index of transformation from traditional rural

economies to modern industrial one. It is progressive concentration of population in urban unit.

Quantification of urbanization is very difficult. It is a long term process.

Davis, (1962) Kingsley Davis has explained urbanization as process of switch from spread out pattern of

human settlements to one of concentration in urban centres.

(Davis and Golden, 1954) collectively mentions urbanization as a finite process--- a cycle

through which a nation pass as they evolve from agrarian to industrial society. He has mentioned three

stages in the process of urbanization. Stage one is the initial stage characterized by rural traditional

society with predominance in agriculture and dispersed pattern of settlements. Stage two refers to

acceleration stage where basic restructuring of the economy and investments in social overhead capitals

including transportation, communication take place. Dependence on primary sector gradually dwindles

and proportion of urban population gradually increases. Third stage is known as terminal stage where

urban population exceeds 70% or more. At this stage level of urbanization (Davis, 1965) remains more or

less same or constant. Rate of growth of urban population and total population becomes same at this

terminal.

Robert Repetto focuses (Rogers et.al. (1997) p.44) his discussion of sustainable development

on “….increasing long term wealth and well being.” In his 1986 book, World Enough and Time, Repetto

wrote that “the core idea of sustainability is that current decisions should not impair the prospects for

maintain or improving future living standards. This implies that our economic system should be

managed so that we can live off the dividends of our resources”

Herman E. Daly (1987) suggested an ethical concept and said that an “increase in moral knowledge or

ethical capital for mankind.”

Mohan Munasinghe (1987) drew the “….distinction between 'survivability', which requires

welfare to be above a threshold in all periods, and 'sustainability', which requires welfares to be non-

decreasing in all time periods.”

John CV Pezzey, another former World Bank official suggests that survivability means that

you are always above some threshold at all points in time, whereas sustainability takes a sort of

millennial view that things are getting better all the time in a monotonic way.

(Isher Ahluwalia, March 2011) mentions even though cities in India are filled with vibrant

activity and energy, they are also chaotic, complicated and too often congested. There is immense wealth

and opportunity, side-by-side with immense poverty and deprivation.. Its standards and needs are rising

but the current service levels are too low in relation to the requirement of urban households

(Kundu, 1997) Problems of urbanization are manifestation of lopsided urbanization, faulty urban



planning, and urbanization with poor economic base and without having functional categories. Likewise

India's urbanization is also followed by some basic problems in the field of housing, slums, transport,

water supply, sanitation, water and air pollution, inadequate provision for social infrastructure. Class I

cities such as Calcutta, Bombay, Delhi and Madras etc have reached saturation level of employment

generating capacity Since these cities are suffering from urban poverty, unemployment, housing

shortage, crisis in urban infra-structural services collectively force these large cities to eject the

distressed rural migrants i.e. poor landless illiterate and unskilled agricultural laborers. Hence this

migration to urban class I cities causes' urban crisis to become more acute. Every state of India is facing

dynamic scenarios with respect to urbanization. It is noteworthy that Tamilnadu is the only state that is

more than 50 per cent urbanized but it is estimated that by 2030 it would be 5 states.

RESEARCH METHODOLOGY

A research design or model indicates a plan of action to be carried out of in connection with a proposed

research work. The type of research is quantitative as well as qualitative in nature. Inferential research

and descriptive research forms a part of the study to arrive at conclusions.

RESEARCH OBJECTIVES

1) To analyze the project components undertaken in 3 different districts.

2) To understand the details of different projects undergone in the state with respect to completed

projects, ongoing projects etc.

3) To conduct a comparative study between the various project components and the stages of the

projects in the separate districts with regard to KSUDP.

RESEARCH DESIGN

The nature of the research paper is analytical as well as descriptive. A combination of

qualitative and quantitative data has been applied. The observation and research is a continuous process.

Primary Data – Primary data are those data that researchers are collecting information for the

specific purposes of their study. In essence, the questions the researchers ask are tailored to elicit the data

that will help them with their study. Researchers collect the data themselves, using surveys, interviews

and direct observations (such as observing safety practices on a shop floor). It is original in character. The

data is collected by the investigator for the first time. Primary data is considered as the raw material to

which statistical methods are applied for the purpose of analysis and interpretation. It can be collected

through Interviews, questionnaires, observation etc. For this particular study primary data was collected

through questionnaire and personal interviews.

Archana Aravindan1


Secondary Data – Data has also been used from websites, journals, newspapers and

magazine. Analytical reports have been utilized for the detailed study of different components. Internet

source was another method used. Secondary data is the prime source of information. References have

been made constantly with regard to journals, newspapers and online sites.

KERALA SUSTAINABLE URBAN DEVELOPMENT PROJECT (KSUDP)

The Projects are being undertaken in the following five municipal corporations of

Thiruvanthapuram ,Kollam , Kochi ,Thrissur ,Kozhikode. The authorized official in charge of the

KSUDP have identified the urban project components to be implemented and refurbished through the

programme on the basis of the data obtained from the socio-economic baseline households survey and

from the qualitative assessments obtained from the participatory rapid appraisal (PRA) method that

includes nine risk parameters.(KSUDP Report, 2005)

RESULTS & ANALYSIS

The research area covers the Kerala Sustainable Urban Development Programmes details

implemented in the districts of Thrissur, Cochin and Thiruvanthapuram. This evaluation is based on data

collected from three urban centers situated in Kerala covering the prime urban local government

characteristics – i.e. the Urban Community Upgrading, Local Government Infrastructure Development,

Urban Infrastructure & Services Improvement,.

The Table I below represents the overall fund allocation, project work distributions, their

percentage of completion, ongoing project details etc that has been made in all the 5 Municipal

Corporations where KSUDP projects are being accomplished. The Table I represent the overall

Community Infrastructure details of the collective projects in all the 5 districts.

TABLE I - COLLECTIVE STATUS OF CIF IN 5 CORPORATIONS

DISTRICTTotal

Projects

Completed Projects

% of completed Projects

Ongoing Projects

% of ongoing projects

Tender Notified

% of Tender Notified

Cancel Project

Amt

Allotted(in Mn

Rs)

% of Amt

Allotted

Disburse

d Amt(in Mn

Rs)

% of Disburse

ment

TVM 98

70

71%

8

8%

11

11%

9

146.00

19%

98.41 67%

Kochi 86

66

77%

14

16%

6

6%

-----

155.75

20%

109.04 70%

Thrissur 120 103 86% 16 13% 1 .8% ----- 159.06 21% 98.66 62%

Kollam 59

40

68%

4

7%

15

27%

-----

149.76

19%

77.49 52%

Kozhikode 65

52

80%

13

20%

-----

-----

-----

159.68

21%

139.75 88%

Total 428 331 55 33 9 770.25 523.33

(SOURCE: - KSUDP QUARTERLY REPORT FOR JULY-SEPTEMBER, 2013)



After understanding the prime necessity of the various sections of the society, KSUDP has

formulated 5 major components in which the foundation and further development shall be laid leading to

the Urban Infrastructure & Services Improvement. These components are Water Supply, Sewerage &

Sanitation, Drainage, Solid waste management, and Road & Transport. Around 90% of the KSUDP fund

has been set aside for the upgrading of these components thereby making the analysis of progress in these

project component areas very important.

The Table II below represents primarily the components under scrutinization and the detailed

financial estimates, amounts allocated for each component, the works that are being undergone in the all

the districts and finally the amount Disimbursed till 30th Sept, 2013. The Table II depicts that the

maximum projects of 16 projects have been implemented in the Sewerage component. Thereby the

maximum allocation of fund i.e. 56% has been made for the progression of this specific component. The

Table also shows that the maximum of 8 completed projects fall under the Urban Road & Transport

component and therefore maximum disbursement of fund up to 70% has also been for this component.

But to the contrary maximum percentage of the deferred projects also come under the Urban Roads and

Transport component i.e. 25%.

TABLE II - COMPONENT WISE WORK STATUS OF KSUDP PROJECTS

COMPONENTNo of

Contract

Estimate

Amt

(MnRs)

Complete

Project

Amt of

Completed

Projects

(Mn Rs)

Ongoing

Projects

Ongoing

Projects

Amt (Mn

Rs)

Tender/

DPR

Tender

Amt

Project

Deferred

Project

Amt

Disbursement

as on

30/9/2013

WATER

SUPPLY

10

1164.7

2

472.59

8

692.12

----

------

------

------ 659.00

% Analysis of all

the criteria

16%

12%

20%

41%

80%

59%

-----

-------

-----

------ 57%

SEWERAGE 21

5261.58

2

764.81

7

1965.58

7

1674.69

5

856.5 735.54

% Analysis of all

the criteria

33%

56%

10%

15%

33%

37%

33%

32%

24%

16% 14%

DRAINAGE 11 904.8 3 155.97 4 445.88 2 185.2 2 116.75 277.10

% Analysis of all

the criteria

18%

10%

27%

17%

36%

49%

18%

20%

18%

13% 31%

SOLID WM 5

185.09

--------

----------

5

185.09

----------

--------

-------

------ 101.4

% Analysis of all

the criteria

10%

2%

-------

-----

100%

100%

----------

--------

-------

------ 55%

ROAD & T 16

1848.01

8

1344.06

2

168.01

2

11.54

4

324.41 1313.34

% Analysis of all

the criteria

26% 20% 50% 73% 12.5% 9% 13% .5% 25% 18% 71%

TOTAL 63 9364.19 15 2737.42 26 3756.68 11 1871.43 11 1297.66 3086.38


Archana Aravindan1


Moving on to further details the Table III shows the consolidated information about the project

components that has been implemented in the Research area i.e. Thiruvanthapuram, Cochin and

Thrissur.

TABLE III

CONSOLIDATED PROJECT COMPONENT DETAILS IN THE RESEARCH AREA

COMPONENT DISTRICTTotal

Contract

Estimate

Amt

(Mn Rs)

Complete

Projects

Amt

Complete

Project(M

n Rs)

Ongoing

Projects

Ongoing

Project

Amt

(Mn Rs)

Tender/DPR

Tender

Amt

Deferred

Project

Deferred

Project

Amt

Disbursement

as on

30/9/2013

SEWERAGE

TVM

5

1393.93

1

726.92

2

648.61

----

-----

2

18.4

461.48

KOCHI

7

1688.29

1

37.89

-----

------

5

1285.1

1

365.4

28.36

TCR

-----

-------

-----

-------

------

-----

-----

-----

-----

------

-------

DRAINAGE

TVM

1

93.73

-----

----

1

93.73

-----

-----

-----

------

30.59

KOCHI

2

123.24

-----

----

1

114.94 -----

-----

1

8.30

104.39

TCR 2 237.22 ---- ---- 2 237.22 ------ ------ ------ ----- -----

SOLID WASTE

MANAGEMENT

TVM

-----

-------

-----

-------

------

-----

-----

-----

-----

------

-------

KOCHI

-----

-------

-----

-------

------

-----

-----

-----

-----

------

-------

TCR

1

49.24

----

------

1

49.24

-----

-----

-----

-----

12.39

ROAD &

TRANSPORT

TVM

3

422.99

1

123.00

1

122.99

----

---

1

177.0

188.54

KOCHI

3

352.10

3

352.10

-----

-------

------

-----

------

-----

279.38

TCR 1 293.4 1 293.4 ---- ----- ------ ------ ------ ----- 285.53

TOTAL


From the above information a pie diagram has been derived and it depicts the individual

districts with their respective percentage of completed projects. It displays that the Thrissur District

leads with an aggregate percentage of 37%, followed by Kochi with 33% and finally Thiruvanthapuram

with 30%. The cancellation of 9 non viable projects in the Thiruvanthapuram District is one among the

prime reason for a low performance percentile.



COMPONENT WISE IMPORTANCE IN THE STATE

WATER SUPPLY: -Drinking water supply and sanitation in India continue to be inadequate,

despite longstanding efforts by the various levels of government and communities at improving

coverage. The level of investment in water and sanitation, albeit low by international standards, has

increased in size during the 2000s. Access has also increased significantly. For example, in 1980 rural

sanitation coverage was estimated at 1% and reached 21% in 2008.Also, the share of Indians with access

to improved sources of water has increased significantly from 72% in 1990 to 88% in 2008.At the same

time, local government institutions in charge of operating and maintaining the infrastructure are seen as

weak and lack the financial resources to carry out their functions.

SEWERAGE & SANITATION:- The challenge of sanitation in Indian cities is acute. With

very poor sewerage networks, a large number of the urban poor still depend on public toilets. Many

public toilets have no water supply while the outlets of many others with water supply are not connected

to the city's sewerage system. The problem of sanitation is much worse in urban areas than in rural due to

increasing congestion and density in cities.

DRAINAGE:- Drainage systems will be improved in all corporations through rehabilitation

of existing culverts and construction of new ones; and construction of new drains to improve the storm

water drainage network. This project component has also been taken up very seriously in order to raise

the standard of living of the dwellers. But even this project implementation is not a cheese cake instead

hindrances are a part and parcel of the work.

SOLID WASTE MANAGEMENT :-The management and disposal of solid waste generated

in Indian cities leaves a great deal to be desired, though the generation of solid waste is at much lower

rates than in most countries. Neither households nor municipalities in India practise segregation of

biodegradable waste from the rest, and public awareness on the benefits of segregation is low. The

collection of the garbage from dumpsites is infrequent, processing is not done in most cases, and disposal

rules are followed more in the breach. The Municipal Solid Waste Rules were put in place in 2000 but

their enforcement has been poor.

ROADS & TRANSPORT:-Indian cities are increasingly faced with the twin challenges of

providing adequate road space for future use and improving the poor condition of existing roads due to

the neglect of maintenance over the years. The highly inadequate and poor quality of the public transport

system in Indian cities not only poses a major challenge to realising the growth potential of the economy

but also has adverse impact on the health and wellbeing of the people.

REASONS FOR SLOW IMPLEMENTATION OF THE PROJECTS

Experts (Ernst & Young,2011) have identified the following roadblocks towards urban

infrastructure development, the stagnating and even declining public sector spending levels on urban

Archana Aravindan1


infrastructure, Lack of incentives for the private investments in financing urban infrastructure, Higher

risk perceptions, Ambiguous guidelines and policies regarding PPP's, Under spending and low cost

recovery are typical of projects at the municipal levels, Projects efficiency and viability reduces

substantially due to very low allocations on maintenance-shift to new infrastructure that has high cost

escalation, Lack of recognition of the consequences of urban ills in policy making, Continuation of

multiplicity of institutional network that make service delivery complex as well as costly with less

accountability and less efficiency, Lack of sufficient capacity for urban planning and implementation at

the urban local bodies level, Inadequate compensation and finally poorly planned rehabilitation

packages.

Replacement of experienced officials with inefficient personnel leading to delays in the

execution of project during the final stage is a very crucial reason for the slow progression of the projects.

Scarce availability of filter media and the associated difficulties caused due to running the plant is a main

issue faced in the water supply works. Inadequate funding leading to contractors' protests also led to the

stagnation of the project work movements. Misuse of allotted funds makes it difficult to add continuity

and uninterrupted working pattern with regard to implementation of each component. Impending

shortfall in funding- Structural impediments in the financial system coupled with the national credit

crisis will constrain capital flows to the sector.

Lack of technical know-how leading to malfunctioning of implemented projects has been a

major setback. Incompletion of the designed projects during the stipulated period of time leading to

discontinuity in the mode of finance causes interruption in the working. Another prime reason for the

incompletion of project is the non viable project designs being submitted for approval as well as projects

being deferred and postponed is also extending the time period for completion of projects. It further

causes inefficiencies in the project that leads to retendering of the once completed projects causing

severe delay and also lapse of fund. Land Acquisition is one of the major constraints being faced by the

authorities. One more important factor is the lack of Capacity Building which suppresses the need for

adequate human resource to proceed with the projects.

Quality of planning and engineering design is poor: Project plans are of poor quality and lack

attention to detail, which creates problems such as scope changes and variations during project

execution, thereby creating disputes and delays. Also, nodal agencies often do not adopt a value

engineering mindset to project design, thereby increasing the project costs.

Lack of best-in-class procurement practices: While most Indian providers attempt to optimise

procurement, their practices are not best-in-class. Global majors commonly follow practices such as

demand consolidation, new vendor development, preferred relationships through frame contracts, and

joint cost reduction. Prevalence of these procurement practices in India remains relatively limited. As a



result, our estimates suggest that potential savings opportunities of 5 to 20 per cent of the addressable

costs are forgone. Low prevalence of lean construction principles: Lean construction is a nascent

phenomenon globally. Discussions with leading industry players suggest that most Indian providers

have not adopted lean principles. As a result, opportunities to reduce time and costs by 20 to 30 per cent

are forgone.

Lack of quality products being used to implement the work effectively makes the quality of

work fall into the sub standard segment. It further losses the confidence of the general public. The

extension of project completion dates has aroused a sense of distress to sanction more finance by the

ADB. Red Tapism being an integral part of the official formalities leading to unpredictable delay. This

makes the projects to remain in black and white alone.

Fragmented institutional set up within the multiplicity and its agencies results in overlapping

of jurisdictions and fragmented roles and responsibilities becomes a major factor in the poor delivery of

urban services. Capacity constraints lead the Municipal administration to typically suffer from

overstaffing of untrained, unskilled manpower on the one hand and shortage of qualified technical staff

and managerial supervisors on the other hand.

Performance management is weak: Nodal agencies are hampered by weak performance

management including: 1) low transparency in performance, which would help create public pressure; 2)

lack of meaningful incentives (financial or otherwise); and 3) absence of clearly defined consequences

in the event of under-performance.

Tendering unviable PPP projects is common: Many examples of unviable projects exist in the

national highways sub-sector. Three issues that hamper the viability of projects are: projects that are

planned beyond their scope, dated cost estimates that lead to insufficient viability gap funding (VGF),

and increased risk to the provider due to several contractual terms such as the possibility of termination

of concession, if traffic crosses a threshold level.

Contracts in use are inappropriate: Item rate contracts are common as opposed to lump-sum

EP&C contracts. These contracts allow the designs to be variable and increase the frictional cost of

interaction between the nodal agency and the construction contractor.Pre-tendering approval process is

centralised and slow: The multitude of approvals required across many infrastructure sectors (e.g., from

the External Finance Committee, Public Investment Board or by the Cabinet Committee for Economic

Affairs) can add almost up to one year to the pre-tendering process. Several processes, such as

ministerial approvals, do not have defined timelines. Furthermore, the individuals involved are not

always held accountable f0or delays in approvals.

Lack of sufficient capacity for urban planning and implementation at the urban local body level

results in lack of clarity regarding the projects. The low spending on O&M of existing assets has further

Archana Aravindan1


contributed to the problem of service delivery. Lack of recognition of the consequences of urban ills in

policy-making worsens the situations. An inadequate investment in urban infrastructure makes the

Municipal budgets in India to be heavily dependent on fiscal transfers from the higher tiers of

government, which tends to be inadequate considering the needs of Indian cities.

Mohanty et al. (2007) study shows that for 35 municipal corporations, there was, on average,

under spending of 76 per cent on capital investments necessary to meet minimum standards of services.

Poor maintenance of assets results in the low spending on O&M of existing assets further contributes to

the setback of service delivery.

Availability of skilled and semi-skilled manpower is insufficient: The growth of skilled and

semi-skilled manpower in India has not kept pace with the growth in infrastructure projects. While a

survey by the National Sample Survey Organisation7 estimates that 13 million workers enter the market

every year, only 3 million receive training. India's vocational training curriculum is largely outdated and

not based on clear standards. Further, the current certification process is based largely on theoretical

testing, and does not ensure employability.

Climatic conditions of the state are major hindrances that act as a barricade in the continuous

implementation of the project. The unexpected torrential rainfall causes stoppage of the projects.

Extensions of the deadlines are causing immense pressure on the authorities forcing them to complete

the projects with low quality materials and cheap technologies leading to inefficient projects. The works

have come to a standstill, and their commissioning will be further delayed. Earlier, the Asian

Development Bank, which finances the KSUDP schemes, had criticised the government for its

unenthusiastic approach to implementing the works. As the projects are in the state of limbo authorities

who are being replaced find it hard to start from the scratch due to which the projects get delayed. The

increased vehicles and traffic on the roads have made it very hard to start off such projects and as the

work duration gets extended it is unmanageable to control the public protests.

Weak risk management skills: The skills and tools Indian providers have to assess and manage

risks are weak compared with their counterparts in developed countries. McKinsey's assessment of

leading construction companies in India reveals a low prevalence of global norms of risk assessment.

This increases project costs and results in project failures when providers take up projects beyond their

capabilities.

Below-par design and engineering skills: Providers under-utilize the value engineering

opportunity in EP&C and PPP projects due to the lack of a value engineering mindset as well as poor

capabilities. Most providers do not have an adequate organizational set-up to capitalize on this

opportunity.



CONCLUSION

The tensions that urbanization creates and the structural shifts it puts into motion suggest why

developing country policy makers do not always welcome rapid urbanization. Viewed from the long

perspective of history, urbanization is necessary for achieving high growth and high incomes. In its early

stages urbanization is beneficial, but it can also be painful. Managing urbanization will affect politics,

social norms, institutional change, and the broader financial system. Policymaking in this environment

is rife with problems of the second best. Shaping strategies that make cities work for the national

economy will demand pragmatism and sensitivity to what is viable in a given context, but such strategies

will reap large rewards. The tensions that urbanization creates and the structural shifts it puts into motion

suggest why developing country policy makers do not always welcome rapid urbanization. Viewed from

the long perspective of history, urbanization is necessary for achieving high growth and high incomes. In

its early stages urbanization is beneficial, but it can also be painful. Managing urbanization will affect

politics, social norms, institutional change, and the broader financial system. Policymaking in this

environment is rife with problems of the second best. Shaping strategies that make cities work for the

national economy will demand pragmatism and sensitivity to what is viable in a given context, but such

strategies will reap large rewards. The tensions that urbanization creates and the structural shifts it puts

into motion suggest why developing country policy makers do not always welcome rapid urbanization.

Viewed from the long perspective of history, urbanization is necessary for achieving high growth and

high incomes. In its early stages urbanization is beneficial, but it can also be painful. Managing

urbanization will affect politics, social norms, institutional change, and the broader financial system.

Policymaking in this environment is rife with problems of the second best. Shaping strategies that make

cities work for the national economy will demand pragmatism and sensitivity to what is viable in a given

context, but such strategies will reap large rewards.

The findings of this study shows that projects are being structured and implemented in the

various districts but at a much slower pace. Urban local governments in Kerala continue to remain

plagued by numerous problems, which affect their performance in the efficient discharge of their duties.

These problems relate to the extent of participation and rule of law in the municipal decision making

process, transparency in the planning and implementation of infrastructure projects, and level of

efficiency in various municipal management and finance practices. A quick implementation procedure

has to be set so that the projects can be realized during the stipulated period. This shall enable to lay a

strong foundation for the urban infrastructural development programmes by creating the factor of trust in

the funding authorities resulting to provide their continuous financial support for the state. It is

concluded that fresh thinking is necessary to resolve the problems confronting urban local governments

in Kerala as well as in India as a whole. Urban Infrastructural Development is a vital necessity that has to

Archana Aravindan1


be taken care of so that the state can prosper and grow by using the complete resources.

REFERENCES

lAhluwalia, Isher Judge (2011) \“Report on Indian Urban Infrastructure and Services”, March

2011

lBurgess, R. and A. Venables (2004), \“Towards a Microeconomics of Growth", World Bank

Working Paper 3257, April, Washington D.C.

l

l

l

l

l

l

l

l

l

l

l

Daly, Herman E (1987) \ "The economic growth debate: what some economists have learned

but many have not," Journal of Environmental Economics and Management, 14, 4, (Dec,

1987), pp. 323-336.

Davis, Kingsley (1965) \ "The urbanization of the human population". Scientific American,

213(3), 41-53

Davis, Kingsley (1962) \ "Urbanisation in India - Past and Future", in Turner, R. (ed.) India's

Urban Future, University of California Press, Berkley.

Davis, Kingsley and Golden H.H.(1954) \ "Urbanisation and development in pre-Industrial

Areas", Economic Development and Cultural Change, Vol.3 no 1

Kerala Sustainable Urban Development Project (Ppta 4106 - Ind) Final Report volume 2 - City

Report Thrissur, May 2005

Kerala Sustainable Urban Development Project (Ppta 4106 - Ind) Final Report volume 2 - City

Report Thiruvananthapuram, May 2005

Kundu, A. (1997) \ "Trends and Structure of Employment in the 1990s: Implications for Urban

Growth", Economic and Political Weekly, 32(24): 1399-1405

Landes, D. (1969), \ "The Unbound Prometheus", Cambridge, Cambridge University Press

Lucas, R. (2004), \ "Life-Earnings and Rural-Urban Migration", Journal of Political

Economy, 112, S29-S59

Munasinghe, Mohan. (1993) \ "Environmental Economics and Sustainable Development,"

World Bank Environment Paper, No. 3. Washingon, D. C., 1993

Pezzey, John. \ "Sustainable Development Concepts: An Economic Analysis."World Bank

Environment Paper No. 2. Washington, D.C.: The World Bank, 1992.

lRepetto, Robert \ "World Enough and Time". New Haven: Yale University Press, 1986.

lReport of the Committee of Ministers Constituted by the Central Council of Local Self

Government (1963); Government of India (1966); Sachdeva, Pardeep (1993); Constitutional



Provisions Relating to Village Panchayats and Municipalities in India (1999)

lRogers, Peter \ " An Introduction to Sustainable Development", 2007

l"Urban India", Journal of the National Institute of Urban Affairs Vol 31,Issue 2, July-

December 2011, ISSN 0970- 9045

lVaidya, Chetan \ "Urban Issues, Reforms & Way Forward in India", Working Paper No.4/2009

-July 2009.

lWilliamson, J. (1988), \ "Migration and Urbanization", in Handbook of Development

Economics Vol 1, Edited by. H. Chenery and T.N. Srinivas, Amesterdam, Elsvier.

REFERENCE OF WEBSITE

lh t t p : / / w w w . u r b a n i n f r a s t r u c t u r e i n d i a . o r g / p d f / 0 c -

userhttp://en.wikipedia.org/wiki/Infrastructure%20guide_web.pdf

lhttp://www.urbaninfrastructureindia.org/pdf/1-Urban&goverance_web.pdf

lhttp://www.lse.ac.uk/asiaResearchCentre/_files/ARCWP19-Aijaz.pdf

lhttp://www.ibef.org/download%5CKerala_060710.pdf

lh t t p : / / a r t i c l e s . t i m e s o f i n d i a . i n d i a t i m e s . c o m / 2 0 1 3 - 0 8 -

21/thiruvananthapuram/41432078_1_adb-asian-development-bank-action-plan

lhttp://www.thehindu.com/news/cities/kozhikode/ksudp-sewerage-pipes-not-up-to-mark-

report/article4739090.ece

lhttp://www.thehindu.com/news/cities/kozhikode/sewerage-project-in-kozhikode-comes-to-

a-halt/article5152997.ece?ref=relatedNews


21/thiruvananthapuram/41432078_1_adb-asian-development-bank-action-plan


01/thiruvananthapuram/40306383_1_septage-sewage-drainage-lines


26/thiruvananthapuram/39538005_1_sewage-plant-work-fund-lapse-ksudp

larticles.timesofindia.indiatimes.com/2013-08-22/kochi/41436528_1_sewage-treatment-

plant-work-govt-nod

lhttp://www.newindianexpress.com/cities/kochi/Drainage-construction-stuck-awaiting-

ADB-approval/2013/07/27/article1704508.ece#.UwY5NvmSzVs

lhttp://www.thehindu.com/news/cities/kozhikode/sewerage-project-in-kozhikode-comes-to-

a-halt/article5152997.ece

Archana Aravindan1


LIQUIDITY AND STOCK RETURNS:A STUDY OF THE INDIAN MARKET

1Shazia Parwez

2Valeed Ahmed Ansari

Abstract

This paper examines the effect of liquidity on returns in the Indian stock market for the period

between April 2000 and March 2012, using Amihud's illiquidity measureas the proxy. It is found that

illiquid stocks earn a premium of 4.50 per cent per month over liquid stocks. Further, an empirical

comparison of the three-moment CAPM, the Fama and French model and a liquidity-augmented four

factor model reveals that liquidity as a risk factor is priced in India. The Fama-French three factors

model augmented with liquidity factor has the maximum explanatory power to account for the cross

section of returns. The results remain robust in sub-periods and to different market conditions.

JEL Classification: G12

Key Words: Liquidity, asset pricing, stock returns, Indian stock market

1. Introduction

Traditional asset pricing models such as Capital Asset Pricing Model assume a frictionless

market and ignore liquidity. However, the seminal work of Amihud and Mendelson(1986) and

subsequent studies by Brennan and Subrahmanyam (1996); Brennan, Chordia and Subrahmanyam

(1998); Datar, Naik and Radcliffe (1998); Jacoby, Fowler and Gottesman (2000); Amihud (2002);

Huberman and Halka (2001); Chordia, Roll and Subrahmanyam (2000); Hasbrouck and Seppi (2001);

Pastor and Stambaugh (2003) and Acharya and Pederson (2005) proved that illiquid stocks command

higher expected returns than relatively liquid ones. Liquidity may be priced in two ways. One strand of

literature considers the level of liquidity of a stock as a determinant of asset returns (Amihud and

Mendelson, 1986). The second strand considers liquidity as a risk factor i.e. the sensitivity of stock

returns to changes in market liquidity that may not be diversifiable (Acharya and Pederson, 2005).

Most of the empirical evidence on the liquidity- return relation is US centric and represents

developed markets. A few studies such as by Dey (2005); Bekaert, Harvey and Lundblad (2007); Lee

(2011) and Amihud, Hameed, Kang and Zhang (2015), have examined markets other than developed

ones. India also figures in these studies. However, a detailed examination of liquidity is missing.The

1 Research Scholar, Department of Business Administration, Faculty of Management Studies & Research, Aligarh Muslim University, Aligarh, Uttar Pradesh-202002Email- [email protected], Ph. no. 9411415075

2. Dean Faculty of Management Studies & Research, Chairman and Professor, Department of Business Administration, Faculty of Management Studies and Research Aligarh Muslim University, Aligarh, Uttar Pradesh-202002. Email- [email protected], Ph. no. 9897920437


paper attempts to fill the empirical void by conducting the study in an Indian context to investigate

whether expected returns in the Indian stock market are related to liquidity. India is one of themost

important emerging market economies of the world. The study attempts to answer whether the evidence

is a product of data snooping, as noted by Lo and Mackinlay (1990). Liquidity as a risk factor is of

particular importance in the context of such emerging markets which are likely to have greater friction

due to the lesser number of securities, fewer traders and lower efficiency of trading mechanisms.

The paper proceeds as follows. Section 2 reviews relevant literature. Section 3 details the

methodology, section 4 has the results of the regression and the robustness tests and section 5 concludes.

2. Related literature

This relationship was studied for the first time by Amihud and Mendelson (1986) who used the

bid-ask spread as liquidity proxy and found a positive relation between illiquidity and stock returns for

the US market. It has since been re-examined extensively and generally found to hold good with a few

exceptions. Eleswarapu and Reinganum (1993) for example, find this effect to be restricted to the month

of January.

The strength of the liquidity-return relation has been put to test in various ways. Firstly, it has

been found to be robust to different trading mechanisms by including stocks being traded on different

stock exchanges. Haugen and Baker (1996) find a statistically significant negative return-turnover rate

relationship for Russell 3000 stocks. Eleswarapu (1997) re-examines the Amihud and Mendelson study

for NASDAQ stocks, which is a dealer driven exchange, finding stronger support for the model

compared to earlier results for NYSE listed stocks. Jones (2001) covers the Dow Jones Index, Hegde and

McDermott (2003) investigate the S&P 500 index and Acharya and Pederson (2005) study the AMEX.

Secondly, the liquidity-return relationship has been documented to be robust to the use of a

variety of liquidity proxies. Jones (2001) uses quoted spread and turnover to find liquidity to be a

positively significant factor affecting asset prices; Easley, Hvidkjaer and O'Hara (2002) use the

probability of information tradingto proxy for liquidity; Amihud (2002) uses 'Illiq', the daily ratio of

absolute stock return and dollar volume, averaged over a period; Pastor and Stambaugh (2003) construct

a return reversal based liquidity measure and Liu (2006) develops LMx, the standardized turnover-

adjusted number of zero daily trading volumes over the prior x months, said to capture the dimension of

trading speed. All these studies find liquidity, as proxied by various measures, to be a significant factor

affecting asset prices.

Third, the effect of liquidity on returns has not been examined in isolation. Studies reveal that

liquidity has an effect that is significant and clearly distinct from other factors that affect stock returns.

Davila (2001) using a model containing real stock returns, excess liquidity and real interest rate finds that

1Shazia Parwez2Valeed Ahmed Ansari


stock returns were negatively affected by excess liquidity. Chordia et al (2000) find a negative and strong

relation between liquidity volatility and expected stock returns even after controlling for size, book-to-

market ratio, momentum, price level and dividend yield effects.

A fourth trial of the significance of liquidity as a factor in asset pricing has been to subject the

liquidity-return relation to out-of-sample stocks i.e. stocks traded in different markets of the world, even

though it is the US market that has been examined the most. Marshall and Young (2003), for example,

study the Australian Stock Exchange (ASX), to find the liquidity-turnover relation to be statistically

significant and negative throughout the year. Demir, Muthuswamy and Walter (2004); Chan and Faff

(2005) and Domowitz, Hansch and Wang (2005) also study the Australian market and obtain the same

results. Loderer and Roth (2005) study the Swiss Exchange (SWX); Wang and DiIorio (2007) examine

the Shanghai and Shenzhen stock exchanges; Chang, Faff and Hwang (2010) study the Tokyo Stock

Exchange; Lam and Tam (2011) study the Hong Kong market; Chung and Wei (2005) examine the

Chinese stock market and Chuang and Lee (2010) deal with the Taiwanese stock market. All studies find

the liquidity-return relation holds good.

It can be noted that most of studies have been carried out on developed markets. There are,

however, a few studies which have covered Asia and other emerging markets of the world. Dey (2005),

using portfolio turnover as liquidity proxy, studies 48 developed and emerging stock markets spanning

all the five continents, through the Federation of International Stock Exchanges (FIBV). He finds that,

though, there generally exists a positive return-liquidity relationship, further tests show this to be

exclusive to emerging markets. Bekaert et al (2007) study 18 emerging markets and find that liquidity is

priced in these. Hearn (2010) using the bid-ask spread and Liu's measure proposes a size and liquidity

augmented CAPM to explain the cross-section of stock returns in South Asian emerging markets

including India. He finds the size effect to be all pervasive but the liquidity effect to be present in only a

few industries of India. Hearn replicates this study for four markets of West Asia and Africa namely

Egypt, Morocco, Algeria and Tunisia. He finds that though the relationship between liquidity and stock

returns holds across all of them it is particularly robust in Morocco. Lee (2011) studies 50 different

markets of the world to find that liquidity risks are priced in international financial markets even after

controlling for liquidity level, size and the book-to-market ratio. The study by Amihud et al. (2015)

examines 45 markets of the world, both developed and developing. Controlling for the three Fama-

French factors both at the regional and the global level they find that a liquidity premium exists across

markets and it is higher in the emerging markets than in the developed ones. Illiquid stocks in India in

particular earn a monthly premium of 2.60 per cent over liquid ones.

It is evident from the foregoing discussion that the liquidity-return relationship has been

Liquidity and Stock Returns: A Study of The Indian Market


scantly studied in the Indian context. We investigate whether liquidity as a characteristic (stock level)

and liquidity as risk factor is priced in India. We employ a time-series regression approach and use three

different models for the purpose of comparison. These are the three-moment CAPM, the Fama-French

three factor model, and a liquidity-augmented four factor model. We thus account for all the well-

documented factors considered to affect asset returns. Amihud's proxy for illiquidity (hereafter 'Illiq'),

which represents the price-impact of a trade, is our liquidity proxy as well. Market capitalization and

book-to-market ratio are used to construct the Fama-French SMB and HML factors. The liquidity factor

is constructed as the difference in the returns of the least and most liquid stocks, a method previously

employed by Marcelo and Quiros (2006); S. Kim, D. Kim and Shin (2012), and Amihud et al (2015). The

factor of coskewness has been constructed on the lines of Lam and Tam (2011). Finally, as a test of

robustness we subject the data to a sub-period analysis as well as testing during up-market and down

market conditions.

3. Methodology

The data are obtained from Prowess, a database maintained by the Centre for Monitoring the

Indian Economy (CMIE).The sample consists of the stocks that constitute BSE 500 index. It represents

93 per cent of the universe by market capitalization. The study covers a period of 12 years from April

2000 to March 2012.

Our proxy for the main independent variable i.e. illiquidity is the 'Illiq', a measure of the price

impact of (il) liquidity on the market, developed by YakovAmihud (2002). It is the average ratio of the

absolute daily stock return to the trading volume.

Illiqit = (1/Nit) Ód (|rid| / volid)

Nit is the number of trading days for stock i in period t.

|rid| is the absolute return in rupees on stock i on day d.

Volid is the trading volume in rupees, obtained by multiplying the number of shares traded by

the closing price.

Illiqit is calculated for each stock i based on daily data over the previous 12 months and

averaged for the year.

We sort stocks on their annual illiquidity and aggregate them into ten equal size portfolios

every year. The equally weighted average returns of these portfolios are computed in the following year.

This is in keeping with the methodology followed in previous studies (Lam and Tam, 2011; Amihud et

al., 2015 etc.).

We test three different models of asset pricing in this study. These are the three-moment

CAPM, the Fama-French three factor model and the liquidity-augmented four-factor model. All of the



factors in these models have been documented to have an effect on the variation of stock returns. The

three-moment CAPM was studied for the first time by Kraus and Litzenberger (1976). More recently,

Harvey and Siddique (2000) and Chen, Hong and Stein (2001) have also found a relationship between

coskewness and stock returns. The Fama- French factors are supported by a plethora of studies in various

markets of the world. The effect of liquidity is also considered to be an important factor. Apart from the

three main models, for the purpose of comparison, two other combinations of factors have also been

subject to regression. These are a market factor only model and a 'market and liquidity' factors model. We

estimate the Ordinary Least Squares (OLS) time-series regressions for the ten portfolios on the said

models. This procedure is repeated for every month for the period between May 2000 and March

2012.The three main models examined in our study are:

R – R = a + b R -R + ö CSK+ å (1)pt ft p p M f p pt

R – R = a + b R -R + s SMBt+ h HML + å (2)pt ft p p M f p p t pt

R – R = a + b R -R + s SMBt+ h HML + ø LIQ + å (3)pt ft p p M f p p t P t pt

Where (R – R ) is portfolio excess returns; RM-Rf is market excess return where RM is the pt ft

market return represented by the BSE 500 index return and Rf is the risk-free rate represented by the

yield on the 91 days treasury bill (RBI website); CSK is coskewness, calculated as the square of the

difference between market excess return and its time series average; SMBt is the size factor; HMLtis the

book-to-market factor and LIQt is the liquidity factor; åpt is the error term assumed to have a zero mean

and uncorrelated to all the other explanatory factors. The factor sensitivities/loadings, bp, öp, sp, hp, and

øP, are the slope coefficients in the regressions for RM-Rf, CSK, SMB, HML and LIQ respectively.

The SMB and HML factors are formed as follows. All stocks in a year are divided into two

groups based on the median market capitalization at the beginning of the year (in this case March). Both

the size groups are further divided into three groups based on their annual book-to-market ratio. This

results in the formation of six portfolios. The SMB factor is the difference in the average returns of the

small market capitalization and the large market capitalization portfolios. HML is the difference in the

average returns of the high and low book-to-market ratio portfolios within the size portfolios. The

liquidity risk factor 'LIQ' is composed on the lines of Kim et al (2012), by the difference of returns

between the most illiquid stocks (top 20 per cent) and most liquid stocks (bottom 20 per cent).

To check the soundness of our results, we also conduct two robustness tests: a sub-period test

(dividing the total period into two equal sub-periods) and a conditionality test (dividing the total period

into up-market and down-market periods). For both of these we perform monthly regressions on

equations (2) and (3).We divide the entire period into two equal sub-periods of six years each i.e. from

May 2000 to March 2006 and April 2006 to March 2012. Up and down markets are classified in

accordance with the procedure of Petengill, Sundaram and Mathur (1995). If the market excess return is



positive (negative) the market is classified as up-market (down market). The months in which the market

is up, are separated from the months in which the market is down, and separate regressions are run on

equations (2) and (3) for these months.

The purpose of this study is to investigate whether liquidity has a role to play in stock returns.

To evaluate whether one model performs better than other, the improvement in the number of

insignificant intercepts and the percentage in the adjusted R squared values is checked. For instance, if

one model is better than the other, it will yield an increase in the number of insignificant intercept and in

the adjusted R squared percentage (Lam and Tam, 2011).

4. Results

4.1 Descriptive statistics and correlations

Table 1 presents the descriptive statistics of the 10 portfolios sorted by our main proxy 'Illiq'. The average

illiquidity decreases from 1.069 for portfolio one to the almost negligible value of 0.00015 for portfolio

10. Average returns for the 10 'Illiq' based portfolios show a decreasing trend from 4.63 per cent for the

least liquid (P1) to 0.13 per cent for the most liquid portfolio (P10). As expected, the average size of

companies also shows a fairly smooth, increasing trend, from 18,460 million rupees (278 million USD)

to 694,860 million rupees (10 billion USD), between portfolios one and ten respectively. The average

book-to-market ratio declines from 2.054 for the most illiquid portfolio to 0.522 for the most liquid

portfolio.



L1

L2

L3

L4

L5

L6

L7

L8

L9

L10

L1-

L10

Mea

n0.

0463

0.02

92

0.02

22

0.01

96

0.02

14

0.01

88

0.01

66

0.01

51

0.00

97

0.00

13

0.04

5

Med

ian

0.03

7

0.

0314

0.

0279

0.

0317

0.02

6 0.

0293

0.

0196

0.

0144

0.01

51

0.

0104

0.

0263

Max

imu

m0.

4742

0.

4199

0.

4976

0.

4668

0.51

68

0.53

72

0.49

29

0.57

46 0.

4237

0.

4909

0.

4283

Min

imu

m-0

.221

8

-0.3

004

-0

.286

4

-0.3

256

-0

.343

2 -0

.347

8

-0.3

01

-0.3

086

-0.3

441

-0

.347

8

-0.1

773

Std

. Dev

.0.

1199

0.

1087

0.

1001

0.

1081

0.11

04

0.10

54

0.10

33

0.11

28 0.

0977

0.

1011

0.

0899

Sk

ewn

ess

0.59

72

0.29

18

0.54

91

0.11

86 0.

2593

0.

3776

0.

2483

0.

9738

0.0

122

0.

4031

0.

9574

Ku

rtos

is3.

785

4.

1132

5.

9732

4.

7462

5.53

8 6.

9805

5.

984

8.

167

5.3

788

6.

7291

5.

1985

Ave

rage

R

etu

rns

4.63

%

2.92

%

2.22

%

1.96

%

2.14

%

1.88

%

1.66

%

1.51

% 0.

97%

0.

13%

4.

50%

t-st

ats

(4.6

16)*

*

(3.2

09)*

*

(2.6

53)*

*

(2.1

66)*

(2

.314

)*

(2.1

32)*

(-

1.92

5)

(-1.

602)

(-1.

19)

(-

0.15

)

(5.9

87)*

*

Av.

Ill

iq1.

0690

0.

3855

0.

2077

0.

1119

0.04

89

0.

0190

0.

0073

0.

0033

0.00

09

0.

0002

A

v S

ize

1,84

1.80

64

1,47

8.09

83

1,72

4.88

16

2,48

4.03

99

3,76

9.29

57

6,22

1.91

20

7,73

8.71

11

11,1

27.7

222

19,6

22.0

647

69,4

86.2

164

Av.

BM

2.05

441.

0401

0.96

890.

9040

0.86

090.

7951

0.72

390.

7121

0.57

960.

5221

Tab

le 1

.

Des

crip

tive

sta

tist

ics

of t

he 1

0 p

ort

foli

os

sort

ed o

n IL

LIQ

on

ly f

or t

he p

erio

d b

etw

een

May

20

00

and

Mar

ch 2

01

2. '

L1

-L10

' is

the

hed

ge p

ortf

olio

. T

he d

aily

Ill

iq v

alue

of

ever

y st

ock

lis

ted

on

th

e B

SE

50

0 f

or t

he

give

n p

erio

d i

s ca

lcul

ated

in

acc

ord

ance

wit

h

Am

ihud

's f

orm

ula.

The

dai

ly I

lliq

val

ues

are

then

ave

rag

ed a

t th

e en

d o

f M

arch

eve

ry y

ear

for

the

prec

edin

g 1

2 m

on

ths.

Sto

cks

are

then

so

rted

in d

esce

nd

ing

ord

er o

f th

ese

valu

es. T

hey

are

su

bse

quen

tly

div

ided

into

10

port

foli

os w

ith

L1

bein

g th

e le

ast l

iqui

d (m

ost

illi

quid

) and

L1

0 b

eing

the

mo

st li

qu

id (l

east

illi

quid

).Y

earl

y ti

me-

seri

es a

ver

age

retu

rn v

alu

es a

re re

port

ed h

ere

for t

he 1

0 p

ortf

olio

s.

Ave

rage

ret

urn

s (i

n pe

rcen

t) a

re t

he r

etu

rns

of a

ll t

he

sto

cks

in a

por

tfo

lio

fo

r th

e en

tire

12

year

per

iod.

T-s

tati

stic

s fo

r th

e av

erag

e

retu

rns

are

repo

rted

in p

aren

thes

es a

nd

mar

ked

wit

h '*

*' t

o de

note

sig

nif

ican

ce a

t th

e 1%

lev

el a

nd w

ith

'*' t

o d

eno

te s

ign

ific

ance

at

the

5% l

evel

. Av.

Ill

iq i

s th

e av

erag

e il

liqu

idit

y c

alcu

late

d u

sin

g A

mih

ud

's I

lliq

, of

all

th

e co

mpa

nies

in

a p

ort

foli

o ov

er t

he e

nti

re

per

iod.

Av.

Siz

e is

the

aver

age

mar

ket c

apit

aliz

atio

n in

mil

lion

rup

ees,

ove

r th

e en

tire

per

iod

for

all

the

com

pan

ies

in a

po

rtfo

lio

. Av.

BM

is th

e av

erag

e b

ook-

to-m

ark

et ra

tio

of a

ll th

e co

mpa

nies

in a

giv

en p

ortf

olio

, fo

r th

e en

tire

per

iod.



Table 2 has the descriptive statistics of the explanatory variables. The average value of the

excess market return (RM-Rf) is 0.87 per cent (t= 1.23) per month. The pre sub-prime crisis excess

market return values for the US was 0.41per cent (Keene and Peterson, 2007). Compared to this value,

the return in India is roughly twice. The monthly size premium (SMB) and the average monthly book-to-

market value premium (HML) are 1.79 per cent (t= 5.70) and 1.93 per cent (t= 4.74) respectively. While

the SMB value for India is more than eight times that of the US market (0.21 per cent, Keene and

Peterson, 2007), the HML value is four times that of the US (0.43 per cent, Keene and Peterson, 2007).

This shows that investors in India are much more sensitive to the size and the book-to-market ratio of

stocks as compared to investors of the US market.The liquidity factor (LIQ) registers an average

monthly return of 3.11 per cent. This is the return obtained on a zero investment portfolio, by buying long

the top 20 per cent (most illiquid) firms and selling short the bottom 20 per cent (most liquid) firms. On

the other hand, the returns yielded bottom decile and top decile illiquidity portfolio generates a return of

4.50 per cent which is 16 times that of the US liquidity premium (Amihud et al, 2015). This is an

indication that Indian investors are more concerned about the liquidity of the stocks they invest in than

investors in the US market.

Table 2.

These are the descriptive statistics of the explanatory variables in the time-series regressions

for May 2000 to March 2012. 'Rm-Rf' is the monthly market excess return, calculated as the difference

between the return on the BSE 500 index and the 10 year government security rate of return. Following

Fama and French (1993) SMB is the difference in the average returns of the two size based portfolios

(small minus big), HML is the difference between the returns of two extreme book-to-market ratio based

portfolios across the two size portfolios. CSK is the coskewness factor, calculated as the square of the

monthly market excess return minus its time-series average, and LIQ is the liquidity factor represented

by the difference between the returns of the least liquid 20 per cent and the most liquid 20 per cent of

stocks.

RM_RF

SMB

HML

CSK

LIQ

Mean

0.00873

0.017947

0.019367

0.00718 0.03114

Median 0.014486 0.013269 0.015666 0.002921 0.019877

Maximum 0.330631 0.164276 0.277793 0.109317 0.31754

Minimum -0.27844 -0.06821 -0.06123 1.52E-06 -0.12349

Std. Dev. 0.084581 0.037653 0.048819 0.013426 0.06575

Skewness -0.22565 0.797138 1.464936 4.630854 1.106773

Kurtosis 4.597637 4.352156 7.648132 30.38887 5.643648



Table 3 has the 'Pearson's pair-wise correlation's between the explanatory factors. Overall, the

highest correlation between any two explanatory variables is 0.71, between the liquidity factor' LIQ' and

Fama and French's size factor SMB. The weakest correlation is '-0.00982' found between the market

factor (Rm-Rf) and the coskewness factor (CSK). Correlations among all the other factors are also quite

weak with three of the ten being negative (all of them with CSK). Apart from the highest correlation

between size and liquidity, they never go beyond 0.28 (between the liquidity factor and HML). The low

correlations lead us to conclude that none of the factors are proxies for each other.

Table 3.

The table reports Pearson's pair-wise correlations between the explanatory variables Rm-Rf

(the market factor), SMB and HML (Fama-French size and book-to-market factors), CSK (coskewness)

and LIQ (the liquidity factor), for the entire sample period between May 2000 and March 2012.

RM_RF

SMB

HML

CSK

LIQ

RM_RF 1

SMB 0.0884 1

HML 0.2123 0.2507 1

CSK -0.0098 0.0166 -0.0118 1 LIQ 0.0180 0.7102 0.2869 -0.0565 1

4.2 Regression analysis

Table 4 contains the regression results for the three models examined in this study. Panel A has

the results of the three-moment CAPM model. Three of the ten intercepts are found to be significant, two

of them at the one per cent level. They are large and positive for the portfolios of the least liquid firms and

steadily decrease, turning negative for the most liquid firms.The market factor coefficients are highly

significant at the one per cent level and with double digit t-statistics. The average market factor

coefficient is almost one which is consistent with results of previous studies (e.g. Fama and French,

1993). Six of the ten coefficients of the coskewness factor are significant. The adjusted R squared values

increase from 40 per cent for the least liquid portfolio to 63 per cent for the most liquid portfolio. The

average adjusted R squared value for the model is 57.67 per cent.

Panel B shows results for a market and liquidity factors model. All intercepts are now

insignificant. The increasing trend that they exhibited in the three- moment CAPM model has

disappeared as well giving way to an irregular pattern. All but the hedge portfolio coefficient for the

market factor are significant. Six of ten coefficients for the liquidity factor are significant, four of them at

the one percent level. Their magnitude is also decreasing consistently,with the least liquid firms having



the largest liquidity factor coefficients and the two portfolios of the most liquid firms having the smallest

coefficients in relative terms. The average adjusted R squared value for this model is 62.11 per cent.

Panel C has the regression results for the three-factor Fama-French model. All intercepts continue to be

insignificant. Similar to the three-moment CAPM they show a generally decreasing trend, with the least

liquid firms having the highest coefficients and the most liquid firms having smallest coefficients,

relatively. All coefficients for the market factor, seven of ten for SMB and two out of ten for the HML

factor are significant. The significance of the SMB and HML coefficients means that they are relevant in

the Indian stock market, the latter albeit less so. The adjusted R squared values range between 70 per cent

(P1) to 60 per cent (P8).The average value is 65 per cent.

Panel D shows the results of the four-factor liquidity-augmented model. All intercepts are insignificant

and show no discernible trend. All coefficients of the market factor, nine of ten coefficients for SMB and

six of ten coefficients for HML are significant. For the fourth factor 'LIQ' depicting liquidity, seven out of

ten coefficients are significant, four of them at the one per cent level. Also there is a fairly clear

decreasing trend where the LIQ coefficient is positive and largest for the most illiquid portfolio (P1), and

turns negative from the third portfolio onwards till the most liquid portfolio (P10). The adjusted R

squared values range from 75 per cent (P1) to 59 per cent (P8) with the average adjusted R squared being

68.04 per cent, an increase of three percentage points over the average adjusted R squared of the three-

factor model.

Table 4.

The table reports the coefficients with the corresponding t-statistics (in parentheses) from

regressions run on the monthly returns of the 10 portfolios formed of BSE 500 stocks sorted on the basis

of their liquidity for the period May 2000 to April 2012. The models covered are – The three-moment

CAPM :Rpt – Rft= ap+ bpRM-Rf + öpCSK+ åpt (Panel A), Market and Liquidity factors model: Rpt –

Rft= ap+ bpRM-Rf+ øPLIQt+ åpt the Fama-French model Rpt – Rft= ap+ bpRM-Rf+spSMBt+

hpHMLt+ åpt(Panel C), and the four-factor Liquidity augmented model : Rpt – Rft= ap+ bpRM-Rf +

spSMBt+ hpHMLt+ øPLIQt+ åpt(Panel D).The last but one column contains the coefficients for hedge

portfolio (L1-L10). The last column contains the average adjusted R squared values of portfolios one to

ten, computed for the three models for the purposes of comparison. ** indicate significance at the 1%

level, * indicates significance at the 5% level.



L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L1-L10 Av.adj R 2

Panel A –Three Moment CAPM

C 0.0334** 0.0167* 0.0084 0.0063 0.0058 0.003 0.0025 0.0016 -0.0047 -0.0145* 0.0478**

(3.7766) (2.3594) (1.2957) (0.944) (0.8888) (0.5043) (0.4393) (0.2113) (-0.8253) (-2.4833) (5.5551)

RM_RF 0.9019** 0.9408** 0.8593** 0.9785** 1.0189** 1.003** 0.9984** 0.9425** 0.9139** 0.9436** -0.0417

(9.803) (12.7829) (12.6687) (14.1826) (14.9957) (16.3872) (17.0151) (11.9036) (15.5621) (15.5759) (-0.4653)

CSK 0.6974 0.5939 0.8699* 0.6651 0.9278* 0.9839* 0.756* 0.7338 0.892* 1.0422** -0.3448

(1.2033) (1.2809) (2.0357) (1.5304) (2.1676) (2.5518) (2.0452) (1.4712) (2.4113) (2.7309) (-0.6107)

Adjusted R-squared

0.4017 0.534 0.5331 0.5861 0.6151 0.6572 0.6721 0.4992 0.6333 0.6352 -0.0101 0.5767

Panel B - Market + LIQ

C 0.0069 0.0025 0.0061 0.0048 0.0076 0.007 0.0072 0.0019 0.0067 0.0011 0.00582

(1.1502) (0.4239) (0.984) (0.7499) (1.1837) (1.2063) (1.2963) (0.2585) (1.2214) (0.1923) (1.9254)

RM_RF 0.8866** 0.9315** 0.8541**

0.9746**

1.0153**

1.0001**

0.9969**

0.9391**

0.9147** 0.9456** -0.0590

(13.846) (14.8181) (12.865)

(14.2689)

(14.8648)

(16.0542)

(16.7446)

(11.8728)

(15.504) (15.811) (-1.8269)

LIQ 1.0157** 0.5952** 0.2768**

0.2014*

0.1582

0.0969

0.0222

0.1603

-0.1608* -0.259** 1.2748**

(12.3309) (7.3599) (3.2407)

(2.2918)

(1.8003)

(1.2095)

(0.2897)

(1.5753)

(-2.1189) (-3.3672) (30.7000) Contd.

L1 L2 L3

L4

L5

L6

L7

L8

L9 L10 L1-L10 Av. adj R 2

Adjusted R squared

0.7102 0.6601 0.5528

0.5944

0.6112

0.645

0.6625

0.5003

0.63 0.6446 0.8690 0.6211

Panel C – Fama French Model

C 0.0036 -0.001 -0.0024

-0.0052

-0.0011

-0.0007

-0.0022

-0.009

-0.0043 -0.0094 0.0130**

(0.578) (-0.1739) (0.0059)

(-0.8575)

(-0.1751)

(-0.1231)

(-0.4098)

(-1.317)

(-0.7531) (-1.5718) (2.1033)

RM_RF 0.7951** 0.8776** 0.8076**

0.9251**

0.9694**

0.9632**

0.9584**

0.8438**

0.8904** 0.9291** -0.1341**

(12.0583) (14.1698) (13.0127)

(14.4005)

(14.6485)

(15.7803)

(16.4858)

(11.6547)

(14.7127) (14.5894) (-2.0399)

SMB 1.6227** 1.0808** 0.8165**

0.7178**

0.5447**

0.4304**

0.3726**

0.1119

0.2355 0.048 1.5746*

(10.8531) (7.6964) (5.8016)

(4.9281)

(3.6302)

(3.1099)

(2.8266)

(0.6815)

(1.7162) (0.3325) (10.5675)

HML 0.3414** 0.161 0.1487

0.1967

0.2176

0.1735

0.1968

0.7599**

0.1044 0.0892 0.2522**

(2.9042) (1.4586) (1.3441)

(1.7173)

(1.8443)

(1.5945)

(1.8992)

(5.8881)

(0.9678) (0.7855) (2.1527)

Adjusted R squared

0.7069 0.6853 0.6272

0.6578

0.6518

0.6748

0.693

0.6006

0.6286 0.6155 0.4821 0.6542

Panel D – Four factor liquidity augmented model

C -0.0005 -0.0028 -0.0012 -0.0033 0.0005 0.0009 0.0002 -0.0084 -0.0003 -0.0052 0.0048

(-0.0797) (-0.4751) (-0.1997) (-0.5542) (0.0722) (0.1595) (0.0325) (-1.2112) (-0.0672) (-0.9647) (1.5153)

RM_RF 0.8276** 0.8916** 0.7978** 0.9101** 0.957** 0.9502** 0.939** 0.8387** 0.8587** 0.8952** -0.0676*

(13.7293) (14.5477) (12.864) (14.336) (14.5268) (15.6995) (16.7138) (11.5071) (15.744) (15.6579) (-2.0352)

SMB 0.9108** 0.7749** 1.0309** 1.0457** 0.816** 0.7157** 0.798** 0.2239 0.9303** 0.7900** 0.1208

(4.8387) (4.0494) (5.3236) (5.2756) (3.967) (3.7869) (4.5492) (0.9839) (5.4626) (4.425) (1.164) Contd.

L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L1-L10 Av. adj R 2

HML 0.2367* 0.116 0.1803 0.2449* 0.2575* 0.2155 0.2594* 0.7764** 0.2066* 0.1983 0.0384

(2.1785) (1.0507) (1.6127) (2.1405) (2.1687) (1.9753) (2.562) (5.9112) (2.1019) (1.9245) (0.6406)

LIQ 0.5963** 0.2562* -0.1796 -0.2746* -0.2272 -0.2389* -0.3563** -0.0938 -0.5819** -0.6214** 1.2177**

(5.4719) (2.313) (-1.6022) (-2.3932) (-1.908) (-2.1835) (-3.5085) (-0.7123) (-5.9022) (-6.0127) (20.2715)

Adjusted R-squared

0.7574 0.6948 0.6314 0.669 0.6583 0.6834 0.7161 0.5992 0.7013 0.6931 0.8689 0.6804



4.3 Comparison of the three moment, three-factor and four factor models

We compare the intercepts, variable coefficients and adjusted R squared values of the three

models as well as the market factor only and the 'market and liquidity' factors model. The following

results emerge. The number of significant intercepts goes down from the market factor and three-

moment CAPM models (four and three significant intercepts respectively), to the four-factor liquidity

model (nil significant intercepts). A stronger argument in favour of the four-factor liquidity augmented

model is the average adjusted R squared value. This value increases steadily from 52 per cent for the

'market only' model, to 56 per cent for the 'three-moment CAPM', to 62 per cent for the 'market and

liquidity' model. It becomes 65 per cent for the Fama and French model and finally peaks at 68 per cent

for the four-factor liquidity-augmented model.

A separate examination of the 'market and liquidity factors' model brings out the significance

of the liquidity factor. The average adjusted R squared value for it is 62 per cent, which is higher than the

'market factor' model's average adjusted R squared of 56 per cent. The liquidity factor alone has therefore

contributed eight per cent to the explanatory power of the market factor model. Also, this value is only

three per cent lower than the Fama-French model's average adjusted R squared value of 65 per cent. The

four-factor liquidity-augmented model has by far the most explanatory power. It is a corollary that the

liquidity factor has enhanced the explanatory power of the asset pricing model. Thus it may be said that

(il) liquidity is a relevant factor in the consideration of pricing of assets in the Indian market.

4.4 Robustness tests

Table 5 has the results of the first sub-period for the Fama and French model (Panel A) and the

liquidity-augmented four factor model (Panel B). The pattern of results obtained is the same as that for

the entire period. Though the intercepts are insignificant for both the Fama-French and the four-factor

models, for the first sub-period, the adjusted R squared values show an increase of three percentage

points from the Fama-French to the four-factor model (37.6 per cent to 40.2 per cent resp.). Similarly for

the second sub-period (Table 6, panels A and B), there is an increase in the average adjusted R squared

value from the three-factor to the four-factor model (91.02 per cent and 92.03 per cent resp.).



Sub-period 1

L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L1-L10 Av adj R2

Panel A – Fama - French model

C 0.0028 -4.67E-05 -0.0003 0.0012 0.0076 0.0067 0.0007 -0.0048 0.0027 -0.0072 0.01

(0.2343) (-0.0041) (-0.0251) (0.1037) (0.6589) (0.6167) (0.0717) (-0.3702) (0.252) (-0.6509) (0.9316)

RM_RF 0.6558** 0.7238** 0.5379** 0.6382** 0.6262** 0.6284** 0.6304** 0.4954** 0.5514** 0.5199** 0.1359

(5.3468) (6.1416)

(4.6757)

(5.2462)

(5.3113)

(5.6103)

(6.051)

(3.7213)

(4.9437)

(4.5922) (1.2356)

SMB 1.8638** 1.2018**

0.8117**

0.5843*

0.521*

0.3979

0.3114

-0.0371

0.2384

0.1397 1.7242**

(8.0551) (5.4057)

(3.7404)

(2.5462)

(2.3424)

(1.8832)

(1.5843)

(-0.1476)

(1.133)

(0.6539) (8.3122)

HML 0.4826** 0.2726

0.2645

0.2707

0.2441

0.1917

0.1665

0.9457**

0.061

0.0745 0.4082**

(2.8758) (1.6907)

(1.6807)

(1.6261)

(1.5132)

(1.2506)

(1.168)

(5.1911)

(0.3994)

(0.4806) (2.7131)

Adjusted R-squared

0.6161 0.515

0.3672

0.3512

0.3451

0.3447

0.3671

0.3799

0.2558

0.2201 0.5448 0.37622

Panel B – Four factor liquidity augmented model

C 2.26E-05 -0.0009 0.0005 0.0021 0.0085 0.0074 0.0016 -0.0051 0.005 -0.0049 0.0049

(0.0021) (-0.0758) (0.0464) (0.1794) (0.7374) (0.6766) (0.1598) (-0.3909) (0.4888) (-0.47) (0.8431)

RM_RF 0.5414** 0.6898**

0.5709**

0.6753**

0.6634**

0.6564**

0.6671**

0.4825**

0.6441**

0.6157** -0.0743

(4.6349) (5.6453)

(4.7867)

(5.3591)

(5.4358)

(5.6412)

(6.2012)

(3.4703)

(5.9406)

(5.6091) (-1.2092)

Contd.

L1 L2

L3

L4

L5

L6

L7

L8

L9

L10 L1-L10 Av adj R2

SMB 0.9617** 0.9337**

1.0724**

0.8766*

0.8143*

0.619

0.6007*

-0.1389

0.9696**

0.8948** 0.0669

(2.9636) (2.7504)

(3.2362)

(2.504)

(2.4013)

(1.9149)

(2.01)

(-0.3596)

(3.2188)

(2.9341) (0.3917)

HML 0.2886 0.2149 0.3206 0.3336 0.3072 0.2392 0.2287 0.9238** 0.2183 0.2369 0.0516

(1.772) (1.2618) (1.9282) (1.8987) (1.8055) (1.4747) (1.5253) (4.7655) (1.444) (1.5481) (0.6026)

LIQ 0.6813** 0.2025 -0.1969 -0.2207 -0.2215 -0.167 -0.2185 0.0769 -0.5523** -0.5703** 1.2517**

(3.6767) (1.0448) (-1.0404) (-1.1042) (-1.1437) (-0.9047) (-1.2805) (0.3487) (-3.2106) (-3.2749) (12.8344)

Adjusted R-squared

0.6766 0.5157 0.368 0.3533 0.3481 0.343 0.3731 0.3717 0.3466 0.3189 0.868 0.4015

Table 5.

Results from the regressions for the first sub-period (May 2000 to March 2006), run for the

monthly returns of the 10 portfolios formed of BSE 500 stocks sorted on the basis of Amihud's Illiq.

Panel A has results of the Fama-French model and Panel B of the liquidity-augmented four-factor model.

The last but one column contains the regression coefficients for the hedge portfolio. The last column

represents the average adjusted R squared values (averaged L1 to L10), for the models. ** indicate

significance at the 1% level, * indicates significance at the 5% level.



Table 6.

Results from the regressions for the second sub-period (April 2006 to March 2012), run for the

monthly returns of the 10 portfolios formed of BSE 500 stocks sorted on the basis of Amihud's Illiq.

Panel A has results of the Fama-French model and Panel B of the liquidity-augmented four-factor model.

The last but one column contains the regression coefficients for the hedge portfolio (L1-L10). The last

column represents the average adjusted R squared values for the models. ** indicate significance at the

1% level, * indicates significance at the 5% level.

Sub-period 2


Panel A – Fama-French model

C 0.0035 -0.0015 -0.0019 -0.0069 -0.0042 -0.0029 -0.0006 -0.0089 -0.0059 -0.0073 0.0108

(0.7694) (-0.3407) (-0.4383) (-1.7095) (-0.8389) (-0.735) (-0.1558) (-2.069) (-1.6032) (-1.9519) (1.9438)

RM_RF 0.9661** 1.0426** 1.0533** 1.1652** 1.2441** 1.2263** 1.1901** 1.1669** 1.1354** 1.2361** -0.27**

(19.0628) (21.3415) (21.917) (25.9625) (22.1889) (28.0587) (27.1239) (24.2784) (27.4916) (29.4861) (-4.3441)

SMB 1.2156** 0.8883**

0.8792**

0.9793**

0.5288**

0.4406**

0.4609**

0.4952**

0.1409

-0.1624 1.378**

(8.3179) (6.3054)

(6.344)

(7.5671)

(3.2708)

(3.4958)

(3.6427)

(3.5727)

(1.1829)

(-1.3437) (7.6882)

HML -0.1547 -0.2561

-0.3083*

-0.1746

-0.0267

-0.0238

0.2307

0.0258

0.1259

0.0692 -0.2239

(-1.1317) (-1.9434)

(-2.3781)

(-1.4423)

(-0.1766)

(-0.2016)

(1.949)

(0.1993)

(1.13)

(0.6122) (-1.3356)

Adjusted R-squared

0.8799 0.8886

0.8922

0.9237

0.8931

0.9297

0.9301

0.9103

0.9273

0.9336 0.5123 0.91085


C -0.0001 -0.0044 -0.0022 -0.0065 -0.0051 -0.0032 -0.0003 -0.0089* -0.0039 -0.0052 0.0051

(-0.0313) (-1.1439)

(-0.4999)

(-1.5921)

(-1.0164)

(-0.7964) (-0.065)

(-2.0271)

(-1.1419)

(-1.5182) (1.5155)

RM_RF 1.0865** 1.1388**

1.0634**

1.153**

1.2753**

1.2362**

1.1784**

1.1666**

1.0669**

1.1655** -0.0791

(24.676) (24.5117)

(19.9642)

(23.2025)

(20.7118)

(25.5241)

(24.2526)

(21.864)

(25.8417)

(27.9083) (-1.9315) Contd.

L1 L2

L3

L4

L5

L6

L7

L8

L9

L10 L1-L10 Av. Adj.R 2

SMB 0.5163** 0.3297

0.8203**

1.05**

0.3475

0.3833*

0.5292**

0.4973*

0.539**

0.2475 0.2688

(3.2776) (1.9833)

(4.3043)

(5.9054)

(1.5774)

(2.2122)

(3.0446)

(2.6052)

(3.6489)

(1.6567) (1.8355)

HML -0.0528 -0.1747 -0.2997* -0.1849 -0.0003 -0.0154 0.2207 0.0255 0.0679 0.0095 -0.0623

(-0.4847) (-1.52) (-2.2745) (-1.5041) (-0.0019) (-0.1288) (1.8364) (0.1935) (0.6645) (0.0917) (-0.615)

LIQ 0.6933** 0.5538** 0.0584 -0.07 0.1798 0.0568 -0.0678 -0.0021 -0.3947** -0.4064** 1.0997**

(6.5103) (4.9289) (0.4531) (-0.5826) (1.2071) (0.4847) (-0.5767) (-0.0164) (-3.9526) (-4.0239) (11.1098)

Adjusted R-squared

0.9253 0.917 0.8909 0.923 0.8938 0.9289 0.9295 0.9089 0.9401 0.9457 0.8259 0.92031



Table 7 has the results for the robustness check of conditionality where the previous results are

checked for consistency during up and down market conditions. The up and down markets test also

reveals the same pattern of results as that for the entire period, albeit with differing magnitudes. During

up-market conditions the number of significant intercepts for the three-factor model is two which is

reduced to one on the addition of liquidity. Average adjusted R squared values go up from 53.7 per cent to

56.8 per cent for the Fama-French and four-factor model respectively. Similarly during down market

conditions (Table 8), though the intercepts are insignificant throughout, the adjusted R squared values

increase from 39.06 per cent to 44.36 per cent for the three and four-factor models respectively.

Table 7.

Table shows results of the regressions for up-market conditions run on 10 portfolios. In

accordance with the procedure followed by Petengill et al (1995) the period where excess market returns

are positive is classified as a period of up-market conditions. Panel A has results of the Fama-French

model and Panel B of the liquidity-augmented four-factor model. The last column represents the average

adjusted R squared values for the three models. ** indicate significance at the 1% level, * indicates

significance at the 5% level.

Up-market



C -0.013 -0.0177 -0.0199 -0.0103 -0.0191 -0.0181 -0.012 -0.0267* -0.0142 -0.0253* 0.0124

(-0.9647) (-1.4795) (-1.6281) (-0.8694) (-1.5708) (-1.6219) (-1.075) (-2.4922) (-1.4251) (-2.1899) (0.8861)

RM_RF 1.0171** 1.0875** 1.0509** 1.0275** 1.2145** 1.2086** 1.1106** 1.1515** 1.094** 1.2131** -0.196

(6.8028) (8.1743)

(7.7128)

(7.7917)

(8.9662)

(9.7299)

(8.9553)

(9.6448)

(9.8602)

(9.4263) (-1.2622)

SMB 1.774** 1.1886**

0.9477**

0.5918**

0.5375**

0.3891*

0.3629*

0.3888*

0.1248

0.0502 1.7238**

(8.9662) (6.7517)

(5.256)

(3.3912)

(2.9984)

(2.3671)

(2.2114)

(2.461)

(0.8499)

(0.295) (8.3895)

HML 0.2104 0.1005

-0.0481

0.2397

0.19

0.153

0.1581

0.2644

0.0761

-0.0655 0.276

(1.1207) (0.6016)

(-0.281)

(1.4472)

(1.1168)

(0.9807)

(1.015)

(1.7634)

(0.5458)

(-0.4055) (1.4153)

Adjusted R-squared

0.6141 0.5673

0.4851

0.4784

0.5246

0.5536

0.5133

0.5645

0.5498

0.5211 0.535 0.53718


C -0.0169 -0.0194 -0.0194 -0.0094 -0.0189 -0.0178 -0.0102 -0.0258* -0.0123 -0.0231* 0.0061

(-1.5206) (-1.6834)

(-1.5747)

(-0.7935)

(-1.5437)

(-1.5844)

(-0.9555)

(-2.4191)

(-1.3155)

(-2.1333) (0.8445)

RM_RF 1.0881** 1.119**

1.0406**

1.0109**

1.2112**

1.2033**

1.0798**

1.1344**

1.0592**

1.1729** -0.0848

(8.7506) (8.6772)

(7.5864)

(7.6712)

(8.8498)

(9.5959)

(9.0221)

(9.5408)

(10.1894)

(9.7199) (-1.0477) Contd.

L1 L2

L3

L4

L5

L6

L7

L8

L9

L10 L1-L10 Av. Adj. R 2

SMB 0.6807** 0.7033**

1.1061**

0.8473**

0.5884*

0.471

0.8378**

0.652**

0.6607**

0.6686** 0.012

(2.8033) (2.7931)

(4.1297)

(3.293)

(2.2018)

(1.9235)

(3.5849)

(2.8081)

(3.2551)

(2.8377) (0.0762)

HML 0.0598 0.0336 -0.0262 0.2749 0.197 0.1643 0.2235 0.3006* 0.1499 0.0197 0.0401

(0.3798) (0.2061) (-0.1512) (1.6477) (1.1369) (1.0347) (1.4752) (1.9974) (1.139) (0.1287) (0.3917)

LIQ 0.8156** 0.362* -0.1182 -0.1906 -0.038 -0.0611 -0.3542** -0.1963 -0.3998** -0.4613** 1.2769**

(6.1007) (2.6111) (-0.8013) (-1.3456) (-0.2584) (-0.4531) (-2.7531) (-1.5356) (-3.5773) (-3.5558) (14.6786)

Adjusted R-squared

0.7354 0.597 0.4827 0.4837 0.5189 0.549 0.5507 0.5718 0.6083 0.5826 0.8748 0.56801



Table 8.

The table shows results of the regressions for down-market conditions run on 10 portfolios

sorted on Amihud's Illiq. In accordance with the procedure followed by Petengill et al (1995) the period

where excess market returns are negative is classified as a period of down-market conditions. Panel A

has results of the Fama-French model and Panel B of the liquidity-augmented four-factor model. The last

but one column contains the regression coefficients for the hedge portfolio (L1-L10). The last column

represents the average adjusted R squared values for the model. ** indicate significance at the 1% level,

* indicates significance at the 5% level.

Down-market



C -0.0015 -0.0045 0.0004 -0.0089 -0.0011 -0.0006 -0.0061 -0.0096 -0.0158 -0.0199 0.0184

(-0.1171) (-0.3507) (0.0341) (-0.6434) (-0.0804) (-0.0484) (-0.507) (-0.5578) (-1.1282) (-1.476) (1.5931)

RM_RF 0.6744**

0.7773**

0.7906**

0.8818**

0.9233**

0.9254**

0.8889**

0.7871**

0.742**

0.7701**

-0.0957

(4.7567)

(5.3798)

(5.7303)

(5.5765)

(5.7138)

(6.2485)

(6.4516)

(4.0153)

(4.6522)

(5.0146)

(-0.7255)

SMB 1.4543**

0.9759**

0.8546**

1.0333**

0.7665*

0.7335*

0.4962

0.0272

0.5553

0.2553

1.199**

(5.3131)

(3.4984)

(3.2083)

(3.3846)

(2.4568)

(2.5652)

(1.8653)

(0.0719)

(1.8033)

(0.8612)

(4.7098)

HML 0.4211**

0.192

0.2764

0.1764

0.2334

0.1875

0.225

1.0972**

0.137

0.2029

0.2183

(2.8447)

(1.2724)

(1.9185)

(1.0684)

(1.3833)

(1.2121)

(1.5637)

(5.3604)

(0.8226)

(1.2652)

(1.5852)

Adjusted R-squared

0.4744

0.3786

0.4142

0.3825

0.3795

0.4157

0.433

0.4541

0.267

0.307

0.3128 0.3906


C -0.0043 -0.0055 0.0029 -0.0058 0.0032 0.0035 -0.0029 -0.0103 -0.0084 -0.0122 0.0079

(-0.3446) (-0.4268) (0.2356) (-0.4194) (0.231) (0.2751) (-0.2462) (-0.5875) (-0.6821) (-1.0639) (1.398)

Contd.

L1

L2

L3

L4

L5

L6

L7

L8

L9

L10

L1-L10 Av. Adj. R 2

RM_RF 0.6909**

0.7835**

0.7763**

0.8632**

0.8978**

0.9013**

0.87**

0.7911**

0.6981**

0.7245**

-0.0336

(4.9355)

(5.3774)

(5.6693)

(5.5301)

(5.7467)

(6.3146)

(6.4557)

(3.9927)

(5.0401)

(5.5949)

(-0.5246)

SMB 1.2039**

0.8823**

1.0722**

1.3139**

1.1529**

1.0993**

0.7817*

-0.0346

1.2196**

0.9441**

0.2598

(3.8929)

(2.7411)

(3.5449)

(3.8104)

(3.3407)

(3.4868)

(2.6258)

(-0.079)

(3.9861)

(3.3002)

(1.8361)

HML 0.3745*

0.1745

0.3169*

0.2287

0.3054

0.2556

0.2781

1.0857**

0.2607

0.3311*

0.0434

(2.5217) (1.1292) (2.1818) (1.3809) (1.8426) (1.6881) (1.9455) (5.1648) (1.7743) (2.4104) (0.6382)

LIQ 0.3039 0.1136 -0.264 -0.3405 -0.4689* -0.4439* -0.3464 0.075 -0.8061** -0.8357** 1.1396**

(1.6527) (0.5938) (-1.4682) (-1.6611) (-2.2854) (-2.3685) (-1.9575) (0.2881) (-4.4315) (-4.914) (13.5478)

Adjusted R-squared

0.4901 0.3713 0.426 0.4013 0.423 0.4602 0.4603 0.445 0.45 0.5097 0.8387 0.44369



The coefficients of the liquidity factor, similar to those for the total period, are positive for the

most illiquid first two portfolios and turn negative thereon, decreasing consistently, till the most liquid

portfolio. This pattern is the same across the two sub-periods as well as the two conditions of the market.

The liquidity factor is therefore independent of the period as well as the market conditions as the four-

factor model works equally well across all the above specifications.

5. Conclusions

In this study, we examine the role of liquidity in pricing of stock returns in India. The results

show that portfolio of illiquid stocks earn a premium of 4.50 per cent per month over liquid ones, which

underlines the significance of liquidity as a characteristic of a stock. The significant magnitude of the

liquidity premium leads us to investigate whether liquidity as a risk factor is priced. An evaluation of the

performance of the three-moment CAPM, Fama and French three-factor model, the liquidity-

augmented four factor model and other specifications,provides evidence of the explanatory power of the

models. The results indicate that liquidity augmented Fama-French model has the maximum

explanatory power. Further, the intercepts show no pattern in terms of magnitude suggesting that

characteristic liquidity does not subsume liquidity risk.The results are robust to a sub-period test and

different market conditions.It implies that liquidity is an important factor in the determination of stock

returns in the Indian market. It has important implications for investors in portfolio construction as they

must take into reckoning the impact of liquidity on expected returns.

References

lAcharya, V. & Pedersen, L. (2005).Asset pricing with liquidity risk. Journal of Financial

Economics, 77 (3), 75-410.

Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal

of Financial Markets,5, 31-56.

lAmihud, Y. &Mendelson, H. (1986).Asset pricing and the bid-ask spread. Journal of Financial

Economics, 17, 223-49.

lAmihud, Y., Hameed, A., Kang, W. &Zhang, H. (2015). The illiquidity premium: International

evidence. Journal of Financial Economics.117 (2), 350-368.

lBekaert, G., Harvey, C. & Lundblad, C. (2007). Liquidity and expected returns: lessons from

emerging markets. Review of Financial Studies, 20, 1783–1831.

lBrennan, M. &Subrahmanyam, A. (1996). Market microstructure and asset pricing: on the

compensation for illiquidity in stock returns. Journal of Financial Economics, 41, 441-64.

lBrennan, M., Chordia, T. &Subrahmanyam, A. (1998).Alternative factor specifications,

l



security characteristics, and the cross-section of expected stock returns.Journal of Financial

Economics, 49(3), 345-73.

lChan, H.W. &Faff, R.W.(2005).Asset pricing and illiquidity premium. Financial Review, 40,

429–458.

lChang, Y.Y., Faff, R. &Hwang, C. (2010). Liquidity and stock returns in Japan: new evidence.

Pacific-Basin Finance Journal, 18, 90–115.

lChen, J., Hong & H., Stein, J. (2001). Forecasting crashes: trading volume, past returns, and

conditional skewness in stock prices. Journal of Financial Economics, 61, 345–381.

lChordia, T., Roll, R. &Subrahmanyam, A. (2000). Commonality in liquidity. Journal of

Financial Economics, 56, 3-28.

lChung, S. & Wei, P. (2005). The relationship between bid–ask spreads and holding periods: the

case of Chinese A and B shares. Global Finance Journal, 15, 239–249.

lChuang, W. & Lee, H. (2010). The impact of short sales constraints on liquidity and liquidity

related returns relations. Pacific Basin Finance Journal, 18, 521-535.

lDavila, J., C., W. (2001). Asset prices and monetary liquidity in Latin America. Ciencia

Economica (Spanish Version). Retrieved from

lDemir, I., Muthuswamy, J. &Walter, T., (2004). Momentum returns in Australian equities: The

influences of size, liquidity and return computation. Pacific-Basic Finance Journal, 12, 143-

158

lDey, M. K. (2005), Turnover and return in global stock markets.Emerging Markets Review, 6,

45– 67.

lDomowitz, I., Hansch, O. &Wang, X., (2005). Liquidity commonality and return co-

movement. Journal of financial markets 8(4), 351-376.

lEasley, D., Hvidkjær, S. &O'Hara, M., (2002). Is information risk a determinant of asset

returns? Journal of Finance, 57, 2185–2221.

lEleswarapu, V. R. &Reinganum, M. (1993). The seasonal behaviour of liquidity premium in

assetpricing. Journal of Financial Economics, 34, 373–386.

lEleswarapu, V.R., (1997). Cost of transacting and expected returns in the NASDAQ market.

Journal of Finance, 52, 2113–2127.

lFama, E.F. & French, K.R. (1992).The cross-section of expected stock returns. Journal of

Finance, 47, 427-65.

lHarvey, C., Siddique, A., (2000). Conditional skewness in asset pricing tests.Journal of

Finance 55, 1263–1295.



Hasbrouck, J. &Seppi, D.J. (2001), Common factors in prices, order flows and liquidity.

Journal of Financial Economics, 59, 383-411.

lHaugen, R.A. &Baker, N.L., (1996). Commonality in the determinants of expected stock

returns. Journal of Financial Economics, 41, 401–439.

lHearn, B., (2010). Time varying size and liquidity effects in South Asian equity markets: A

study of blue-chip industry stocks. International Review of Financial Analysis, 19, 242–257.

lHegde, S. P. &McDermott, J. B. (2003). The liquidity effects of revisions to the S&P 500 index:

an empirical analysis. Journal of Corporate Finance, 6, 413- 459.

lHuberman, G. &Halka, D. (2001).Systematic liquidity. Journal of Financial Research, 24,

161–178.

lJacoby, G., D.J. Fowler, & A. A. Gottesman. (2000). The capital asset pricing model and the

liquidity effect: a theoretical approach. Journal of Financial Markets, 3, 69 – 81.

lJones, C.M., (2001). A century of stock market liquidity and trading costs. Graduate School of

Business, Columbia University.

lKeene, M. & Peterson, D.(2007).The importance of liquidity as a factor in asset pricing.

Journal of Financial Research, 30, 91–109.

lKim, S., Kim D. & Shin, H. (2012).Evaluating asset pricing models. Pacific Basin Finance

Journal, 20 (198-227)

lKraus, A. &Litzenberger, R.H.(1976).Skewness preference and the valuation of risk

assets.Journal of Finance, 31, 1085–1100.

lLam, K.S. K. &Tam, L.H. K. (2011). Liquidity and asset pricing: evidence from the Hong

Kong stock market. Journal of Banking and Finance,35, 2217–2230.

lLee, K.(2011). The world price of liquidity risk. Journal of Financial Economics, 99, 136–161.

lLiu, W. (2006).A liquidity-augmented capital asset pricing model. Journal of Financial

Economics, 82, 631–671.

lLo, A. & MacKinlay, C. (1990). Data snooping biases in tests of financial asset pricing models.

Review of Financial Studies, 3, 431–467.

lMarshall, B. R. (2006). Liquidity and stock returns: evidence from a pure order-driven market

using a new liquidity proxy. International Review of Financial Analysis,15, 21–38.

lLoderer, C. & Roth, L. (2005). The pricing discount for limited liquidity: evidence from SWX

Swiss Exchange and the NASDAQ. Journal of Empirical Finance, 12, 239– 268.

l



Marcello, J. L. M. &Quiros, M. M. M. (2006). The role of an illiquidity risk factor in asset

pricing: Empirical evidence from the Spanish stock market.The Quarterly Review of

Economics and Finance, 46, 254–267.

Pastor, L. &Stambaugh, R. F. (2003).Liquidity risk and expected stock returns. Journal of

Political Economy, 111, 642-85.

lPettengill, G., Sundaram, S. &Mathur, I. (1995). The conditional relation between beta and

returns. Journal of Financial and Quantitative Analysis, 30, 101- 116.

lMarshall, B. R. & Young, M.R.(2003). Liquidity and stock returns in pure order-driven

markets: evidence from the Australian stock market. International Review of Financial

Analysis, 12, 173–188.

lWang, Y.& Di Iorio, A. (2007).The cross section of expected stock returns in the Chinese A-

share market. Global Finance Journal, 17, 35–349.

l

l



LEVERAGING EMOTIONAL INTELLIGENCE FOR THE ENHANCEMENTOF THE ORGANIZATIONAL EFFECTIVENESS –

PARADIGMS AND PARAGONS

1Dr. Navdeep Kumar

Abstract

The present paper attempts to examine the relevance of emotional intelligence for the

enhancement of the organizational effectiveness. The recognition of emotional intelligence has sprouted

to cope with the challenges of human behaviour in the dynamic and diverse environment that requires

emotionally intelligent human resources to adopt the changes without conflicts. The core aspect of

emotional intelligence focuses on understanding and managing emotions for better understanding. In

this context, the role of a manger as leader becomes more significant to augment organizational

performance through his emotional intelligence skills to incorporate the change by resolving conflict.

The present study represents the relationship of emotionally intelligent leader as a transformational

leader to act as an agent between conflict and change for enhancing organizational effectiveness. The

paper concludes with suggestions to develop emotional intelligence skills and also provides further

scope of research in this domain.

Key Words: Emotional Intelligence, Organisational Effectiveness, Change, Conflict, Leader.

1. Introduction

The transitional era in the 21st century has remarked incessant changes and it has become key

challenge for a leader to recognize the need for change and implement the changes with his positive

approach and cooperation to contribute towards organizational excellence. Every organization is a blend

of diverse elements that requires proficient functioning to ensure overall organizational performance. In

this process, the human element is vital because the responsibility as well as accountability lies with the

human resources to make optimum use of the resources. The efficiency of human resources is

significantly affected by their capabilities to contribute towards the success of organisational goals.

However, the personal competencies play an important role to create and maintain effective work culture

to enhance organizational effectiveness. In today's competitive environment, the concept of emotional

intelligence has gained considerable recognition as it directly impacts the human behaviour in a given

situation and organisational effectiveness. Emotional intelligence refers to the ability of a person to

1. Assistant Professor, PG Department of Commerce and Business Administration, Lyallpur Khalsa College, Jalandhar. - [email protected]


understand and respond to a situation in a rational manner. The importance and relevance of emotional

intelligence has increased owing to the various drivers such as escalated competition due to the wave of

liberalisation, privatisation and globalisation, stress, anxiety, skill gaps in a changing environment,

performance standards etc. The recognition of strategic significance of emotional intelligence has

surfaced as it affects the organisational effectiveness by contributing towards leadership development,

change management and conflict management. These three factors are very crucial in the present

scenario of competition that demands continuous scope for the flexibility to cope with the changing

environment through effective leadership to avoid conflict. Normally, conflict arises due to

misunderstanding among the persons. Better understanding is possible only if the level of emotional

intelligence is high in a given situation. It is possible only if there is high level of emotional intelligence

prevails among the human force in the organization (Bunker, 1997).

Against the above backdrop, the present article intends to examine the relevance of emotional

intelligence for enhancing organisational effectiveness through effective leadership that acts as an agent

of change by resolving conflicts. For this purpose, the paper has been structured in the following mode.

Besides introduction in Section-I, the conceptual framework of emotional intelligence has been

described in Section-II. The relevance of emotional Intelligence for enhancing organizational

effectiveness has been elucidated in Section-III of the paper. Section-IV deals with the concluding

remarks as well as provides areas of further research in this perspective.

II. Emotional Intelligence – Conceptual Framework

Emotional intelligence depicts human capabilities concerning self and social awareness for

better relationship management. It is not only confined to the self understanding but also understating of

others. Creation and maintenance of a healthy work culture depends upon the level of understanding

among various levels of workforce that sprouts into rational understanding, effective decision making

and managing conflicts. The cohesiveness of relationships depends upon the competencies to adjust

ourselves as well as emotions of others. Emotions refer to the response of an individual in a particular

situation that reflects the level of emotional intelligence to understand self and others. Emotions contain

vital information that assists various employees' different levels “to be better at what we do” (Wolfe and

Caruso, 2004).

The concept of emotional intelligence was initiated by Solvency and Mayer (1990) following

the Gardner's (1983) theory of motivation. Emotional intelligence is a set of competencies that perceive,

understand and direct emotions in ourselves and in others in different changing circumstances provides

better team work while dealing with people having different ideas, opinions and suggestions (Ashforth

et. al., 1995).

1Dr. Navdeep Kumar


Mayer and Salovey (1993) and Goleman (1995) describes emotional intelligence as the ability

to identify, understand and regulate one's own emotions and those of others in order to have efficient

impact on relationship management. Salovey and Mayer (1990) summarized five domains of emotional

intelligence:-

lKnowing one's emotions.

lManaging emotions.

lMotivating oneself.

lRecognising emotions in others.

lHandling relationships.

Following the above model, Goleman (1998) described five emotional and social

competencies:-

lSelf awareness

lSelf-regulation

lMotivation

lEmpathy

lSocial skills.

Further, Anjula et. al. (2013) opines that the human capabilities create competitive edge in a

competitive business environment. Emotional intelligence plays a pivotal role in organisational

performance through the development of the personal and social skills. Emotional intelligence is also a

powerful strategic weapon for the mangers to deal with diverse workforce by maintaining balanced

approach even in a stressing situation to avoid conflicts. Diverse workforce is healthy for the

organization as it bring multidimensional capabilities in the organization and on the same side it also

creates stress when there is misunderstanding due to inherent differences among various groups.

Emotional intelligence facilitates to cope with the dynamic changes of business environment. Emotional

intelligence develops a great sense of understanding and mange emotional responses for greater

comforts in relationships, effectiveness in interactions and inner peace (Jofri et. al., 2010 and

Gardenswartz et.al., 2010).

Various studies found a positive correlation of emotional intelligence of the leaders with the

job satisfaction and performance. Emotional intelligence of leaders has favourable impact on

influencing the behaviour and attitudes of the subordinates towards the accomplishment of

organizational goals. Highly emotionally intelligent leaders can act as transformational leaders and

make subordinates self-confident to face the challenges of working environment (Sosik and Megerian,

1999).

Leveraging Emotional Intelligence for the Enhancementof the Organizational Effectiveness – Paradigms And Paragons


III. Emotional Intelligence and Organisational Effectiveness

The current wave of development in the Indian context has created new challenges for HRM

especially related to Emotional Intelligence, which focuses on conflict management, teamwork,

interpersonal sensitivity, change management which are more significant than other skills. Emotionally

intelligent behaviour facilitates conducive work culture in the organizations for improving

organizational excellence. The development of emotional capabilities among the human resources

resolves behavioral issues that results into the enhanced organizational performance (Elakumaran et. al.,

2005 and Singh, 2010).

The relationship between organisational effectiveness and emotional effectiveness connotes

work culture in an organization. Organisational effectiveness is crucial for enhanced business

performance that depends up on various factors. It requires appropriate strategic alliance of

organisational resources for the achievement of organisational objectives. The most significant factor

for the organisational effectiveness is the workforce in the organization; it requires capable and credible

leadership and conducive work culture to utilize the human capital as per business strategy. Cherniss

(2008) outlined the various aspects of emotional intelligence and organizational effectiveness such as:-

lEmployee retention.

lHuman resource development conducive

lTeamwork

lInnovation

lCustomer loyalty

Efficiency in any factor that affects organisational effectiveness, the role of emotional

intelligence is very significant. However, there are also certain challenges that includes coping with

rapid changes as well as resistance, managing diverse workforce, maintaining favourable work

environment etc.

Emotional competence in a workplace is very essential to deal with different situations. The

persons with higher emotional intelligence can recognize and mange emotions efficiently (The Tribune,

2014b). Conducive work culture is the hallmark of emotionally intelligent leadership that enhances the

morale and productivity of team members to contribute towards organizational performance by better

understanding of emotions. In a study by Williams (1994) of CEO's in U.S. insurance sector, observed

that high level of emotional intelligence resulted into better financial performance in terms of

profitability and growth. The main determinants of work culture include clear communication,

innovation, change management, conflict management and the behaviour of team leader (Litmin and

Stringer, 1968; Tagiuri and Litman, 1968). Further, Mayer and Caruso (2002) explained that

relationships are affected by behaviour, cooperation and dominance arising out of emotions. The leaders

1Dr. Navdeep Kumar


with effective understanding of emotions gains competitive strength in the organization.

In the present complex, dynamic and competitive global regime, the strength level of emotional

intelligence determines the organizational performance, growth and development (Jorfi et. al., 2010).

The development of emotional intelligence leads to the development of interpersonal skills those results

into effective organizational effectiveness. The analytical study of emotional intelligence provides a

comprehensive framework regarding organization structure and outlines the various factors affecting

the emotions that have profound impact o the organizational effectiveness. Although it is a human

behaviour aspect, still it accounts significantly as far as the organizational performance is concerned.

Enhanced level of emotional intelligence indicates higher interpersonal and social skills. Such

skills are more essential as compared to the other technical skills, though these are related with the

human behaviour. The vast amount of literature advocates the relevance of emotional intelligence for

directing and regulating the human emotions for attaining the desired results. Different models have

been developed by various researchers to establish the role of emotional intelligence.

OrganisationalEffectiveness

EmotionalIntelligence

Conflict

Leadership

Change

Figure 1: Relationship Between Emotional Intelligence andOrganisational Effectiveness

The core philosophy behind the emotional intelligence lies on the understanding of emotions.

Since it is concerned with the human behaviour, which is difficult to predict leads to different perceptions

for different situations. In any organization, the need of change arises owing to the changes in the internal

and external environment. It demands considerable scope for the adoption of required changes to cope

and compete for survival as well as growth. On the other hand, there are also chances of resistance for the

change as it is inherent feature of human nature. In such state of affairs, conflicts arises that signals

impasse over the change to be incorporated owing to conflicting interests of different stakeholders. Now,



the role of emotional intelligence evolves around the leadership qualities to handle the situation through

high level of emotional intelligence. Highly emotionally intelligent leader can tackle with more

efficiency and effectiveness. Thus, results into the enhanced organisational effectiveness by

incorporating change through effective leadership by way of resolving the conflicts (Figure-1).

An emotionally intelligent leader responds to the situation after analyzing the various factors in

most appropriate manner. Effective conflict management is imperative for healthier relationship

management. A visionary leader is able to march towards organizational vision and mission with

confidence and act as agent of change (George and Bettenhausen, 1990). Emotional intelligence

supports in influencing the behaviour of the team members towards the accomplishment of a given task.

However, the leadership qualities need to be sharpen as far as emotional intelligence is concerned. The

effectiveness of a leader is determined by the achievement of the goals assigned to the team without any

conflict. It happens only when there is better understanding among all the team members and it is only

teamwork that leads any organization towards the ultimate success by the achievement of the

organisational objectives. The level of cohesiveness determines the output of the teamwork that is

significantly depends upon the understanding level among the diverse elements in a team.

Understanding of different aspects and implications of emotional intelligence and its interrelationships

with various factors will help organization to meet the new challenges and leadership effectiveness

(Bratlon et al., 2011).

Developing Emotional Intelligence Skills

The development of emotional intelligence skills requires muti-dimensional approach for the

enhancement of individual performance and organsational effectiveness. The most crucial factor is the

healthy atmosphere that encourages effective communication for better understanding. For this purpose

an effective emotional environment should be created that promotes healthy work culture and conducive

working environment. Further, the reconciliation of individual's interests with the organizational

interests also plays a vital role. It is possible only when there is rational behaviour of the superiors with

their subordinates particularly in a climate of continuous changes. The management of diverse

workforce is also a challenging task through strategic approach in the preset competitive regime for

organizational excellence.

The competition wave has increased the stress and anxiety levels among the human beings

which is adversely affecting the job performance and organizational efficiency. Efforts must be made to

reduce the stress level among the workforce. Further, the focus of emotional intelligence is on the

understanding of emotions and in this process non-verbal communication has a critical role. The

development of non-verbal communication skills should also be given due attention for creating

1Dr. Navdeep Kumar


emotional intelligence. Creating an interactive learning environment in which employees have the

opportunity to explore the bond between social and social skills would also facilitate towards the

advancement of emotional intelligence environment. Emotional intelligence skills should be developed

to attain leadership effectiveness and organizational performance. Modern leaders require to focus on

intellectual capital besides traditional resources to generate emotional capital. Emotional capital is the

value of the energy, motivation and commitment held by everyone connected with the business that can

be enhanced through emotional intelligence. Basically, leadership is a relationship to influence human

behaviour. Although some aspects of emotional intelligence are innate, the evidence is overwhelming

that anyone who is motivated can develop his or her emotional intelligence and boost their emotional

competence (The Tribune, 2014b). The role of a leader determines the performance of subordinates and

organization. For effective leadership, there is no single style is suitable for all situations. There must be

flexibility approach for effective leadership to resolve conflicts by understanding the situation smartly.

Moreover, in increasingly diverse and inclusive workplace, conflict became inevitable. Leaders who

realize the positive aspects of conflict resolution skills to construct better teams, gain productivity and

develop better communication among employees. For this strong communication and crisis solving

skills are essential. Nevertheless, objectivity, honesty, creativity and tolerance are crucial in this process

(The Tribune, 2014a). Thus, combination of aforementioned factors would contribute towards the

improvement of emotional intelligence in an organization for the enhancement of organizational

effectiveness.

III. Conclusion

The level of organizational affects the organizational effectiveness as it establishes the shared

sense of relationship among team members towards the achievement of organizational goals. Although

the quality of emotional intelligence is personal in nature to a great extent but it considerably influences

the individual's behaviour and organisational performance. Emotionally intelligent leader facilitates the

transformational process by incorporating changes to cope with the dynamic environment by resolving

conflicts to enhance organizational effectiveness.

Further Scope of Research

The following are the some areas for the further research in this perspective:-

lEmotional Intelligence and Competitive Work Culture

lRole of HR Practices in Developing Emotional Intelligence Skills.

lAdoption of Emotional Intelligence models for Effective Leadership.

lLeadership Styles and Emotional Intelligence.



References

lAnuja J. A.1, M. Sivaraman and D. Mohan (2013), “Role Of Emotional Intelligence in

Service Sector-A Retrospective Survey”, Opinion, Vol. 3 No. 2 Dec.

lAshforth, B.E. and Humphrey. R.H. (1995), “Emotion in the Workplace. A Reappraisal”,

Human Relations, Vol. 48, No.2.

lBunker, K. A. (1997), “The Power of Vulnerability in Contemporary Leadership”, Consulting

Psychology Journal, Vol. 49, No. 2.

lCherniss, C. (2008), The Business Case for Emotional Intelligence, Consortium for Research

on Emotional Intelligence in Organizations. Electronically Available at

http://www.eiconsortium.org/research/business_case_for_ei.pdf. Accessed on 2013 May, 13.

lElankumaran, S., Rekha, S. and Anwar, H. (2005), “ Transcending Transformation:

Enlightening Endeavours at Tata Steel”, Journal of Business Ethics, Vol. 59.

lGardenswartz,L., J. Cherbosque and A. Rowe (2010), “Emotional Intelligence and Diversity -

A Model for Differences in the Workplace”, Journal of Psychological Issues in Organizational

Culture, Vol.1, No. 1, Electronically available at http://www.iveybusinessjournal.com.

Accessed on 2014 January, 11.

lGardner, H. (1983), Frames of Mind: The Theory of Multiple Intelligences, New York: Basis

Books.

lGeorge, J.M. and Bettenhausen, K. (1990), “Understanding Prosocial Behavior, Sales

Performance, and Turnover: A Group Level Analysis in a Service Context,” Journal of Applied

Psychology, Vol. 75.

lGoleman, D. (1995), Emotional intelligence. New York: Bantam.

lGoleman, D. (1998), Working with Emotional Intelligence, New York: Bantom Books.

lJorfi, H., Jorfi, S., Moghadam, K. (2010), “Impact of Emotional Intelligence on Performance

of Employees”, Postmodern Openings, Vol 4, No. 1,December.

lLitwin, G.H. and Stringer, R.A., Jr. (1968), Motivation and Organizational Climate, Boston:

Division Research, Harvard Business School.

lMayer, J. D. and Salovey, P. (1993), “The intelligence of emotional intelligence”, Intelligence,

Vol.17.

lMayer, J.D. and D. Caruso (2002), “The Effective Leader: Understanding and Applying

Emotional Intelligence”, IVEY Business Journal, Nov.-Dec., Electronically available at

http://www.iveybusinessjournal.com. Accessed on 2013 December, 15.

lSalovey, P. and Mayer, J. D. (1990), “Emotional intelligence”. Imagination, Cognition and

Personality, Electronically available at http://www.sciencedirect.com. Accesed on 2013

1Dr. Navdeep Kumar


December, 28.

lSingh, K. (2010), “ Developing Human Capital By Linking Emotional Intelligence with

Personal Competencies in Indian Business Organizations”, International Journal of Business

Science and Applied Management, Volume 5, No.2.

lSosik, J.J. and Megerian, L.E. (1999), “Understanding Leader Emotional Intelligence and

Performance: The Role of Self-other Agreement on Transformational Leadership

Perceptions”. Group and Organization Management, Vol. 24.

lTagiuri, R. and Litwin, G.H. (1968), Organizational Climate: Explorations of a Concept,

Boston, MA: Harvard Business School Press.

lThe Tribune (2014a), 12 March, p.4.

lThe Tribune (2014b), 19 March, p.4.

lWilliams, D. 91994), Leadership for the 21st Century: Life Insurance Leadership Study,

Boston:Haygroup.

lWolfe, C.J. and Caruso, D.R. (2004), Emotional intelligence. Shelton, CT: New Haven

Consulting Group

lWong, C. L. and K. S. (2002), “The Effects of Leader and Follower Emotional Intelligence on

Performance and Attitude: An Exploratory Study”, Leadership Quarterly, Vol. 13, No. 3.



AN EMPIRICAL STUDY OF VARIATIONS IN CRITICAL SUCCESSFACTORS OF QUALITY MANAGEMENT PRACTICES

IN INDIAN MANUFACTURING INDUSTRY

1Dr. Anu Kohli

2Ram Singh

Abstract

This paper is an empirical study on the critical success Factors (CSFs) of Quality Management

in the Indian Manufacturing Sector with special reference to industries in Uttar Pradesh. The

preliminary list of forty-five CSFs of Quality Management Practices were identified and compiled

through in depth literature review. Subsequently 74 Quality Professionals representing 74 different

manufacturing units operating in Uttar Pradesh were surveyed. The study analyzes the differences in

various critical success factors of Quality Management across Sectors, across companies in different

Age Groups and also across companies with different annual turnovers. The research concluded that

there are significant differences in factors like Team work, Updated Technology, Leadership Skills,

Strategic planning and social Responsibility across various sectors. It was also observed that Updated

Technology, Leadership skills and Strategic planning showed significant variations across companies

with different Annual turnover. The Organizational Age affects the Friendly working Environment,

Continuous improvement, Top management commitment towards TQM, Steering Groups, Updated

Technology, Leadership skill and Conducting frequent Quality meetings in the organizations.

Key Words: Critical Success Factors, Quality Management, Indian Manufacturing Sector

JEL: L1-L15

1. Introduction

Quality has emerged as one of the most important factor needed for the survival and growth of

an organization in manufacturing sector. This sector provides employment to the growing labor force

and stimulates the growth of other sectors. However it has not reached its true potential and is far from

performance level it can reach. In general manufacturing sector involves technical issues related to

reliability, measurement of defects and statistical Quality control. Today quality aspects have diversified

into other Management dimensions like human resource management, employee's participation, supply

chain management, Benchmarking etc. Hence this paper identifies the critical success factors

responsible for the successful implementation of TQM practices in the Indian Manufacturing sectors and

1. Assistant Professor, Department of Business Administration, University of Lucknow, Lucknow2. Junior Research Fellow, Department of Business Administration, University of Lucknow, Lucknow


also examines their variations across sectors, organizational age and annual turnover.

2. Literature Review

Critical Success factors help the organization to yield competitive advantage. These are the

areas where company should perform in a right direction in order to sustain business. The Review of

Literature reveals forty-five critical Success Factors. These are further grouped into six groups i.e.

Organization related, Employee related, Vendor related, Effective Communication related, Quality

Techniques related and Customers' related CSFs of Quality Management.

The Organizational Factors include friendly working environment, Continuous improvement,

Top management commitment towards TQM initiatives, Formation of Steering Group, conducting

Frequent Quality Meetings, working for sustainable development, Team Work, updated Technology

implementation, leadership skills of top level management, Effective and Efficient Strategic planning,

Social Responsibility, organization Culture & support and knowledge management & innovation.

Continuous improvement is the path towards the quality goals of the organization. It is required for the

success of the Quality Policies in the organization [Faisal Talib et al (2011), Christos et al (2009), David

Gallier et al (2004)]. Strategic planning is the long term planning of the organization, which focuses on

the organizational goals and the customers' requirement in the upcoming future. Friendly working

environment is required for smooth working of the organization [Faisal Talib et al (2011), Christos et al

(2009)]. Social Responsibility leads the organization towards quality goals by providing them

sustainable development, environment protection, social equity and growth [R Sarvanan et al (2007),

Kureshi et al (2009)], Knowledge Management and innovation along with the integration of IT enabled

TQM (Rahman 2006) helps the organization to adapt itself according to the dynamic business

environment by updating them with the recent trends in the market and the technology.

The CSFs related to Effective Communication includes Publishing Newsletter consisting of

TQM results, Written & Well Communicated Policies and Information Circulation about the corporate

results, which in turn helps in defining the role of each and every employee of the organization for

achieving quality goals [Dixit et al (2011), Mehmatet al (2008)].

The CSFs related to Employees includes Trust between Management &Workforce, Job

Security, Regular feedback to workers about their performance, Staff attitude towards management,

Implementation of health and safety measures, respect to humanity and flexible workforce[ John

Mcmanus et al (2007), Nadine et al (2014)]. Employee Training [Mehmet et al (2008) Ben Clegg et al

(2010)], Employee Empowerment and Organization culture alsohelps in the development of the certain

skills like Leadership, which in turn motivates the employees towards quality goals [Prattana

Punnakitikashem et al (2010), Deepak Chawla et al (2010].

1Dr. Anu Kohli2Mr. Ram Singh


The Quality Techniques related CSFs' include Use of Six Sigma, Use of Statistical Process

Control, Frequent Benchmarking[ R Sarvanan et al (2007), Lee, et al 2006)], Periodic measure of

quality cost, internal quality audits at regular interval, automation of work process, preventive

maintenance, smooth flow of production, lean Manufacturing [Bhim Singh et al (2010), Shahram et al

(2009)], Application of Ergonomics (Lee et al, 2005), Reliability of Tools &equipment and Work

Measurement system(Shrivastava et al, 2006). These factors help the organization to assure the

production of defect free product.

Factors related to Vendors of the organization includes Periodic Evaluation of Vendors, Supply

Chain Management and integration of value chain which plays a vital role in the implementation of Total

quality Management in the organization. The poor quality of the raw material and purchased parts are the

source of quality problems in the organization [Rashid et al (2012), Kwai et al (2006), Victor et al

(2006)].

Satisfied Customers are the key to the success of the organization. Well-educated and aware

customers require accurate customers' need identification, which enhances customers' satisfaction.

Efficient Customers' feedback Mechanism is one of the important factor for maintaining quality in the

organization and must be regularly recorded in order to make improvements in the existing product

[Jitendra Kumar et al (2014), Assadej et al (2014), Ali Mohammad et al (2006), Evangloes et al ( 2010),

Satish Mehra et al (2008), Rahman et al (2005)]. The organization should focus on the quick redressal of

the customers' complaint in order to increase the product loyalty among customers.

3. Research Objectives:

The main objectives of this paper are: -

1. To analyze the variations in various critical success factors of Quality Management across

Sectors.

2. To analyze the variations in various critical success factors of Quality Management across

companies in different Age Groups.

3. To analyze the Variations in various critical success factors of Quality Management across

companies with different Annual Turnover.

4. Research Methodology

After reviewing the literature the preliminary list of forty-five CSFs of Quality Management

Practices were identified and compiled. Subsequently a survey was conducted and responses from

Quality Professionals were collected by sending 150 questionnaires to the various Manufacturing

Industries operating in Uttar Pradesh. Convenience Sampling Technique is used for selecting the

respondents. 74 Questionnaire were received with response rate of 49%. The data was then tabulated for

An Empirical Study of Variations In Critical Success FactorsOf Quality Management Practices In Indian Manufacturing Industry


analysis. The normality of the data was tested using Kolmogorov-Smirnov and Shapiro Wilk Test and

was found to be not normal (Annexure 1). Therefore Kruskal Wallis Test is used to analyze the

differences in CSFs across different sectors on the basis of annual turnover and Organizational Age. Five

point Likert scale for each of the45 items was used to record the responses of the respondents. The scale

represents 1as Strongly Disagree and 5 as Strongly Agree. The Reliability of the scale used in

Questionnaire is tested by using Cronbach's Alpha Test. The Value of Cronbach's Alpha is found to be

.893, which shows the higher internal consistency and reliability of the scale.

5. Analysis

5.1 Description of Data:

The Data is first analyzed by using the descriptive statistics. TABLE 1 shows the profile of the

organizations surveyed. ISO 9000/2000 and ISI Certifications are common in all sectors. It was also

observed that Graphical Measurement Index (GMI) Certifications is common in Pharmaceuticals sector.

Table1 : Profile of Organization Surveyed

Sector Frequency

Certification

ISO 9000/2000

ISI

GMI

Automobile

10

7

3

0

Chemical

9

7

2 0

Pharmaceuticals 25 25 0 20

Food processing 13 7 6 0

FMCG 1 1 0 0

Electrical and

Electronics

5

3

2

0

Iron and steel

10

9

1

0

Plastic 1 1 00

Total 7460 14 0

The Organizational Age and Annual Turnover of organization surveyed are shown in TABLE

2.The sample is categorized into three-sub group on the basis of the Organizational Age, wherein Young

represents less than 10 years; Adult represents 10 to 20 years and mature organization, which has more

than 20 years of operation. It can also be observed that most of the organizations surveyed belong to

Adult category. Further, the Sample is categorized into three groups on the basis of Annual turnover of

the organization i.e. organizations having annual turnover of less than Rupees 10 lakhs, 10 to 20 lakhs

and more than 20 lakhs.



Table 2 :Organizational Age

and Annual Turnover of Organization

surveyed

Organizational Age

Frequency

Annual Turnover

(Rs

in lakhs) Frequency

Young 17 Less than 10 lakhs

14

Adult43

10 to 20 lakhs 19

Mature14

More than 20 lakhs 41

Total74

Total

74

5.2 Impact of Sector, Annual Turnover and Organization's Age on Critical Success Factors of

Quality Management.

5.2.1 CSFs related to Organization

Null Hypothesis were formulated and tested at 5 % level of significance using the Kruskil

Walis Test. It can be observed from the TABLE 3 that factors like Teamwork, Organization's attitude

towards Social Responsibility, and organization culture &support show significant variations across

Sectors. Other factors like Friendly Working Environment, implementation of continuous improvement,

Top management commitment towards TQM initiatives and the Leadership skills of top-level

management and implementation of updated Technology show significant variations due to the

organizational age. These factors did not show any variations across companies with different annual

turnover.

Table 3: The variation in CSFs of Quality Management related to Organization across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age GroupS. No. Hypothesis Variation across Sectors Variation across Annual Turnover Variations across Organizational Age

Chi-Square

Df Sig. Result Chi-Square Df Sig. Result Chi-Square

Df Sig. Result

1. There is no variation in Friendly Working Environment across companies in different sectors, having different annual turnover and belonging to different age group.

8.059 7 .327 Accepted 2.399 2 .301 Accepted 9.970 2 .007 Not Accepted

2. There is no variation in implementation of continuous improvement ac ross companies in different sectors, having different annual turnover and belonging to different age group.

5.487 7 .601 Accepted 1.100 2 .577 Accepted 11.002 2 .004 Not Accepted

3. There is no variation in the Top management commitment towards TQM initiatives across companies in different sectors, having different annual turnover and belonging to different age group.

6.626

7

.469

Accepted

.458

2

.795

Accepted

7.956 2 .019 Not Accepted

4. There is no variation in the formation of Steering group

across companies in different sectors, having different annual turnover and belonging to different age group .

7.325

7

.396

Accepted

.138

2

.933

Accepted


5. There is no variation in Conducting frequent Quality meetings

across companies in different sectors, having different annual turnover and belonging to different age group

.

8.695

7

.275

Accepted

2.344

2

.310

Accepted

2.720 2 .257 Accepted

6. There is no variation in Team work across companies in different sectors, having different annual turnover and belonging to different age group .

14.618

7

.041

Not Accepted

2.375

2

.305

Accepted

2.394 2 .302 Accepted

7. There is no variation in the implementation of Working for sustainable development across companies in different sectors, having different annual turnover and belonging to different age group .

2.549 7 .923 Accepted 6.000 2 .050 Accepted 2.847 2 .241 Accepted

8. There is no variation in the implementation of Updated Technology across companies in different sectors, having different annual turnover and belonging to different age group

.

.

11.748

7

.109

Accepted

1.502

2

.472

Accepted 12.299 2 .002 Not Accepted

9. There is no variation in the Leadership skills of top level management across companies in different sectors, having different annual turnover and belonging to different age group

.

13.735

7

.056

Accepted

.051

2

.975


10. There is no variation in the Effective and Efficient Strategic planning across companies in different sectors, having different annual turnover and belonging to different age group .

12.563

7

.083

Accepted

1.258

2

.533

Accepted .020 2 .990 Accepted

11. There is no variation in the attitude of Organization towards Social Responsibility across companies in different sectors, having different annual turnover and belonging to different age group .


1.495 2 .474 Accepted 4.107 2 .128 Accepted

12. There is no variation in the Organization Culture and Supportacross companies in different sectors, having different annual turnover and belonging to different age group .


1.169 2 .557 Accepted 5.902 2 .052 Accepted

13. There is no variation in the Knowledge Management and Innovation across companies in different sectors, having different annual turnover and belonging to different age group .




5.2.2 CSFs related to Effective Communication


Walis Test. It can be observed from TABLE 4 that in general there is no significant impact of Sectors,

Annual Turnover and Organizational Age on these CSF. Information circulation about the corporate

results is the only factor that shows significant variation across Companies belonging to different

organizational age.

5.2.3 CSFs related to Employees


Walis test. It can be observed from TABLE 5 that factors like Regular Feedback to worker, Staff attitude

towards management, and implementation of health & safety measures show significant variations

across sectors. The only factor i.e. Implementation of health & safety measures varied across companies

with different Annual Turnover. Trust between Management and workforce is the only factor that varied

across companies with different Organizational age.

5.2.4 CSFs related to Vendors of the Organization

Null hypothesis were formulated and tested at 5 % level of significance using the Kruskil Walis

test. The conclusion of the test is deciphered in TABLE 6. It can be seen that these factors did not show

any variation across companies with different sectors, different turnover and belonging to different

Organizational age.

5.2.5 CSFs related to Quality Techniques used in the Organization


Test. The conclusion of the Test is deciphered in TABLE 7.It shows that the Use of Six Sigma varies

across Sectors, while the Annual Turnover of the organization affect implementations of Work

Measurement Systems and Reliability of Tools & Equipment. Implementation of Lean Manufacturing

varies with the Organizational age.

5.2.6 CSFs related to Customers


Test. It can be seen from the TABLE 8, that the Mechanism of Quick Redressal of the customers'

complaints varied across Sectors, while there is no impact of the Annual Turnover on these factors.

Implementation of Customers' need identification and Mechanism of Quick Redressal of the customers'

complaints also varied with Organizational age.



Table 4 : The variation in CSFs of Quality Management related to Effective Communication across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age GroupS. No. Hypothesis Variation across Sectors Variation across Annual Turnover Variations across Organizational Age

Chi-Square

Df

Sig.

Result

Chi-Square

Df

Sig.

Result

Chi-Square

Df Sig. Result

1. There is no variation in the implementation of Written and well communicated company policy across companies in different sectors, having different annual turnover and belonging to different age group .

3.826

7

.800

Accepted

.260

2

.878

Accepted

3.853 2 .146 Accepted

2. There is no variation in Information circulation about the corporate results across companies in different sectors, having different annual turnover and belonging to different age group

.

5.473

7

.602

Accepted

1.638

2

.441

Accepted


3. There is no variation in Publishing Newsletter consist of TQM results across companies in different sectors, having different annual turnover and belonging to different age group .

12.697 7 .080 Accepted .971 2 .615 Accepted 1.756 2 .416 Accepted

Table 5: The variation in CSFs of Quality Management related to Employees across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age GroupS. No. Hypothesis Variation across Sectors Variation across Annual Turnover Variations across Organizational Age

Chi-Square

Df Sig. Result Chi Square

Df Sig. Result Chi-Square

Df Sig. Result

1. There is no variation in Trust between Management and work

force across companies in different sectors, having different

annual turnover and belonging to different age group.

1.649 7 .977 Accepted .823 2 .662 Accepted 6.064 2 .048 Not Accepted

2. There is no variation in perception about Job Security

across

companies in different sectors, having different annual turnover

and belonging to different age group.

4.053

7

.774

Accepted

1.252

2

.535

Accepted

1.892 2 .388 Accepted

3. There is no variation in Employee Empowerment

across



9.247

7

.235

Accepted

.986

2

.611

Accepted

2.363 2 .307 Accepted

4. There is no variation in the Regular Feedback Mechanism to

worker across companies in different sectors, having different


15.128

7

.034

Not

Accepted

.135

2

.935

Accepted

4.876 2 .087 Accepted

5. There is no variation in Staff attitude towards management

across companies in different sectors, having different annual

turnover and belonging to different age group.

10.525

7

.161

Not

Accepted

1.072

2

.585

Accepted

3.653 2 .161 Accepted

6. There is no variation in implementation of health and safety

measures across companies in different sectors, having different


6.065

7

.532

Not

Accepted

6.176

2

.046

Not

Accepted

1.807 2 .405 Accepted

7. There is no variation in the implementation of Staff training

across companies in different sectors, having different annual

turnover and belonging to different age group.

8.519 7 .289 Accepted .628 2 .730 Accepted 1.284 2 .526 Accepted

8. There is no variation in giving respect to humanity across




9. There is no variation in the flexibility of work force across




Table 6: The variation in CSFs of Quality Management related to vendors

across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age Group

S. No. Hypothesis Variation across Sectors

Variation across Annual Turnover Variations across Organizational Age

1. There is no variation in the implementation of Periodic

evaluation of vendors across companies in different sectors,

having different annual turnover and belonging to different age

group.

2.500

7

.927

Accepted

1.452

2

.484

Accepted 5.80

9

2 .055 Accepted

2. There is no variation in the implementation of Supply chain

management across companies in different sectors, having

different annual turnover and belonging to different age group.

5.829 7 .560 Accepted 5.293 2 .071 Accepted 3.44

3

2 .179 Accepted

3. There is no variation in the implementation of Integration of

value chain across companies in different sectors, having


3.692 7 .814 Accepted 3.004 2 .223 Accepted 2.06

8

2 .356 Accepted



Table 7: The variation in CSFs of Quality Management related to Quality Techniques across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age GroupS. No. Hypothesis Variation across Sectors Variation across Annual Turnover Variations across Organizational Age

Chi-Square


Df Sig. Result Chi Square

Df Sig. Result

1. There is no variation in the implementation of Use of Six Sigmaacross companies in different sectors, having different annual turnover and belonging to different age group.


1.969 2 .374 Accepted .807 2 .668 Accepted

2. There is no variation in the implementation of Use of Statistical Process control Techniques across companies in different sectors, having different annual turnover and belonging to different age group.

2.509 7 .926 Accepted .542 2 .762 Accepted .487 2 .784 Accepted

3. There is no variation in the implementation of Frequent Benchmarking across companies in different sectors, having different annual turnover and belonging to different age group.

6.318

7

.503

Accepted

2.869

2

.238

Accepted 1.974 2 .373 Accepted

4. There is no variation in the implementation of Periodic measure of quality cost .

6.287

7

.507

Accepted

1.714

2

.424

Accepted .324 2 .850 Accepted

5. There is no variation in the implementation of Internal quality audits at regular interval across companies in different sectors, having different annual turnover and belonging to different age group.

6.402

7

.494

Accepted

4.245

2

.120


6. There is no variation in the implementation of Automation of work process across companies in different sectors, having different annual turnover and belonging to different age group.

4.078

7

.771

Accepted

1.736

2

.420


7. There is no variation in the implementation of Preventive Maintenance across companies in different sectors, having different annual turnover and belonging to different age group.

4.619

7

.706

Accepted

2.219

2

.330


8. There is no variation in the implementation of Smooth flow of production across companies in different sectors, having different annual turnover and belonging to different age group.

6.083

7

.530

Accepted

4.998

2

.082


9. There is no variation in the implementation of Lean Manufacturing across companies in different

sectors, having different annual turnover and belonging to different age group.

13.790

7

.055

Accepted

1.819

2

.403


10. There is no variation in the implementation of Application of Ergonomics across companies in different sectors, having different annual turnover and belonging to different age group.

5.478 7 .602 Accepted 2.129 2 .345 Accepted .313 2 .855 Accepted

11. There is no variation in the implementation of Reliability of Tools and equipment across companies in different sectors, having different annual turnover and belonging to different age group.

8.085 7 .325 Accepted 7.404 2 .025 Not Accepted

.855 2 .652 Accepted

12. There is no variation in the implementation of Work Measurement System across companies in different sectors, having different annual turnover and belonging to different age group.

2.835 7 .900 Accepted 7.090 2 .029 Not Accepted

1.279 2 .527 Accepted

Table 8: The variation of CSFs of Quality Management related to Customers across Companies in different Sectors, Having Different Annual Turnover and Belonging to Different Age GroupS. No. Hypothesis Variation across Sectors Variation across Annual Turnover Variations across Organizational

Age Chi-Square



Df Sig. Result

1. There is no variation in the implementation of Well educated and

aware customers across companies in different sectors, having


4.622

7

.706

Accepted

1.461

2

.482

Accepted

3.254

2 .197 Accepted

2. There is no variation in the implementation of Customers’ need

identification ac ross companies in different sectors, having

different annual turnover and belonging to different age group .

4.144

7

.763

Accepted

.785

2

.675

Accepted

6.621

2 .037 Not Accepted

3. There is no variation in

the implementation of practices

enhancing customers’ satisfaction across companies in different

sectors, having different annual turnover and belonging to

different age group.

6.756

7

.455

Accepted

.611

2

.737

Accepted

.487 2 .784 Accepted

4. There is no variation in

the implementation of Efficient

Customers’ feedback mechanism

across companies in different

sectors, having different annual turnover and belonging to

different age group.

12.276

7

.092

Accepted

.462

2

.794

Accepted

5.126

2 .077 Accepted

5. There is no variation in the implementation of Quick Redressal of

the customers’ complaints across companies in different sectors,

having different annual turnover and belonging to different age

group.

15.893 7 .026 Not

Accepted

1.034 2 .596 Accepted 13.360

2 .001 Not Accepted



6. Findings

6.1 ISO 9000/2000 and ISI Certifications are common in all sectors.

6.2 It was also observed that Graphical Measurement Index (GMI) Certifications is common in

Pharmaceuticals sector's organizations

6.3 CSFs such as Teamwork, Social Responsibility, Organization culture & Support, Regular

Feedback to worker, Staff Attitude towards management, Health &Safety measures, Use of Six

Sigma and Quick Redressal of customers' complaints varied across various Sectors.

6.4 Annual Turnover of the organization affects the implementation of Health & safety measures,

Reliability of Tools & Equipment and Implementation of Work Measurement system.

The Factors like Friendly work Environment, Continuous improvement, Top management

commitment towards TQM initiatives, Steering Groups, Updated Technology, Leadership skill of Top

Level Management, Information Circulation about the corporate results, Trust between Management &

Workforce, Lean Manufacturing, Customers' Need Identification, and Quick Redressal of customers'

complaints shows significant variation on the basis of the Organizational age.

7. Conclusion

It can be concluded that Quality Management Policies are all pervasive in Manufacturing Industry while

their certain practices vary across sectors, Annual Turnover of the Organization and Organizational age.

CSFs are the enablers of the Quality Management Practices. These CSFs are classified into five sub

groups i.e. Organization related, Employee related, Vendors related, Quality Techniques related and

Customers related. The paper concludes that CSFs are significantly affected by Organizational age, as

organization becomes more awakened about quality with age. It is also concluded that specific

requirement of the sectors leads to variation in the quality practices. Annual turnover also impacts the

Quality practices as the organization with large turnover has more resources to effectively and efficiently

work for quality goals as compared to the organization with lower turnover.

References

1. Ali Mohammad Mosadegh Rad, (2006) "The impact of organizational culture on the

successful implementation of total quality management", The TQM Magazine, Vol. 18 Issue:

6, pp.606 – 625

2. AssadejVanichchinchai , (2014) "Supply chain management, supply performance and total

quality management: An organizational characteristic analysis", International Journal of

Organizational Analysis, Vol. 22 Issue: 2, pp.126 - 148

3. Ben Clegg, Chris Rees, Mike Titchen, (2010) "A study into the effectiveness of quality

management training: A focus on tools and critical success factors", The TQM Journal, Vol. 22



Issue: 2, pp.188 - 208

4. Bhim Singh S.K. Garg S.K. Sharma, (2010),"Development of index for measuring leanness:

study of an Indian auto component industry",Measuring Business Excellence, Vol. 14 Issue 2

pp. 46 – 53

5. Christos B. Fotopoulos, Evangelos L. Psomas, (2009) "The impact of “soft” and “hard” TQM

elements on quality management results", International Journal of Quality & Reliability

Management, Vol. 26 Issue: 2, pp.150 – 163

6. David Gallear& Abby Ghobadian (2004) An Empirical Investigation of the Channels that

Facilitate a Total Quality Culture, Total Quality Management & Business Excellence, Vol

15(8)pp. 1043-1067.

7. Deepak ChawlaHimanshu Joshi, (2010),"Knowledge management practices in Indian

industries – a comparative study", Journal of Knowledge Management, Vol. 14 Issue 5 pp. 708

– 725.

8. Faisal Talib, ZillurRahman, M.N. Qureshi, (2011) "Analysis of interaction among the barriers

to total quality management implementation using interpretive structural modeling approach",

Benchmarking: An International Journal, Vol. 18 Issue: 4, pp.563 – 587.

9. Jitendra Kumar Vimlesh Kumar SoniGeetaAgnihotri , (2014),"Impact of TPM

implementation on Indian manufacturing industry", International Journal of Productivity and

Performance Management, Vol. 63 Issue 1 pp. 44 – 56.

10. John McManus, Trevor Wood-Harper, (2007) "Software engineering: a quality management

perspective", The TQM Magazine, Vol. 19 Issue: 4, pp.315 – 327.

11. Kamran Rashid, M.M. HarisAslam, (2012) "Business excellence through total supply chain

quality management", Asian Journal on Quality, Vol. 13 Issue: 3, pp.309 – 324

12. Kureshi, N. I., Mann, R., Khan, M. R., & Qureshi, M. F. (2009). Quality management practices

of SME in developing countries: a survey of manufacturing SME in Pakistan. Journal of

Quality and Technology Management, Vol 5(II), pp. 63-89.

13. Kwai Sang Chin, I-Ki Yeung, Kit Fai Pun, (2006) "Development of an assessment system for

supplier quality management", International Journal of Quality & Reliability Management,

Vol. 23 Issue: 7, pp.743 – 765.

14. Lee, K. S. (2005). Ergonomics in total quality management: How can we sell ergonomics to

management?. Ergonomics, Vol. 48(5), pp. 547-558.

15. Lee, Y.P., Zailani, S. and Soh, K.L. (2006), “Understanding factors for benchmarking

adoption: new evidence from Malaysia”, Benchmarking: An International Journal, Vol.

13(5),pp. 548-65.



16. Mehmet Demirbag, Sunil Sahadev, (2008) "Exploring the antecedents of quality commitment

among employees: an empirical study", International Journal of Quality & Reliability

Management, Vol. 25 Issue: 5, pp.494 – 507.

17. Nadine Hietschold, Ronny Reinhardt, Sebastian Gurtner. 2014. Measuring critical success

factors of TQM implementation successfully – a systematic literature review. International

Journal of Production Research Vol. 52, pp. 6254-6272

18. PrattanaPunnakitikashem, TritosLaosirihongthong, DotunAdebanjo, Michael W. McLean,

(2010) "A study of quality management practices in TQM and non-TQM organizations:

Findings from the ASEAN automotive industry", International Journal of Quality &

Reliability Management, Vol. 27 Issue: 9, pp.1021 – 1035

19. R. Saravanan K.S.P. Rao, (2007),"The impact of total quality service age on quality and

operational performance: an empirical study", The TQM Magazine, Vol. 19 Issue 3 pp. 197 –

205.

20. R. Saravanan K.S.P. Rao, (2007),"The impact of total quality service age on quality and

operational performance: an empirical study", The TQM Magazine, Vol. 19 Issue 3 pp. 197 –

205.

21. Raj Kumar, Dixit Garg, T.K. Garg, (2009) "Total quality management in Indian industries:

relevance, analysis and directions", The TQM Journal, Vol. 21 Issue: 6, pp.607 – 622.

22. SatishMehra, SampathRanganathan, (2008) "Implementing total quality management with a

focus on enhancing customer satisfaction", International Journal of Quality & Reliability

Management, Vol. 25 Issue: 9, pp.913 – 927

23. ShahramTaj, LismarBerro, (2006) "Application of constrained management and lean

manufacturing in developing best practices for productivity improvement in an auto assembly

plant", International Journal of Productivity and Performance Management, Vol. 55 Issue: 3/4,

pp.332 - 345

24. Shrivastava, R. L., Mohanty, R. P., &Lakhe, R. R. (2006). Linkages between total quality

management and organisational performance: an empirical study for Indian industry.

Production Planning & Control, 17(1), 13-30

25. Victor H.Y. Lo, Alice Yeung, (2006) "Managing quality effectively in supply chain: a

preliminary study", Supply Chain Management: An International Journal, Vol. 11 Issue: 3,

pp.208 – 215.

26.. Rahman, J. Siddiqui, (2006) "Exploring total quality management for information systems in

Indian organizations: Application and benefits", Business Process Management Journal, Vol.

12 Issue: 5, pp.622 – 631


Kolmogorov-Smirnova Shapiro-Wilk

Statistic Df Sig. Statistic Df Sig.

Friendly Working Environment

.285

74

.000

.768

74

.000

Believes in continuous improvement

.301

74

.000

.759

74

.000

Top management commitment towards TQM initiatives

.294

74

.000

.759

74

.000

Steering group

.252

74

.000

.791

74

.000

Conducting frequent Quality meetings

.300

74

.000

.761

74

.000

Team work

.285

74

.000

.768

74

.000

Publishing Newsletter consist of TQM results

.276

74

.000

.778

74

.000

Updated Technology implementation

.270

74

.000

.795

74

.000

Leadership skills of top level management

.294

74

.000

.759

74

.000

Effective and Efficient Strategic planning

.316

74

.000

.749

74

.000

Social Responsibility

.253

74

.000

.788

74

.000

Organization Culture and Support

.253

74

.000

.788

74

.000

Knowledge Management and Innovation

.267

74

.000

.785

74

.000

Written and

well communicated company policy

.279

74

.000

.781

74

.000

Information circulation

about the corporate results

.238

74

.000

.800

74

.000

Trust between Management and workforce

.316

74 .000

.764

74

.000

Job Security

.307

74 .000

.749

74

.000

Employee Empowerment

.302

74 .000

.767

74

.000

Regular Feedback to worker about their performance

.293

74 .000

.780

74

.000

Staff attitude towards management .272 74 .000 .792 74 .000

Implementation of health and safety measures .268 74 .000 .783 74 .000

Staff training .307 74 .000 .749 74 .000

Respect to humanity .308 74 .000 .734 74 .000

Flexible work force .349 74 .000 .730 74 .000

Use of Quality Tools .335 74 .000 .735 74 .000

Use of Statistical Process control Techniques

.364

74 .000

.712

74

.000

Frequent Benchmarking

.291

74 .000

.771

74

.000

Periodic measure of quality cost

.281

74 .000

.767

74

.000

Internal quality audits at regular interval

.329

74 .000

.723

74

.000

Automation of work process

.291

74

.000

.748

74

.000

Preventive Maintenance

.335

74

.000

.744

74

.000

Smooth flow of production

.321

74

.000

.737

74

.000

Lean Manufacturing

.349

74

.000

.730

74

.000

Application of Ergonomics

.377

74

.000

.703

74

.000

Reliability of Tools and equipment

.337

74

.000

.758

74

.000

Work Measurement System

.373

74

.000

.694

74

.000

Working for sustainable development

.352

74

.000

.703

74

.000

Periodic evaluation of vendors

.308

74

.000

.723

74

.000

Supply chain management

.315

74

.000

.732

74

.000

Integration of value chain

.358

74

.000

.708

74

.000

Well educated and aware customers

.443

74

.000

.594

74

.000

Customers’ need identification

.417

74

.000

.639

74

.000

Enhancing customers’ satisfaction

.427

74

.000

.624

74

.000

Efficient Customers’ feedback mechanism .429 74 .000 .620 74 .000

Quick Redressal of the customers’ complaints .438 74 .000 .604 74 .000

Annexure 1

Tests of Normality



92


LEADERSHIP IN TQM CONTEXT:A CASE STUDY

1Dr. K.K. Garg

2Pranav Mishra

Abstract

Purpose- The increasing competition is motivating the Indian automobile industry to

implement Total Quality Management (TQM) by using a wide variety of Critical Success Factors of

TQM. Purpose of this paper is to review the practices of Leadership on Total Quality Management

(TQM) in Indian Automobile Industry.

Design/Methodology/Approach- In this paper, an effort is made for the analysis covering a

sample of 35 organizations from Indian automobile industry in a case study mode.

Findings- the paper reveals that total quality management has a direct bearing on the

performance of TQM journey. The Survey findings indicate that quality scenario in the Indian

automobile industry is improving and automobile manufacturer (OEMs) & Suppliers (Tier-I) are more

focusing on quality Leadership of TQM practices and sub-contractors (Tier-II) is not responding as the

changing needs of market.

Originality/value- the value of the paper is point out which Leadership component to

successfully implement TQM context in Indian automobile industry.

Research limitations/implications- the investigation and research findings are still exploratory.

Key Words: Total Quality Management

Introduction

The TQM concept refers to company-wide quality assurance from supplier to customer using

system approach of documented sets of procedures and control of process variability in a team spirit with

top management commitment. “Leadership” is a process of creating a vision for the future, and

developing a strategy for moving towards that vision. Vision is the foundation for creating right focus in

the company. The role of Leadership metamorphoses into that of a change agent, working for “clock

building, not time telling”. Leadership in a TQM system is not a single individual; it is the top

management team that leads and provides systems and platform for the organization to operate.

Leadership is the degree of which top management sets up QM objectives and strategies, provides and

1. Associate Professor,Dept. of Management, Lingaya's Lalita Devi Institute of Management & Sciences, Mandi road, Mandi, New Delhi-110047 Email:- [email protected] Phone no.- 9650687688

2. Associate Professor,Dept. of Management, Lingaya's Lalita Devi Institute of Management & Sciences, Mandi road , Mandi, New Delhi-110047 Email:- [email protected] Phone no.- 9212472425


allocates necessary resources, contributes in quality improvements efforts, and assesses QM 2

implementation and performance.

Indian Automobile Industry

The automobile industry is one of the core industries in Indian economy, whose prospect is

reflective of the economic resilience of the country. With 4 percent contribution to the GDP and nearly 5

percent of the total industrial output, the automotive industry has become a significant contribution to the

exchequer. Continuous economic liberalization over the years by government of India has resulted in

making India as one of the prime business destination for many global automotive players3. The Indian

automobile industry comprises of the automobile and auto component industry.

India is the largest three-wheeler market and second largest two –wheeler market in the world and is the

fourth largest and fastest growing passenger car market in Asia. India is also the second largest producer

of motorcycles in the world. The percentage distribution of different types of vehicles in total production 4is tabulated in table:1

Table 1: Indian Auto Production

Type of Vehicles Percentage Production (in %)

Number of Vehicles(2011 -12)

Two Wheelers 77% 13,435,769

Three Wheelers 3% 513,251 Passenger Cars 15% 2,618,072 Commercial Vehicles 5% 809,532

Indian companies such as Bharat Forge, Brakes India and Sundaram Clayton Limited have moved into

high value added areas of production. According to the Automotive Component Manufacturers

Association (ACMA), the Indian auto component manufacturers would see and exponential growth in

output over the next decade. They have become reliable suppliers to global manufacturers such as

Toyota, Honda, Suzuki, General Motors, Ford, Cummins, Volvo and Daimler Chrysler. Instead of a high

production rate of the vehicles in India, the share of export in total output is low. The complete vehicle

export share is lower than the auto components export. The auto component industry can be divided into

six main segments, which are illustrated in table.2

S.No.

Segment

Component

1. Engine Parts

Components piston, piston rings, cylinder, and fuel delivery system like, carbure tor, diesel -

based fuel delivery systems,

engine valves.

2. Electrical parts Starter motors, generators, spark plugs and distributors. 3. Drive transmission

and steering parts Gears, wheels, steering systems, axles and clutches.

Table: 2 Segments of Auto Component Industry

1Dr. K.K. Garg2Mr. Pranav Mishra


4. Suspension and

Breaking Parts

Brakes and leaf springs, Shock absorbers.

5. Lighting and dashboard equipment

Headlights and dashboards instruments.

6. Others Sheet metal components and plastic molded parts

These auto components produced in India and the production range of these components in shown in 5

table.3 this table is graphically represented in Fig.1

Table: 3 Indian Auto Component Market

Auto Components Production (in %)

Engine parts 31%

Equipments-Dashboards Headlight 10% Suspension & Breaking Parts 12% Drive Transmission &Steering Parts 19% Electrical parts 9% Body & chassis 12% Others 7%

, 31%

Equipments-

Dashboards

, 10%

Suspension &

Breaking

, 12%

Drive Transmission

&Steering Parts

, 19%

Electrical

, 9%

Body &

, 12%

, 7%

Fig.1 Indian Auto Components Markets

The size of auto component industry in India is around USD 34.7 billion and has growth at 26% p.a. since

FY056.

The automobile Industry is one of the largest industries with deep forward and backward linkage and

hence has a strong multiplier effect. Among the forward linkages the key generators of employment are

the oil industry, distribution, after-sales service network and supply of spares and replacement by the

auto component industry. Other critical forward linkages include auto finance and leasing industry. As

for the backward linkages, the automobile industry is the largest consumer of raw material like CR/HR

steel, aluminum and Zink alloys, and also of high value of rubber and plastics. Moreover, the automobile

industry is the most important driver of machine tool industry, the bed-rock of industrial growth7.

In early 80's Government of India, making a turning point for the automobile sector, announced some of

liberal policy changes as Maruti Udyog Limited (MUL), a joint venture with Suzuki Motors Ltd. of

Japan was set up and Indo-Japanese joint ventures were set up in two- wheeler industry like Hero Honda,

Leadership in TQM Context: A Case Study


TVS Suzuki, Escorts Yamaha, Kinetic Honda etc. Further, the deli censing of auto sector in 1993 opened

up the gates to a virtual flood of international automakers into the country to tap the large population base

of more than one billion people. This revolution brought a greater systems emphasis, more market

orientation\customer focus, continuous improvement culture, latest tools & technique and practices of

TQM and top management commitment towards quality.

LITERATURE REVIEW

Leadership is fundamental to management and organizational behavior and is on just about

everyone's short list of prerequisites for organizational success. Thus, it is not surprising that leadership

plays a crucial role in Total Quality Organization. “Teach & institute leadership” is one of Deming's 14

points. Leadership is the first category in the Malcolm Baldridge National Quality Award, and it is

recognized as the “Driver” of successful quality system8. Levinson & Dehont (1992) emphasized that

“Without management Leadership, quality and productivity will result only as fortunate accident9”.

India's interest about TQM came about by years of selfless contribution of one Japanese

Professor yoshikazu tsuda, invited by confederation of Indian industry (CII) to introduce TQM to Indian

manufacturing industry. He was the guide assigned by Japanese union of scientist and engineers that is

responsible of the promotion of TQM in Japan & the world over.

The resounding success of several Indian manufacturing and service firms in recent times has

invariably been linked to excellent practices to quality management. If you consider the auto-component

manufactures in India, many of them won the Deming Award for quality, the largest number outside

Japan.

Indian companies seem to be in the favorites list of the Deming Awards (termed as the Nobel

Prize in the world of manufacturing) of Japan. The Japanese Union of Scientists and Engineers (JUSE)

Started the Deming prize in 1951. Initially, this prize was open only to the Japanese industry, but in 1985

it was open thrown open to the rest of the world. From 1998 onwards, Indian companies started figuring

in the Deming prize list, with Sundaram Clayton's brakes division claiming the honor first. Deming

Grand Prize is the highest honor in quality awarded to a company for excellence in Total Quality

Management. This prize given to companies for demonstrating practicing TQM in areas of production,

customer service, safety, human resource, corporate social responsibility, environment



1998 Sundram-Clayton Limited, Brakes Division2001 Sundaram Brake Lining Limited2002 TVS Motor Company Limited

2003 Brakes India Limited, Foundry Division

Mahindra and Mahindra Limited, Farm Equipment SectorRane Brake Linings Limited

Sona Koyo Steering System Limited

2004 SRF Limited,

Industrial Synthetics Business

Business Lucas-

TVS

Indo-Gulf Fertilizers Limited 2005 Krishna Maruti Limited, Seat Division

Rane Engine Valves Limited Rane TRW Steering System Limited, Steering Gear Division

2007 Aashi India Glass Limited, Auto Glass Divi sion

Rane (Madras) Limited 2008 Tata Steel Limited

2010 National Engineering Industries Limited (India)

2011 Sanden Vikas ( India ) Limited

The Deming Grand Prize

2012 Tata Steel Limited (India)

Rane (Madras) Limited (India)Lucas-TVS Limited (India)

10Table: 4 List of India Deming Prize Winners

Significant number of auto component companies are focusing on global best practices like 5-S, Kaizen,

TPM, 6-SIGMA etc.

11Table: 5 Auto Component Manufacturer- Quality Certification and Recognitions

Category

ISO

9001 TS

16949 ISO

14001 OHSAS

18001 JIPM

Deming

Award TPM

Award Japan

Quality medal

Shingo

Silver Medallion

QS9000

No. of Firms

576 467 208 105 3 12 15 2 1 34

RESEARCH METHODOLOGY

OBJECTIVES OF THE STUDY

1. Understanding the concept of Leadership in TQM context of Indian Automobile Industry.

2. To analyze Practices & Importance of TQM in Indian Automobile Industry.

3. To Review the experiences with the development of Leadership in TQM context of Indian

Automobile Industry.

To obtain an insight on the awareness of TQM practices in the Indian Automobile Industry, a sample of

35 respondents (05 automobile manufacturers, 20 suppliers, and 10 sub-contractors) were obtained

while 200 organizations were requested to participate in the study. The study indicated a comparative

level of awareness and practice of Total Quality Management in the Automobile Industry. The

questionnaire was checked for reliability and validity by expert and practicenors. The questionnaire was



validated by sample data from original equipment manufactures (OEMs), suppliers (Tier-I), sub-

contractors (Tier-II). In the global scenario, the automobile components manufacturing companies are

classified as Tier-I and Tier-II suppliers12. The Tier-I Suppliers are those which supply components to

the original equipment manufactures (OEMs). Tier-II suppliers are those which supply components to

Tier-I suppliers13. The survey reported here was conducted from March, 2013 to May, 2013 and was

restricted to companies located in NCR region of India.

RESULTS & DISCUSSION

The average score of 2.51 of the Indian automobile sector on leadership as shown in Table 6. It

is particularly more predominant in case of automobile manufacturers and supplier categories where

average score is 2.66 and 2.69 respectively on a 5- point scale.

The key value emphasized is the importance of the customer focus, continuous improvement,

teamwork, database decisions, mutual contributions and open communication. Some organizations

developed core values, vision and mission statement also as change of leadership style and attitude from

commanders to coaches.. This is evident by the higher average score of 2.71 lowest score is assigned to

the aspect,” the top management gives effective consideration to quality of work in appraisal system”.

This score is 2.67 in automobile manufacturer category, 2.74 in supplier category and only 2.11 in sub-

contractor category on a 5-point scale. This implies that most of the organizations are not giving due

consideration to the performance appraisal system with the quality of work. Another weak area is for the

aspect, “benchmarking the organization's performance against the best performer”. The average score is

2.55, 2.48 and 1.44 in case of automobile manufacturer, supplier and sub-contractor categories,

respectively. This implies challenge is to change the mindset through leadership in TQM practice.

Visible change management is weak due to internal factors as is evident from the average score

of 2.31 on a 5-point scale. However the appreciation that quality management is not a “quick fix” but

requires along –term commitment for continuous improvement is very much there. Deming (1993),

Juran (1986) also give great emphasis on developing leadership.

Table 6: Leadership

Leadership Automobile manufacturers category

Supplier category

Sub-contractor category

Automobile sector

1. The top management is having personal visible involvement in all aspects of quality

management.

2.70 3.06 2.14 2.63


9.

The top management shows

trust and confidence in their subordinates and empowers

them to take decision.

2.73

2.87

2.1

2.57

10. The top manag ement commits itself to the organization vision and mission and informs everyone down the line.

2.90

2.98

2.63

2.84

11. The top management views customers and suppliers as an integral part of value chain.

2.64

2.86

2.63

2.71

2. The top manag ement trains the members of the core team (constitute of senior level managers) on group jobs. Always active in providing and receiving training.

2.78 2.54 1.92 2.41

3. The top management actively involve themselves in timely recognition and appreciation of Individual’s/Team’s contribution

2.73

2.71

2.21

2.55

4.

The top management encourages the core team to set high performance goals and provide appropriate resources

2.53

2.72

1.72

2.32

5.

The top management gives effective consideration to qu ality of work in appraisal system.

2.67

2.74

2.11

2.51

6.

The top management encourages core team to monitor and evaluate the level of performance and assess its effectiveness.

2.78

2.84

1.86

2.49

7.

The top management respect

and value all emp loyees and encourage open communication and exchange of information among different teams for enhancing innovativeness and creativeness in each individual.

3.02

2.47

2.14

2.54

8. The top management is supportive and pays sufficient attention to the n eeds of the people and maintains comparative status with other similar organization.

2.47 2.66 1.96 2.36




12. The top management give s importance to the suggestions made by the employees and encourages taking up incremental improvement efforts.

2.78

2.8

2.91

2.83

13. The top management is committed to change management through

14 Benchmarking the organization’s performance agai nst the ‘best’ performer,

2.55

2.48

1.44

2.16

15

Challenges due to the changes in the environmental factors,

2.35

2.55

2.13

2.34

16

Poor performance of the organization due to internal factors.

2.31

2.07

2.56

2.31

Total 39.94 40.35 32.46 37.58

Average 2.66 2.69 2.16 2.51

Standard Deviation 0.19 0.25 0.38 0.27

One of the important roles of the senior managers is to provide clear vision and values that

promote total quality. The top management needs to spell a clear quality policy or mission as the

underpinning process to realize the value and vision14. The top management needs to build culture, and

progressively remove cross – departmental barriers. It needs to act as facilitators to improve the ways

things are done by encouraging participation, involvement and development of employees. Leaders

need to become a part of the team to pursue customer satisfaction both internal and external

Top management leadership is paramount importance to the success of any organization.

Unless top managers provide clear vision and values that promote total quality in the organization, other

enabling variables (such as strategic planning, human resource focus, customer and market focus,

supplier focus, process management and information management) are unlikely to make a positive

impact. Thus, for the success of any organization, developing leadership attributes and skills should be at

the top of the management agenda15

Finally, a proactive l and supportive Leadership is crucial for success of TQM process.

Reference:

1. Oakland, JS, 1989, Total Quality Management, Heinemann Publishing Co, Oxford.

2. Saraph, G.V, Benson, G.and Schroeder, R.G., 1989, an instrument for measuring the critical

factors of TQM, Decision Sciences, Vol. 20, No. 4

3. In Overdrive Mode, November 19, 2006, Business India

4. www.siam.in SIAM Annual Report 2011-12



5. www.acmainfo.com ACMA Overview(2012-13)

6. www.acmainfo.com ACMA Industry Statistics june,2013

7. J.P. Sharma & Anjali Bhatnagar (2006), Automobile Industry and Productivity, Productivity,

Vol 47, 1-2 April-September

8. James R. Evans (2005) Total Quality Management, Organization, and Strategy, 4th Edition

9. Harry J. Levinson and Chuck DeHont, “Leading to Quality”, Quality Progress, May 1992, pp.

55-60

10. www.juse.or.jp/e/deming

11. www.acma.info

12. Bennett D and O'Kane J (2006), “Achieving Business Excellence through Synchronous

Supply in the Automotive Sector”, Benchmarking: An Introduction Journal, Vol. 13, No. ½, pp.

12-22.

13. M (2003), “JIT Inventory and Aghazadeh S Completion in the Global Environment: A

Comparative Study of American and Japanese Values in Auto Industry”, Cross Cultural

Management, Vol. 10, No. 4, pp. 29-42

14. Waldman, D.A., 1994, The contributions of total quality management to a theory of work

performance, Academy of Management Review, Vol. 19, No. 3, pp. 510-536

15. Deming, W.E., 1993, Out of the Crises- Quality, Productivity and Competitive Position,

Cambridge University Press, Productivity and Quality Private Limited Madras


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Faculty of Management and Research, Integral University, Kursi Road, Dasauli, Post Basha, Lucknow – 226026 (U.P.)

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A Journal of Management - Integral University · 2016-06-01 · Department of Business Management Faculty of Management and Research Lucknow-226026 U.P. (India) p-ISSN : 0974-8032