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SERVLOYAL Amongst Bank Customers Of

Indore: An Exploratory Research

Nishant Joshi, Dr.KaruneshSaxena

Abstract- The Indian banking industry is going throughturbulent times. With the lowering of entry barriers and blurringproduct lines of banks and non-banks since the financial sector

reforms, banks are functioning increasingly under competitivepressures. Hence, it is imperative that banks maintain a loyalcustomer base. In order to achieve this and improve their marketpositions, many retail banks are directing their strategies towards

increasing customer satisfaction and loyalty through improvedservice quality. Moreover, with the advent of international bankingand innovations in the marketplace, customers are having greater andgreater difficulty in selecting one institution from another. Hence, to

gain and sustain competitive advantages in the fast changing retail

banking industry in India, it is crucial for banks to understand in-depth what customers perceive, to be the key dimensions of servicequality and to evaluate banks on these dimensions. This is because if service quality dimensions can be identified, service managers should

be able to improve the delivery of customer perceived quality duringthe service process and have greater control over the overall outcome.

In the process a pre-tested and verified questionnaire has beenadministered on 220 respondents and both econometric andregression analysis has been applied for drawing model for analyzingdimensionality for future understanding future course.

Keywords-Loyalty, Service Quality, Indore, Banking

I. INTRODUCTION EGULATORY, structural and technological factors aresignificantly changing the bankenvironment throughout theworld. One factor that is spurring the growth ofthe service

economy in India is liberalisation that has been ushered in, by

thegovernment in the bank sector.The financial sector reform in Indiawas designed to infuse greater competitivevitality in the system. Toachieve this objective, the Narasimhan Committee,recommended theliberalisation of entry norms and suggested that new banks should

bepermitted in the private sector provided they conformed to theminimum startupcapital and other requirements. The committeerecommended too, a liberal policytowards allowing foreign banks toopen offices in India. Since the reforms started, theinterest rate

structure has been deregulated to a greater extent and banks havebeengiven a great degree of freedom in determining their ratestructure for deposits andadvances, as well as their product range.

Banking has also become more competitivein respect of the locationof points of sale, that is, the branch network. The final outcome isthat market power is getting shifted from banks to their customers.

Nishant.Joshi is Assistant Professor with Prestige Institute of Managementand Research, Indore, Madhya Pradesh, India (Phone: +91-9893301006; (e-

mail: [email protected]).

Dr.KaruneshSaxena is Professor in Faculty of Management Studies, MohanLalSukhadiya University, Udaipur, Rajasthan, India (e-mail:

[email protected])

Increased price competition, reduced regulation and reducinconsumer loyalty has brought customer retention and custome

relationship management in lime light. Customer satisfaction is nowsupposed to be a primary tool for retaining customers. Customesatisfaction has become standard with firms around the world tsustain customer loyalty and customer retention leading t

profitability. But the current thinking is that the relationship betweesatisfaction and loyalty is more complex than was originally thoughA lot of evidence exists regarding how satisfaction influences repepurchase (both volume and frequency) behavior, and price

sensitivity. The biggest advantages that a loyal customer gives arrepeat business and promotion of the company through word o

mouth.Withthe lowering of entry barriers and blurring product lineof banks and non-banks,the oligopolistic nature of Indian banking fast changing and giving way to relatively freer market place. Thleads to freedom of choice which banks' customers did nothav

earlier, dueto standardised products and regimented intererates(SubramanianandVelayudham, 1997).In other words, financiliberalisation has led to intense competition and consequently,bankare directing their strategies towards increasing customersatisfactio

and loyalty through improved service quality. Retail bankarepursuing thisstrategy, in part, because of the difficulty idifferentiating based onthe service offering. Typically, customerperceive very little difference in the servicesoffered by retail bank

and any new offering is quickly matched by competitors.

II. CONCEPTUAL FRAMEWORK AND REVIEW OFLITERATURE

Lovelock (2010) opined that loyalty is an old-fashioned wortraditionally used to describe fidelity and enthusiasticdevotion to

country, a cause, or individual. More recently, it has been usedin business context, to describe a customer’s willingness to continupatronizing afirm over the long term, preferably on an exclusivbasis, and recommending the firm’sproducts to friends an

associates. Customer loyalty extends beyond behavior anincludespreference, liking, and future intentions. Loyal customer cabe a consistent source ofrevenue over a period n therefore activmanagement of the customer base andcustomer loyalty is require

which often refersto “Customer Asset Management”.Today, in marketing context,the term defection is used to describe customerwho drop off a company’s radarscreen and transfer their bran

loyalty to another supplier. Reichheld and Sasser popularizedthe term zero defections, which they describe as keeping every customer thcompanycan serve profitably. Not only does a rising defection raindicate that somethingis wrong with quality (or that competitor

offer better value), it may also be a leadingindicator signaling a fall iprofits. Big customers don’t necessarily disappearovernight; theoften may signal their mounting dissatisfaction by steadilreducingtheir purchases and shifting part of their business elsewhere

Service quality is an array of factors or determinants comprising ofive dimensions of service i.e., quality, namely, tangiblereliability,responsiveness, assurance and empathy and use these athe basis for their servicequality measurement instrumen

R

International Conference on Business, Economics, Management and Behavioral Sciences (ICBEMBS'2012) Jan. 7-8, 2012 Dubai

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SERVQUAL (Parasuramanet al., 1988; Zeithaml et .al., 1990). Theresult was development of the SERVQUAL instrument, basedon the

gap model. The central idea in this model is that service quality is afunctionof the difference scores or gaps between expectations andperceptions. An importantadvantage of the SERVQUAL instrument

is that it has been proven valid andreliable across a large range of service contexts. However, while the SERVQUALinstrument hasbeen widely used, it has been subjected to certain criticisms as

well.The contention that service quality consists of five basic

dimensions (Parasuramanet al., 1988) is according to someresearchers questionable and they have suggestedthat SERVQUAL'sdimensions are contextual and not universally applicable ( Ekinci and

Riley, 1999; Brown et al., 1993; Cronin and Taylor, 1992; Teas,1993; Bouman and Van der Wiele, 1992; Gagliano and Hathcote,1994). Instead, the number andcomposition of the service qualitydimensions are probably dependant on the servicesetting (Brown et

al., 1993; Carman, 1990). It has been suggested that for someservicesthe SERVQUAL instrument needs considerable adaptation(Dabholkaret al.,1996) and that items used to measure service qualityshould reflect the specific servicesetting under investigation, and that

it is necessary in this regard to modifysome of the items and add ordelete items as required (Carman, 1990). Moreover,research suggeststhat culture may play a fundamental role in determininghowconsumers perceive what constitutes service quality.

Szymanski et al. (2001)explored that satisfaction influences repeatpurchase(both volume and frequency) behavior and price-sensitivity.The biggestadvantages that a loyal customer gives

arerepeat business and promotion of thecompany through word of mouth.But customer loyalty is much more thanrepeat purchases orincreased volume of purchases. While it has been argued that loyalty

does not mean anyone who buys repeatedly from the samecompany,Reichheld (2003) contradicted that not purchasingfrequently can be due to changed circumstances or customer mayhave reduced his or her requirements for the company’s products and

services. Going by this logic, repeat purchases or increased numbersof purchases may not be true indications of customer loyalty.Reinartzand Kumar (2002) opined that positive word of mouth publicitygenerated by loyal customers can be one of the ways of advocating acompany’s offerings to friends, colleagues and family. A customer

puts his own reputation at stake when he recommends a company;this act of recommendation should be considered the best indicator of customer loyalty. They further suggested that loyal customers areconsidered as the key to survival and success in many service

businesses, especially in the hospitality, insurance and financialsectors. According to Pullman and Gross (2003), a slight change inthe percentage of loyal customers can bring about a huge change in

profits and the overall value of the firm.Heskettet al., (1990) narratedthat company’s path to profit and growth may lie in its ability tomake its loyal customers market it. Many researchers feel that

competitive differentiation can no longer be achieved along thetraditional dimensions of corporate performance. Ascommoditisationof many service offerings continues, a new source of competitivedifferentiation/advantage will come from focusing on the

management of customer experiences.Loyalty is so very important to the survival and profitable growth of acompany, thus measuring customer loyalty is the prime concern (Pineand Gilmore, 1998).

III. RATIONALE

Research on service quality has been in the developed countries(Herbig and Genestre, 1996), even though services are among the

fastest growing sectors in emerging countries (Malhotraet al, 1993).In fact, the bulk of the research on service quality in banks has beenin the context of US and European banking institutions. Today,Madhya Pradesh in general and Indore in particular has become the

face of central India and the long stopped development has triggered.

The importance of the study at this juncture, it is important to alsstudy branches of banking institutions based in developing cities. A

branches in such cities in India provide mature, lessons may blearned from their experiences in developing cities. Banking ha

becomes more and more globally integrated. Thus, there exists service gap on how consumers evaluate service quality in contexand cultures very different from the developed countries, and no prioresearch has attempted to explore this area.

IV. OBJECTIVES

1. To determine the impact of dimensions affectinservice loyalty in banking services in Indore city.

V. HYPOTHESIS1. There is no significant impact of Attitude, Cognitivenes

Behavior and Trust on Service Loyalty.

VI. RESEARCH METHODOLOGY6.1 The Study:

The research was exploratory in nature. The main objectivbehind this research was to identify service loyalty amongbank customers of Indore.

6.2 Independent Variable

Attitude, Cognitiveness, Behavior and Trust

6.3 Dependent Variable

Service Loyalty

6.4 The Sample

The data was collected through convenience samplinmethod. A sample of 220 respondents was taken fromscheduled banks like state bank of India, Punjab Nationa

bank, CanaraBank,HDFC, ICICI, IDBI etc. These wercustomers of the various above listed banks.

6.5 Tools for Data CollectionPrimary Data has been collected from 220 respondenbased on a Lickert four point scale. The questionnaire ha

been adapted from the service loyalty scale oSudhahar,Israel, Britto and Selvam (2006) published in thAmerican Journal of Applied Sciences. The questionnair

was divided in four sections and each section represents dimension namely Behavioral, Attitudinal, Cognitive anTrust.

6.6 Tools for Data AnalysisThe data was collected and Dimensional averages werdrawn. In order to form a model firstly the data wa

subjected to augmented dickey fuller test for stationaryUpon finding the data being stationary it was subjected tmultiple regression using SPSS17.0. In the process Durbi

and Watson test was also applied to finally test thapplicability of multiple regression.

.VII. RESULTS

The computed ADF test-statistic as per table 01 for series0(behavioral), series02 (Attitudinal), series03 (cognitive) and series0(Trust) as per table 01 are (-7.692029, -5.608724, -5.619938 and

7.622569respectively) are smaller than the critical values - "tau" a10%, 5%, 1% significant level. It means that that the seriecollectively and individually are not having unit root problem and arstationary series at 1%, 10% and 5% significant level. Upon testin

Durbin-Watson test d= ∑ Tt=2 (e t-e t-1)

2/ ∑ Tt=2 (e t)

2 we find thvalue of d= 1.956633, 2.01, 1.919288 and 2 respectively for the fou


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series which arevery close to 2 or either 02 and according to theoriginal paper of Durbin and Watson (1951) the value of the test

closer to 2 or 2( d < 2) shall mean nearly zero, this confirms level of autocorrelation hence supports the ADF results.

The dimensional averages of 220 respondents when subjected tolinear regression using the enter method. The resulting synthesized

and tabulated dimensional data thus drawn is having one dependentand four independent variables. In the first stage three independent

variables namely behaviour, attitude, cognitiveness is subjected tomultiple regression using SPSS 17.0. The model summary generated

as per table 02 shows correlation between the observed and predictedvalues of the dependent variable produced by the regressionprocedure generally range from 0 to 1. Table 02 shows larger values

of R indicating stronger relationships.R squared is the proportion of variation in the dependent variable explained by the regressionmodel.The values of R squared ranges from 0 to 1.The R squaredvalues also optimistically estimate that models arefitting the

population. The Durbin- Watson test value is also very close to 2indicating strength. The output for Regression ANOVA as per table03 displays information about the variation accounted for by themodel.The output for Residual displays information about the

variation that is not accounted for by the model.And the output forTotal is the sum of the information for Regression and Residual.As

the model is having a large regression sum of squares in comparisonto the residual sum of squares indicates that the model accounts for

most of variation in the dependent variable.The mean square is thesum of squares divided by the degrees of freedom. The F statistic isthe regression mean square (MSR) divided by the residual meansquare (MSE).The regression degrees of freedom is the numerator df

and the residual degrees of freedom is the denominator df for the Fstatistic. The total number of degrees of freedom is the number of cases minus 1.The significance value of the F statistic is small

(smaller than 0.05) thus it can be stated that the independent variablesdo a good job explaining the variation in the dependent variable.Asper table 04 the model equation would be:

Loyalty = 0.2+ 0.365(Behaviour) + 0.387(Attitude) + 0.167(Cognitiveness)……Eq. 1 (1)

For drawing the second equation the fourth independent variableTrust is regressed with dependent variable loyalty using enter method

of regression. As per table 05 the model summary generated showscorrelation between the observed and predicted values of thedependent variable produced by the regression procedure generally

ranging from 0 to 1. Table 05 shows larger values of R indicatingstronger relationships.R squared is the proportion of variation in thedependent variable explained by the regression model.The values of

R squared ranges from 0 to 1.The R squared values alsooptimistically estimate that models arefitting the population. TheDurbin- Watson test value is a little higher than 2 but still in vicinityindicating strength. Table 06 generated is the regression

ANOVAdisplaying information about the variation accounted for bythe model.The output for Residual displays information about thevariation that is not accounted for by the model.And the output forTotal is the sum of the information for Regression and Residual.As

the model is not having a large regression sum of squares incomparison to the residual sum of squares indicates that the modelmight not accounts for most of variation in the dependent variable,but as the Durbin Watson test is indicative of a good result we can

proceed.The mean square is the sum of squares divided by thedegrees of freedom. The F statistic is the regression mean square(MSR) divided by the residual mean square (MSE).The regressiondegrees of freedom is the numerator df and the residual degrees of

freedom is the denominator df for the F statistic. The total number of degrees of freedom is the number of cases minus 1.The significance

value of the F statistic is small (smaller than 0.05) thus it can bstated that the independent variables do a job explaining the variatio

in the dependent variable.

As per the result generated the equation is as follows

Loyalty = 1.23 + (0.460) Trust …… Eq.02 (2)

Simplifying Eq01 and 02

∑Eq. 01+ Eq. 02

L= (1.43 + 0.365B + 0.387 A+ 0.167 C + 0.46 T)/ 2 (3)

L= 0.715 + 0.1825 B + 0.1935 A+ 0.0835 C + 0.23 T (4)

Here L is loyalty, B is Behaviour, A is attitude, C is Cognitivenesand T is trust.

Upon testing both the hypothesis we can found that the hypothesis rejected.

VIII. CONCLUSION

It can be concluded that there is positive impact of dimensionaffecting service loyalty. In order to retain the customers trust has tbe maintained along with proper behaviour and attitude towards themfollowed by Cognitiveness expressed by bank employees. Trust is th

key to all banking activities the name bank itself is synonymous otrust. But trust alone cannot be the key to customer retentionServices are very sensitive and according to berry, the human factohas high degree of responsibility towards customer satisfactio

behaviour and attitude towards customers in the banking sector shaenable banks to retain them followed by a cognitive eye towardthem shall make them feel delighted. In words of Keller, “Delightecustomers is yours forever, till delighted”, the author expressed th

concern that in global business formats the customers have choices she shall remain with the service provider till he is delighted. Thbanking reforms in India have brought foreign banks into Indi

increasing competition in the sector the model suggested above shaenable the banks to retain old customers and add new customers.

IX. IMPLICATIONS

The descriptionpresent here simply betokens the need fodevelopmentof SERVLOYAL for use in the servic

marketingresearch. The robustness of the measurement of itemsiterms of relationship among latent variables canalways stanimprovement. Therefore, future researchcan be conducted tcontinuously refine this measurementscale and corroborate th

findings of this empiricalstudy. The effect of psychological angeneticpredispositions to Service Loyalty has yet to beinvestigateand the same could also be attempted asa future study. ThDimensionality has been conducted to only take further the study an

delimit the existing research material. This also indicates that thImpact of the four dimensions is very high in the universe of thresearch and banking organizations working in the area can reall

build and retain more number of customers. The act of maintaininlong-term relationship withcustomers has been proving to bbeneficial for thecorporate of any rung, be it profitability o

loyalty,irrespective of the sectors they belong to. In todaycompetitive environment, organizations shouldprotect the long-terminterest of the customers andhence should seek the ways througwhich the customerloyalty toward the organizations will be forged.


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APPENDIX

TABLE 1

TABLE 2MODEL SUMMARY

Model R R Square Adjusted RSquare

Std. Error of theEstimate

Durbin-Watson

1 .749 .561 .558 .30024

2 .933 .870 .869 .16361

3 .948 .899 .898 .14446 1.925

TABLE 3REGRESSION ANOVA

MODEL SUM OFSQUARES

DF MEANSQUARE

F SIG.

1 REGRESSION 25.062 1 25.062 278.023 .000

RESIDUAL 19.652 218 .090

TOTAL 44.714 219

2 REGRESSION 38.905 2 19.453 726.709 .000

RESIDUAL 5.809 217 .027

TOTAL 44.714 219

3 REGRESSION 40.206 3 13.402 642.231 .000

RESIDUAL 4.507 216 .021

TOTAL 44.714 219

TABLE 4- COEFFICIENTS

UNSTANDARDIZ

EDCOEFFICIENTS

STANDARDIZ

EDCOEFFICIENT

S

TSI

MODEL BSTD.

ERRO

R

BETA

1 CONSTANT 1.245 .064 19.55 .0

BEHAVIO .542 .032 .749 16.67 .0

2 CONSTANT .357 .052 6.84 .0

BEHAVIO .438 .018 .606 23.96 .0

ATTITUDE .433 .019 .575 22.74 .0

3 CONSTANT .200 .050 3.981 .0

BEHAVIO .365 .019 .505 19.63 .0

ATTITUDE .387 .018 .514 21.76 .0

COGNITIV .167 .021 .215 7.89 .0

TABLE 5MODEL SUMMARY

Model R R SquareAdjusted R

SquareStd. Error of the

EstimateDurbin-Watso

1 .716 .513 .510 .31620 2.110

t-Statisti

c

Prob.*

Augmented Dickey-Fuller test statistic

SERIES01(behavioral) -7.69 0.000

SERIES02(Attitudinal) -5.60 0.000SERIES03(cognitive) -5.62 0.000

SERIES04 (Trust) -7.62 0.000

Test critical values:1%

level-3.469 -3.467 -3.46 -3.46

5%level

-2.878 -2.877 -2.87 -2.87

10%level

-2.575 -2.575 -2.57 -2.57


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TABLE 6REGRESSION ANOVA

Model Sum of Squares df Mean Square F Sig.

1 Regression 22.917 1 22.917 229.212 .000

Residual 21.796 218 .100

Total 44.714 219

TABLE 7COEFFICIENTS

UnstandardizedCoefficients

StandardizedCoefficients

t Sig.

Model BStd.

ErrorBeta

1(Consta

nt)1.230 .071 17.39 .00

TRUST .460 .030 .716 15.14 .00

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