JOURNAL OF INTERNATIONAL ACADEMIC RESEARCH FOR MULTIDISCIPLINARY Impact Factor 1.393, ISSN: , Volume 2, Issue 2, March 2014

Transcription

1 LINKAGE BETWEEN SERVICE QUALITY AND CUSTOMERS LOYALTY IN INSURANCE SECTORS DR.S.MANIMARAN* *Professor & Head, Dept. of Management Studies, PSNA College of Engineering & Technology, Dindigul, Tamilnadu, India ABSTRACT This study examines the nature of linkage between service quality and customer loyalty in Insurance Sectors. The Investors in Insurance are the customers. Study used confirmatory factor analysis to identify the service quality dimension. The resulted dimensions are Reliability, Responsiveness, Knowledge and recovery; and Tangibles. The service quality dimensions lead to customer satisfaction and the customers satisfaction leads to customer s loyalty. The structural equation model reveals that there is no significant direct linkage between service quality and customers loyalty. At the same time, the service quality has a significant indirect impact on customer s loyalty especially through customer s satisfaction. The study indicates that the management of the Insurance Sector needs to develop a systematic assessment programs to monitor service quality and customers satisfaction over time. Once the service culture is established, that will lead to customer satisfaction. and customer satisfaction result in customer s loyalty. LINKAGE BETWEEN SERVICE QUALITY AND CUSTOMERS LOYALTY IN INSURANCE SECTORS During the past two decades or so, regulatory, structural and technological factors have significantly changed the services environment throughout the world (Angur et al., 1999). In a milieu which becomes increasingly competitive, service quality as a critical measure of organizational performance continues to compel the attention of servicing institutions and remains at the forefront of services marketing literature and practice (Lasser et al., 2000; Yavas and Yasin, 2001). The interest is largely driven by the realization that higher service quality results in customer s satisfaction and loyalty, greater willingness to recommend to someone else, reduction in complaints and improved customer retention rates (Danaher, 1997; Magi and Julander, 1996; Levesque and McDongall, 1996). Undoubtedly owing to the belief that delivery of higher service quality is a must for attaining customers satisfaction and a number of other desirable behavioural outcomes, recent years have witnessed a flurry of research exploring inter relationship between service quality and, satisfaction and behavioural outcomes (Festus and Hsu, et al., 2006; Thamariselvan and 386

2 Raja, 2007). This study expands the research stream into India. The specific objectives of the study are: To reveal the dimensions of service quality in Insurance Sectors. To examine the inter relationship between dependent and independent variables and To study the direct and indirect effects of service quality on customer loyalty. A study addressing these issues is relevant and significant for at least three reasons. First, while much is known about the items in the SERVQUAL instrument that are global in nature, the outcome of administering the SERVQUAL scale to the customers of a service is of little utility value for instituting an operational instrument process for the service. Some researchers (Babakus and Boler, 1992; Lapierre, 1996; Levitt, 1981) have suggested that the search of universal conceptualization of the service quality construct may be futile, and to be a practical utility, a service construct should not only be operational, but also context specific. Secondly, while much is known about the relationships between service quality, satisfaction and behavioural outcomes as a result of research initially as conducted in the USA and England (Angur et al., 1999; Jamal Nasser, 2002; Yavas et al., 1997; Anthanassapoulous, et al., 2001), still there is a paucity of research dealing with these issues in the context of India. Thirdly, in today s fiercely competitive service environment, where insurance institutions consider delivery of excellent service quality to customers as a key to success and survival, the findings from the study can provide them with valuable insights in ways of enhancing service quality to induce greater customer satisfaction and customer s loyalty. Conceptual Foundations Over the past 40 years, several authors have attempted to develop coherent classification schemes for services. The intent of such schemes is to bring parsimony and order to allow a better understanding of the characteristics that differentiate services and the organizations that provide them. The following section reviews some of these schemes. Service Quality Service quality is considered a multi-attribute construct-the product of the comparison between the customers expectations and their perceptions of the company s actions (Parasuraman et al., 1985; 1998; Boulding et al., 1993; Gronroos, 1994). Perceived service quality has been defined as the consumer s global attitude or judgement of the overall excellence or superiority of the service. Perceived service quality results from comparisons 387

3 by consumers of expectations with their perceptions of service delivered by suppliers (Lewis et al., 1994; Takeuchi and Onelch, 1983; Zeithaml, 1988). Customers expectation are beliefs about a service that serve as standards against which service performance is judged (Zeithaml et al., 1993); what customers think a service provider should offer rather than what might be on offer (Parasuraman et al., 1988). Expectations are formed from a variety of sources such as the customer s personal needs and wishes (Edvardsson et al., 1994). Measurement of Service Quality The SERVQUAL instrument proposed by Parasuraman et al., (1988) posits the computed disconfirmation approach whereby the difference between a customer s expectation and the actual performance is calculated. This approach has been criticized by several authors for a number of weaknesses. The alternative approach namely SERVPERF, is that measurement of the customer s perception of the performance of a service which provides adequate assessment for service quality (Gronroos, 1988; 1990; Cronin and Taylor, 1992; Peter et al., 1993; Brown et al., 1993; Bebko, 2000). The increasing support on the measurement of service quality by performance-only measurement (SERVPERF) is witnessed (Andaleeb, and Basu, 1994; Zeithaml, 1996 and Cronin et al., 2000). Since the weight of evidence in the literature supports the use of performance perception, the present study adopts the SERVPERF scale to measure service quality. Service Quality Dimension in Insurance Sectors Several researchers have suggested that the search for universal conceptualization of the service quality construct may be futile (Levist, 1981; Lovetock, 1983). The service quality construct is either industry or context specific (Babakus and Boller, 1992). The measurement of the service quality construct is multidimensional. In its original structure, service quality consists of five dimensions (Parasuraman et al., 1988; Carman, 1990; Rust and Oliver, 1994). These are: 1. The tangibility aspects of the service 2. The reliability of the service provider 3. The assurance provided by the service provider 4. The responsiveness of the service provider; and 5. The service provider s empathy with customers In the present study, the included service quality variables are twenty seven (See Table 1). 388

4 Customer Satisfaction Several studies seem to conclude that satisfaction is an affective construct rather than a cognitive construct (Oliver, 1997; Olsen, 2002). Cronin et al., (2000) assessed service satisfaction using items that include interest, enjoyment, surprise, anger, wise choice, and doing the right thing. Rust and Oliver (1994) defined satisfaction as the customer s fulfillment response which is an evaluation as well as an emotion-based response to a service. In the present study, the more popular Westbrook and Oliver s (1991) four emotionladen items have been used. Perceived Value Customers perceived services have been theoretically represented as consisting of two dimensions. Berry and Parasuraman (1991) distinguish a process and an outcome dimension, whereas Gronroos (1990) makes a distinction between functional and technical quality. The process of functional quality refers to how the service is delivered, while the outcome or technical quality refers to what customers perceive, the benefits of using the service. In the Insurance sectors, how operations are being carried out as functional benefit, easy to learn, confidence on the technology infrastructure benefits that customers perceive as technical benefits. In the present study, the number of items used to measure the perceived value on service is three (See. Table 1). Customer s Loyalty According to a model presented by Zeithaml et al., (1996), behavioural intention can be captured by such measures as repurchase intentions, words of mouth, loyalty, complaining behaviour, and price sensitivity. High service quality often leads to favourable behavioural intention (Burton et al., 2003). Loyal customers are important, because they contribute to the profitability by passing positive words of mouth and also retain their customership. (Anderson and Mittal, 2000; Storbacka et al., 1994). Loyalty is predominantly satisfaction driven (Rust et al., 1995) and therefore customers satisfaction measurements are believed to give a better indication of future performance of service firms (Anderson and Fornell, 1999) than, for instance financial and accounting based measures (Kaplan and Nortan, 1996). Customer loyalty is a feeling of commitment on the part of the consumer to a product, brand, marketer, or services above and beyond that for the competitors in the market place, which results in repeat purchase (Szymigin and Carrigan, 2001). 389

5 Inter Relationship among Service Quality, Customer Satisfaction and Customer Loyalty There is no clear message in the literature on the causal ordering of service quality and customers satisfaction, and on which of the two constructs is a better predictor of customer loyalty (Bolton and Drew, 1991; Cronin and Taylor, 1992). One group of researchers upholds that satisfaction is antecedent to service quality (Brady and Robertson, 2001). Dabholkar, 1995; and Winstanley, 1997). Another group of researchers believe that the service quality is antecedent to satisfaction (Brady and Robertson, 2001, Bloemer et al., 2002; Newman 2001). A third perspective maintains that there is a non-recursive relationship between service quality and satisfaction (Taylor and Cronin, 1994). The impact of service quality, customer satisfaction on customer loyalty is complex. The present study, however predicts the direct and indirect effects of service quality, customers satisfaction on customer loyalty with the help of structural equation modeling. The proposed research model is presented in Figure 1. FIGURE 1 Proposed Research Model Reliability Responsivenes Knowledge and Recovery Service Quality Perceived Quality Customer Satisfaction Customer Loyalty Tangibles Research Methodology Scale Development Parasuraman et al. (1994) emphasized an alternative approach in giving customers definitions related to five underlying dimensions of service quality and asking them to assign the items into the dimension only on the basis of each items content. Similar to the essence of Parasuraman et al. s approach, the questionnaire items in the present study were generated via a series of focus groups. Specifically, the focus group customers comprised teams of customers of Insurance sectors. The research developed a service blue print for insurance 390

6 sectors because this gives the customers an opportunity to better understand the sequential stages of service encounter. The operational definition of the construct of perceived quality (SERVPERF) was introduced to the customers prior to their development and verification of the service quality measurement scale. The focus groups (investors) were requested to check the variables included to measure the service quality of Insurance sectors. TABLE 1 The Survey Instrument Sl.No Particulars I. Reliability 1. Error-free records 2. Timely Passion of service 3. Right at first time itself 4. Staffs sincerity in service 5. Providing service at promised time 6. Sincere in solving problems II. Responsiveness 7. Employees adopt service to the customer needs 8. Staffs readiness to customers request 9. Customers informed about service performance 10. Well handling of peak hours 11. Providing correct response to customers 12. Courteous among employees 13. Willing to help customers III. Tangibles `14. Attractive interior design 15. Upto-date equipment 16. Neat and professional appearance of employees 17. Comfortable parking space 18. Visually appealing facilities IV. Recovery 19. Employees empowered for correction 20. Response on Claims 21. Quick Correction on mistakes made 22. Convenient operating hours 23. Personalized service 391

7 Sl.No Particulars V. Knowledge 24. Customer Relationship 25. Knowledge of staffs 26. Awareness on Latest insurance facts 27. Provision of adequate information VI. Perceived Value 1. Navigation Easy 2. Safety 3. Confidence on Insurance Sector 4. Accessibility VII. Customer Satisfaction 1. I am satisfied with my decision to choose this Investment 2. I did a right thing 3. My choice is a wise one 4. I feel good experience with this insurance sector VIII. Customer Loyalty 1. I am proud to be a customer of Insurance Sector 2. I want to continue as a customer of Insurance Sector 3. I recommend others about Insurance Sector Each item of the service quality of Insurance Sectors was rated on a five point likert type of scale. In addition, the perceived value, customer satisfaction and customer loyalty were also measured with the help of related statements. The Sample In total, 20 Insurance units in Madurai, TamilNadu have been purposively selected for the present study. From each Unit, 20 customers are purposively selected. The total sample size came to 400 customers. Among the total customers, the important age group is 46 to 50 which alone constitutes per cent to the total. The important occupational background among the customers is business and private employment which constitute and per cent to the total respectively. The important annual income among the customers are Rs.15,000 to per month which constitutes per cent to the total. Most of the customers have an experience of years in their present banks. Data analysis The present study first reviewed the descriptive statistics (Mean, standard deviation, coefficient of variation, kurtosis and skewness) and was satisfied with the data distribution. Next, focusing on the customers of Insurance units, the present study used an iterated factor analysis with item commonality estimated from squared multiple correlations, and maximum 392

8 likelihood as the estimation method. This procedure resulted in a four-factor solution that was rotated by a Promax algorithm (i.e. an oblique rotation). As a conservative, heuristic, items with a loading small than 0.4 on any factor were deleted. Moreover, items that demonstrated cross-loadings greater than 0.4 on more than one factor were also dropped because they do not provide pure measures of specific construct. In addition, the scree test and the Kaiser (1960) eigen value one criterion were both used to identify the number of factors. The results are given in Table 2. TABLE 2 Factor loadings for the underlying dimensions of service quality Sl.No V.No Variabels Reliabi Responsiven Tangibles lity ess 1 V4 Staffs sincerity in service V2 Timely Provision of service V1 Error free records V6 Sincere in solving Problems V5 Providing service at promised time 6 V3 Right at first time itself V11 Providing correct response to customers V9 Customers informed about services 9 V13 Willing to help customers V8 Staffs readiness to customer request 11 V10 Well handling at peak hours V21 Quick correction on mistakes made Knowled ge and Recovery V24 Customer Relationship V25 Knowledge of staffs V27 Provision of adequate information V23 Personalized service V18 Visually appealing facilities V16 Neat and Professional appearance of employees 19 V15 Upto date equipment V14 Attractive interior design Eigen value Percent of variance explained Cronbach alpha *Factor loading less than 0.5 are not shown Out of 27 service quality variables, seven variables were dropped because of their poor factor loading (less than 0.4) and more than 0.4 in more than one factors. The 20 variables were taken for the data validity test namely Kaiser-Meyer-Ohlin (KMO) measure of sampling adequacy and Bartletts test of sphericity. Both the two tests satisfied the validity of data for factor analysis. The factor analysis result in four important factors with the 393

9 cumulative variance explained of per cent. The identified factors are Reliability, Responsiveness, Knowledge and Recovery; and Tangibles. The above said service quality factors consist of 6,5,5 and 4 variables with the reliability coefficient of , , and respectively. Notably all of the calculated reliability coefficient are above the widely recognized rule of thumb of 0.7 (Nunnally, 1978) which suggests a good internal consistency among item in this each identified Dimension. Assessing reliability and validity of constructs It should be noted that a more rigid procedure was also performed to assess the dimensionality of the service quality measure. Empirically, convergent validity (the degree if association between measures of a construct) was assessed by reviewing the t tests for the factor loadings. The composite reliability scores for each of four factors have been also computed. The results are given in Table 4. TABLE 4 Properties of the CFA for SERVPERF Construct and Indicators Items Standardised Loading T- Statistic s Composite Reliability Service Reliability Error free records * 0.93 Timely provision of service * Staffs sincerity in service * Providing service at promised time * Responsiveness Customers informed about service performance * Providing correct response to customers * 0.82 Willing to help customers * Staffs readiness to customers request * Knowledge and recovery * Knowledge of staffs * 0.87 Quick correction on the mistakes made * Provision of adequate information * Customer Relationship * Tangibles Upto date equipment * 0.86 Visually appealing facilities * Neat and professional appearance of employees * The metric for each scale was established by fixing the coefficient for one indicator to 1.00 for each of four factors. Other than the fixed loadings, each item evidenced highly significant t statistics (value < 0.01), suggesting that all indicator variables provide good measures to their respective construct. Specifically, the entire set of indicators has a standardized loading higher than with the highest being These results generally supported the convergent validity of the indicators. (Anderson and Gerbing, 1988). 394

10 Composite reliability is similar to Cronbach alpha, and reflects in the internal consistency of the indicators measuring each Confirmatory Factor Analysis construct (Fornell and Larcker, 1981). Results show that all four factors have composite reliability scores greater than the commonly recommended 0.7 benchmark, and this suggests that each of the factors is reliably measuring its respective constructs. Discriminant Validity It is not easy to establish discriminant validity. (the degree to which items of constructs are distinct) when the involved constructs are theoretically related to a hierarchically high order construct (i.e. service quality), as is the case here. The existence of a second order factor structure suggests the sub-dimensions of service quality share common variance. However, discriminant validity can be empirically assessed in a weak sense by using the confidence interval test (plus or minus two standard deviations around the factor correlations). Discriminant validity is said to be satisfied if a 95 per cent confidence interval of the inter-factor correlation between two constructs does not include an absolute value of one (Anderson and Gerbeing, 1988). The Correlations among all the constructs are presented in Table 5. TABLE 5 Correlation Matrix for all exogenous and endogenous Variables Sl.No. Variables Reliability Responsive ness Knowledge and Recovery Tangibles Perceived value Customer Satisfaction Customer loyalty 1. Reliability * * * * * * 2. Responsivene * * * * * ss 3. Knowledge * * * * and Recovery 4. Tangibles * * * 5. Perceived * * data 6. Customer * Satisfaction 7. Customer Loyalty *Significant at five per cent level. Though some of the correlation coefficients were found to be relatively high, the 95 per cent confidence intervals for the inter factor correlation were not found to include 1.0. As a result, this confidence interval test tends to support to the discriminant validity of the studied constructs. 395

11 Impact of independent variable on dependent variable The impact of service quality on perceived value, perceived value on customer satisfaction, and customer satisfaction on customer loyalty have been estimated with the help of structural equation Modeling. The fit indices like x 2, RMSEA, TLI, AGFI, GFI, CFI and NFI have also been computed. The implications of these with the proposed model are explained in Table 6. TABLE 6 Results of the Structural Equation Modeling Sl.No Hypothesis Standardized t-statistics p-value Data 1. Service Quality with Perceived value 2. Perceived value with Customer Satisfaction 3. Customer Satisfaction with Customer Loyalty Fit Indices Chi-square= RMSEA=0.041 TLI = p-value (.0018) AGFI = GFI=0.946 CFI=0.952 NFI=0.923 The standardized coefficient in the Hypothesis namely service quality with a positive impact on the perceived value of the insurance sector has a significant value ( = ; t- value= ), supporting the assertion that the service quality significantly and positively influences the perceived value of the service offered by the insurance sectors. This fundamental concept reiterates that the insurance sectors should focus on the quality of service to increase the perceived value of service among the customer s mind. The real challenge for insurance sectors is to find SERVQUAL dimensions and their significance to overall service quality. The second Hypothesis is trying to predict the relationship between the perceived value of the service by the customers to their satisfaction. This hypothesis supports and proves that the perceived value of service plays a significant impact on the overall customer satisfaction since its value is and the t-statistics of which is significant at one per cent level. This direct effect would give clear relationship between perceived value and customer satisfaction. The third hypothesis reveals the impact of customers satisfaction on their loyalty. The -value (0.5739) and the t-statistics (5.9708) are significant at two per cent level. The present study reveals that there is a significant and positive direct impact of customers satisfaction on customers loyalty. 396

12 The fit indices for this model indicate how well the data fit with model. Infact, all fit indices are well within the range accepted among the researchers. The significant Chi-square value (113.08) supports the model. The comparative fit index that is Normed Fit Index (0.923) value signifies the best of fit of model with the collected data. The variances are also greatly explained. The Goodness of Fit Index (GFI=0.946), Adjusted Goodness of Fit Index (AGFI=0.917) and Tucker Lewis Index (TLI= 0.934) along with Root Mean Square, Error of Approximation (RMSEA =.052) strongly supports this model. Direct and indirect effects on Customer loyalty The direct and indirect effects of service quality, perceived value and customer satisfaction on customer loyalty are evaluated with the help of structural equation modeling. The results are shown in Table 7. TABLE 7 Total effects of the factors involved in evaluation of service quality on Customer Loyalty Sl.No Factors Direct effects Indirect effects Total effect Relative Percentage 1. Service Quality Perceived value Customer satisfaction Customer Loyalty From table 7, customer satisfaction clearly has the high level of impact (59.79%), followed by perceived value (22.19%) and service quality (18.02%). The customer satisfaction has a direct impact whereas perceived value and service quality have indirect effects on the customer loyalty. Conclusion and Managerial Implication The service quality scale developed in this study was first calibrated using the data from customers of public sector banks (i.e. sample-1) and then cross-validated using a more diversified data set (i.e-sample-2). Four service quality factors were identified as the first order dimensions of service quality in the context of commercial banks. These are Reliability; Responsiveness; knowledge and Recovery; and Tangibles. Notably, the variables in knowledge and recovery are correlated together and formed as a factor namely knowledge and recovery. Subsequently, the confirmatory factor analysis was employed to confirm the dimensionality of the first order service quality factors. The purification process in the present study was dictated by the desire to develop a more parsimonious as well as reliable 397

13 measure of service quality that would be widely useable to most industries falling under service sector. The result highlights the need not only to operationally the service quality construct, but also to identify to which typology a service belongs, because the latter fact may suggest the service quality factor. So emphasize for training service staffs and for formulating competitive operations strategy. Based on results reported in the present study, consequently, service providers in the commercial banks could interpret these results suggesting that they may downplay the role of reliability, responsiveness, knowledge and recovery; and tangibles. In order to achieve customer satisfaction, Insurance sectors need to understand what customers want and how they assess the service quality. The present study compiled a list of 16 service quality variables (grouped into four factors) that an average customers often use to assess insurance services. Our operationalizable questionnaire items could provide several hints to insurance sector in terms of how to shape customer s experience. Concentrating on the four identified service quality factors, the reliability and responsiveness appear to be slightly more important than the knowledge and recovery; and Tangibles. As far the reliability dimensions are concerned, error free records and timely provision of service need to give customers, special attention. On the other hand, in order to enhance the responsiveness dimension, insurance staffs have to be highly responding the customers call. In terms of knowledge on recovery dimension, knowledge of staffs is the key whereas in the case of tangibles, it is up to date equipment. Insurance managers may improve the tangibles dimension by keeping insurance sectors physical environment up to date and visually appealing. It is worth noting that improving all dimensions of service quality sounds a good and audacious goal, but the main advantage of a distinctive sequential improvement allows insurance managers and staffs more opportunity to learn from possible mistakes in one clinical change before a full-range service quality program is implemented. The findings indicate that while service quality is an important driver of customer loyalty, its indirect effect through perceived value and customer satisfaction is overwhelmingly larger than the direct effect in generating higher customer loyalty. It is important for the insurance managers to understand the relevant service quality dimensions in their sector that could reinforce positive customer satisfaction assessments. Insurance managers need to develop a systematic assessment programs to monitor service quality and customer satisfaction overtime. Insurance staffs should be kept informed of results and be encouraged to take part in figuring out an effective resolution strategy. Only when a service culture is created, can the insurance sectors management ensure the efficient delivery of 398

14 services most desired by customers. The customers loyalty should be generated only through customers satisfaction. So the insurance managers should aim at customer satisfaction, then they ensure customers loyalty through the customer satisfaction but not directly through the service quality of insurance sectors. REFERENCES 1. Anderson, J.C and Gerbeing, D.W (1988), Structural equation Modeling in Practice: A Review and Recommended Two-Step Approach, Psychological Bulletin, 103(3), pp Athanassopoulous, A., Gounaris, S. and Stathakoporelous, V., (2001), Behavioural Responses to Customer Satisfaction: An Empirical Study, European Journal of Marketing, Vol.No.516, pp Babakus, E. and Boller, G.W. (1992), An Empirical Assessment of the SERVQUAL scale, Journal of Business Research, 24 (3), pp Bebko, C.P., (2000), Service intangibility and its impact on consumer expectations of service quality, Journal of Services Marketing, 14(1), pp Brady, M.K., and Robertson, C.J., (2001), Searching for a consensus on the antecedent role of service quality and satisfaction: an exploratory cross national study, Journal of Business Research, 51(1), pp Bridgewater, S., (2001), Virgin direct 2000: Market oriented personal financial services, in Jobber, D., (Ed.,) Principles and Practice of Marketing, 3 rd ed., Mc.Graw Hill, Maidenhead. 7. Brown, T.J., Churchill, G., and Peter, J., (1993), Research note: improving the measurement of service quality, Journal of Retailing, 69(1), pp Carman, J.M., (1990), Consumer Perceptions of Service Quality: an assessment of the SERVQUAL dimensions, Journal of Retailing, 66(1), pp Cronin, J.J., and Taylor, S.A., (1992), Measuring service quality: a re-examination and extension, Journal of Marketing, 56(3), pp Cronin, J.J., Brady, M.K., and Hult, T.M., (2000), Assessing the effects of quality, value, customers satisfaction on consumer behavioural intentions in service environment, Journal of Retailing, 76(2), pp Dalholkar, P.A., (1995), A contingency framework for predicting causality between satisfaction and service quality, in Kardes, F.R., and Sujan, M., (Eds.), Advances in consumer research, vol.22, Association for consumer research, Provo, UT., pp Danaker, P.J. (1997), Using Conjust Analysis to Determine the Relative Importance of Service Attributes measured in Customer Satisfaction Surveys, Journal of Retailing, No.2, pp Edvardsson, B:, Thomasson, B and Ruet-veit, J.(1994) Quality of service, Barrie dale, London. 14. Festus Olorunnivo and Maxwell, K.Hsu, (2006), A typology analysis of service quality, customer satisfaction and behavioural intentions in mass services, Managing Service Quality, 16 (2), pp Fisher, A., (2001), Winning the battle for customers, Journal of Financial Services Marketing, 6(2), pp Fornell, C and Larcker, D.M. (1981), Evaluating Structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18(1), pp Gronroos, C (1990), Service Management and Marketing Lexington Books, Lexington, MA. 18. Gronroos, C., (1988), Service Quality : the six criteria of good perceived service quality, Review of Business, 9(3), pp Gronroos, C., (1990), Service Management and Marketing, Lexington Books, Lexington, M.A. 20. Kish, J., (2000), Before your customers leave, Bank Marketing, 32(2), p Lapierre, J. (1996), Service quality: The construct, its dimensionality, and its measurement, in Swartz, T.A., Bowen, D.E., and Brown, S.W. (Eds.), Advances in Services Marketing and Management, Vol.5, JAI Press Inc., Greenwich, CT, pp Levitt, T. (1981), Marketing Intangible Products and Product Intangibles, Harvard Business Review, 59 (3), pp Levitt, T., (1981), Marketing intangible products and product intangibles, Harvard Business Review, 59(3), pp Lovelock, C.H., (1983), Classifying services to gain strategic marketing in sights, Journal of Marketing, 47(3), pp

15 25. Magi, A. and Julander, C.R., (1996) Perceived service quality and customer satisfaction in a store performance framework, Journal of Retailing and Consumer Services, No.1, pp Maxwell, K. Hsu, Festus Ulorunniwo and Godwin J. Udo (2006), Service quality, Customer satisfaction, and behavioural intentions in the service factory, Journal of Services Marketing, 20 (1), pp Mushtag A., Bhat, (2005), Corrlates of service quality in banks: An Empirical investigation, Journal of Service Research, 5(1), April-September, pp Nozrul Islam and Ezaz Ahamed (2005), A measurement of customers service of banks in Dhata city of Bangaladesh, South Asian Journal of Management, 12(1), pp Nunnally, J. (1978), Psychometric Theory, McGraw-Hill, New York, NY. 30. Oliver, R.L., (1997), A Behavioural Perspective on the Consumer, Mc.Graw, Hill, New York. 31. Olsen, S.O., (2002), Comparative evaluation and the relationship between quality, satisfaction and repurchase loyalty, Journal of the academy of marketing sciences, 30(3), pp Parasuraman, A., Zeithaml, V. and Bery, C. (1985), A Conceptual Model of Service Quality and its Implications for Future Research, Journal of Marketing, Fall (49), pp Parasuraman, A., Zeithaml, V. and Bery, C. (1988), SERVQUAL: A Multiple-item scale for measuring consumer perceptions of Service Quality, Journal of Retailing, Spring (64), pp Peter, J., Churhill, G. and Prown, T., (1993), Contain in the uses of difference scores in consumer research, Journal of Consumer Research, 19(4), pp Rust, R.T., and Oliver, R.L., (1994), Service Quality: insights and managerial Implications from the frontier, in Rust, R.T. and Oliver, R.L., (eds.) Service Quality: New Directions in Theory and Practice, Sage Publications, Thousand Oaks, CA., pp Szymigin, I., and Caruigan, M., (2001), Wherefore customers loyalty?, Journal of Financial Services Marketing, 6(2), pp Takeuchi, H., and Quelch, J.A., (1983), Quality is more than making a good product, Harvard Business Review, July-August, pp Taylor, S.A., and Cronin, J.J., (1994), Modelling patient satisfaction and service quality, Journal of Health Care Marketing, Spring (14), pp Thamaraiselvan, N. and J. Raja (2007), Customers Evaluation of Automated Teller Machines Service Encounters-An Empirical Model, The Journal Contemporary Management Research, 1(1), March, Verma, D.P.S., and Ruchika Vohra, (2000), Customers perception of banking service quality-a study of state bank of India, The Journal of Institute of Public Enterprises, 23(324), pp Westbrook, R.A., and Oliver, R.L., (1991), The dimensionality of consumption emotion patterns and consumer satisfaction, Journal of Consumer Research, 18(1), pp Winstanley, M., (1997), What dries customers satisfaction in commercial banking, Commercial Leading Review, 12(3), pp Yavas, U. and Ysin, M.M. (2001), Enhancing Organisational Performance in Banks: A Systematic Approach, Journal of Services Marketing, No.6, pp Zeithaml, V.A., (1988), Consumer perceptionsof price, quality and value: a means end model and synthesis of evidence, Journal of Marketing, vol.52, July, pp Zeithaml, V.A., Berry, L.L. and Parasuraman, A(1993), The nature and determinants of customer expectation of service, Journal of the academy of marketing science, 21(1), winter, pp: Zeithaml, V.A., Berry, L.L., and Parasuraman, A., (1996), The Behavioural consequences of service quality, Journal of Marketing, 60(2), pp Zillur Rahman, (2005), Service Quality gaps in the Indian Banking Industry, The ICFAI Journal of Marketing Management, February, pp