CRM SCALE DEVELOPMENT & VALIDATION
IN INDIAN BANKING SECTOR

Arun Kumar Agariya; Deepali Singh

CRM SCALE DEVELOPMENT & VALIDATION IN INDIAN BANKING SECTOR

Arun Kumar Agariya¹ and Deepali Singh²

Ph.D. Scholar, ABV-Indian Institute of Information Technology & Management, Gwalior (M.P.)-474010, India Postal Address: Room No.103, E-Business Lab, A-Block, ABV-Indian Institute of Information Technology & Management, Morena Link Road, Gwalior (M.P.)-474010, India, E-mail: arunagariya@gmail.com
B.Tech., M.B.A with 2 years of industrial experience. Presently Pursuing Ph.D. in the area of Customer Relationship Management at ABV-IIITM, Gwalior.
Professor, ABV-Indian Institute of Information Technology & Management Postal Address: Room No.101, A-Block, ABV-Indian Institute of Information Technology & Management , Morena Link Road, Gwalior (M.P.)-474010, India, E-mail: dr_deepali@iiitm.ac.in
Dr. Deepali Singh is a Professor of Management at ABV- IIITM, Gwalior. She has been a university top rank in MBA (1994) and completed Ph.D. in the area of Management in 1999. She has been teaching nearly 16 years at PG level (Post PhD 12 years and Pre- PhD 4 years experience). She is Gold-medalist UGC-NET qualified, Accredited Management Teacher and merit holder throughout her academic career. She has been very active in research in the area of Marketing for over 16 years. She has guided many Ph.D. students and PG Students (MBA, M Tech) in new and innovative areas of e- Marketing, e-CRM, Ethical Brand Positioning; IT enabled Distribution Systems, Neuro- Marketing, Customer Centric New Product Development, Customer Perceived value, Services Quality framework for Telecom Services, SRM etc.

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Abstract

The aim of this paper is to develop a reliable and valid CRM (Customer relationship management) scale specifically catering to Indian banking sector. An exhaustive review of literature on CRM was followed by depth interview and questionnaire survey. Exploratory factor analysis was followed by confirmatory factor analysis, which was presented in three forms; the single factor model, covariance model and the structural model. The covariance model shows CRM in Indian banking sector as a multidimensional construct comprising of factors namely organizational structure and customer support, service quality, trust, technology, personalization and market orientation. The structural model validates the previously extracted factors along with their indicators. The findings of this study validate the long held belief that CRM is a multidimensional construct and serves as a critical success factor for business performance. Since this study was conducted in context of Indian banking sector, the generalizability of the CRM scale has to be tested in other countries. A fair amount of literature on Indian banking sector dealt with identifying factors explaining the constructs of quality, value or satisfaction. But there is paucity of research pertaining to industry specific CRM scale development and validation. This study is an attempt to bridge this gap in the existing literature. It provides a conceptually validated CRM scale catering to Indian banking sector, which can help the managers in implementing the CRM in an effective manner and also can be used as a tool to identify the major areas requiring attention.

Keywords

CRM scale, Indian banking sector, exploratory factor analysis, confirmatory factor analysis, structural equation modeling

INTRODUCTION

Reforms initiated in 1991 have changed Indian economy significantly in a span of 20 years and is expected to reach top league in coming years, according to McKinsey research report, 2009. In most emerging economies, the regulatory changes are structured to facilitate a threefold agenda that includes liberalization, privatization and globalization. The banking index has shown a highly impressive compounded annual growth rate of more than 51% since April, 2001. As on 31^st March, 2010 there were 167 commercial banks operating in India out of which 163 are scheduled commercial banks and 4 were non-scheduled commercial banks. Out of 163 scheduled commercial banks 82 are regional rural banks (RBI Report, 2011). Apart from the public sector /nationalized banks there are private and foreign players that are contributing significantly to Indian banking sector. Foreign banks also grow faster at 30 per cent due to a relaxation in regulations. The contribution of banking sector in GDP increases to over 4.7 per cent. In the current Indian banking scenario of intense competition, deregulation and the availability of internet, the customers have a diversified array of banking and financial products and services to choose from. Indian rural banking sector contributes only 3 percent of the market of Indian banks (Kamath, 2007).

Dynamic changes in the competition as well as customer expectations have resulted in a dramatic shift from one time transaction based approach to long-term relationship orientated approach. Increasing demands of the customers as well as the intense competition in the marketplace forced banks to device their strategies accordingly to tap the growing market potential. One example of such strategy that has been adopted by banks in varying degrees is the implementation of a superior market orientation. Market orientation draws its relevance from marketing concept that clearly indicates that to maintain the consistency in the success; firms should do the need assessment of its customers and satisfy them more effectively than their competitors in the marketplace (Day, 2000).

Initially the financial services industry believed less in the marketing philosophy (Howcraft and Durkin, 2003). The past decade has seen substantial and rapid changes in the way the customer relationship is dealt with in financial services (Berger, 2009). Indian banks are realising the importance of implementing customer relationship management (CRM) for acquiring and retaining their customers. This clearly indicates the need for identifying and addressing the major dimensions that plays a crucial role in the effective CRM implementation.

LITERATURE REVIEW

A fairly developed Indian commercial banking system is in existence since the time of independence in 1947. Indian banking sector has traditionally been one of the most stringently regulated sectors in the country. Since the beginning of deregulation of the financial sector in the late 1980s, banks have started operating in the six segments namely retail banking, corporate banking, investment banking, asset management, life insurance and general insurance(Deol, 2009). Indian banking system comprises of commercial and cooperative banks, out of which the commercial banks account for more than 90% of the assets of the banking system. There are two types of categories within the commercial banks. These are schedule commercial banks (which are listed in RBI Act, 1934 under schedule II) and non-scheduled commercial banks. Schedule commercial banks have been further categorized into public sector banks, private sector and foreign banks and rural and local banks. The figure-1 shows the composition of Indian banking system.

The recent studies on Indian banking industry have concentrated only on the efficiency measurement of banks in terms of utilization of resources (i.e. operating efficiency). However, the main aspects of effectiveness of banks in achieving their pre-determined policy objectives is completely ignored (Mukherjee et al., 2002; Kumbhakar and Sarkar, 2003; Sathye, 2003; Ram Mohan and Ray, 2004; Shanmugam and Das, 2004; Sanjeev, 2006; Sensarma, 2006; Debnath and Shankar, 2008). As indicated from the work of prominent authors it can be safely concluded that the overall performance of the organization appraisal should take into consideration both the criteria i.e. resource utilization efficiency and effectiveness in achieving pre-decided goals (Asmild et al., 2007; Mouzas, 2006).

Many of the researchers have already validated the positive associations between performance outcomes and levels of market orientation (Kumar et al., 1998; Narver and Slater, 1990; Jaworski and Kohli, 1993). However some of the researchers have found that performance is related to market orientation only under moderate environmental conditions (Harris, 2000). Customers do complain when they are not satisfied with the products or services of the organisations, which clearly indicates the absolute number, or percentage of the dissatisfied customers.

Like zero defects in manufacturing organisations, if the organisations succeed in reducing the customer complaints to zero, this itself will indicate that customer dissatisfaction is eliminated. However the organisations have to recognise that reduction in customer dissatisfaction not always be considered as same as achieving satisfaction (Brige, 2006). Rowley (2005) urges researchers to focus on managing the value offered to the customer. The institutional characteristics along with the behaviour of the managers are the major factors influencing customer satisfaction, service innovation, market orientation and outreach performance within regional rural banks (Megicks et al., 2005).

As validated by the previous researchers that the main pillar of organisational success is the market-led approach. That has triggered the necessity for investing the nature of market orientation (Siguaw and Diamantopoulos, 1995; Deshpande et al., 1993; Webster, 1992), the barriers and antecedents faced while implementation (Harris, 2000; Avlonitis and Gounaris, 1999; Slater and Narver, 1995; Ennew et al., 1993), its key components (Kumar et al., 1998; Kohli and Jaworski, 1990) and the relationship of performance outcomes with it (Doyle and Wong, 1998; Pelham, 1999; Harris, 2001).

In the service firms, the market orientation is now considered as a failure-prevention factor sometimes called as a hygiene factor (Barnabas and Mekoth, 2010). Similar to the concept of zero defects in the manufacturing industries, some of the researchers have suggested the concept of flawless performance during service encounters for service industries (Berry and Parasuraman, 1991). Some of the research findings from hospitality sector clearly indicate that disposition and behavior of the service provider are crucial in the final determination of consumer’s evaluation of the services delivered as well as the level of satisfaction and sometimes act as a part of the product experience itself (Reisinger, 2000; Collie and Sparks, 1999). For financial services sector especially the banks the above suggestion holds true (Sobti, 2003).

As identified by previous researchers that the employees of the organizations i.e. internal customers have a crucial role in influencing the end customer’s perceptions i.e. external customers about the quality service (Bitner et al., 1990; Berry et al., 1983). This is the main reason because of which the concept of market orientation is getting momentum (Jaworski and Kohli, 1993; Kohli and Jaworski, 1990; Narver and Slater, 1990), as it deals with the implementation of the marketing concept through the generation, dissemination and responsiveness to market intelligence throughout the organization. Moreover, employees of an organization have the tendency to replicate the same behavior to the customers as they receive from the organization (Straughan and Cooper, 2002; Carter and Gray, 2007).

The terms relationship marketing and customer relationship management are almost used interchangeably in many of the previous works of prominent authors. Still there exist differences between the concepts of relationship marketing and customer relationship management as highlighted by Sin et al., 2005. Fournier et al. (1998) have pointed out in their study that without a precise understanding of when and why consumers respond favorably and strongly to the relationship-building efforts of the business organizations, customer relationship management remains elusive. The study done by Kumar and Gulati, 2010 clearly indicates that high efficiency does not stand for high effectiveness in the Indian public sector banking industry.

One of the research study on Indian banking shows that the private and foreign banks are performing relatively better in offering a diversified range of products and services including e-banking facilities as compared to public sector banks. The experience, size, financing pattern and ownership of the bank were found out to be major factors influencing the extent of e-banking services for urban customers (Malhotra and Singh, 2010). Das et al., 2009 has proposed a list of 29 CRM best practices, for helping the business organizations in achieving comprehensive CRM deployment. The findings also indicate that going for CRM deployment may not be a profitable strategy for Indian retail banks.

Recent study done by Riadh et al., 2011, clearly indicates that service quality perceptions vary for the customers of the different geographical and cultural context. In the marketing literature, the concept of CRM has emerged since more than a decade and interest in CRM has been gaining momentum among both academic and business researchers (Rigby and Ledingham 2004; Srivastava et al. 1999).

The focus now is shifted on to how firms implement CRM to enhance profits (e.g., Crosby and Johnson 2001; Kennedy 2004). Various prominent authors (Berry et al., 1983; Gummenson 1990; Gronroos, 1996; Wang et al., 2004; Sin et al., 2005; Ndubisi et al., 2007; Chahal and Kumari, 2010; Lo et al., 2010; Basar et al., 2011; Mamoun et al., 2011) have identified different defining constructs in the area of customer relationship management pertaining to several industrial and national contexts. Interestingly, there is still much debate over what exactly constitutes CRM (Nevin, 1995; Parvatiyar and Sheth, 2001; Sin et al., 2005; Agariya & Singh, 2012a, 2012c).

For developing a comprehensive list of CRM practices, there is an essential requirement for identification of the key constructs of CRM. Thus relationship marketing as an emerging discipline is in need of further theoretical development (Gummesson, 2002). CRM success mainly depends on understanding the needs and desires of the customers which can be achieved by placing these needs at the top-priority and integrating the same with the people, processes, technology and strategy of the business organisations (Heygate, 1999).

In Indian banks CRM is gradually picking up and is definitely considered as a viable proposition in improving services to their customers (Gupta and Shukla, 2002). Although there are a lot of promises on the role of customer relationship management (CRM) in enhancing the performance of business organizations, but the practical guidelines on how to design and implement CRM effectively are few, and academicians as well as business analysts have been struggling because of this (Agariya & Singh, 2011a; Lindgreen and Antiaco, 2005).

Although CRM has now become as a powerful concept to align the interests of a firm and its customers (Boulding et al., 2005), its success depends upon the appropriateness of the firms CRM strategy as well as the effectiveness of CRM implementation. There is very little research which has been done on defining constructs of CRM and development of scale specifically catering to Indian banking sector. Table-1 briefly enumerates the select list of scale development studies carried out.

METHODOLOGY

For this study, we initially developed 50 scale items (Agariya & Singh, 2011b), for identifying CRM constructs from relevant literature review. This was followed by depth interviews with the customers of different banks all across India. A total of 21 customers were interviewed for major issues that exist while availing banking services, this resulted in pruning and fine tuning the items. In the subsequent questionnaire survey a total of 448 responses were received. The exploratory factor analysis is performed with the first half of the data (224) to identify the major CRM dimensions based on which authors have proposed a construct, which is confirmed through confirmatory factor analysis and validated through Structural equation modeling by using the other half(224) of the data.

Depth Interview

Depth interview was conducted of length with 21 high valued customers of different banks all across India. The duration of depth interview varied anywhere between 15 to 20 minutes. A list containing 50 dimensions extracted from the literature review is given to the interviewee along with a brief description of each dimension. Based on the results of the depth interview the questionnaire was modified.

Key results of depth interview

The initial list of 50 dimensions collected from literature review was further reduced to 36 after this phase of depth interview. Findings of depth interview shows, 90% of the respondents were aware of all the banks operating in their region. The main facilities they were availing from there bank are cheque book, ATM card, investment facilities, credit card and e-banking facilities. The major issues identified were related to responsiveness of the bank employees, behaviour and attitude of the bank staff, technological infrastructure, wealth management, security, privacy, one stop banking, service recovery, tailor-made products and services, round the clock availability of banking services, customer support and services and image in the market place.

Questionnaire survey

The modified questionnaire is based on these 36 dimensions followed by a pilot survey of the questionnaire to assess the content validity. Content validity can be evaluated by a panel of persons, sometimes experts, who judge whether a scale logically appears to accurately reflect what it purports to measure (Zikmund, 1991). From the result of the pilot survey 12 dimensions are removed as a result, the revised questionnaire contained 24 dimensions (survey items). The revised questionnaire structure comprises of:

Section-1: Demographic information of the respondents and

Section-2: Items measuring the respondent’s perceptions on specific characteristics of banking services and overall banking services quality.

The respondents were requested to select the response that best indicates their experiences or perceptions on each statement, using a five point Likert-type scale (From 1= strongly disagree to 5= strongly agree).

Key results of questionnaire survey

Responses to the revised questionnaire were received through online as well as offline from the respondents all across India. The respondents of this study were the customers of different banks all across India. A total of 448 responses were received. Furthermore, the reliability analysis, sampling adequacy analysis and exploratory factor analysis was carried out with the first half of the data (Sample size: 224) to identify the major constructs. Subsequently confirmatory factor analysis was carried out with the second half of the data (Sample size: 224) to confirm the factor structure as well as to provide evidence of scale reliability, dimensionality and validity. After this the structural equation modeling was carried out to validate the results. SPSS-15 and AMOS-7 software were used for carrying out statistical analysis mentioned above. The demographic profile of the respondents is given in Table-2.

ANALYSIS OF RESULTS

The reliability of the data is checked by calculating Cronbach-α value that is found 0.936. The calculated value is in the quite acceptable range (> 0.7) (Nunnally, 1978). Further to this, Kaiser Mayer Oklin statistics is calculated for checking the sampling adequacy, the calculated value is 0.914 (>0.5) which is found quite suitable for carrying out exploratory factor analysis. Exploratory factor analysis was carried out and based on the rotated component matrix a total of 6 factors were extracted along with 19 indicators contributing towards 67% of the variance. Based on these factors the authors have proposed the CRM models. The extracted factors along with their indicators are shown in Table-3.

In the first model (Figure-2) CRM is represented as an uni-dimensional construct and all the extracted dimensions from the factor analysis are leading to CRM. This model is verified through confirmatory factor analysis by using the second half of the data (Sample size: 224). This model is discarded because of poor fit based on the calculated absolute measures, incremental fit measures and parsimonious fit measures. The calculated statistics of these measures is shown in Table-4. In the second model (Figure-3) CRM is represented as a multi-dimensional construct explained by the six factors extracted through exploratory factor analysis. This measurement model is verified through confirmatory factor analysis by using the second half of the data (Sample size: 224). This model is accepted because of much improved level of fit as compared to model-1 based on the calculated absolute measures, incremental fit measures and parsimonious fit measures. The comparative calculated statistics of these measures are shown in Table-2. The measurement model indicated an acceptable model fit of the data (χ2 = 305.18, df = 137, p <.05; χ2/df =2.23; GFI=0.881; AGFI= 0.835; CFI = 0.919; TLI = 0.898; PCFI = 0.736 and RMSEA = 0.07) (Anderson and Gerbing, 1988). In addition to this, all the indicators loaded significantly on the corresponding latent constructs. The values of the fit indices indicate a reasonable fit of the measurement model with the sample data (Byrne, 2001).

The Table-5 shown above clearly indicates that the composite reliability of all the constructs is more than 0.6, which is quite acceptable (Carmines and Zeller, 1988). Construct validity is established in this study by establishing the content validity, convergent validity and discriminant validity. Content validity is verified through existing literature and expert’s interaction in the area of CRM. Convergent validity is assessed by examining the average variance extracted and factor loadings (Fornell and Larcker, 1981). All the indicators have shown significant loadings onto their respective latent constructs with values varying in between 0.51 to 0.85. In addition, the average variance extracted (AVE) for each construct is greater than or equal to 0.50, which further supports the convergent validity of the constructs. As suggested by Fornell and Larcker (1981) the discriminant validity can be assessed by comparing the average variance extracted (AVE) with the corresponding inter-construct squared correlation estimates. AVE values for each latent construct were found more than the square of the interconstruct correlations. Thus, the measurement model reflects good construct validity and desirable psychometric properties (Ganguli and Roy, 2011).

In the third model (Figure-4) the structural CRM model is validated by using structural equation modelling. The calculated statistics of absolute measures, incremental fit measures and parsimonious fit measures is shown in Table-5. The structural model indicated an acceptable model fit of the data (χ2 = 348.13, df = 146, p <.05; χ2/df =2.38; GFI=0.866; AGFI= 0.826; CFI = 0.902; TLI = 0.885; PCFI = 0.770 and RMSEA = 0.07) (Anderson and Gerbing, 1988). In addition to this all the indicators loaded significantly on the corresponding latent constructs. The values of the fit indices indicate a reasonable fit of the structural model with the sample data (Byrne, 2001). In short, the structural model confirms the six-factor structure of Customer relationship management.

CONCLUSION

The study verified the long held belief that CRM is a multi dimensional construct. The critical factors that explain CRM in Indian banking sector have been identified as organizational structure and customer support, service quality, trust, technology, personalization and market orientation.

Organizational Structure & Customer Support

This factor includes many dimensions. The dimensions are working conditions of staff i.e. the workload and satisfaction level of the employees; responsiveness (i.e. willingness of bank employees to help the customers and providing prompt service to them); assurance (i.e. the competence and courtesy of employees and their ability to foster confidence and trust in the minds of the customers) and conflict handling (i.e. includes the top management ability to avoid conflicting situation and in case of any unavoidable conflict solve it). Practicing them in the organisation will attract large number of customers in future and propagate a positive word of mouth improving the goodwill of the company. This will also play a big role in retaining the customers of the companies.

Service Quality

This factor is of vital importance in the light of more enlightened and demanding customers than ever before who put lot of emphasis on getting a better quality of service that they avail from a particular bank. They in fact are even prepared to pay a premium for getting a better quality service from their bank; but will not compromise on inferior or poor service quality.

This factor includes dimensions such as promise fulfilment i.e. it is the experience of the customer with the bank that whatever has been promised earlier is always fulfilled, empathy/market orientation i.e. it is the individualised care and attention provided to the customers, commitment i.e. the extent to which a customer perceives the demand to maintain a relationship, service recovery i.e. banking organisation response in case of service failure and all of them play a pivotal role in improving the service quality.

Trust

Customers now-a-days being more enlightened and assertive than ever before, expect consistency in the services that they receive from their bank. Additionally by embarking upon benchmarking and rendering the services that are compared with those of the best in class companies in the world, the banks can maintain its competitive posture and in turn improve its reputation in the eyes of its customers. The dimensions such as reliability i.e.it is the ability of the bank to perform the promised service dependably with accuracy, privacy and security i.e. privacy is the claim of customers to determine for themselves how, when and to what extent information about them is shared or communicated with others whereas security refers to freedom from doubt/risk during the service delivery process, interdependence i.e. indicates if two or more persons e.g. between the customer and the bank, want to achieve their objectives, in such a scenario they have to consider each other and benevolence i.e. it is the belief of the customer that the bank cares about and is motivated to act in one’s interest, may infuse a positive feeling in the mind of its customers because this is what they expect from their bank in today’s fiercely competitive global scenario.

Technology

Banking sector requires sound and effective technological requirements in meeting and/or exceeding the expectations of its customers. Dimensions such as technological infrastructure, knowledge management and dissemination system & information analysis system i.e. data mining tools to analyze the patterns and other important information are some of the parameters which today’s customer expect from their banks. Apart from this, use of various analytical tools like cause and effect analysis for prompt/timely exploration of probable causes of problems and barriers to success, and the customers feeling about latest technology in services being used, also play a lead role in enhancing the customers’ expectations of their bank.

Personalization

This factor comprises of dimensions such as collaboration in product design and customer life time value identification i.e. it is the measure of expected future value of profit to a business derived from customer relationships from the current time to some future point, has a positive impact on the customers’ perceptions about the services which they receive from their bank.

Market Orientation

Banks customers rely heavily upon the reputation of their banking organization while choosing it as their banking service provider. Some of the dimensions upon which the customers usually rely when reputation is the deciding factor are – competitor orientation coupled with brand/market image may tilt the balance in favor of a particular banking organization in the eyes of its customers.

These factors should be duly considered by the Indian banks in order to achieve a high degree of customer satisfaction and business performance which are the primary and compulsive goals for any business organization in the current competitive scenario. Academically this research work bridges the gap in the existing literature by proposing a comprehensive scale for CRM specifically catering to Indian banking sector. Managerially by implementing the proposed model by Indian banks can enhance their customer acquisition, customer retention and overall profitability. This will ultimately have a positive impact on Indian economy as the banking system serves as a backbone.

Novelty of this work lies in the fact that considering the views of customers of different banks all across India and proposing a comprehensive model for better implementation of CRM in banking sector. The proposed CRM scale can serve as a diagnostic tool to identifying the problem areas as well as exploring new business opportunities in a much better way than even before.

LIMITATIONS & FUTURE RESEARCH LINES

The sample sizes itself were relatively small, which is one of the limitations of this study. Large and more diversified samples can be taken for the further enhancement as well as validation of this research work. The applicability, validation and generalizability of the proposed scale can be done by replicating this study in CRM aspects of other business segments at a national level.

Tables at a glance


Table 1	Table 2	Table 3


Table 4	Table 5	Table 6

Figures at a glance


Figure 1	Figure 2	Figure 3	Figure 4

References

Agariya, A.K. and Singh, D. (2011a). CRM In Banking: One Size Doesn’t Fit All. AIMA Journal of Management & Research, 5(2), 1-25.

Agariya, A.K. and Singh, D. (2011b). What Really Defines Relationship Marketing? A Review of Definitions, General and Sector-Specific Defining Constructs. Journal of Relationship Marketing, 10(4), 203-237.

Agariya, A.K. and Singh, D. (2012a). CRM Index Development & Validation in Indian Banking Sector. International Journal of Customer Relationship Marketing and Management, 3(2), 10-32.

Agariya, A.K. and Singh, D. (2012b: In Press). E-learning Quality Scale Development & Validation in Indian Context. International Journal of Customer Relationship Marketing and Management.

Agariya, A.K. and Singh, D. (2012c: In Press). CRM Index Development & Validation in Indian Insurance Sector. Journal of Relationship Marketing.

Anderson, J. C., and Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411ÃÂ¢Ãâ¬Ãâ423.

Arjan Burgers, Ko de Ruyter, Cherie Keen, Sandra Streukens, (2000). Customer expectation dimensions of voice-to-voice service encounters: a scaledevelopment study. International Journal of Service Industry Management, 11(2), 142 - 161

Asmild, M., Paradi, J.C., Reese, D.N. and Tam, F. (2007). Measuring overall efficiency and effectiveness using DEA. European Journal of Operational Research, 178(1), 305-21.

Avlonitis, G. and Gounaris, S. (1999). Marketing orientation and its determinants: an empirical analysis. European Journal of Marketing, 33(11/12), 385-402.

Barnabas Nattuvathuckal and MekothNandakumar (2010). Autonomy, market orientation and performance in Indian retail banking. Asia Pacific Journal of Marketing and Logistics, 22(3), 330-350.

BasarOztaysi, SelimeSezgin and Ahmet Fahri Ozok, (2011). A measurement tool for customer relationship management processes. Industrial Management and Data Systems, 111(6), 943 ÃÂ¢Ãâ¬Ãâ 960.

Berger Sven C. (2009). Self-service technology for sales purposes in branch banking. International Journal of Bank Marketing, 27(7), 488-505.

Berry, L.L. and Parasuraman, A. (1991). Marketing Services, New York: Free Press.

Berry, L.L., Shostack, G.L. and Upah, G.D. (Eds) (1983). Emerging Perceptions on Service Marketing, American Marketing Association, Chicago, IL.

Bitner, M. J., Booms, B. H., and Tetreault, M. S. (1990). The service encounter: Diagnosing favourable and unfavourable incidents. Journal of Marketing, 54, 71-84.

Boulding, William, Richard Staelin, Michael Ehret and Wesley J. Johnston (2005). A Customer Relationship Management Roadmap: What Is Known, Potential Pitfalls, and Where to Go? Journal of Marketing, 69, 155-166.

Brige, A. (2006). Building relationship with customers by using technological solutions in commercial banks of Latvia. Baltic Journal of Management, 1(1), 24-33.

Byrne, B.M. (2001). Structural Equation Modeling with AMOS: Basic Concepts, Applications and Programming, Lawrence Erlbaum Associates, Mahwah, NJ.

Carmines, E.G. and Zeller, R.A. (1988).Reliability and Validity Assessment. Sage, Beverly Hills, CA.

Carter, L. and Gray, D. (2007). Relational competence, internal market orientation and employee performance. The Marketing Review, 7(4), 385-400.

Chahal H. and Kumari N., (2011). Evaluating customer relationship dynamics in healthcare sector through indoor patients' judgement, Management Research Review, 34(6), 626 ÃÂ¢Ãâ¬Ãâ 648.

Chien-Ta Bruce Ho, Wen-Chuan Lin, (2010). Measuring the service quality of internet banking: scale development and validation. European Business Review, 22(1), 5 ÃÂ¢Ãâ¬Ãâ 24.

Clement Sudhahar, J. and M. Selvam, (2007). Service quality scale development in Indian retail banking sector: An empirical investigation. Journal of Applied Science, 7, 766-771.

Collie, T. and Sparks, B.A. (1999). Perceptions of key success factors and key success inhibitors in Australian restaurant and catering business operations. Australian Journal of Hospitality Management, 6(2), 23-33.

Crosby, L.A. and Johnson, S.L. (2001). Technology: Friend or Foe to Customer Relationships. Marketing Management, 10(4), 10-13.

Das, K., ParmarJitesh, and Sadanand V.K. (2009). Customer Relationship Management (CRM) Best Practices and Customer Loyalty A Study of Indian Retail Banking Sector. European Journal of Social Sciences, 11(1), 61-85.

Day, G.S. (2000). Managing market relationships. Journal of the Academy of Marketing Science, 28(1), 24-30

Debnath, R.M. and Shankar, R. (2008). Measuring performance of Indian banks: an application of data envelopment analysis. International Journal of Business Performance Management, 10(1), 57-85.

Deol, H.S. (2009). Strategic environment and intellectual capital of Indian banks. Journal of Intellectual Capital, 10(1), 109-120.

Deshpande, R., Farley, J. and Webster, F. (1993). Corporate culture, customer orientation and innovativeness in Japanese firms: a quadrand analysis. Journal of Marketing, 57, 23-37.

Doyle, P. and Wong, V. (1998). Marketing and competitive performance: an empirical study. European Journal of Marketing, 32 (5/6), 514-35.

Ekiz, E.H., Bavik Ali and Arasli, H. (2009). RENTQUAL: A new measurement scale for car rental services. Tourism: Original Scientific Paper, 57(2), 135-153.

Ennew, C., Filatotchev, I., Wright, M. and Buck, T. (1993). Constraints on the adoption of the marketing concept. European Journal of Marketing, 27, 21-35.

Fornell, C. and Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measure. Journal of Marketing Research, 18, 39-50.

Fournier S., Dobscha S and Mick D.G. (1998). Preventing the premature death of relationship marketing. Harvard Business Review, 76(1), 42-51.

Francis, J. E. (2009). Category-specific RECIPEs for internet retailing quality. Journal of Services Marketing, 23 (7), 450-461.

Ganguli S. and Roy S.K., (2011). Generic technology-based service quality dimensions in banking: Impact on customer satisfaction and loyalty. International Journal of Bank Marketing, 29(2), 168 - 189

Gronroos, C. (1996). Relationship marketing: strategic and tactical implications. Management Decision, 34(3), 5-15.

Gummesson, E. (2002). Total Relationship Marketing, 2nd edition, Butterworth- Heinmann, Oxford.

Gummesson, E. (1990). The Part-time Marketer, Centre for Service Research, Karlstad, Sweden.

Gupta M.P. and Shukla S. (2002). Learnings from Customer Relationship Management (CRM) Implementation in a Bank. Global Business Review,3(1), 99-122.

Harmeen S. and Sandhu H.S.(2008). Does Customer Relationship Management Activity Affect Firm Performance? Global Business Review, 9(2), 189ÃÂ¢Ãâ¬Ãâ206.

Harris, L. (2000). The organisational barriers to developing market orientation. European Journal of Marketing, 34(5/6), 598-624.

Harris, L. (2001). Market orientation and performance: objective and subjective empirical evidence from UK companies. Journal of Management Studies, 38(1), 17-43.

Heygate, R. (1999). CRM 123. CRM Resources, IEEE Computer Society, December.

Howcraft, B. and Durkin, M. (2003). Effective marketing management in financial services context. Journal of Marketing Management, 19, 911-14.

Jaworski, B. and Kohli, A. (1993). Market orientation: antecedents and consequences. Journal of Marketing, 57(July), 53-70.

Jurgen Kai-Uwe Brock, Yu (Josephine) Zhou, (2005). Organisational use of the internet: Scale development and validation. Internet Research, 15(1), 67-87.

Kamath G. Barathi (2007). The intellectual capital performance of Indian banking sector. Journal of Intellectual Capital, 8(1), 96-123.

Kennedy, Michael E. (2004). Using Customer Relationship Management to Increase Profits. Strategic Finance, 85(9), 37-41.

Kohli, A. K. and Jaworski, B. J. (1990). Market Orientation: The Construct, Research Propositions and Managerial Implications. Journal of Marketing, 54(April), 1-18.

Kumar, K., Subramanian, R. and Yauger, C. (1998). Examining the market orientation performance relationship: a context specific study. Journal of Management, 24(2), 201-233.

Kumar, S. And Gulati, R. (2010). Measuring efficiency, effectiveness and performance of Indian public sector banks. Journal of Productivity and Performance Management, 59(1), 51-74.

Kumbhakar, S.C. and Sarkar, S. (2003). Deregulation, ownership, and productivity growth in the banking industry: evidence from India. Journal of Money, Credit and Banking, 35(3), 403-24.

Lindgreen A. and Antioco M. (2005). Customer relationship management: the case of a European bank. Marketing Intelligence and Planning, 23(2), 136-154.

Lo Ada S., Lawrence D. Stalcup and Amy Lee, (2010). Customer relationship management for hotels in Hong Kong. International Journal of Contemporary Hospitality Management, 22(2), 139ÃÂ¢Ãâ¬Ãâ159.

MalhotraPooja and Singh Balwinder (2010). An analysis of Internet banking offerings and its determinants in India. Internet Research, 20(1), 87-106.

Mamoun N. Akroush, Samer E. Dahiyat, Hesham S. Gharaibeh, Bayan N. Abu-Lail (2011). Customer relationship management implementation: An investigation of a scale's generalisability and its relationship with business performance in a developing country context. International Journal of Commerce and Management, 21(2), 158ÃÂ¢Ãâ¬Ãâ190.

Megicks Philip, Mishra Atul and Lean Jonathan (2005). Enhancing microfinance outreach through market-oriented new service development in Indian regional rural banks. International Journal of Bank Marketing, 23(1), 107-125.

Mouzas, S. (2006). Efficiency versus effectiveness in business networks. Journal of Business Research, 59(10/11), 1124-32.

Mukherjee, A., Nath, P. and Pal, M.N. (2002). Performance benchmarking and strategic homogeneity of Indian banks. International Journal of Bank Marketing, 20(3), 122-39.

Narver, John C. and Stanley F. Slater (1990). The Effect of a Market Orientation on Business Profitability. Journal of Marketing, 54(October), 20-35.

Ndubisi Nelson Oly, Chan KokWah and Gibson C. Ndubisi, (2007). Supplier-customer relationship management and customer loyalty: The banking industry perspective. Journal of Enterprise Information Management, 20(2), 222 ÃÂ¢Ãâ¬Ãâ 236.

Nevin, J.R. (1995). Relationship marketing and Distribution Channels: Exploring Fundamental Issues, Journal of the Academy of marketing Science, 23, 327-334.

Nunnally, J. C. (1978). Psychometric theory, 2nd edition, New York, McGraw-Hill.

Parvatiyar, A., and Sheth, J. N. (2001). Customer relationship management: Emerging practice, process, and discipline. Journal of Economic and Social Research, 3(2), 1-34.

Pelham, A. (1999). Influence of environment, strategy, and market orientation on performance in small manufacturing firms. Journal of Business Research, 45, 33-46.

Ram Mohan, T.T. and Ray, S. (2004). Productivity growth and efficiency in Indian banking: a comparison of public, private, and foreign banks. Working Papers, University of Connecticut, Storrs, CT.

Reisinger, Y. (2000). Unique characteristics of tourism, hospitality and leisure services. In Kandampully, J., Mok, C. and Sparks, B. (Eds), Service Quality Management in Hospitality, Tourism and Leisure, Haworth Hospitality Press, New York, NY.

Riadh Ladhari, Ines Ladhari, Miguel Morales (2011). Bank service quality: comparing Canadian and Tunisian customer perceptions. International Journal of Bank Marketing, 29(3), 224ÃÂ¢Ãâ¬Ãâ246.

Rigby, D. and Ledingham, D. (2004). CRM Done Right. Harvard Business Review, 82(11), 118.

Rosalind McMullan, (2005). A multiple-item scale for measuring customer loyalty development. Journal of Services Marketing, 19(7), 470ÃÂ¢Ãâ¬Ãâ481.

Rowley, J. (2005). Building Brand Webs: Customer Relationship Management through the Tesco Clubcard Loyalty Scheme. International Journal of Retail and Distribution Management, 33(3), 194-206.

Sanjeev, G.M. (2006). Does banks’ size matter in India. Journal of Services Research, 6(2), 135-44.

Sathye, M. (2003). Efficiency of banks in a developing economy: the case of India. European Journal of Operational Research, 148(3), 662-71.

Scott R. Colwell, May Aung, VinayKanetkar, Alison L. Holden, (2008). Toward a measure of service convenience: multiple-item scale development and empirical test. Journal of Services Marketing, 22(2), 160 ÃÂ¢Ãâ¬Ãâ 169.

Sensarma, R. (2006). Are foreign banks always the best? Comparison of state-owned, private and foreign banks in India. Economic Modelling, 23(4), 717-35.

Shanmugam, K.R. and Das, A. (2004). Efficiency of Indian commercial banks during thereform period. Applied Financial Economics, 14(9), 681-686.

Sharma D. and Gassenheimer Jule B., (2009). Internet channel and perceived cannibalisation: Scale development and validation in a personal selling context. European Journal of Marketing, 43(7/8), 1076 ÃÂ¢Ãâ¬Ãâ 1091

Siguaw, J. and Diamantopoulos, A. (1995). Measuring market orientation: some evidence on Narver and Slater’s three-component scale. Journal of Strategic Marketing, 3, 77-88.

Sin, L. Y. M., Tse, A. C. B., Yau, O. H. M., Lee, J. S. Y. and Chow, R. (2002). The effect of relationship marketing orientation on business performance in a serviceoriented economy. Journal of Services Marketing, 16(7), 656-76.

Sin, Leo Y.M., Tse, Alan C.B. and Yim Frederick H.K. (2005). CRM: Conceptualisation and scale development. European Journal of Marketing, 39(11/12), 1264-1290.

Slater, S. and Narver, J. (1995). Market orientation and the learning organisation. Journal of Marketing, 59(July), 63-74.

Sobti, R. (2003). Banking and Financial Services in India: Marketing Redefined, New Century Publications, New Delhi.

Srivastava R.K., Shervani T.A. and Fahey L. (1999). Marketing, business processes, and shareholder value: an organisationally embedded view of marketing activities and the discipline of marketing. Journal of Marketing 63(Special Issue), 168-179.

Straughan, R.D. and Cooper, M.J. (2002). Managing internal markets: a conceptual framework adapted from SERVQUAL. The Marketing Review, 2, 253-65.

Sweeney, Jillian C. and Soutar, Geoffrey N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203.

Wang Yong-gui and FengHui(2008). CRM Capability in Service Industries: Conceptualisation and Scale Development. IEEE Explore http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04686367

Wang Y., Hing Po Lo, Chi Renyong and Yang Yongheng, (2004). An integrated framework for customer value and customer-relationship-management performance: a customer-based perspective from China. Managing Service Quality, 14(2/3), 169ÃÂ¢Ãâ¬Ãâ182.

Webster, F. (1992). The changing role of marketing in the organisation. Journal of Marketing, 56(October), 1-17.

Zhilin Yang, Minjoon Jun, Robin T. Peterson, (2004). Measuring customer perceived online service quality: Scale development and managerial implications. International Journal of Operations and Production Management, 24(11), 1149 ÃÂ¢Ãâ¬Ãâ1174.

Zikmund, W.G. (1991). Business Research Methods, 3rd ed., the Dryden Press, Chicago, IL.