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					International Journal of Management (IJM)
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
ISSN 0976 – 6502(Print), (2011), © IAEME
Volume 2, Number 1, Dec - JanISSN 0976 – 6510(Online)                           IJM
Volume 2, Number 1, Dec - Jan (2011), pp. 41-51
© IAEME, http://www.iaeme.com/ijm.html                                       ©IAEM             E


    CUSTOMER RELATIONSHIP MANAGEMENT IN INDIAN
             RETAIL BANKING INDUSTRY

                                  T.VIJAYAKUMAR
                              Assistant Professor (Sr.Grade)
                              SRM School of Management
                                     SRM University
                                Kattankulathur-603 203

                                     Dr. R. VELU
                         Professor, SRM School of Management
                            SRM University, Kattankulathur

ABSTRACT
The prime objective of the research work is to develop a framework for Customer
Relationship Management Model (CRMM), applicable to Indian retail banks and to
analyze the influence of service quality on customer behavior with respective to retail
banks. The results of the research study reveal that there appears to be lack of
awareness with the bank employees as well as adoption of CRM packages available in
the market. It is suggested that the successful implementation of CRM package can be
achieved only if the bank can create the right environment, culture and attitude of the
employee aiming to serve the customers in the best possible manner.

Keywords: Customer Relationship Management (CRM); Retail Bank; Standard
Processing Time (SPT) and Crafting Complaint Resolution Mechanism (CCRM)

1.0 INTRODUCTION                      TO          CUSTOMER            RELATIONSHIP
MANAGEMENT (CRM)

        The traditional mode of marketing mainly focused on segmenting and
acquiring new customers by using tools and techniques developed for mass
marketing. In the present competitive era, this proves vain. Today there are different
approaches to business such as relationship marketing, customer retention and cross-
selling leading to customer extension, which is a far cry from the traditional
segmentation model.
        The relative and marked emergence of CRM as a business strategy has
radically transformed the way organizations operate. The shift in business focus from
transactional to relationship marketing keeps the customer at the centre of all business
activities. Organizations are trying to restructure their processes to meet the needs of
their strategically significant customers. The critical driver of such a dramatic shift
towards customer orientation is the realization that customers are business assets and
when managed effectively they can derive continuous and sustainable economic value
for an organization over their lifetime.
        The dynamics of the banking ecosystem have changed the business format of
retail banks both in relationship management and in streamlining their operations.


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

Relationship marketing or customer relationship management has been emerging as a
core marketing activity for businesses in the fiercely competitive environment. On an
average, companies spend six times more to acquire new customers than to retain
them. Therefore, many firms are now paying more attention to their relationships with
existing customers to retain them and to increase their share of customer purchases.
        In order to improve the relations with the customers, today’s Retail Banking
comprehensively concentrates on the quality of the products and the services offered
to the customer, as it is the basic foundation for maintaining and developing long-term
relations with the customer. Offering quality products and services is not only
essential to develop long-term customer relations, but is also essential to improve
marketing productivity and long run profits and growth.
        In sum, managing customers today has turned into a well formulated and well
studied science and art known as Customer Relationship Management (or) CRM.

2.0 STATEMENT OF PROBLEM

        The intensity of competition in banking industry is bound to grow in the years
to come which in turn could make banking operations more challenging and complex.
A paradigm shift is noticeable in the banking industry in India. Such a shift reflects in
terms of number of banks, Volume of Business in banking as well as nature of
business operations. Bankers in general have moved a long way from mere financial
intermediaries to full-fledged financial institutions.
        In the context of competing bankers who are performing with almost
undifferentiated services, for almost equal prices; the customers of one bank are left
with multiple options to move over to some other banks in search of better services,
with little or no barrier of switch over from one bank to another.
         Bankers have to necessarily perform their banking operations with the
likelihood risk of the customer making a bank switches over at any given point of
time that might result in decline in revenue or loss of revenue on the whole.
        To prevent or minimize this possibility of customer deflection; bankers have
to come out with customer centric strategic decision. Obviously the conditions draw
the attention in evolving meaningful CRM which would provide a platform for not
only retaining existing customers but also to expand the customer base by attracting
additional customers.
        In a rapidly scaling up retail banking industry, the major issues are to hold
back the existing customers from migrating towards competitors and in acquiring new
customers. In retail banking, product development is limited to the government
regulations henceforth the other major challenge is to have product differentiation.

3.0 STATEMENT OF OBJECTIVES
        •   To develop a framework for Customer Relationship Management Model
            (CRMM), applicable to Indian retail banks.
        •   To analyze the influence of service quality on customer behavior with
            respective to retail banks.
        •   To examine and assess customer satisfaction levels and their influence in
            building the customer loyalty to achieve a sustained market share and
            profit.
        •   To examine and assess the external and internal service quality perceptions
            in respect of retail banks.


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME



4.0 REVIEW OF LITERATURE
        Government of India has appointed several committees and task force groups
on the basis off specific needs with the overall aim of enhancing the efficiency of the
banking systems in the country. Following is the review of selected reports and
Studies. Further, Select research Studies, in the area pertaining to the field of research
has also been reviewed
        Various Committees have been appointed from time to time to study service
quality in banks and to provide concrete recommendations. The Banking Commission
appointed Saraiya Committee in 1972 which provides 77 recommendations, followed
by Talwar Committee (1975) with 176 suggestions and Goipuria Committee (1980)
which studied the causes of below par customer service in banks and suggested 97
recommendations for improvement of work culture in Indian banking. These
recommendations give a clear picture about the need of CRM in banks.
        Barbara R Lewis1 (1991),in a research on service quality, an empirical
research findings presented from an investigation of consumer expectation and
perception of service quality customer of banks, in the UK and US; indicated the
importance of a range of elements of services quality and their perception of service
actually received.
        Number of similarities and difference between the UK and the US respondents
are highlighted together with evidence of success to date of the banks in their delivery
of service quality. In their findings with respect to the increasing customers,
expectations both the UK and the US respondents were found to have very high
expectation of service from their banks across most of the dimensions which were
investigated, in particular with respect to the reliability elements, honesty,
trustworthiness and discretion of contact staff. The UK bank customer gave higher
rating to privacy, interior and staff appearances and using customer suggestions to
improve service and the US respondents were more concerned about location and
parking, opening hours, number of staff available to serve and several of the personal
characteristics of bank staff they came in contact with.
        Median and Arthur2 (1994), in a study investigate the main dimensions and
attributes that Greek cardholders consider of importance. When selecting a card
market, characteristic competitive environment and cardholders profiles in relation to
credit is considered. By investigating a representative quota sample of Greek
cardholders taking into account demographic factors such as age, sex and income on
the relative important of the main attributes that play a role in card selection.
        Freeman and Andrew3 (1996) have examined an electronic banking
experiment by an American bank, First union, at a branch in Asheville, North
Carolina, the use of so-called customer relationship managers and challenges the bank
faces from customer behavior. The findings shows that customer get elated by a new
look. The walls knocked out to create open areas and desks repositioned to seem; less
intimidating. The ATM in the branches, being enhanced to offer such services as



1
   Barbara R Lewis1 (1991),,”Service Quality: An International Comparison of Bank
Customers Expectation and Perception”, Journal of Marketing Management, Vol(27), (July),
p.47
2
   Median and Arthur (1994), ‘Credit and Charge Card Selection Criteria in Greece’,
International Journal of Bank Marketing, 12(2): 36.
3
  Freeman and Andrew (1996),’It’s Consumer Banking’, Economist, 10/26/96, 341(7989): 6.


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

instant cheque-cashing, mini-statement of recent transactions, split deposits and coin
facilities.
         Pacek, Megan4 (2000) highlighted a survey conducted by American
Management Systems showing that the financial services company that got the most
profit from their retail customer did so with integrated cross-departmental strategies.
He also said that the process of CRM should involve identifying your most valuable
customer and making sure to put together special tactics that help them through the
transition. He conclude by saying in a merger one of the key factors of success is the
systematic management of the 20 % who are profitable while not ignoring the other
80 % and ensuring that the key value segments are experiencing minimal disruption.
         Tynan and Thomas5 (2000) reported on the Internet’s influence on bank CRM
in United State. They went into the importance of CRM to banks profits; Customer
comparison of the level and customization of services and the use of customer
services to generate sales. The findings suggest the optimal program for banks as
managing the customer experience; generate customer insight and managing customer
value.
4.1 THE CRM MODEL FOR RETAIL BANK




                        Figure 1: The CRM Model for Retail Bank
5.0 RESEARCH METHODOLOGY
5.1 Area of the Study
       The area preferred for the research is Kancheepuram District.
5.2Population
       The population for the study consisted of the total number of retail banks in
kancheepuram district and their customers. Of the total banks, the following six banks
namely SBI, Indian Bank, ICICI, CUB, Barclays Bank and CITI bank control more

4
  Ptacek and Megan J (2000),’Banks Missing out on Customer Relationship Bounty, Survey
Finds’, American Bankers, 05/04/2000, 165(86): 11.
5
  Tyana and Thomas G (2000),”Web adds Pressure for CRM”, American Banker, 04/20/2000,
165(77): 6.


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

than sixty percent of the deposits and loans6 in kancheepuram District. Therefore the
study was confined to these six banks. The details of the number of branches of these
six retail banks in Kancheepuram District are as follows:
Table 1: Number of branch of the retail banks in Kancheepuram District taken for the
study
                       Name of the Bank                  Number of Branches
                       SBI                               14
                       Indian Bank                       27
                       ICICI Banks                       4
                       City Union Bank                   3
                       Barclays Bank                     1
                       CITI Bank                         1
                       TOTAL                             50
                                          Source: Primary Data – 2010

In determining the sample size the factors that played a major role are time taken by
the respondents to fill up the questionnaires, the number of respondents willing to part
with information, resources required and the working hours of the bank. The
researcher visited the customer’s of various bank branches of six banks on different
days during the month of December 2009 to June 2010 to collect data.
5.3 Data Sources
5.3.1 Primary Data
Primary data was collected by interacting with the bank`s customers
5.3.2 Secondary Data
    Secondary data from the various websites and information from the various
    studies carried out previously in this area, source from RBI offices in Mumbai,
    National Institute of Bank Management office at Pune, RBI websites, books,
    report-published as well as unpublished and journals
5.4 Data Collection Tools
    Based on suggestions given by the bank managers, account holders and
    statisticians two detailed interview schedule were framed; one for the retail bank
    customers and another for bank employees.
    Part I of the interview schedule is designed for collecting the information related
    to the behavior of the respondent and their external service quality.
5.5 The Sample
    The questionnaire drafted for the interview schedule meant for the customers was
    distributed to 451 respondents of the various bank branches taken for the study.
    Nine customers in a branch are considered as a research sample in each bank as
    presented in Table 2
               Table 2: Distribution of Sample Respondents (Bank customers)
             Name of the Bank                         Number of Bank Customers
             SBI                                      126
             Indian Bank                              244
             ICICI                                    36
             City Union Bank                          27
             Barclays Bank                            9
             CITI Bank                                9
             Total Sample size                        451
           Source: Primary Data – 2010
6
    Business Today Survey of India`s Best banks dated December 22,2002,p52


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      International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
      Volume 2, Number 1, Dec - Jan (2011), © IAEME

      6.0 DATA ANALYSIS
      Explanatory factor analysis is used to identify the underlying constructs and
      investigate relationship among the variables. To test the suitability of the data for
      factor analysis, the following steps are taken.
                  • The correlation matrix was computed and examined. It reveals that
                      there are enough correlations to go ahead with factor analysis.
                  • To test the sampling adequacy, Kaiser-Meyer-Olkin measure of
                      sampling adequacy is computed which is found to be 0.804. It indicates
                      that sample is good for sampling.
      The overall significance of correlation matrices is tested with Bartlett test of
      sphericity ((Approximately Chi-square 4442.044 and significant at 0.000) provided as
      well as support for the validity of the factor analysis of the data set.
                                  Table 3 KMO and Bartlett`s test
      KMO and Bartlett`s test
      Kaiser – Meyer – Olkin Measure of Sampling Adequacy               0.804
                                    Approx.Chi-Square                   4442.044
      Bartlett`s Test of Sphericity Df                                  435
                                    Sig.                                0.000
                                       Source: Output from SPSS

The table above shows that the standards indicated makes the data suitable for factor
analysis. Principal component Analysis is employed for extracting factor. Orthogonal
rotation with Varimax was applied. The latent root criterion is used for extraction of
factors. As per it, only the factors having Eigen values greater than one are considered
significant. All the factors with Eigen values less than 1 are considered insignificant and
disregarded.
                                Table 4 Total Variance Explained
          Initial Eigenvalues          Extraction Sums of Squared Loadings Rotation Sums of Squared
                                                                           Loadings
Component Total    % of     Cumulative Total       % of      Cumulative Total        % of        Cumulative
                   Variance %                      Variance %                        Variance %
1         7.136    23.786   23.786     7.136       23.786    23.786        3.382     11.273      11.273
2         2.024    6.747    30.533     2.024       6.747     30.533        2.555     8.516       19.790
3         1.814    6.047    36.580     1.814       6.047     36.580        2.424     8.079       27.868
4         1.568    5.225    41.805     1.568       5.225     41.805        2.235     7.451       35.319
5         1.510    5.035    46.840     1.510       5.035     46.840        2.208     7.359       42.678
6         1.337    4.457    51.297     1.337       4.457     51.297        1.902     6.338       49.016
7         1.179    3.931    55.228     1.179       3.931     55.228        1.863     6.211       55.228
8         1.125    3.749    58.977
9         1.064    3.546    62.523
10        .944     3.145    65.668
11        .858     2.860    68.528
12        .827     2.757    71.286
13        .788     2.626    73.912
14        .736     2.453    76.365
15        .720     2.399    78.764
16        .671     2.235    81.000
17        .614     2.045    83.045
18        .563     1.877    84.922
19        .529     1.764    86.686
20        .510     1.701    88.387
21        .490     1.634    90.020
22        .476     1.587    91.607
23        .420     1.401    93.009


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     International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
     Volume 2, Number 1, Dec - Jan (2011), © IAEME

24       .373    1.243      94.252
25       .347    1.157      95.408
26       .319    1.065      96.473
27       .302    1.008      97.481
28       .276    .918       98.400
29       .261    .869       99.269
30       .219    .731       100.000
     Extraction Method: Principal Component Analysis
     Source: Output from SPSS
     From the table above, it is observed that there were only seven factors having Eigen
     values exceeding 1. The Eigen values after rotation are 3.382, 2.555, 2.424, 2.235,
     2.208, 1.902 and 1.863. The percent of the total variance which is used as an index to
     determine how well the factor analysis accounts for what the variable together
     represent is 55.228 percent.
                              Table 5 Rotated Component Matrix
                                               Component
                      1         2         3          4         5          6         7
         q7-1                                      .484
         q7-2                                      .794
         q7-3                                      .613
         q7-4                                      .539
         q7-5                                                .728
         q7-6                                                .493
         q7-7       .133
         q7-8                                                                     .515
         q7-9                 .422
        q7-10                                                .572
        q7-11                 .453
        q7-12                                                                     .685
        q7-13                                                           .604
        q7-14                                                           .692
        q7-15                                                           .497
        q7-16                 .577
        q7-17                                                                     .576
        q7-18                 .721
        q7-19       .530
        q7-20       .432
        q7-21       .635
        q7-22       .669
        q7-23       .762
        q7-24       .620
        q7-25       .543
        q7-26       .346
        q7-27                           .568
        q7-28                           .544
        q7-29                           .707
        q7-30                           .762
     Extraction Method: Principal Component Analysis. Rotation Method: Varimax with
     Kaiser Normalization. a Rotation converged in 10 iterations.
     Source: Output from SPSS


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

         The above table shows the variables under each of the seven derived factors.
The first factor consists of eight variables, the second factor consists of five variables,
the third factor consists of four variables, the fourth factor consists of four variables,
the fifth variable consists of three variables, the sixth factor consists of three variables
and the seventh factor consists of three variables.
              Table 6 The name given to all the seven factors depending on the
                         variables grouped together in factor analysis
 Factor         Name given to the Factor       Factor Statement               Factor/Loading
                                               Trust worthiness               .530
                                               Personal touch                 .432
                                               Past experience                .635
 I              Bank personal behavior
                                               Attentiveness                  .669
                                               Assurance                      .762
                                               Reliability                    .620
                                               Responsiveness                 .543
                                               Preferential                   .346
                                               Simplicity of operation        .133
                                               Convenient banking hours       .422
 II             Bank feature                   Attractive product             .453
                                               Interest rate                  .577
                                               Credit facilities              .721
                                               Treatment                      .568
 III                                           Advertisement                  .544
                Promotional activities         Courtesy                       .707
                                               Flexible approach              .762
                                               Computerized services          .484
 IV             Operational effectiveness      Computerized services          .484
                                               Speed of operation             .794
                Operational effectiveness
                                               Responsiveness of staff        .613
                                               Flexible working hours         .539
 V              Customer confrontation         Flexible working time          .728
                                               Handling grievances            .493
                                               Convenient location            .572
                                               Demat facilities               .604
 VI             External service quality       Ambience                       .692
                                               Bank image                     .497
                                               Privacy                        .515
 VII            Bank accessibility             ATM facilities                 .685
                                               Number of branches             .576
Source: Computed Table using SPSS

        Factor analysis was employed to retain from a large set of variables a very few
set of factors. Orthogonal rotation with varimax was applied. The latent root criterion
was used for extraction of factors. Only factors with Eigen values greater than one
were considered significant. All the factors with Eigen values less than 1 are
considered insignificant and disregarded
        There were seven factors with Eigen values exceeding one. The Eigen values
after the rotation are 3.382, 2.555, 2.424, 2.235, 2.208, 1.902 and 1.863. The
percent of the total variance which is used as an index to determine how well the


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

factor analysis accounts for what the variable together represent is 55.228 percent.
The first factor consists of eight variables, the second factor consists of five variables,
the third factor consists of four variables, the fourth factor consists of four variables,
the fifth variable consists of three variables, the sixth factor consists of three variables
and the seventh factor consists of three variables. The seven factors are named by the
researcher as bank personal behaviour, bank feature, promotional activities,
operational effectiveness, customer confrontation, and external service quality and
bank accessibility.
7.0 SUGGESTION AND CONCLUSION
7.1 Suggestion
    1. Customer Relationship Manager
               In the course of the research study there is a constant switch over of 90
       percent of the customers over a period of 3 to 5 years. The major factor for
       such switch over is the lack of satisfaction in the service delivery and
       personalized products/services that cater to the needs of the customer. Hence it
       is suggested to have a dedicated relationship manager to measure the
       satisfaction levels of the customer
    2. Identify Customer Expectation
               Identifying expectations of the customers and meeting the expectations
       by suitable products/services is one of the key elements of relationship
       management. It is suggested through the research study that the identification
       of expectation can be identified from the customer’s perceived service quality
       delivery and the satisfaction level of the customers.
    3. Personalized Product/Services
               It is suggested that, bankers may encourage suitable contribution of
       ideas towards innovative product and services from all concerned in the
       process of product/Services design and delivery system. Such an approach is
       suggested to be continuous in character.
    4. Building Delivery Channels
               Hence it is suggested to build more functional delivery channels to
       reduce the complexity in delivering the products/services. Inspite of
       advancements in delivery channels like ATMs, Internet banking and mobile
       banking only few are gaining popularity among the customers. The retail
       banks need to create more awareness and increase the utilization level of the
       delivery channels. This will improve the service quality, reduces cost of
       providing the service, minimizes the delivery time and in building Eco
       friendly delivery system.
    5. Crafting Complaint Resolution Mechanism(CCRM)
               In the research study the varying nature of customer complaints can be
       observed. The customers look for a system to express their complaints and get
       it resolved in time. It is observed from the study that it takes on an average,
       approximately three days to redress the grievance of a complaint which effects
       on the satisfaction level. Therefore it is suggested to craft a complaint
       resolution mechanism to bring a logical end to the issues thereby minimizing
       the customer complaint cycle. This will strengthen the relationship with the
       customer and build a reliability quotient in the operations.
    6. Standard Processing Time(SPT)
               Generally the retail bank customer expects the service to be offered at
       the right time. In this context it is suggested that every service should be
       framed to a standard processing time and need to explicitly specify to the


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online)
Volume 2, Number 1, Dec - Jan (2011), © IAEME

       customers. The employees need to follow the SPT and bring reliability in the
       system.
    7. Improving Customer Interaction
               The interaction with customers is an essential input for effective
       customer relationship. Active interaction at periodic intervals would reveal the
       relationship status. It is therefore suggested that, bankers may come forward
       with appropriate and effective interaction mechanism. In this context, the
       researcher could observe that some banks have already initiated steps such as,
       appointment of relationship managers. Such approaches should further be
       activated aiming at total customer interaction leading to build up better
       relationship.
    8. Customization of CRM Packages
               The results of the research study reveal that there appears to be lack of
       awareness with the bank employees as well as adoption of CRM packages
       available in the market. It is suggested that the successful implementation of
       CRM package can be achieved only if the bank can create the right
       environment, culture and attitude of the employee aiming to serve the
       customers in the best possible manner.
7.2 CONCLUSION
       The study brings to light the various aspects relating to relationship building in
retail Banking Industry. The variables identified are contributing towards relationship
building and dissolution of relationship. It will definitely help bankers to evolve
appropriate strategies towards relationship building. The study also found that there is
a difference in the service quality perception of customers and bankers as regard to
several aspects of relationship management. On this line of the study various
suggestions towards improving Bank customer relationship by enhancing the
delivered service quality and the development of personnel involved in the delivery
system which is coined as External and Internal service quality.
       The relationship models identified in the study would throw further light on
strategic decision pertaining to relationship building. An effective CRM program
designed and executed will obviously provide a win-win platform to both the service
providers and the customers. It is hoped that this study is a humble contribution
towards achieving this goal.
REFERENCE
    1. Adolf, rueidger, Grant-thompson and Stacey (1997),’ what leading banks are learning
       about big database and marketing’. Mckinseyquarterly, 1997 no.3, p 187.
    2. Agarwal H N (1979), A portrait of Nationalized Banks – A Study with Reference to
       their Social Obligations, Inter-India Publications, pp. 25-26,New Delhi.
    3. Berry L L, Parasuram A and Zeithml V A et al. (1998),”The Service-Quality
       Puzzle”, Business Horizons, September-October, pp 35-43.
    4. Berry, L.L. (1995), “Relationship Marketing of Services-Growing Interest, Emerging
       Perspectives”, Journal of the Academy of Marketing Science, Vol. 23, (4), pp.236-245
    5. Carman, J.M. (1990), “Consumer perceptions of service quality: an assessment of the
       SERVQUAL dimensions”, Journal of Retailing, Vol. 66, pp. 35-55.
    6. Chidambaram R M and Alamelu K (1996), “Service Marketing-Challenges and
       strategies”, SBI Monthly Review, p.303.
    7. Christopher, M., Payne, A. and Ballantyne, D. (1991), Relationship Marketing,
       Butterworth- Heinemann, Oxford.
    8. Dammert, A and Lasagabaster, E (2002), “Success and Failures in Bank Privitisation:
       Lessons from Argentina, Brazil, Latvia, Mexico, Mozambique, and Poland”,
       available at http://www.econwpa.wustl.edu



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Volume 2, Number 1, Dec - Jan (2011), © IAEME

    9. Debasish, Sathya Swaroop (2003), “Service quality in Commercial Banks: A
        comparative Analysis of Selected Banks in Delhi”, Indian Journal of Marketing, Vol.
        30, March.
    10. Elias A H (!982), “Indian Banking Service”, Journal of Indian Institute of Bankers,
        Vol. 35, No. 3
    11. Fisk, R.P., Brown, S.W. and Bitner, M.J. (1993), “Tracking the evolution of the
        services marketing literature”, Journal of Retailing, Vol. 69, pp. 61-103.
    12. Ganesan, S. (1994), “Determinants of long-term orientation in buyer-seller
        relationships”, Journal of Marketing, Vol. 58, April, pp. 1-19.
    13. Harker John Michael (1999), “Relationship Marketing Defined” An Examination of
        Current Marketing Definitions”, Market Intelligence and planning. 17/1,pp 13-20.
    14. Indian Bank Association bulletin march 1997,p.125.
    15. Jackson, B. (1985), “Building customer relationships that last”, Harvard Business
        Review, November-December, pp. 120-8
    16. Khazesh K and Decker W H(1992), “How Customer Choose Banks”, Journal of
        Retail Banking,Vol.14.
    17. Lehtinen, U and J R Lethinen (1991), “Two Approaches to Service Quality
        Dimesions”, The Service Industries Journal, Vol. 11,No. 3, pp 287-303.
    18. Madhukar G A,Rajan N and Jahera J S Jr. Et al. (1999),” Service Quality in the
        Banking Industry: An Assessment in a Developing Economy”, International Journal
        of Bank Marketing,Vol 17, pp. 116-123
    19. N.E., Brooks, R.W. and Little, V. (1997), “Towards a Paradigm Shift in Marketing?
        An Examination of Current Marketing Practices”, Journal of Marketing Management,
        Vol. 13, (5), pp.383-406
    20. Oliver et al(1999) Is Relationship Marketing for everyone? European Journal of
        Marketing,Vol- 34,No-9/10,2000,pp 111-27.
    21. Parasuraman A, Zeithaml V A and Berry L et al.(1988),”SERVQUAL:A Multiple-
        Item Scale for Measuring Consumer Perception of Service Quality”, Journal of
        Marketing
    22. R.Adolf,S.Thompson,W.Harrington “What leading banks are learning of big
        databases and marketing”, The Mc Kinsey Quarterly,1997.
    23. Sada, Asish., S.Chitale. Soniya,” Customer Relationship Management & The banking
        Industry” productivity , Vol. 42, No.1, April – June 2001.
    24. Teas, R.K. (1994), “Expectations as a comparison standard in measuring service
        quality: an assessment of a reassessment”, Journal of Marketing, Vol. 58 No. 1, pp.
        132-9.
    25. Varughese A G (2005),” Retail Banking in India: A Paradigm Shift”, Professional
        Banker, ICFAI University Press. April.
    26. Webster, F. (1992), “The Changing Role of Marketing in the Corporation”, Journal of
        Marketing, Vol. 56, October, pp.1-17
    27. Zeithamal and Berry (1988),”Consumer perceptions of price, quality and Value: A
        means – end Model and Synthesis of Evidence” Journal of Marketing, Vol – 52, No –
        3, July, pp 2-22.




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