A MODEL FOR PREDICTING CUSTOMER LOYALTY BASE ON QUALITY SERVICE AND RELATIONSHIP MARKETING USING DATA MINING APPROACH (CACE STUDY: BANKING INDUSTRY)

Transcription

1 ISSN: (Print) ISSN: (Online) A MODEL FOR PREDICTING CUSTOMER LOYALTY BASE ON QUALITY SERVICE AND RELATIONSHIP MARKETING USING DATA MINING APPROACH (CACE STUDY: BANKING INDUSTRY) MAHSHID TOFIGH a1, HOSSEIN SALIMIAN b AND MAHMOOD NASROLLAHI c a Master of Business Management, Islamic Azad University of Malayer, Iran b Supervasor of Business Management, Islamic Azad University of Malayer, Iran c Student of MA In EMBA, Islamic Azad University of Arak, Iran ABSTRACT In today s organizations, having loyal customers is considered to be crucial. In this regard, organizations try to have more customers and maintain their loyalty by enhancing service quality and customer satisfaction level. A loyal customer not only reuses the services of his favorite organization but also plays a significant role in improving the image of the organization in the minds of potential customers. The aim of the present article is to study the effect of service quality, customer satisfaction and relationship marketing on customer loyalty and present a model based on which customer loyalty may be predicted. To this end, a conceptual model was developed and research data were collected using closed questionnaire for 380 customers of five banks and then using variance test and Chi-square test of independence, the significance of the effect of variables on loyalty was tested. Then, using data mining method, a model for predicting customer loyalty was obtained. In this research, the factors which have a significant effect on customer loyalty were determined and the minimum level of each of the components to ensure customer loyalty were provided. In this regard, an innovative method has been used for formulating and explaining the rules based on which loyal customers are predicted. KEYWORDS: Service Quality, Relationship Marketing, Customer ty, Decision Tree Customers are one of the most important factors in maintaining organizations and if organizations manage to win customers loyalty by satisfying them, their longterm growth and development (Asse, 2001). Therefore, marketers search for ways to create customer loyalty. On the other hand, the fact is that customers expectations have increased dramatically and companies should no longer seek to merely meet the basic needs of the customers, but rather they should go beyond those needs and focus mainly on mutual interest and long-term relationships (Gould, 2005). Relationship marketing as a new model in marketing, seeks to discover customers needs and increase their loyalty and decrease company expenses. Using this approach, besides creating a long-term relationship with the customer, we can identify and enhance activities which are considered important and valuable by the customer, and attract more customers and make them loyal to the organization(ndubisi and Wah, 2005). Due to the importance of relationship marketing over the recent years, especially in service industries and manufacturing factories, the concept of loyalty has been taken into consideration. Customer loyalty also depends on the customer s understanding of the quality of the provided products and services. Thus, by enjoying customer loyalty, organizations can improve their position in competitive markets. Services are one of the main pillars of economy and banks as service organizations, are responsible for directing and supporting many of the economic activities in society. In the meantime, what ensures the continuation of the activities of financial institutions is providing services in a suitable and reliable manner that meets customers needs and expectations and leads to their satisfaction and loyalty. Reducing costs, increasing satisfaction level, maintaining customers, increasing profitability and word of mouth advertisement are among the benefits of service quality. In order to achieve these benefits, organizations must become aware of customers expectations and using warning mechanisms, identify problems quickly and show appropriate reactions (Guo et al., 2008). According to experts such as Parasuraman et al. (1988) and Gronroos (1983), the surest way to gain success is to remain in the minds of customers and this is only achieved through quality products and services. Competition for improving service quality is considered a key strategic issue for organizations which operate in the service sector. Organizations that achieve a higher level of service quality will enjoy higher levels of customer satisfaction as a prerequisite for gaining competitive advantage. Thus, all the efforts of the organizations for increasing service quality and gaining competitive advantage is aimed at having more customers and maintaining them or in other words, turning them into loyal customers, because a loyal customer not only refers to his favorite organization anew to use its services but also plays a significant role in improving the image of the organization in the minds of potential customers. Nowadays, taking into consideration the establishment of private banks, intensification of competition and expansion of international communications, attracting and maintaining customers in 1 Corresponding author

2 the banking industry has become ever more difficult. As a result, customer loyalty is a determining factor in the success of the banks. Many banks have realized that constant provision of better services than their competitors can be a powerful competitive advantage (Horowtiz, 2001). A review of the literature of research Studies on relationship marketing suggest the components of trust, commitment, communication and conflict handling, which have been explained in Table 1: Table1: Definition of relationship marketing components Relationship marketing components Trust Commitment Communication Definition Trust is your tendency towards a transaction company which you trust. Trust has been defined as one of the aspects of a business relationship which is the level at which each party feels that he can trust the promises of the other. High level of customer trust in the service provider leads to long term and more constant relationships. Trust has been defined as understanding the good reputation, credibility and support provided by the other party. In fact, the success of a relationship to a large extent depends on the amount of trust between the customer and the service provider. Commitment is the constant tendency to maintain a valuable relationship. Commitment is one of the significant variables for understanding marketing strength, and also a useful tool for measuring the probability of loyalty and predicting customer s future purchases. Higher tendency towards cooperation, meeting the needs of the other party, solving problems mutually and sharing information suggest that business parties are committed to one another. Communication, especially timely communication, means helping to resolve the disputes and aligning the conceptions and expectations in order to enhance mutual trust in a relationship. Regarding the relationship between the customer and the provider, communication means providing information that is trustable. Researchers (Moorman et al., 1992) (Yau et al., 1999) (Moorman et al., 1992) (Vasudevan al., 2006) (Sin et al., 2002) (Ndubisi, 2007) et Conflict handling Conflict handling refers to the ability to minimize the negative and obvious consequences of potential conflicts, of course prior to their leading to any problems. Conflict in relationships is predictable and its consequence is wrong conceptions of the parties about their aims and roles in the relationship. Conflict handling is the ability of the provider to avoid potential conflicts, resolving potential conflicts before they become problematic and finding solutions when problems are raised. (Dwyer et al., 1987) (Aydin et al., 2005)

3 By introduction of the concept of relationship marketing, many definitions have been provided for it. Gronroos (1999) considers relationship marketing as the process of creating, maintaining and developing useful business relationships with customers and other beneficiaries. These relationships must be adjusted in a way that they meet the interests of all the beneficiaries. Kotler et al. (1999) define relationship marketing as creating, maintaining and promoting powerful relationships with customers and other beneficiaries. They believe that marketing is increasingly moving away from individual transactions and toward building relationships with customers and marketing networks. Morgan and Hunt (1994) conclude that relationship marketing is a set of activities that lead to creating, maintaining and developing successful transactions. They emphasize the importance of trust, cooperation and mutual values in successful sustainable relationships. Service quality is also a concept which has been taken into consideration by the researchers. Zeithaml (1996) defines service quality as providing services higher than customer s expectations. Parasuraman et al.(1985) have defined perceived service quality as a global judgment or an attitude related to superiority of a service. They have mentioned that judging service quality is a reflection of the degree and level of difference between consumers conceptions and expectations. In regard to bank services, service quality is defined as the attitude of the customer towards superiority of a service which is provided at the bank. Among various models proposed for measuring service quality such as Bank Service Quality (BSQ) or SYSTRA-SQ, SERVQUAL Service Quality Measurement Method has attracted considerable attention over the recent years. This model provides a technology for measuring service quality and comprehensibility of its aspects for different services has been confirmed (Buttle, 1995). In this research, SERVQUAL model has been used in which five main aspects are studied: 1. Tangibility: appearance of equipment, means of communication and the appearance of personnel at the workplace 2. Reliability: organization s ability to fulfill its promises accurately and continuously 3. Responsiveness: tendency toward helping customers and providing timely and quick services 4. Assurance: personnel s knowledge and courtesy and their ability to establish trust 5. Empathy: organization s care for all its customers (Zeithaml and Parasuraman, 2008) In today s competitive world, services provided by rival companies are more similar to each other than ever before and one can hardly surprise the customer by providing a totally new service in the long term, because the most innovative services are immediately imitated by the competitors and offered to the market. Therefore, investing in customer loyalty area is an effective investment for the service companies. According to Dick and Basu (1994), since customers expectations are continually increasing, organizations have to meet customers expectations and even go beyond fulfilling their needs and focus on creating loyalty through establishing a long-term, mutual and profitable relationship for both sides. Oliver (1999) considers customer loyalty as a strong commitment to purchase a product or superior service again in the future in a way that the same brand or product is bought in spite of the impact of potential marketing efforts by competitors. The relationship between service quality and relationship marketing and customer loyalty has been taken into consideration by the researchers. Lages et al.( 2008) have studied the effect of procedures and policies related to relationship, commitment, mutual cooperation and satisfaction with relationship on loyalty and using factor analysis, obtained the correlation coefficient and realized that there is a positive and significant relationship between the variables under study and loyalty. Hennig et al. (2002) discovered that the benefits of social trust and special behavior as independent variables and satisfaction and commitment as mediators have a significant effect on loyalty and word of mouth communication. The results of a study by Sin et al. (2002) indicated that trust, social relationships, communication, mutual values, empathy and mutual effort have a positive and significant effect on the performance of enterprises, which means sales and market share growth. Also, in a research entitled Relationship Marketing and Customer ty, Ndubisi (2007) studied the effect of the independent variables of trust, commitment, communication and conflict handling on loyalty and concluded that all these variables have a significant effect on loyalty. Bloomer (1999) presented a model of the impact of mind image, service quality and customer satisfaction on loyalty. The results of his research indicated that mind image affects loyalty indirectly through service quality. On the other hand, service quality affects loyalty both directly and indirectly through satisfaction. Yonggui (2003) used SERVQUAL model in order to evaluate bank service quality. Based on the findings of this researcher, the five aspects of SERVQUAL model have a direct effect on bank reputation. Furthermore, bank reputation had an important role in determining purchase and repurchase behaviors as well as customer loyalty.

4 CONCEPTUAL MODEL Taking into consideration what went above, the conceptual model of the research was developed based on Graph (1). This model deals with the relationship between the components of relationship marketing, service quality and customer loyalty. The hypotheses were categorized into the two groups of major and sub hypotheses. Trust Customer satisfaction Service quality Communication Conflict handling Relationship marketing Customer loyalty Customer loyalty Commitment Research questions and hypotheses In this research, two main questions were raised: A) what is the relationship between the components of relationship marketing and service quality and customer loyalty? B) Based on which model can loyal and disloyal customers be predicted? In order to study the relationship between the components of relationship marketing and service quality and customer loyalty and answer question (A), first, the following hypotheses were defined. Main hypotheses: 1: Relationship marketing has a significant effect on customer loyalty. 2: Service quality has a significant effect on customer loyalty. Sub hypotheses: 1: Service quality has a significant effect on customer satisfaction. 2: Customer satisfaction has a significant effect on customer loyalty. 3: Trust has a significant effect on customer loyalty. 4: Communication has a significant effect on customer loyalty. 5: Conflict handling has a significant effect on customer loyalty. 6: Customer commitment has a significant effect on customer loyalty. Figure 1: Conceptual model In order to answer question (B), a model was developed using data mining method and decision tree. Research method Sample and data collection Customers of state bank branches comprise the statistical population of this research. Using the formula for calculating the number of samples in an infinite population, 384 samples were selected. Due to the type of research and also extent of the statistical population and consequently complexity of the statistical sample and in order to access the opinions of the respondents as quickly as possible, questionnaire was chosen as the best data collection method for this research. The questionnaire of this research contained 35 questions adopted from Ndubisi (2007) and Parasuraman et al.(1988) standard questionnaires. Validity and reliability Before being evaluated in the form of a questionnaire, the measured factors were judged by 10 university professors and banking experts and finally the approved questionnaire was used for as data collection tool. Using Cronbach s alpha, reliability of the entire questionnaire was obtained 83.1% which indicates suitable reliability. Data analysis First variance test was used to test the hypotheses and the effects of the components of relationship marketing, service quality and customer satisfaction on customer loyalty were studied. Also, Chisquare test of independence was used to study the relationship between qualitative variables. Then, data

5 mining was used to analyze the statistical research information in which using decision tree and link rules, rules were extracted by which loyal customers may be identified with a high level of correctness. To begin, the data were entered into Clementine 12 software. In the first step, the data were qualitatively evaluated and clearing and preparation stages for developing the model were conducted. Qualitative data analysis examines the three indexes of mismatch, missing values and outlier values. Based on the type of the questionnaire data in this research, it is obvious that outliner values were not among the qualitative indexes of this research. To remove missing values, filler technique was used. To this end, the mean value of the answers to similar questions was chosen as the substitute of the missing values. For the purpose of better analysis, loyalty index score, which was within the range of 1 to 5, was divided into the two categories of loyal and disloyal. Thus, individuals who have scores equal or more than 4 were considered loyal customers and the rest as disloyal customers. Out of 380 respondents, 175 customers or 46.05% were disloyal and 205 or 53.95% were loyal. The results obtained from studying the effect of each of the relationship marketing indexes on customer loyalty using variance test has been presented in Table 2. Table 2: The results of variance test of the effect of relationship marketing c omponents on customer loyalty Components F statistic Significance level Result Trust 39/876 Commitment Communication Conflict handling Relationship marketing 23/415 51/8 12/060 60/556 0/001 The results showed that all the sub relationship marketing indexes along with its total index have a significant effect on customer loyalty at 5% significance level, because their significance level is less than Thus, sub hypotheses 3, 4, 5 and 6 and the main hypothesis 1 were confirmed. In order to study the effect of service quality components on customer loyalty, variance test was used the results of which have been presented in Table 3. Table 3: The results of variance test for the effect of service quality components on customer loyalty Components F statistic Level of significance Result Tangibility Reliability Responsiveness Assurance Empathy 6/889 28/404 13/003 26/357 39/540 The obtained results indicated that all the sub components of quality service along with its total index have a significant effect on customer loyalty at 5% significance level, because their significance level is less than Thus, the main hypothesis 2 was confirmed. 0/009 The effect of satisfaction on customer loyalty was also studied using variance test and the results, as shown in Table 4, indicated that since significance level is less than 0.05, sub hypothesis 2 is also confirmed and customer satisfaction has a significant effect on customer loyalty.

6 Table 4: The results of variance test for the effect of satisfaction on customer loyalty Compoenet F statistic Level of significance Customer satisfaction Result 26/064 In order to test the sub hypothesis 1, based on the responses of 5-point Likert spectrum, according to Table 5, Chi-square test of independence was used. Table 5: Chi-square test of independence of satisfaction and service quality Chi-square satisfaction Degree of freedom Level of significance The results of the above test indicated that since level of significance was less than 0.05, the independence between the two factors of customer satisfaction and service quality was rejected and hypothesis 5 is significant at 5% significance level, therefore, service quality has a significant effect on customer satisfaction. Thus, so far it was shown that all the research hypotheses are significant with certainty level of 95%. In the following using decision tree, we sought to use decision trees to model and evaluate different models of rules that with a high level of certainty determine by emphasis on which components of relationship marketing or aspects of service quality organizations can increase customer loyalty. The aim of modeling in this research is to categorize customers loyalty based on relationship marketing, service quality and satisfaction indexes and some information such as age, gender, profession and education level of the customers and also discovering the latent knowledge and model in the data through studying the relationships and dependencies in the form of if-then. Service quality 40/378 9 Based on the abovementioned points, decision tree technique was selected as the best choice for analysis. Also using link rules and A priori model for extracting rules with a high level of correctness as an option was studied. To evaluate and compare model results, test plan was defined as two sets of educational and test data with the respective proportion of 70 to 30. Thus, the model was constructed based on educational data and through analyzing and comparing the results, decisions were made regarding the set of test data. C5.0, C&RT and CHAID are famous and widely-used algorithms in the area of decision trees. The main difference between the three algorithms is in the method of calculating the deviations and disorders for selecting suitable fields for each layer of the tree. C5.0 model constructs and develops the tree by using entropy index. C&RT model uses Gini coefficient for this purpose and CHAID model uses Chi-square statistic as the scale for choosing the suitable fields. The results of C5.0 model for the two sets of educational and test data have been presented in Table 6. Table 6: The results of C5.0 model

7 As it is seen, degree of correctness of model for educational data is 79.5% and for test data is 65.9%. This indicates over fitting of the constructed model, that is, the model is not capable of categorizing new data. Confusion matrix for educational and test data also shows that the model performs better in identifying loyal customers than disloyal ones. The results of C&RT and CHAID models indicate higher over fitting in comparison with the previous model. Therefore, C5.0 model was selected for further analysis. One of the main reasons of occurrence of over fitting is shortage of educational data. Therefore, in order to solve this problem, cross validation method was used. only prevented over fitting, but also, due to an increase in the number of recorded educational data, led to an increase in model correctness up to 72.1% and the model performed better in identifying loyal and disloyal customers. To obtain suitable rules two conditions were taken into consideration: (1) This law should be supported by a minimum of 10 records and (2) This law should have a minimum certainty of 70%. Regarding the abovementioned conditions, 2 suitable rules were extracted for identifying disloyal customers and 3 suitable rules for identifying loyal customers. The extracted rules for identifying loyal and disloyal customers are presented in Table 7: With regard to limitation of the data, validation was conducted using 380 folds. Using this method not Table 7: The extracted rules for identifying loyal and disloyal customers Number of supporting records Percentage of certainty 100% 73% 83% Then Disloyal customer Disloyal customer customer If 3/667 communication 3 trust 3/667 communication 4/5 trust>3 3/667 empathy Over 20 years of age 3/667 Conflict handling 3/667 communication 4/5 trust> <empathy Individual s job, businessman, doctor, engineer Rules Rule one Rule two Rule three 13 85% customer communication 4/5<trust Rule four % customer <communication over 20 years of age Rule five The decision tree models study the data hierarchically, so a component that has been selected and set aside in the first layer of the tree may be more effective in the next layers. Since link relationships can explore the existing models within the data sets by determining frequent relationships (with high frequency) and all the relationships within the data sets are studied in the search environment of this algorithm, this technique can discover relationships that remain hidden in decision tree models. Therefore, it was sued as complementary technique for this study. Two important indexes of the amount of support and confidence were used to determine selected rules. Minimum support of 10% with 85% confidence led to extracting 14 rules for customer loyalty.

8 Further review of the rules and calculation of their only 3 of the rules have a fairly good condition. support and confidence in the test data set showed that Table 8: Rules obtained from Apriori model Number of supporting records Confidence percentage 85% 86% 86% Then customer customer customer If 5=trust 4=communication man =gender 5=trust 4=Satisfaction man =Gender 4=Empathy 4=Assurance 4 =Satisfaction Rules Rule six Rule seven Rule eight By filtering rule six for the test data, as shown in Table 9, the obtained results showed that 14 supporting records are included in this rule with confidence level of 71 percent. Table 9: filtering rules of Apriori model for the test data Number Percentage Filtering rule seven for the test data showed that 12 supporting records are included in this rule with confidence level of 75 percent. Filtering rule eight for the test data showed that 20 supporting records are included in this rule with confidence level of 70 percent. Value Disloyal Disloyal Disloyal ty rule Rule six Rule seven Rule eight DISCUSSION AND CONCLUSION By studying the research hypotheses, we reached conclusions that by using them factors which have a significant effect on customer loyalty were determined. The conducted studies using variance test and Chi-square test of independence indicated that all the components of relationship marketing including trust, commitment, communication and conflict handling along with its major index and general service quality index and its sub indexes along with customer satisfaction index had a significant effect on customer loyalty and all the research hypotheses were confirmed. The obtained results are comparable to those of similar studies. In his research on Malaysian banks, Ndubisi studied the effect of relationship marketing factors on customer loyalty. The results of his research suggested that the four main relationship marketing components have a significant effect on customer loyalty (Ndubisi, 2007). While studying the effects of customers long-term relationship with the bank and their satisfaction, Molina et al. (2007) concluded that customers trust in the bank has had a significant effect on their satisfaction and eventually, their loyalty. The studies by Bloemer(1999)

9 indicated that service quality affects customer loyalty both directly and indirectly (through satisfaction). Using decision tree and link rules led us to discovering rules for identifying loyal and disloyal customers. On this basis, we came up with two rules for disloyal customers and three rules for loyal customers which were derived based on Table 7 as follows: Based on rule one for disloyal customers, if the mean of answers to the questions related to the component of communication is less than or equal to 3.6 and the mean of the answers to the questions related to the component of trust is less than or equal to 3, then the customer will be disloyal with the confidence level of 100 percent. Rule two states that if the mean of answers to the questions related to the component of communication is less than or equal to 3.6 and the mean of the answers to the questions related to the component of trust is more than 3 and less than or equal to 4.5, and also in the next layer of the tree, the mean of answers to the questions related to the component of empathy is less than or equal to 3.6 and the age of the respondents is over 20 and finally the mean of conflict handling is less than or equal to 3.6, then the customer will be disloyal with the confidence level of 73 percent. Rule three for loyal customers states that if the mean of answers to the questions related to the component of communication is less than or equal to 3.6 and the mean of the answers to the questions related to the component of trust is more than 3 and less than or equal to 4.5, and also in the next layer of the tree, the mean of answers to the questions related to the component of empathy is more than 3.6 and the job of the respondents is businessman, doctor or engineer, then the customer will be loyal with the confidence level of 82 percent. Rule four states that if the mean of answers to the questions related to the component of communication is less than or equal to 3.6 and the mean of the answers to the questions related to the component of trust is more than 4.5, then the customer will be loyal with the confidence level of 84 percent. Rule five states that if the mean of answers to the questions related to the component of communication is more than 3.6 and the age of the respondents is over 20, then the customer will be loyal with the confidence level of 71 percent. When we used link rules as complementary rules in this research, we were able to extract three other rules for loyal customers: Rule six states that if the mean of answers to the questions related to the component of trust for an individual is equal to 3.5 and the mean of the answers to the questions related to the component of communication is equal to 4 and the gender of the individual is male, then he will be a loyal customer with the confidence level of 85 percent. Rule seven states that if the mean of answers to the questions related to the component of trust for an individual is equal to 5 and the mean of the answers to the questions related to the component of satisfaction is equal to 4 and the gender of the individual is male, then he will be a loyal customer with the confidence level of 86 percent. Rule eight states that if the mean of answers to the questions related to the component of assurance for an individual is equal to 4 and the mean of the answers to the questions related to the component of satisfaction is equal to 4, then he will be a loyal customer with the confidence level of 86 percent. RECOMMENDATIONS According to the results of the research and as observed in the text of the rules, the indexes of trust and communication from relationship marketing and the index of empathy from service quality along with age and career were the most important indexes in identifying loyal and disloyal customers because they were the most frequent among the variables. Thus, banks should focus their most attention and investment on factors that attract customers trust. They should educate their personnel to do their tasks carefully and by selection and recruitment of qualified employees who are accountable and responsible, as well as promoting a customer-oriented culture among the personnel and support of the senior management, provide required facilities to fulfill their promises and commitments so that they can stay loyal to their commitments to customers and fulfill their promises in the minimum time possible. Besides, through rapid and timely information, they will be able to communicate effectively with individual customers on their individual and transfer the right information about the available services to customers and keep customers expectations about receiving bank services at a logical level in order to avoid the emergence of a gap between the expected and provided services. And finally, create higher loyalty to the bank by paying special attention to the age and career conditions of individual customers. Since relationship marketing has different models with different variables, including equality, merit, fulfilling promises, good experiences, social ties, customer satisfaction and secret sharing, it is recommended to the future researchers to conduct this research with different variables and study their effect on customer loyalty. Besides, since this research has been

10 done in the field of banking services, other researches can be conducted about other services. REFERENCES Assel H., consumer behavior an dmarketing action, PWS KENT publishing company boston, MA. Aydin S. and Ozer G. and Arasil O., Customer ty and the effect of switching costs as a moderator variable. Marketing Intelligence and Planning., 23 (1): Bloemer J., Linking Perceived Service Quality and Service ty: A Multi-Dimensional Perspective. European Journal of Marketing., 33/11(12): Buttle F., SERVQUAL: review, critique, research agenda. European Journal of Marketing., 30(1): Dick A.S. and Basu K., Customer ty: Toward and integrated conceptual framework. Journal of the Academy of Marketing Science., 22(2): Dwyer F. R. and Schurr P. H. and Oh, S., Developing Buyer-Seller Relationships. Journal of Marketing., 51: Gould G., what is consumer loyalty that count andhow to measure it., l5 (19): 24. Gronroos C., Startegic management and marketing in the service sector. Swedish School of Economics and Business Administration., Helsinki. Gronroos C., Relationship marketing: challenges for organization. Journal of Business Research., 46: Guo X. and Duff A. and Hair M., Service Quality Measurement in the Chinese Corporate Banking Market, International Journal of Bank Marketing., 26(5): Hennig T. and Gwinner K. P. and Gremler D. D., Understanding Relationship Marketing Outcomes, An Integration of Relational Benefitsand Relationship Quality. Journal of Service Research., 4(3): Horovtiz J., Seven Secret of Service Strategies, Prentice-Hall,Harlow, England. Kotler P. and Armstrong G. and Saunders J. and Wong V., Principles of marketing. Prentice-Hall Upper Saddle River., NewJersey: 483 Lages L. F. and Lancastre A. and Lages C., The B2B-RELPERF scale and scorecard: Bringing relationship marketing theory into business-to-business practice. Industrial Marketing Management., 37(6): Molina A. and Martin-Consuegra, D. and Esteban. A., Relational benefits and customer satisfaction in retail banking. International Journal of Bank Marketing,, 25(4): Moorman C. and Zalman G. and Deshpande R., relationship between providesand users of market research: the dynamics of trust within and between organizations. journal of marketing research., 29: Morgan R. M. and Hunt S. D., The commitment_ trust theory of relationship marketing. Journal of Marketing., 58: Ndubisi N. O. and Wah C. K., Factorial and analyses of the underpinning of relationship satisfaction. International journal of marketing., 23(7). Ndubisi N. O., Relationship marketing and customer loyalty. Marketing Intelligence and Planning., 25(1): Oliver R., Whence Customer loyalty?. Journal of Marketing., 63:.34. Parasuraman A. and Zeithaml V. A. and Berry L. L., A Conceptual Model Of Service Quality And The Implication For Further Research. Journal Of Marketing., l49: Parasuraman A. and Zeithaml V. A. and Berry L. L., SERVQUAL: A Multiple Item Scale for Measuring Consumer Perception of Service Quality. Journal of Retailing., 64(1): Sin L. Y. M. and Tse A. C. B. and Yau O. H. M. and Lee J. S. Y. and Chow R., The effect of relationship marketing orientation on business performance in a service-oriented economy. Journal of Service marketing., 16(7): Vasudevan H. and Gaur S. S. and Shinde R. K., Relational switching costs, satisfaction and commitment A study in the Indian manufacturing context. Asia Pacific Journal of Marketing and Logistics., 18(4): Yonggui W., The antecedents of service quality and product quality and their influences on bank reputation: Evidence from the banking industry in china. Managing service quality., 13(1):72-83.