Surveying the Influence of E.B to CRM in Refah Bank (Case Study: Branch City of Tehran)

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1 International Research Journal of Applied and Basic Sciences 2014 Available online at ISSN X / Vol, 8 (5): Science Explorer Publications Surveying the Influence of E.B to CRM in Refah Bank (Case Study: Branch City of ehran) Dr. Mohmmad Reza Kabaranzad GHadim 1, Zahra SHokati 2 1. Assistant Professor, Department of Management, Islamic Azad University Central ehran. 2. Master of Business Administration - Internal Business, Department of Management, Islamic Azad University Central ehran Corresponding Author kabaranzad@yahoo.com ABSRAC: oday's society expects that the efforts to attract deposits from the banking system and the proper allocation of economic activities beneficial to the overall economic and social development as well as move. In this study we impact of e-banking on customer-oriented First, the concept of technology, information, e-government, e-commerce and the importance of customer satisfaction has been investigated in the context of electronic banking, electronic service channels and the impact that such services can increase customer relation management makes the seen. Finally, the results of a field study found that the use of e-banking and customer relation management, there is a significant positive correlation between the acceptable and the observed variables we find the coefficients of rank order variables are as follows:1- the customer satisfaction 2 - Acquisition 3 - customers Loyalty, 4 - keeping the client, 5 - customer trust. Keywords: Electronic Banking, customer relation management,, customer retention, customer trust, customer satisfaction, customer loyalty. INRODUCION Over the last decade, the Internet has a lot of growing and important role in providing such services and has played a completely new communication channel and parallel to the horizon and firms, several measures have been taken to sync with networks.customer relation management is one of the most important issues is involved in the development of organizations. But why so much importance is given to customers by banks.when it was found out that the activity can be beneficial for banks to do business in other activities, took. Electronic Banking Electronic banking is a special type of banking services to its clients to provide an electronic environment such as the Internet uses. Get whether this kind of banking or banking deposit all money, signature verification; see the Balance and other banking operations are conducted electronically. Customer People who use banking services. Banking services to all people who have access to both traditional and electronic methods. Customer satisfaction Customer satisfaction model consists of four steps: identify the customer, identifying customer needs and expectations, as client assessment, action planning and implementation. Customer rust rust means having confidence in the reliability of a person or system that is based on the results of the other party is believed to be reliable. In recent years, consumer confidence is more important. he customer relationship is now much bigger mutual trust and customer satisfaction increases.

2 Customer Loyalty Marketing and technical experts, technology experts and technology issues associated with customer loyalty concept is defined as "maintaining a deep commitment to purchase or re-select your product or service consistently in the future, despite situational influences and marketing efforts, can potentially lead to changes in customer behavior "that completes the notion of three experts believe that customer satisfaction leads to increased revenue and profit. 1 - Customer repeat purchase 2 - buy new products 3 - Purchase of goods. As we see in able 1 and 2, given recent research in the field of internal and external variables have been studied able 1. Internal Investigation Carried Out Researcher( s) In A Research 1 Javadein and Shams 2008 review of the factors affecting customer intention to use Internet banking services (case study Saman ) 2 Mohammad Mirzaei 2010 Determined the factors affecting the acceptance priority banking customer service part - of banks in Kurdistan 3 Maryam Malmir 2010 from the perspective of factors affecting the adoption of e -banking customers BSI 4 Hossein Seyed 2009 examined factors influencing the adoption of Internet banking at Bank Pasargad zadeh 5 Seyed Reza maghami 2011 estimate Impact customers rust using mobile banking technology acceptance model - A case study of Export Development Bank of Iran 6 Mojtaba forutan kudhi 2010 years of application of factors adoption Internet banking customers banking system - A Case Study of Bank Sepah able 2. External Investigation Carried Out Researcher( s) In A Research 1 Pykaranyn et al 2004 Factors affecting the adoption of e-banking customers in Finland based on Davis 2 Edwin Cheng et al 2006 study on consumer acceptance of Internet banking in Hong Kong based on the technology acceptance model 3 Mustafa Ali and Mark olam 2005 provides a framework for assessing payment security mechanisms and security information on the Web e-commerce site 4 Ravi et al 2006 effective factors on the adoption of Internet banking customers in India 5 Nchna Cyril, John 2008 modeling trust and acceptance of mobile payment users, a conceptual model and colleagues 6 Kim Chngsv 2009 study of perceptions of customer confidence and secure electronic payment system he conceptual model of this study is to investigate the theoretical study of the dimensions and parameters of the model to evaluate the factors affecting customer database, and then examine, review and amend the existing index, the researcher was noteworthy then select the model parameters and some new indicators were also designed. It is explained that the SERVQUAL model were used. Adoption of Electronic Banking Customer relation management Customer acquisition Customer retention Customer satisfaction Customer trust Customer loyalty Figure 1. Conceptual 591

3 MEHODOLOGY Research can be classified according to various criteria framework hese criteria and framework provides conditions that can be classified based on their research However, due to the nature of the types of research that are multi-dimensional and complex, are in several categories and this makes it difficult to judge fair and transparent general, the most useful classification scheme of investigation, the case where categories difference between the minimum and the maximum is reache he present study aimed to investigate the impact on e-banking to CRM in the bank (branch of ehran) among the applied research is concerned by customers his paper describes and interprets it to the impact of e-banking to CRM in the bank (branch of ehran) and makes scrolling through a set of structured data (questionnaire ) will be classified as descriptive - survey placed. Statistical analysis was performed using SPSS software. Hypotheses he main hypotheses Use of the E- Banking to (CRM) is a bank of ehran Province. Secondary hypotheses the use of e -banking customer s bank will affect ehran Province. he use of electronic banking customer s bank will affect ehran Province. he use of electronic banking bank of ehran impact on customer satisfaction. he use of e-banking on consumer confidence can impact bank in ehran. he use of e-banking customer s bank on the loyalty of ehran s influence. Data Analysis he data obtained by the research data collection tools (questionnaires) were analyzed by inferential statistics to answer research questions and the research hypotheses were tested and the results are as follows: It should be noted that the regression data are normalized in this matter is given in able 3 able 3. Results of Kolmogorov - Smirnov Variables Kolmogorov - Smirnov z Number Significance level adoption of Electronic Banking customer relation management customer retention customer satisfaction customer trust customer loyalty Significance level of 5% over the normal show able 4. presents the basic theory of linear regression a In this table, the R Square (0.341) stands lower than average shows a relationship between the use of e- banking and customer focus there. able 5. Hypothesis using e-banking and its impact on customer ANOVA Regression a Residual otal he use of electronic banking and CRM circuit, there is a significant linear relationship with 1 degree of freedom he table also shows that the residual value Residual value ( ) is the model or the values that are higher than average, the use of electronic banking, and customer variables in explaining the upper limit is. 592

4 able 6. Hypothesis using e-banking and its impact on customer (Constant) Customer relation management Because the Sig value is smaller than 0.05 and lower than 2 - and 2 + is higher, based on the independent variables to the dependent variable can be indicated according to the following equation: (Customer Focus * 0.562) = Use of Electronic Banking Hypothesis 1 : he use of e -banking customers bank will affect ehran Province. able 7. Regression sub-hypothesis In this table, the R Square (0.327) stands lower than average shows a relationship between the use of e- banking and consumer there. able 8. hypotheses on the impact of e-banking and consumer ANOVA Regression Residual a otal 439 he use of electronic banking and CRM circuit, there is a significant linear relationship with 1 degree of freedom. he table also shows that the residual value Residual value ( ) is the model or the values that are higher than average, the use of electronic banking, consumer variables in explaining the upper limit is. (Constant) able 9.Hypothesis using e-banking and its impact on consumer Coefficient Because the Sig value is smaller than 0.05 and lower than 2 - and 2 + is higher, the independent variable on the dependent variable can be indicated according to the following equation: Banking, e = (1.083 * Acquisition) Hypothesis 2: he use of e -banking customer s bank will affect ehran Province. able 10. Regression sub-hypothesis a In this table, the R Square (0.638) stands above shows a relationship between moderate use and maintenance of e-banking customers there. able 11. ANOVA assumption of e-banking and its impact on customer retention Regression a Residual otal

5 In this table, the value (Sig) is less than 0.05 then the independent variables as well as dependen t variables ( calculated ) does he use of e-banking and customer care, there is a significant linear relationship with 1 degree of freedom. he table also shows that the residual value Residual value ( ) is the model or the values that are lower than average, the use of electronic banking, customer care at relatively low explanatory variables will. able 12. Hypothesis using e-banking and its impact on customer retention (Constant) Comput customer care Because the Sig value is smaller than 0.05 and lower than 2 - and 2 + is higher, the independent variable on the dependent variable can be indicated according to the following equation : Banking, e = ( * Maintain client ) Hypothesis 3: electronic banking bank of ehran impact on customer satisfaction. able 13. Regression sub-hypothesis In this table, the R Square (0.381) stands lower than average shows a relationship between the use of e- banking and customer satisfaction there. able 14. Hypothesis using e-banking and its impact on customer satisfaction ANOVA Regression a Residual otal he use of electronic banking and CRM circuit, there is a significant linear relationship with 1 degree of freedom. Well as the table shows that the residual value Residual value ( ) and the values or the model shows higher than average, the use of electronic banking, customer satisfaction is above average variable explains. able 15. hypothesis using e-banking and its impact on customer satisfaction (Constant) Because the Sig value is smaller than 0.05 and lower than 2 - and 2 + is higher, based on the independent variables to the dependent variable can be indicated according to the following equation : Banking, e = ( * customer satisfaction ) Hypothesis 4 : he use of e-banking on consumer confidence can impact bank in ehran. able 16. Regression sub-hypothesis a In this table, the R Square (0.135) stands lower than average shows a relationship between the use of e-banking and customer trust there. 594

6 able 17. Hypothesis using e-banking and its impact on customer confidence ANOVA Regression a Residual otal In this table, the value (Sig) is less than 0.05 then the independent variables as well as dependent variables (calculated) does. he use of electronic banking and CRM circuit, there is a significant linear relationship with 1 degree of freedom. he table also shows that the residual value Residual value ( ) is the model or the values that are higher than average, the use of e-banking, the highest level of customer trust variable is explained. able 18. Hypothesis using e-banking and its impact on customer confidence (Constant) Because the Sig value is smaller than 0.05 and lower than 2 - and 2 + is higher, based on the independent variables to the dependent variable can be indicated according to the following equation : Use of Electronic Banking = ( * Customer rust ) H5: he use of e-banking customers bank on the loyalty of ehran 's influence. able 19. Regression sub-hypothesis in this table, the R Square (0.173) stands lower than average shows a relationship between the use of e- banking and customer loyalty there. able 20. Hypothesis using e-banking and its impact on customer loyalty ANOVA Regression a Residual otal in this table, the value (Sig) is less than 0.05 then the independent variables as well as dependen t variables (calculated) does he use of electronic banking and CRM circuit, there is a significant linear relationship with 1 degree of freedom.he table also shows that the residual value Residual value ( ) is the model or the values that are higher than average, the use of e-banking, the variables explain a relatively high level of customer loyalty to. able 21. Hypothesis using e-banking and its impact on customer loyalty (Constant) Compute customer loyalty Because the Sig value is smaller than 0.05 and lower than 2- and 2 + is higher, the independent variable on the dependent variable can be indicated according to the following equation: Use of Electronic Banking = (1.078 * customer loyalty) 595

7 able 22. Regression results (hypotheses) Row Ranking Factor Variable Priority 1 customer satisfaction customer retention customer loyalty customer trust By comparing the rank regression coefficients can be concluded variable customer satisfaction index (1.626), the most effective use of e-banking is the highest priority, in order to attract customers with the coefficient (1.083) and customer loyalty coefficient (1.078) is Client variable storage coefficient (1.030) and customer confidence coefficient (0.914) Last priorities are unaffected by electronic banking. DISCUSSION AND CONCLUSIONS the use of electronic banking and customer-oriented relationship with the direct and positive correlation (0.584) exists Results indicated a significant relationship between the level of confidence of 99 % of e-banking and customer focus there he results of direct and positive relationship between the variable rate of indicates an increase in the use of electronic banking " in research reasonable increase " CRM " comes up he use of electronic banking" and " Acquisition " direct and positive relationship with a correlation coefficient ( ) exists. Results indicated a significant relationship between the level of e-banking and consumer confidence in 99 % there he results of direct correlation between the amount of (0.572) between the variables shows With the increase in " Use of Electronic Banking " increase in " " comes up he " Use of Electronic Banking " and " Customer support " direct and positive relationship with a correlation coefficient (0.799) exists. Results indicated a significant relationship between the 99% confidence level using e-banking and customer retention is he results of direct and positive relationship between the variable rate of shows. By increasing the use of electronic banking relatively high increase in customer care" is created.he Use of Electronic Banking " and " Customer Satisfaction" direct and positive. REFRENCES Ally M, oleman M "A Framework for Assessing Payment Security Mechanisms and Security Information on e-commerce Web Sites", PACIS 2005 Proceedings. Changsu K, Wang, Namchul Sh, Ki-Soo K An empirical study of customers perceptions of security and trust in e-payment systems, Electronic Commerce Research and Applications. Cyril CE, Ademu J, ella S "ling User rust and Mobile Payment Adoption: A Conceptual Framework", Communications of the IBIMA,Vol. 3, pp Forutan kudhi M Factors affecting the banking system by customer s adoption Internet Banking - A Case Study of Bank Sepah Javadein, Shams "Investigation of the factors affecting customer intention to use Internet banking services (Case Study Saman ) Maghami SR Assess the impact of customer trust in mobile banking application based on the echnology Acceptance - A Case Study of Saderat Bank Iran Malmir M Factors influencing the adoption of e-banking customers BSI views Mirzaei M priority banking services on behalf of client services acceptance factors - a case study of banks in Ravi V, Mahil Carr, N. Vidya Sagur: profiling of internet banking users in India using intelligent tech Niques Seyed zade hossein H Factors influencing the adoption of Internet banking at Bank Pasargad.C.Ed winching, David Y.C. Lamc. L. Yeung 2006,: Adoption of Internet An empirical ero Pikkarainenetal.2004.Consumer acceptance of On line banking : an extension of the echnology acceptance model 596