TO EVALUATE THE EFFECT OF CUSTOMER RELATIONSHIP MANAGEMENT ON CUSTOMERS COMMITMENT (Case Study: Insurance Companies of Lorestan Province)

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I J A B E R, Vol. 13, No. 6 (2015): 4359-4370 TO EVALUATE THE EFFECT OF CUSTOMER RELATIONSHIP MANAGEMENT ON CUSTOMERS COMMITMENT (Case Study: Insurance Companies of Lorestan Province) Mohammad Jafari 1 Abstract: This study examines the impact of customer relationship management processes on customer satisfaction, customer loyalty, output of customer relationship management, general judgments about customer relationship management and its impact on customer commitment. This research is descriptive, that it has been implemented as a field. Survey are all customers of insurance companies in the province who are unlimited, and 135 clients were selected by stratified random sampling method using the sample, a sample of study. Used equipment for data collection, is a questionnaire. Cronbach s alpha was used to study the reliability of research tools and content and construct validity have been used to check the validity. Factor analysis and path analysis were used to test the hypothesis. The results show that, customer relationship management processes have a significant positive impact on customer satisfaction, customer loyalty, output of customer relationship management, and overall judgment about customer relationship management, as well as customer relationship management processes have a significant and positive impact on customer commitment. Keywords: Customer relationship management, customer loyalty, customer commitment, customer relationship processes INTRODUCTION In the age of post-industrial and global business development managers, faced with unfamiliar and surprising trends and events. In an era when pace of change is accelerating and the presence of transnational corporations has created a new climate change and theories of management with the slogan Think global, act local and it stirred the competitive environment rules traditional main concern of analysts and managers, is to identify the nature of the changes, and the implementation of effective strategies for dealing with the new challenges, challenges, strategies based on past experience, is responsible for them (and Piers Robinson, 1: 2004). 1. Assistant Professor, Department of Economics, University of Lorestan Email: mohjafari@gmail.com

4360 Mohammad Jafari Customer relationship management is a business strategy, which is reinforced by advances in technology, and the company is beneficial relationship, based on the optimization of customers perceptions of value, through it (Alto Pvschmn 2, 1: 2004). the need to maintain and develop a strong and lasting customer relationships, low cost of maintenance of existing customers, to find new customers, and finally, the importance of focusing on key customers, the most effective sources of profitability, driven Firms have to make investment in customer relationship systems, seriously (Ameli and Mobarhan, 5: 2006). The main issue that organizations focused on it is ongoing relations, high-level with customers and clients, and timely respond to their needs and demands. Creating and communicating with customers, has special importance for different companies, especially insurance companies. Responding to customer needs, with the flexibility and adaptability, is one of the key opportunities for these companies in contrast to the older and larger competitors. The organization needs to customers to realize the benefits relationship. For this reason, customer relationship management evaluation tool is important,especially when, it varies from state to state (Lindgreen 3, 70: 2005). The insurance industry is rapidly changing and competitive. In such a situation, understanding of customer needs is essential to the progress and survival. Research conducted on the components of CRM and customer commitment, but the majority of them are theoretical, and fewer have been studied experimentally and comprehensive. Therefore, in view of the importance of this issue, this study examines the impact of customer relationship management processes, the dimensions of customer satisfaction, customer loyalty, customer relationship management outputs, and general judgments about CRM, in the province insurers individually and then discusses the impact of customer relationship management processes and customer commitment. History and Theoretical Foundations Customer relationship management is an approach that introduces consumers, as the core business, and as the success of the company depends on effective management of relationships with them (Ghaffari, 2009). No organization can survive without loyal and satisfied customers. Moreover, due to the fact that customers expectations are constantly increasing, organizations are required to act beyond the satisfaction of basic needs of consumers, and due to loyalty, longterm and profitable bilateral relationship (Aaker, 1991). A general view, every customer is satisfied or dissatisfied after receiving a service or purchase, and use of a product. In fact, this feeling arise due to meet customer expectations and supplier performance. Depending on the expectations of customers and received goods and services are equal to each other, or good,

To Evaluate the Effect of Customer Relationship Management 4361 better or worse than the customer expectations, the feeling of satisfaction or dissatisfaction was built or taste arises (Kermanshahi, 2006). On the other hand, customer loyalty to the brand makes positive word of mouth, creating major barriers to entry, the company s ability to respond to competitive threats, create more sales and revenues, and reduce customer sensitivity competitors marketing efforts. Many customers are loyal to a brand, are considered as corporate assets, and they are known as the main indicator of business value, as well as loyal customers of price changes is less sensitive than non-loyal customers (Drucker, 2007: 45). The researchers are not unanimously, in spite of the difference between commitment and loyalty. Most researchers believe that these structures are linked, but with the difference that commitment, is an incentive for loyalty (Beatty et al., 1988. Pritchard et al., 1999. Hennig-Thurau et al., 2002. Fullerton, 2005). Relationships Between Variables and Development Hypotheses Managers should be aware that, due to product quality may not lead to satisfaction. They should evaluate the different customer experience and judgment. It is possible that two customers they receive the same level of product performance, have a different level of satisfaction (Cartwright, 2009). A study, carried out in 2002 by Richard A. Feinberg, he showed that customer relationship management, has a considerable impact on customer satisfaction and customer loyalty to a particular use of a brand name. A study was carried out in 2007 by Kim, the electronic customer relationship management success; he concluded that the companies that are benefiting from customer relationship management processes, to a large extent lead to increased customer satisfaction. Due to the above, the first hypothesis is presented as follows: The first hypothesis (H1): customer relationship management processes, a significant impact on customer satisfaction. Loyalty, as a preliminary approach, which is sometimes leads to brand associations and brand loyalty, and arises mainly based on overt behavior (Morgan, 2007: 372). Loyalty, has Rating, Exclusive Loyalty is located at the lowest level, is that it means a lack of choice for customers. Sometimes, loyal customers are due to changes in the costs of service or product supplier. The two levels of adherence may still be created, but generally, it was now insufficient levels of loyalty (cm, 2004). A study was carried out by Mohammadi in 2006, the impact on customer loyalty customer relationship management processes of the oil company; he concluded that there is a significant relationship between the processes of customer relationship management and customer loyalty. The second hypothesis (H2): customer relationship management processes, a significant impact on customer loyalty.

4362 Mohammad Jafari In this research, customer relationship management outputs include: increasing the number of customers and increasing customer interest received. Increase customer satisfaction and partners increase profits and revenue, and increase efficiency with robust enterprise-level communicationsis the most important issue in the definition of customer relationship management. In fact, today s customers have high expectations of the companies, and this intensifies the competition. Therefore, to better respond to these expectations is one of the goals of customer relationship management. A study was carried out in 2013 by Hooshmand and partners; they concluded that there is significant correlation between customer relationship management, and increasing the number of customers. Also, studies Anderson & Palma (2005) showed that organizations that have adhered to customer relationship management, lead to expanded customer. The third hypothesis (H3): customer relationship management processes, a significant effect on the output of CRM. Observations have shown that, when the scale is created, it is expected that there is a high correlation between this scale and other scales, since the purpose of this study is, the definition of customer relationship management processes, a overall judgment about customer relationship management will cover the entire process of managing the relationship with the client. The fourth hypothesis (H4): customer relationship management processes, a significant impact on the overall judgment of customer relationship management. The model is based on trust, commitment, firstly, satisfaction, leads to the creation of practical relations between customers and trade names, but it also affects on trust. If brand names, behave properly, there is confidence in personal relationships, and a combination of practical and personal relationships, leads to the emergence of committed relationships. Thus, committed relationships with their customers were shown as subsets of satisfied customers. While satisfied customers may change their buying patterns have rarely, or even lose their dependence on the brand. However, customers are creating deeper relationships. There are two major differences between customer commitment and loyalty of their customers exhibit behaviors. The first difference is the rationale for the behavior of motivation. Customers committed to not only show the loyalty of their behavior, but they are investing in the emotional on the continuation of the relationship. There is a strong relationship between customer and brand. And vice versa, quite satisfied customers may carry out loyalty behaviors, such as repurchase, share purchase, or sole and exclusive Order. Solely for the sake of convenience, the lack of other options, or inertia satisfaction, eliminates, incentives to find other solutions, but it does not act as an obstacle to change their behavior (Ahero, 2008).

To Evaluate the Effect of Customer Relationship Management 4363 In a study conducted in 2002 by Greenberg, about understanding the commitment, and the relationship with the customer relationship management, he showed that there is a significant relationship between CRM and customer commitment. Paulo and (2011), the customer relationship management and customer relationship commitment it showed that there is a significant relationship between CRM and customer commitment. The fifth hypothesis (H5): customer relationship management process has significant influence on customer commitment. Based on the relations between the variables in the hypothesis, conceptual model, introduced in Figure 1: Figure 1: Conceptual model Customer satisfaction Customer loyalty Customer relationship management processes Customer commitment Output for Customer Relationship Management Overall judgments about customer relationship management Figure (1). Conceptual model METHODOLOGY The purpose of this study is applied, and in terms of data collection, is small, and the type of Methodology correlation. The populations of this study are all customers of insurance companies The in purpose the province, of this study they is are applied, unlimited. and in terms Study of sample data collection, was calculated is small, and the type of using the sampling and sample classification, equivalent to 135 people. Due to correlation. The populations of this study are all customers of insurance companies in the the required sample size, 150 questionnaires were distributed randomly among province, they are unlimited. Study sample was calculated using the sampling and sample employees, of which 138 questionnaires were returned, and were analyzed. classification, equivalent to 135 people. Due to the required sample size, 150 questionnaires were distributed randomly among employees, of which 138 questionnaires were returned, and were analyzed. In this study, a questionnaire is to collect data and measure the variables each question is measured using five-point Likert scale. The questionnaire with 28 questions (6 questions for

4364 Mohammad Jafari In this study, a questionnaire is to collect data and measure the variables each question is measured using five-point Likert scale. The questionnaire with 28 questions (6 questions for customer satisfaction, 4 questions for customer commitment, 7 questions for customer loyalty, 4 questions for customer relationship management, 5 questions for management outputs, 2 questions for general judgments about customer relationship management Also, we have used the supervisors, advisors, and experts agreed, to determine the validity of the questionnaire, a questionnaire after certain modifications, finally, the validity was confirmed. Cronbach s alpha coefficient was used to calculate reliability capabilities. Alpha, has proposed to reduce the coefficient of 45%, 75% as moderate and acceptable, and increased 95% coefficient (Cronbach, 1951). As it can be seen from the results in Table 1, all coefficients with a value higher than 0.7, which are indicative of the high reliability of research tools. Table 1 Cronbach s alpha coefficients for the variables Research variables Cronbach s alpha Research variables Cronbach s alpha Customer commitment 0.91 Customer loyalty 0.78 Customer relationship management 0.76 The output of Customer Relationship Management 0.66 Customer satisfaction 0.85 Overall judgment on the Customer Relationship Management 0.71 Total questionnaire: 0.84 Analysis of Results In this study, to assess the data, we have used the most common central and dispersion indices to measure the distribution of the sample, in terms of variables such as gender, education level, and age of the respondents, which was as follows: z Gender respondents: 63% of respondents, of being male and 37 percent are female. z Education level of respondents: 3.9% of respondents under diploma, diploma, 12.6 percent, 28.2 percent had a university degree graduate students, 38.2 percent of undergraduate, graduate and 14.8%, and 2.3% of PhDs respectively.

To Evaluate the Effect of Customer Relationship Management 4365 z The age of the respondents: 14.3% of respondents in the age group below 25 years, 46.4 percent of those in the age group 25 to 35 years, with 27.6% and 11.7% of them aged 36 to 45 years of age have been 45 years. Kolmogorov-Smirnov test was used to assess the normal distribution of data. If you select the null hypothesis that the data are normal, and we use the Kolmogorov-Smirnov test at 95%, the results of this analysis are presented in Table 2. Table 2 Results of Kolmogorov - Smirnov for variables Statistical indicators Variable Customer satisfaction Customer loyalty Output Customer Relationship Management Overall judgment on the Customer Relationship Management Customer relationship management Customer commitment Significance level (Sig) 0.19 0.15 0.12 0.13 0.17 0.21 Kolmogorov-Smirnov statistic (Z) 1.53 1.26 1.47 1.31 1.78 1.45 As you can see, for all the variables, significance testing was higher than 0.05, so the normal distribution assumption is confirmed. The Kolmogorov-Smirnov Z value in the table shows this (smaller +1.96 and larger -1.96). So, with 95% confidence, we conclude that there is no difference between observed and expected frequencies. In other words, distribution is normal. Then, one-sample t-test was used to determine the current state of the respondents in terms of loyalty, commitment and satisfaction among customers as well as customer relationship management, customer relationship process output and overall judgment on the with customer relationship management. The obtained results of this analysis are presented in Table 3 indicate that the value of all variables is lower significance level of 0.05, so the null hypothesis is rejected and we conclude that the test is significant at 95%, and the rate is higher than 3, and it is desirable.

4366 Mohammad Jafari Table 3 One-sample t-test for variables Index Variable mean Std t Sig. Customer satisfaction 3.94 0.68 21.95 0.004 Customer loyalty 3.74 0.66 17.36 0.000 Output Customer Relationship Management 4.07 0.43 31.39 0.000 Overall judgment on the Customer Relationship Management 4.02 0.56 26.86 0.000 Customer relationship management 3.85 0.46 25.29 0.000 Customer commitment 3.96 0.66 21.23 0.000 Test Hypotheses In this study, path analysis was used to test the model and hypotheses. After review and approval of the model, we can test the statistical hypotheses. As Table 5 shows, because the P-value <0.05, so all hypotheses are confirmed, the software output is a figure (2). Figure 2: O Applications Amos 18 Table 4 Conceptual model RMSEA GFI CMIN/DF CMIN DF 0.063 0.950 1.548 78.939 51

To Evaluate the Effect of Customer Relationship Management 4367 In this study, the standard model chi-square (CMIN), an indicator of goodness of fit (GFI) and to estimate the square root mean square error (RMSEA), was used to assess the goodness of fit. It is said that, as CMIN is much smaller, the model developed by the researcher is more satisfying, that the table (4), GFI is greater than 0.9, and RMSE is less than 0.08 (Hooman, 2009, 43-40). In the end, according to the above it can be concluded that the model had a good fit, and it means that, observed variables can measure the hidden variables as well. The results of confirmatory factor analysis, as well as an index component P for the test of the acceptability of the load factor on each question, check out and factor loadings of all the questions were higher than 0.05, and the P component is less than 0.05 So it can be concluded that the observed variables to measure good question. In view of the results of the analysis model, we examine the hypothesis, the results of which are presented in Table (5). Table 5 Path relationships between variables Hypotheses H1: customer relationship management processes customer satisfaction H2: customer relationship management processes customer loyalty H3: processes, Customer Relationship Management CRM outputs H4: customer relationship management processes general judgments CRM H5: process of CRM customer commitment Path coefficient 0.62 0.71 0.35 0.56 0.50 Sig 0.043 0.028 0.020 0.011 0.035 Result Confirmed Confirmed Confirmed Confirmed Confirmed So, at a confidence level of 0.95, we can say that the hypothesis of this study is that the impact of CRM on customer engagement path coefficient of 0.50 is confirmed. Also, all the research hypotheses, including the impact on customer satisfaction, customer relationship management processes, the path coefficient of 0.62, on customer loyalty with the coefficient of 0.71, on the output of customer relationship management with the coefficient of 0.35 and on the overall judgment customer relationship management with the coefficient of 0.56 are confirmed. However, according to the statistical analysis, the conclusion findings and recommendations will be discussed. Discussion and Conclusion After investigations carried out by this study, it was found that many variables play a role in customer satisfaction and loyalty, including insurance service

4368 Mohammad Jafari quality, brand name and brand awareness of insurance companies, insurance agencies obligations, name and address Service Insurance; the change in each of these components, which ones affect customer relationship management, lead to changes in customer commitment. The purpose of CRM, nothing but increase customer satisfaction and partners increase profits and revenue, increase efficiency, using robust enterprise-level. In fact, according to the study, today s customers have high expectations of the companies, and this intensifies the competition. One of the goals of customer relationship managements to respond better to the expectations. The assessed, insurance companies, those firms that have considered customer relationship management processes, have achieved the following successes: Increase revenues, identify new business opportunities, reduce missed opportunities, reduce the loss of customers, build customer loyalty and increase his support improve customer service, reduce costs, increase customer commitment, and also due to positive impact on customer commitment, customer relationship management processes, the study concluded that in the implementation of customer relationship management processes, we should pay attention to improve marketing productivity, and promote mutual value which that we can produce them by increasing marketing effectiveness. Therefore, it is recommended that cases be used: z Beneficial to existing customers to potential customers; z Strengthen the role of innovative services; z Bridge the gap between marketing sales and after-sales service; z Effective communication with the customer, based on data transformed into information; z Distinguish customers through the categories in the market to answer better to their needs; Research Suggestions 1. The implementation of this work in other communities, and to compare the obtained results with each other. 2. Electronic relationships with customers, for customer convenience and save time and energy; 3. The implementation of this large-scale study to evaluate the effects of other variables on the extent of job obligations of the client;

4. With regard to the relationship between customer commitment and customer relationship management process required for staff training to improve customer relationship management carried out; 5. The survey forms and continuous distribution of customers, to evaluate the institution and to address existing deficiencies. 6. The results of the research, increase in customer relationship management skills, be strengthened. Research Limitations To Evaluate the Effect of Customer Relationship Management 4369 Any research from the very beginning, the theme chosen to run the analysis and conclusions has limitations. This study had obstacles and limitations refer to the following: z The lack of similar studies in the country, and even abroad, was the most important limitation of this study was to compare the results with the results of similar studies, it was not possible. z Lack of compliance subjects. z Difficult access to respondents, and their consent to complete questionnaires, was also the limitations of this study. References Aaker, D. (1991). Managing Brand Equity: Capitalizing on the Value of Brand Name, The Free Press, New York, Ny: Free Press. Ahero CRM in Asirpant American www.emeralling sight.com(2008). Alto, P. (2004). Value creation through enriched mar Reting operation linter-ace, Journal of operations management. Anderson, S. P. & de Palma, A. (2005). Price Dispersion and Consumer Reservation Prices, Journal of Economics and Management Strategy, 14(1), 61-91. Beatty, S. E. & Kahle, L. R. & Homer, P. (1988). The involvement commitment model: Theory and implications Journal of Business Research, 16(2), 149 167. Cartwright, Roger. (2009). Customer relationship. Trjmhyly Parsaeian. Tehran. Press Cashmere. First Edition. Cronbach. 1951. Coefficient Alpha and the Internal Structure of Tests, Psychometrical, v. 16 no. 3. Drucker, P. & Cohen, W.(2007). A Class with Drucker: The Lost Lessons of the World s Greatest Management Teacher, p. 242.

4370 Mohammad Jafari Fullerton, G. (2005). The impact of brand commitment on loyalty in retail service Brands Canadian Journal of Administrative Sciences, 22(2), 97 110. Ghaffari Ashtiani, p. (2009). Comorbidity relationship marketing and CRM (www.crm.blogfa. com) Greenberg, P. (2002). CRM at the speed of light: capturing and keeping customer in Internet real time, 2nd edition, McGraw Hill Osbome media. Hennig-Thurau, T., Gwinner, K. P., & Gremler, D. D. (2002). Understanding relationship marketing outcomes: An integration of relational benefits and relational quality Journal of Service Research, 4(3), 230 247. Hooshmand, F. & Jamshidi, B n.& and Maroofi, F. (2013). The Identify factors affecting customer relationship system, Journal of Novel Applied Sciences, 2 (10): 483-488. Kermanshahi, Kurdistan. (2006). Identification of customer satisfaction as the first priority. www.istr.ir Kim, H. S., & Kim, Y. G. (2009). A CRM Performance Measurement Framework: Its Development Process and Application. Industrial Marketing Management, 38, 477-489. lindgrin, Z. (2005). The priority factor model for customer relationship management system. Success, Journal of expect system with application. Marti, J. (2004) Amodel of Customer loyalty in the retail bauling market European Journal marketing, Vol (38), 23-275. Mohammadi, A. (2006). Customer orientation. Tehran. Press expressive cultural institutions. Morgan, F. (2007). Branding implication of partner Firm focal firm relation ship in business to business service networks Journal of business and industrial marketing, Vol (22), 372-382. Paulo, C., & Sergio, M., & Laureano, R. (2011). Using data mining for bank direct marketing: An application of the CRISP-DM methodology. Proceedings of the European Simulation and Modeling Conference, (ESMC 11), Guimarães, Portugal, pp: 117-121. Piers and Robinson. (2004). Strategic management. Translated by Seyyed Mahmoud Hussein. Press. Pritchard, M. P., Havitz, M. E., & Howard, D. R. (1999). Analyzing the commitment loyalty link in service contexts Journal of the Academy of Marketing Science, 27(3), 333 348. Richard A. Feinberg and Rajesh Kadam. (2002). E-CRM Webservice attributes as determinants of customer satisfaction withretail Web sites, International Journal of Service Industry Management, Volume 13. Number 5. 2002. pp. 432-451.