THE ROLE OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM IN
CUSTOMER KNOWLEDGE CREATION
1.
Bahareh Behdadmanesh and
2.Mansur Amini Lari
1.
Department of Management, Fars Science and Research Branch, Islamic Azad University, Fars, Iran
1.
Department of Management, Shiraz Branch, Islamic Azad University, Shiraz, Fars, Iran
2.
Department of Management, Fars Science and Research Branch, Islamic Azad University, Fars, Iran Abstract:
Customer relationship management is a marketing strategy, sales and service of integrated line that operates to identify, acquire and maintain customer. CRM is a modern and developed tool for data mining of customer information that is fed by using different connection points of the system and will create a comprehensive view of the customer. This study examines the relationship between customer relationship management in the creation of customers’ knowledge in the banks of the city of Shiraz. Statistic population of this research includes employees in the banks of Shiraz that the questionnaires on the variables of customer relationship management and customer knowledge were distributed among 300 of them as a statistic sample. The reliability of these two questionnaires for the variables of customer relationship management and customer knowledge were acquired 0.934 and 0.880, respectively. For data analysis and testing the hypotheses SPSS software was used. Correlation coefficient was used to assess the relationship between the variables of the research and finally, the relationship between the parameters was identified by confirming the hypothesis.
Keywords: customer relationship management, customer knowledge, communicative aspect, operative aspect, analytical aspect
1- Introduction:
Customer relationship management is becoming a strategic necessity. In fact, CRM tackles customer satisfaction, sales, web support, customer loyalty and is widely used to support them. (Feinberg et al., 2002).All organizations operating infirm-to-firm and firm-to-client businesses must adapt to the new phenomenon of customer relationship management. Customer knowledge is an important asset, and collection, management and sharing of customer knowledge can be a valuable competitive activity for organizations (Garcia et al., 2002).However, in the wide range of knowledge management, customer knowledge has attracted relatively little attention. Given the above discussion, the role of customer relationship management has turned out to be a necessity in developing customer knowledge. Accordingly, this paper deals with this subject.
2- Review of literature:
Customer Relationship Management
It moves in parallel with an all-round economic and social progress so that it has taken effective steps in fulfilling the expectations and needs of customers and coordinated with community needs. In the banking
system, the main focus is customer satisfaction, and in fact all the activities are based on seeking their attention and ultimately their absorption. Therefore, in the competitive environment between the banks, those are more successful that can attract more customer loyalty. On the other hand, regarding the increasing sensitivity of customers towards the service the banks, so they are always willing to provide better and more desirable services. In fact, CRM is a strategy to gather customers' business behavior and their needs so that this will lead to build stronger relationships with them. Ultimately, a strong relationship with clients is the most important key to the success of any business. Customer relationship management is composed of three main parts: client, relationship and management. By customer, it means the ultimate consumer who has a supporting role in value-originating relations. By relationship, it means creating more loyal and more profitable customers through learning relationships. Management consists of the creation of customer-driven business process and placing the customer at the center of business processes and organization (Elahy, 1387).Customer Relationship Management systems (CRM) are a set of information systems that allow the organizations to communicate with customers and collect, store and analyze customer information in order to provide a comprehensive view of their customers. CRM systems mainly fall into three categories: Operating systems (used to automate processes and increase the efficiency of CRM procedures), analytical systems (used for the analysis of client’s information and knowledge); and collaboration systems (used for management and gathering communicative channels and different points of customer relationships) (Bas, 2003; Gyb, 2006; Hnyng, 2003; Ayryana, 2007; Zhv, 2005).
3- Customer knowledge:
Knowledge management is an indispensable component of customer relationship management (Firoozabadi, 2007).Our present era, the era of knowledge-based organizations. In order to access new sources of knowledge, knowledge management has taken new tours such as society-oriented management into consideration, whose is to achieve a vast source customer's knowledge (Rtnavty N G, 2011).Today, creating and maintaining customer relationship is a new concept not only for selling products and providing services but also for access to their information and knowledge that is discussed in terms of knowledge management systems. Knowledge management helps facilitate the flow of knowledge in the organization and can lead to faster and more effective integration of customer-related knowledge (Rtnavty N G, 2011).Knowledge management also helps transparency in the process of integration of the knowledge of other groups such as employees. When the customer relationship management is implemented, knowledge management program can expand current knowledge about the customer. (Rtnavty N G, 2011).
Today, knowledge is a key competitive factor in the global economy, however, in order to succeed in today's dynamic and changing market, one should also consider another equally important component, namely, the client(Ebrahymy, 1386).Knowledge management is an integral part of customer relationship management (Fyrvzabady, 2007).Organizations can establish effective communication with customers only when they know what services are of importance, and how and when they are valuable to customers and how much they can pay for it (Shahin and Nick Neshan, 2008).Successful customer knowledge depends on the structures, processes and individual skills of the organization (Dal, 1998; Gable, 2008), but it also needs appropriate information systems that support and accelerate knowledge production
processes (Barva, 1995; Gyb, 2006; Piter, 2008). At first glance, Customer Knowledge Management (CKM) may appear to be just another name for a customer relationship management (CRM) or knowledge management (KM); however, customer knowledge managers require a different perspective on some aspects of CRM and KM practices are common. Customer knowledge management is an area of management in which KM practices are applied for customer support knowledge sharing within the organization and between the organization and its customers and where knowledge of the client are used for CRM, to improve processes such as customer service, customer retention and utility connections. CKM is in parallel with innovation and progress. Customer knowledge managers seek opportunities to collaborate with customers under as value-creators of the organization.
This research will examine the role of customer relationship management in developing customer knowledge. This section contains the virtual interactions between customers and between customers and the company. Emotional experiences of a customer are effective on his other components, including a customer satisfaction, commitment, satisfaction with the shopping and other factors.
The main objective of the study is to assess the relationship between customer relationship management and customer knowledge creation.
4- A review of previous studies:
Anaby and Murillo (2002) presented a model that their purpose of the proposed model was taking customer knowledge into account as a part of the company's knowledge. This model consists of three stages including detection, sorting and grading of knowledge (Anaby and Murillo, 2002).
Evaluation of a model for affordable quality management in a customer relationship management environment in real world, (Adair et al., 2010) shows that all parameters of the model can be calculated in this context and all the assumptions related to the model can be strongly held. Evaluation confirms the assumption that the optimal quality (which is expressed in terms of net profit maximization) is not necessarily the highest possible quality.
Sue et al (2006) have emphasized the use of customer knowledge in new product development and utilized data mining tools in the acquisition and application of knowledge. Their emphasis in this model is on acquiring customer knowledge during the use of modern technology and applying it for customer product design. Four stages including "Localization and characteristics of the product", "ranking of customer needs," "market segmentation" and "pattern adapted to customer needs" have been considered in this model (Su, 2006).
Apart from presenting a conceptual model of customer knowledge management, Shami Zanjan and others (2008) have also evaluated its tools in well-known Internet companies in the UK. They discussed the means obtained from ten successful companies. Customer knowledge management includes processes and tools for acquiring, managing and distributing knowledge that provides products and services to customers throughout the organization. Customer knowledge management is defined as a way to create new knowledge obtained by the organizations and share their customers, models and processes (Shami Zanjan, 2008).
Hence, the present study will be conducted with the aim of providing a desired pattern in the relationship between customer relationship management and customer knowledge in the organization. Accordingly, the researcher seeks to answer the following fundamental question: the main question of the research is
whether there is a relationship between customer relationship management and customer knowledge creation?
5- Research methodology:
The present study is based on objective and descriptive data gathering practices, according to a cross-sectional time. This study is an applicable one because its obtained results are used by the studied organizations to solve organizational problems and it is a descriptive one because the research variables will be examined based on the current situation and variables will not be manipulated and finally it is a cross-sectional one since it is studied in a given time period in that field. In this research, customer relationship management and customer knowledge have been specified as independent variable and the dependent variable, respectively. In the light of the above stated issues, the research hypothesis is as follows:
• The main hypothesis: there is a significant correlation between the customer relationship management and customer knowledge creation in the studied organization.
• Sub-Hypothesis 1: there is a significant correlation between customer relationship management and customer knowledge creation in the studied organization.
• Sub-Hypothesis 2: there is a significant correlation between the operational aspect of customer relationship management and customer knowledge creation in the studied organization.
• Sub-Hypothesis 3: there is a significant correlation between the analytical aspect of customer relationship management and customer knowledge creation in the studied organization.
The following model is presented as a proposed model for the study in which the association between variables and dimensions of the paper is presented as follows:
Figure 1: Research model and hypotheses
The statistic population of the research is staff and experts from the banks of Shiraz located in the banks, staff and management of the province. According to the conducted studies the study population included a total of 1350 cases. Sampling is done in a random manner and Morgan table is used is to obtain a sample size. Due to the sample size that is 1350 individuals, 300 questionnaires were distributed and finally 286 questionnaires were collected. The tool for data collection in this survey is the questionnaire. To measure variables in the form of Lynkrt spectrum, the responses to the questions in the questionnaires were organized in terms of the five options for each questionnaire. To ensure the content validity of the questionnaire, the expertise of university professors and experts of the bank was employed. With the acquisition of the mention expertise, the necessary reforms have been done on the questions and thus ensure that the questionnaire measures the characteristics of the study. KMO index was measured using the construct validity and its reliability was approved. Cronbach's alpha was used to assess reliability and to this end, the questionnaire was distributed among 30 employees. Cronbach's alpha coefficient should be more than 0.7 so that its reliability will be verified. Otherwise reform continues until the above ratio is achieved. Cronbach's alpha test results are represented in the table below.
Table 1: Cronbach's alpha of separate questionnaires questionnaire Number of Questions Cronbach's alpha Communicational aspect of CRM 15 871 / 0 Operational aspect of CRM 13 867 / 0 Analytical aspect of CRM 7 867 / 0 Customer Relationship Management 35 934 / 0 Customer knowledge 22 880 / 0 Descriptive statistics:
In this paper we use descriptive statistics in the demographic statistics section and its results are shown in the following table:
Table 2: Results of demographic variables of statistic sample of the study
Gender Male Female %23.4 %76.6 Marital status Married Single %72.4 %27.6 Age 25 to 35 years 35 to 45 years 45 to 55 years Over 55 years %43 %42 %12.6 %2.4 Education Diploma Associate Degree Bachelor of Arts MA PhD %7.7 %20.6 %57.7 %13.6 %0.3 Organizational status Expert Supervisor Director Assistant Senior Manager No Answer %64.7 %10.5 %10.8 %11.5 %2.1 %0.3 Employment history Less than 5 years 5 to 10 years 10 to 15 years More than 15 years No Answer %23.1 %25.9 %28 %20.3 %2.8 Familiarity with Customer Relationship Very high High Average Low Very low %17.8 %50 %25.2 %4.9 %2.1
Management Familiarity with knowledge of customer Very high High Average Low Very low %15.4 %43.7 %30.1 %8 %2.8
Table 3 deals with the descriptive statistics of the variables of the research, as well as aspects of research. The minimum and maximum of respondents are specified in this table. Moreover, the mean, standard deviation and variance have also been expressed.
Table 3 describes the variables and dimensions of the research Number Minimum Maximum Average Standard deviation Variance Communicational aspect 286 1.67 4.93 3.4575 .52752 .278 Operational aspect 286 1.46 4.92 3.2237 .68213 .465 Analytical aspect 286 1.00 4.86 3.9327 .92069 .848 Customer Relationship Management 286 1.48 4.74 3.2047 .60121 .361 Customer knowledge 286 1.86 4.91 3.5495 .60308 .364 Inferential statistics:
The Pearson correlation coefficient for the hypothesis:
• Sub-Hypothesis 1: There is a significant correlation between the customer relationship management and customer knowledge creation in the organization under study.
According to Table 5.3 it can be seen that the significant amount of the Pearson correlation coefficient obtained for the main hypothesis is smaller than five hundredths, (Sig =0.05>0.000). That's why H0 is rejected with 95% assurance and H1 hypothesis is confirmed, so this relationship is significant. Also on the basis of this table, it can be said that the intensity of correlation between two variables is equal to +66.4 which indicates a direct relationship between the two variables.
Given the importance of communicational aspect in customer relationship management system, banks, apart from enjoying a call center through which they can get information, should also receive offers about new services. This organization has an electronic support site that provides online services. Within the organization, there are a number of ports including "voice of the customer" port that improves the communication and sharing customer knowledge.
The studied collaboration systems have accelerated the relationship with the customer relationships as well as the connection within the organization. Collaboration systems that are used as channels of communication with the client (e.g., web site, e-mail and social networks) can expedite externalizing knowledge to customers to help them learn more about their products and services. Accordingly, customers can view their feedback and share with the organization by these systems.
• Sub-Hypothesis 2: There is a significant correlation between the operational aspect of customer relationship management and customer knowledge creation in the organization under study.
According to Table 4 it can be seen that the significant amount of the Pearson correlation coefficient obtained for the main hypothesis is smaller than five hundredths, (Sig =0.05>0.000). That's why H0 is rejected with 95% assurance and H1 hypothesis is confirmed, so this relationship is significant. Also on the basis of this table, it can be said that the intensity of correlation between two variables is equal to +59.7 which indicates a direct relationship between the two variables.
Customer databases and serves are used as the operational CRM systems. This organization should have call center, internal portals, and client database and the service provider points, so that the customers rely primarily on Excel calculations to do the analysis.
This study confirmed that the operational CRM systems such as POS and customer databases can help organizations attract and externalize knowledge about their customers. Operating systems such as call centers, which are widely used in offices, support social relations with customer strongly. By the process of social relationships, the organizations provide information and knowledge for customers (such as product information and offers), gather knowledge about the customer and learn from customers (e.g. customer feedback).
• Sub-Hypothesis 3: There is a significant correlation between the analytical aspect of customer relationship management and customer knowledge creation in the organization under study.
According to Table 5.3 it can be seen that the significant amount of the Pearson correlation coefficient obtained for the main hypothesis is smaller than five hundredths, (Sig =0.05>0.000). That's why H0 is rejected with 95% assurance and H1 hypothesis is confirmed, so this relationship is significant. Also on the basis of this table, it can be said that the intensity of correlation between two variables is equal to +39.0 which indicates a direct relationship between the two variables.
Data resources and data extraction, analysis of customer data in this organization are used in the analytical aspect after registration and bank electronic systems.
Case studies have shown that analytical CRM systems strongly support the combined processes of the organization and provide a lot of knowledge about their customers which allow organizations to better understand the behavior and needs of clients. However, interviewees pointed out that for effective support for combination processes, analytical capabilities of the systems should be in accordance with customer data volume and IT staff skills and expertise. For example, the educational system uses a kind of CRM that has high analytical capabilities. However, these abilities "scare" people because many of the staff lack IT skills and suitable data analysis for them. As a result, most of the time they do not use these abilities and instead, they resort to Excel for analysis of lower degree of customer data.
• Main idea: There is a significant correlation between customer relationship management and customer knowledge creation in the organization under study.
According to Table 5.3 it can be seen that the significant amount of the Pearson correlation coefficient obtained for the main hypothesis is smaller than five hundredths, (Sig =0.05>0.000). That's why H0 is rejected with 95% assurance and H1 hypothesis is confirmed, so this relationship is significant. Also on the basis of this table, it can be said that the intensity of correlation between two variables is equal to +4.75 which indicates a direct relationship between the two variables.
The studied organizations can have an online cooperation system between all branches all of which are connected to the management and all employees are allowed to share their knowledge at once. Customers will also be able to share their knowledge and desires and have this level of access.
Diverse applications of CRM systems have been examined to support the processes of customer knowledge creation in these organizations. Some of these systems, such as call centers, local area networks and customer databases were used in each of the studied organization. But, fewer score was obtained in the analytical dimension compared to that of the other two dimensions. The interviewees were asked to explain their CRM processes in departments and agencies and identify the applications of CRM systems for these processes.
Table 4) the results of the correlation coefficient test of hypotheses Hypotheses Intensity of correlation coefficient Significant level Test results Sub hypothesis 1 0/664 000 / 0 Hypothesis approval Sub hypothesis 2 597 / 0 000 / 0 Hypothesis approval Sub hypothesis 3 390 / 0 000 / 0 Hypothesis approval
The main hypothesis 754 / 0 000 / 0 Hypothesis approval
Summarizing the study findings:
Given the fact that the main issue of this study is to investigate the association between customer relationship management and customer knowledge creation among banks in Shiraz city, the overall results of the primary and secondary hypotheses test confirm the existence of a direct and positive relationship to the studied assumptions. The results of the assumptions are given in Table 1-5. It was also used to measure the correlation of each dimension (communicational dimension, operational dimension and analytical dimension) with independent variable (customer relationship management) on the dependent variable (customer knowledge), the correlation coefficient was used and regression testing was used for evaluation.
Many organizations invest on expensive CRM systems but do not use their capacity fully to acquire customer knowledge. This study has important implications. In this study, we examined the
organizational creation of knowledge in order to systemically provide ideas to investigate the role of various CRM systems to accelerate the processes of knowledge production in the organization. In conclusion, this study suggests the idea of customer knowledge and attracts attention to the three-way relationships between systems, CRM, different forms of customer knowledge and knowledge production processes. As far as the researcher has examined, no previous study in the country has examined in detail these relationships and their importance has not been mentioned.
Generally speaking, the findings of this study confirm a case study. As predicted, analytical CRM systems had the highest level of support for the combined processes and a great ability to produce useful knowledge about their customers. Some operating systems (such as call centers) supported their social relations, and the rest of them (such as databases and POS systems) had a medium support for externalizing. Cooperation systems had the highest capacity to support the processes of knowledge production. Several collaboration tools were used for organizations to support CRM processes. Many of these systems accelerated externalizing and internalizing, provided knowledge to their customers and gave opportunities to organizations so that they learn something from their customers. More research is needed to confirm the results of observations.
In summary, case-studies show that organizations often do not make good use of the capabilities of their CRM systems to gain knowledge of customers. Customers are very valuable sources of knowledge for organizations, "but only a few companies employ their most valuable resources fully: The knowledge is in the hands of customers. The knowledge obtained from customers can combine effectively with knowledge bases of organizations. Customers give creative feedback and suggestion that can improve marketing processes and operations of many organizations.
Limitations of the study are those factors that make barrier in the course of data collection, analysis and obtaining the desired results. Limitations are inherent in any research. This research is not an exception from this rule either and has the following limitations: 1) One of the major limitations of this study was the lack of cooperation of some branches or guardian to complete the questionnaire which required spending time and giving the necessary permits and approval from the security department and the researcher was involved in administrative procedures. 2) In this study, the distribution of the different branches in the city necessitated travelling to different parts of the city to collect the questionnaires. 3) Some of the questions had a negative meaning, so some of the respondents were evading from answering these questions so that the researcher, with relation to the management and agency officials, tried to resolve the ambiguities in order to convince them to respond. 4) In many cases, the data regarding the existence of enough opportunities, conditions, mental health, and safety of the respondents were not available to researchers at the time of distributing the questionnaires and this, due to the fact that the questionnaires sought to determine the mental, emotional and spiritual state of the people in the organization, was possible to reduce the reliability of the accuracy of the response. 5) Finally, one of the most important limitations that is regarded as the specific features of social science research is the impact of the variables that are outside the control of the researcher and its influence on the results is not far-fetched, in a way that there no possibility of examining or controlling on the researcher's part. 6) Limitation of Persian articles and books on the customer knowledge management. 7) Long-term response to a question by clients. 8) Some of the interviewees in the organizations stated that the operating systems are primarily used to collect customer information and data sorting and lacked the ability to produce a
high level of customer knowledge. 9) This system is mainly used as an operational tool used to manage contact list and track customer activity. Many analytical and cooperative capabilities of the system have not been applied. 10) Given the fact that the selected experts and technical staff to respond to analytical and operational dimensions were in the management building located in the center of Provinces or Tehran, so it was difficult to access them and coordination with them was time-consuming. So in order to resolve this issue, the researcher mailed the necessary permits and questionnaires to them and their answers were returned through the mail. This issue also took a great deal of time. 12) With respect to the fact that information is of significant importance for all enterprises financial institutions in the competition, so commencing the activities of the researcher faced with a number of problems that this problem was resolved by presenting the necessary documents and letters to authorities.
One of the most basic functions of research is to create new insights to achieve optimal performance, and this issue turns true in research proposals. The following suggestions have come to the researcher's mind during and after the final conclusions: 1) the courses of introduction and necessity of customer relationship management systems need to be presented for personnel. 2) Sites related to staff should have online forums for employees in order to share customers' knowledge and their demands among clients. 3) Creating forums (group chat) in specialized areas and report on the sites and discussion management and providing information were entrusted to informed people in the organization to reduce one-sided relationship in order to take step into a two-way relationship between customer and bank officials. 4) With the increasing pervasiveness of social networks and smart phones and tablets, organizations can use these tools to inform and contact points. 5) Collaborative CRM systems are used to accelerate the cooperation within the organization. These systems help the staff externalize knowledge about their customers, collectively decide and find solutions to business problems (such as an electronic suggestion box). In addition, some collaborative systems provide work opportunities for learning (knowledge resources, online courses, etc.) and thus accelerate internalizing knowledge for each employee. 6) This study suggests that there should be a culture of support for the production of knowledge in organizations. 7) Proper training is required to ensure that the appropriate IT staff has required skills and expertise to make effective use of their system capabilities. 8) A proper evaluation and rewarding structure can motivate employees to participate in activities to increase customer knowledge. 9) These practitioners can benefit from this study: (1) the directors of IT / developers who are involved in the management and development of CRM systems need to know the weaknesses of these systems and support potential users of the system so that they can employ the system capabilities properly; (2) Management marketing / CRM and the analysts who rely on customer knowledge to make a decision and determine marketing strategies; And (3) users of CRM systems who need to know the capabilities of this system and receive appropriate training for making optimal use of these features. There are many challenges ahead that have negative impacts on knowledge production support provided by CRM systems which were identified in this study, and suggestions for dealing with these challenges were briefly discussed. This study helps managers understand the possible benefits and challenges of knowledge production cycle and assists them in using their existing CRM systems to support the production of knowledge to assess.
Finally, this research has the following suggestions for future researchers to continue research: 1) Studying the effect of client relationship management on the agility of doing organizational studies. 2) Studying the impact of organizational intelligence on the success of customer relationship management.
3) Investigating the impact of knowledge management on customer relationship management. 4) Examining the effect of data mining in customer relationship management. 5) Examining the impact of information technology to improve customer relationship management. 6) Exploring the main factors of management of electronic communication with clients in the banking industry and banking. 7) Due to the limitations of the research it is proposed that this model is tested in a wider scale and in a larger population. 8) Moreover, it has also been proposed to other researchers to study the patterns of CRM systems and their application in industry and other countries to see how the profile of the business environment (culture, level of competition, the ups and downs of the industry, etc.), influence the use and support of CRM systems for the processes of customer knowledge creation.
References:
Babak. Abrahymy,. (2007) . knowledge management in customer relationship. Management magazine, Issue 178.
Elahy, Shaban. Heydary, Bahman. (2008) . customer relationship management, Tehran: business publishing company affiliated with the Institute for Trade Studies and Research Publications Business: Second Edition.
Barua, C.H. Kriebel, T. Mukhopadhyay,) 1995(.information technologies and business value:an analytic and empirical investigation, Information System Research 6, p,3.
Bose R., Sugumaran V. )2003 (. Application of Knowledge Management Technology in Customer Relationship Management. Knowledge and Process Management; 10(1): 3-17.
Doll, G. Torkzadeh, )1998(. Developing a multidimensional measure of system-use in an organizational context, information & Management 33, , pp. 171-185.
Edire.even,G.shanakaranarayanan,Pauld.Berger.(2010). Evaluating a model for cost-effective data quality management in a real-world CRM setting. Decision Support Systems, Volume 50, Issue 1, December 2010, Pages152–163.
Feinberg, R., and Romano, N.( 2002). e-CRM web service attributes as determinants of customer satisfaction with retail web sites. IJ ServInd Manage; 13 (5): 432-451.
Gable, D. Sedera, T.Chan ,) 2008.( Re-conceptualizing information systm success: the IS-impact measurement model, Journal of Association for information System 9, pp.377-408.
Garcia-Murillo, H. Annabi).2002).customer knowledge management, Journal of the operational Research Socienty 53, pp. 875-884.
Geib, L. M. Kolbe, W. Brenner, )
2006 .( CRM Collaboration in financial services networks: a multi-case
analysis , Journal of Enterprise information management 19, pp.591-607. Henning, M. Geib, L. Kolbe, W. Brenner,) 2003(. Knowledge-enabled customer relationship management: integrating customer relationship management and knowledge management concepts, Journal of knowledge Management 7, pp. 107-123.
Iriana, F. Buttle)2007.( Strategic, operational, and analytical customer relationship management, Journal of Relationship Marketing 5, pp.23-42.
Martha Garcia-Murillo,annabi.)2002.(. Customer Knowledge Management February 15, 2002Journal of the Operational Research Society, Vol. 53, No. 8.
petter, W. Delone, E. Mclean )2008(.Measuring information systems success: models, dimensions, measures, and interrelationship, European Journal of Information System 17, pp.236-263.
Retna, S Kala & Tee NG Pak, (2011), " Communities of practice: Dynamics and success factors". Leadership & Organization Development Journal Vol.32 No. 1, pp. 41-5.
Shahin, A. and Nikneshan, P. (2008), Integration of CRM and QFD / A novel model for enhancing customer participation in design and delivery, Iran. The TQM journal, 20 (1): 68 – 86.
Shami Zanjani M., Rouzbehani R., Dabbagh H. Proposing a Conceptual Model of Customer Knowledge Management: A Study of CKM Tools in British Dotcoms; 2008.
Suo,s.petter(2006).measuring information system :model is dimensions, measuresand
interrelationship,european jornal ofinformation system 17.pp.236-263.
Xu,m., & Walton,J.,(2005), “Gaining Customer Knowledge through Analytical CRM”, Industrial Management & Data system, Vol.105, No.7, PP.955-971.
