مقایسه عملکرد مبتنی بر مدیریت ارتباط با مشتری با استفاده از فرایند شبکه تحلیلی

Customer relationship management (CRM) is a multi-perspective business paradigm which aims maximizing the benefits gained from relationships with customers. The aim of this paper is to compare the CRM performances of e-commerce firms using a multiple criteria decision making (MCDM) approach. Analytical network process (ANP) is a MCDM methodology which can take the inner and outer dependencies among multiple criteria into consideration. As there are dependencies among CRM performance evaluation criteria, ANP is used for comparing the CRM performances of the e-commerce firms under consideration. A sensitivity analysis also provided in order to monitor the robustness of the proposed ANP framework to changes in the weights of evaluation criteria. To the authors’ knowledge, this will be the first study which evaluates CRM performance using ANP.

Customer relationship management is a multi-perspective business paradigm that is composed of people, process and technology (Chen & Popovich, 2003). Keeping its roots in relationship marketing and information technologies, CRM aims at maximizing the benefits gained from relationships with customers. However, no single definition has been accepted in the literature. The researchers has investigated 48 different CRM definitions and concluded with five categories of definitions: strategy, process, philosophy, capability and technology (Zablah, Bellenger, & Johnston, 2004). In this study CRM is defined in a micro view which can be defined as a process that is concerned with managing customer interactions (Plakoyiannaki and Tzokas, 2002, Reinartz et al., 2004 and Srivastava et al., 1999). As a result of its promises and benefit, CRM term has become popular and companies have been making investments on CRM projects. The most important expected outcomes of CRM can be listed as: improvements in efficiency, cost reduction, improved profitability, increase in sales, enhanced customer value, customer satisfaction and improved customer loyalty (Buttle, 2004, Eid, 2007, Jones et al., 2005, Ko et al., 2008, Reinartz et al., 2004, Richard et al., 2007a, Roh et al., 2005, Rust et al., 2001, Sheth and Sharma, 2001 and Verhoef, 2003). Managing the performance of CRM is especially important because of the low success rates (Brewton and Schiemann, 2003, Krol, 2002 and Richards and Jones, 2008). Many companies are still making investments in CRM projects (Richards & Jones, 2008). Performance measurement can be defined as a part of a management process that is realized periodically in order to determine the success or quality of a particular process or activity (Oztaysi, 2009). Performance measurement is used to evaluate the overall results of the past and identify the future position of the company in the top level management, in the individual level, performance measurement provides information about the shortcomings and motivate for the upcoming activities (Meyer, 2002). PM is a combination of companies’ characteristics that are numerically expressed (Folan, Browne, & Jagdev, 2007). In another perspective, performance measurement is process of choosing different attributes (and indicators about them) and generating a combined evaluation based on these attributes. The researchers define performance as a multi attribute decision making problem with the following requirements (Oztaysi & Ucal, 2009): (i) Ability to reflect meaningful numerical results that shows the overall performance of a period. (ii) Ability to reflect the performance of any sub-division or perspective. (iii) Ability to trace the performance improvements by time. (iv) Ability to be flexible to design according to companies preferences. (v) Ability to be dynamic so that firm can change the model when needed. (vi) Ability to give insight about future performance. Current performance evaluation in CRM literature can be analyzed in four groups. (i) Indirect measures and operational indicators. (ii) Self assessment. (iii) Benchmarking with best practices. (iv) CRM Scorecards. Indirect measures aim at evaluating CRM performance by indicators such as customer equity and brand equity (Kellen, 2002 and Richards and Jones, 2008). Operational indicators on the other hand identify information about the efficiency of the customer related operations. In the second group, there are tools/scales that are generated by statistical methods (Crosby et al., 1990, Dorsch et al., 1998, Dwyer et al., 1987, Jain et al., 2003, Kumar et al., 1995, Lagace et al., 1991 and Sin et al., 2005). These studies aim at measuring relationship quality, behavioral dimensions or holistic CRM. Customer Measurement Assessment Tool (Woodcock, Stone, & Foss, 2003) is the only tool that takes place in the third group. The method has defined nine assessment areas which are; Information technology, people, process, customer management, analysis, proposition customer management, measurement, customer experience and competitors. Differently from others, the method is an assessment tool which is based on comparison of companies’ performance with the best practices in the same performance assessment area. The last group is composed of the CRM scorecard studies. There are two studies in the literature that propose CRM scorecard (Kim and Kim, 2009 and Kim et al., 2003). Also there are some studies that define the most important steps in CRM scorecard applications (Brewton and Schiemann, 2003 and Wiedmann and Buxel, 2007) . There are many studies in the literature which utilize ANP in performance evaluation. Sarkis (1999) proposed a methodological framework for evaluating environmentally conscious manufacturing programs. Yurdakul (2003) measured long-term performance of a manufacturing firm using ANP approach. Leung, Lam, and Cao (2006) used ANP to facilitate the implementation of the Balanced Scorecard (BSC) in order to incorporate a wider set of non-financial attributes into the measurement system of a firm. Sarkis (2003) showed how ANP approach could be used to enhance the manufacturing strategy performance evaluation models. Chen and Lee (2007) constructed a performance evaluation model for project managers on the basis of leadership behaviors that lead to managerial practices. Chen, Huang, and Cheng (2009) proposed an approach of measuring a technology university’s knowledge management performance from competitive perspective. Chen and Chen (2010) interviewed Taiwanese higher education experts to integrate critical measurement criteria and develop an ANP based original performance appraisal system to present complex interdependent relationships and to construct a relation structure among measurement criteria for performance appraisal. The purpose of this study is to compare the CRM performances of e-commerce firms using a multicriteria decision making method. ANP is a decision making methodology which can take the inner and outer dependencies among multiple criteria into account. Since there are dependencies among CRM performance evaluation criteria, ANP is used for comparing the CRM performances of the firms under consideration. To our knowledge, this will be the first study that evaluates CRM performance using ANP. The rest of the paper is organized as follows. Section 2 includes a literature review about the performance evaluation criteria used in CRM studies. In Section 3, a summary of ANP methodology and the CRM network structure used in this study are briefly given. In Section 4, the proposed ANP framework is applied to a case study in Turkish e-commerce market. In this section, a sensitivity analysis is also provided. Finally, in the fifth section concluding remarks and suggestions for further research are given.

CRM is a multidimensional business paradigm which aims at enhancing the benefits gained from relationships with customers. Assessing CRM performance of a company requires considering interdependent factors. Therefore CRM performance evaluation is a MCDM problem which has to take inner and outer dependencies into account. ANP is an excellent methodology which can deal with such issues by considering dependencies between nodes and clusters of criteria. In this paper, CRM performances of three e-commerce companies operating in Turkey have been compared using ANP approach. For this purpose, based on an extensive literature review, a network structure has been built. The model has been established and ran in Super Decisions package. Sensitivity analyses have also been conducted. The results showed that the ranking among the alternatives are sensitive to changes in the parameters. To the knowledge of the authors, this paper is the first study which evaluates CRM performance of firms using ANP MCDM methodology. In the future research, the framework established in this study can be applied to different sectors like fast moving consumer goods, airlines, and banking. Moreover, to monitor the dynamics in CRM performances of the considered firms, this model can be re-used periodically. Finally, the results obtained in this paper can be compared with that of alternative approaches like Choquet integral or multi-attribute utility models which can also take the interactions and dependencies among evaluation criteria into consideration.