A Data Envelopment Analysis Method for Evaluating Performance of Customer Relationship Management

By Karimi-Ghartemani, Samaneh; Shekarchizadeh, Ahmadreza et al. | Iranian Journal of Management Studies, Autumn 2018 | Go to article overview

A Data Envelopment Analysis Method for Evaluating Performance of Customer Relationship Management


Karimi-Ghartemani, Samaneh, Shekarchizadeh, Ahmadreza, Khani, Naser, Iranian Journal of Management Studies


(ProQuest: ... denotes formulae omitted.)

Introduction

Understanding how to manage customer relationships has received considerable attention from organizations in recent years. Since customers give companies economic power, organizations are constantly improving their customer relationships and their communication with costumers. As a result, organizations are concentrating on customeroriented approach instead of brand-oriented marketing. Customer relationship management (CRM) is a great tool in attracting and retaining customers and has an important impact on the success of organizations (Nguyen, Sherif, & Newby, 2007). Transforming organizations into customer-oriented establishments and expanding revenue and profit at the same time is known as CRM (Ebrahimi, Fathi, & Irani, 2016). CRM is a multiple perspective business paradigm which helps companies to have better relationships with their customers to achieve competitive advantage (Ebrahimi et al., 2016). CRM has been implemented in several organizations since it will lead to customer satisfaction, loyalty and in general to an increase in sale (Feinberg & Kadam, 2002; Kotorov, 2002). CRM is an essential tool for delivering superior customer value and will lead to sustaining competitive advantage for organizations (Jensen, 2001).

To manage, to assess and to improve the effectiveness of the CRM, a measurement system or an evaluation tool is essential (Kim, Suh, & Hwang, 2003). This measurement system or tool helps manages to handle quick changes and to compete with other organization. An effective measurement system should provide a better picture for managers on how their CRM polices and their plans are progressing (Winer, 2001).

Several techniques for evaluating CRM have been proposed by researchers such as Balanced Scorecard (BSC) (Shafia, Mahdavi Mazdeh, Vahedi, & Pournader, 2011), multi-criteria decision making (MCDM) methods (Ebrahimi et al., 2016) and Data envelopment analysis (DEA) (Haridasan & Venkatesh, 2011). All of these methods have their own advantages and disadvantages (Dessler, 2000). Choosing a technique for the evaluation of performance depends on the purpose of evaluating or the status and type of the organization.

One of the effective methods to evaluate the efficiency of different decision-making units (DMUs) is DEA, since DEA is a nonparametric method which accounts for qualitative and quantitative measures and transfers multiple inputs into multiple outputs (Kianfar, Ahadzadeh Namin, Alam Tabriz, Najafi, & Hosseinzadeh Lotfi, 2016). This efficiency estimation technique can be used for solving many problems of management such as ranking of DMUs and evaluating CRM policy (Krasnikov, Jayachandran, & Kumar, 2009). DEA is a powerful model for ranking and evaluating DMUs, but, there is a drawback to this model. DEA model considers DMUs as a black box that get inputs and changes them to the output, while the internal linking activities in the DMUs are neglected (Goto, Otsuka, & Sueyoshi, 2014; Xiaoli, Rui, & Qian, 2014). So, when utilizing DEA for efficiency evaluation, only the initial inputs and final outputs are needed, whereas the data related to the internal activities in each DMU is usually omitted. To deal with this problem, Network DEA (NDEA) model is proposed (Sexton & Lewis, 2003). NDEA calculates the efficiency of DMUs with network structure. NDEA is a more beneficial model, since in real world many cases have network structure (Tavassoli, Farzipoor Saen, & Faramarzi, 2015).

In this paper, a customer-oriented evaluation model by NDEA structure is proposed for evaluating the efficiency of CRM in bank branches. While a variety of studies have defined CRM and its elements, this paper tries to suggest some of the most reputable and important of these factors to come to a network CRM to be used in NDEA method. These factors include service quality, customer loyalty, and customer satisfaction that have been discussed in lots of studies (Amin, 2016; Faizan, Yuan, Kashif, Pradeep Kumar, & Neethiahnanthan Ari, 2016; Jiao, Yang, & Zhu, 2012; Wah Yap, Ramayah, & Nushazelin Wan Shahidan, 2012). …

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