Analysis of Business Customers’ Value Network Using Data Mining Techniques

سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 407

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شناسه ملی سند علمی:

JR_JIST-5-3_004

تاریخ نمایه سازی: 20 آبان 1397

چکیده مقاله:

In today s competitive environment, customers are the most important asset to any company. Therefore companies should understand what the retention and value drivers are for each customer. An approach that can help consider customers‘ different value dimensions is the value network. This paper aims to introduce a new approach using data mining techniques for mapping and analyzing customers‘ value network. Besides, this approach is applied in a real case study. This research contributes to develop and implement a methodology to identify and define network entities of a value network in the context of B2B relationships. To conduct this work, we use a combination of methods and techniques designed to analyze customer data-sets (e.g. RFM and customer migration) and to analyze value network. As a result, this paper develops a new strategic network view of customers and discusses how a company can add value to its customers. The proposed approach provides an opportunity for marketing managers to gain a deep understanding of their business customers, the characteristics and structure of their customers‘ value network. This paper is the first contribution of its kind to focus exclusively on large data-set analytics to analyze value network. This new approach indicates that future research of value network can further gain the data mining tools. In this case study, we identify the value entities of the network and its value flows in the telecommunication organization using the available data in order to show that it can improve the value in the network by continuous monitoring.

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نویسندگان

Forough Farazzmanesh

Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

Monireh Hosseini

Department of Information Technology, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran