Azadnia, Amir Hossein, Mat Saman, Muhamad Zameri, Wong, Kuan Yew and Hemdi, Abdul Rahman (2011) Integration model of Fuzzy C means clustering algorithm and TOPSIS Method for Customer Lifetime Value Assessment. In: 2011 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, pp. 16-20.
Preview
AA_integration model.pdf
Download (550kB) | Preview
Abstract
Nowadays, companies should establish a long-term
relationship with their customers throughout customer
relationship management (CRM). In order to be a winner in
the market competition, marketing managers want to
maximize customer lifetime value (CLV) and customer
equity. So, creating a customer value assessment system is
obligatory for companies to identify customers’ value,
develop strategies for customers’ segments, and preserve the
high value for them. Commonly, customer lifetime value is
evaluated by RFM (recency, frequency and monetary)
method. In this paper a model for customer value assessment
integrated with multi-criteria decision making method and
Fuzzy clustering method based on customer purchasing
behavior was proposed. Fuzzy Analytical Hierarchy Process
was utilized to calculate the weight of RFM variables. Then,
based on the weighted RFM values, Fuzzy c-means
clustering was used in order to cluster customers. Finally,
TOPSIS (Technique for Order Preference by Similarity to
Ideal Solution) has been employed to rank customer lifetime
value. A case study was used to demonstrate the employment
of the proposed model.
Item Type: | Book Section |
---|---|
Keywords: | Customer lifetime value; fuzzy c-means; fuzzy analytic hierarchy process; TOPSIS; |
Academic Unit: | Faculty of Social Sciences > School of Business |
Item ID: | 15915 |
Identification Number: | 10.1109/IEEM.2011.6117870 |
Depositing User: | Amir Azadnia |
Date Deposited: | 04 May 2022 11:01 |
Publisher: | IEEE |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/15915 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year