A Novel Hybrid Correlation Measure for Probabilistic Linguistic Term Sets and Crisp Numbers and Its Application in Customer Relationship Management

Xiao Fang Zhang (), Ze Shui Xu and Pei Jia Ren ()
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Xiao Fang Zhang: Business School, Sichuan University, Chengdu 610064, China
Ze Shui Xu: Business School, Sichuan University, Chengdu 610064, China
Pei Jia Ren: Business School, Sichuan University, Chengdu 610064, China

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 02, 673-694

Abstract: With the development of technology, people have entered the Big Data era, where the insurance companies meet with opportunities for their massive customer data. To make full use of these data and promote the insurance companies’ benefits, this paper aims to propose a method to reasonably measure the similarity among customers and segment them. However, there exists a challenge to deal with different types of data, i.e., linguistic data and crisp numbers, in customer relationship management. Considering that probabilistic linguistic term set possesses an apparent superiority in reducing linguistic information losses during the process of customer evaluation and data processing, we give a novel correlation measure of two data sequences with both crisp numbers and probabilistic linguistic term sets. Furthermore, we put forward the weighted form of the correlation measure to increase its application elasticity, and then apply the proposed correlation measures to insurance companies’ customer relationship management based on an improved clustering algorithm. Finally, a numerical example is given to illustrate the validity of our correlation measures.

Keywords: Correlation measure; probabilistic linguistic term set; customer relationship management; insurance industry; clustering (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S021962201950007X

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