An Analysis of the Optimal Customer Clusters Using Dynamic Multi-Objective Decision

Shen-Tsu Wang ()
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Shen-Tsu Wang: Department of Commerce Automation and Management, National Pingtung University, 51 Min Sheng E. Road, Pingtung 900, Taiwan, Republic of China

International Journal of Information Technology & Decision Making (IJITDM), 2018, vol. 17, issue 02, 547-582

Abstract: The M-type society has emerged in recent years, under which the Food and Beverage (F&B) industry is facing more intense competition. Product innovation and development capabilities, competition, increasing raw material costs, and the rising awareness of consumers pose even further challenges. This study used a project portfolio as the decision subject to identify customer clusters, with the research purposes: (1) to identify the optimal customer clusters by minimizing inter-cluster relationships and (2) to maximize the intra-cluster relationships. The findings help address the problem of a dispersed optimal intra-group structure caused by clustering in the inter-group relationships. Computerized management of that is conducive in accounting and information analysis. Thus, dynamic multi-objective service decisions can provide the related industries with development strategies when facing uncertainties.

Keywords: Food and beverage industry; optimal customer clusters; dynamic multi-objective service decision (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0219622017500468

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