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Article type: Research Article
Authors: Ding, Ji-Fenga | Weng, Ju-Huib | Chou, Chien-Changc; *
Affiliations: [a] Department of Aviation and Maritime Transportation Management, Chang Jung Christian University, Tainan City, Taiwan | [b] The Ph.D. Program in Business and Operations Management, Chang Jung Christian University, Tainan City, Taiwan | [c] Department of Shipping Technology, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
Correspondence: [*] Corresponding author. Chien-Chang Chou, Department of Shipping Technology, National Kaohsiung University of Science and Technology, Kaohsiung 80543, Taiwan. E-mail: ccchou@nkust.edu.tw.
Abstract: Evaluating the factors affecting customer value in department stores will shed light on the motivations of customers when choosing department stores, which will help department stores to improve their business performance and competitiveness. This paper applies the fuzzy Analytic Hierarchy Process (AHP) method to empirically analyze the determinants of customer value at department stores in Taiwan. This study first found the major factors influencing customer value at department stores in Taiwan through a review of the literature and expert interviews, and these factors consisted of four evaluation dimensions and 20 evaluation criteria. An empirical investigation was then conducted through an AHP expert questionnaire survey. The main findings of this paper were as follows: (1) “Physical environment” was the most important evaluation dimension for customer value at department stores in Taiwan. (2) The four leading factors influencing customer value in department stores were “roomy and comfortable space,” “responsive customer service,” “planning of lines of movement at counters,” and “parking area and facilities.” This study also performed further discussion of the four evaluation criteria as a reference for department stores that wish to raise their competitiveness.
Keywords: Customer value, determinant, department store, fuzzy, analytic hierarchy process (AHP)
DOI: 10.3233/JIFS-222175
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 6, pp. 9073-9089, 2023
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