EXPLORING LOCATION DETERMINANTS OF ASIA’S UNIQUE BEVERAGE SHOPS BASED ON A HYBRID MADM MODEL

Author:

Lin Sheng-Hau1ORCID,Hsu Chih-Chen2,Zhong Taiyang3,He Xiwei4,Li Jia-Hsuan5,Tzeng Gwo-Hshiung6,Hsieh Jing-Chzi7

Affiliation:

1. Law School, Ningbo University, Ningbo City, China

2. Department of Business Administration, Soochow University, Taipei City, Taiwan

3. School of Geography and Ocean Science, Nanjing University, Nanjing City, China

4. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing City, China

5. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing City, China

6. Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, New Taipei City, Taiwan

7. Department of Land Management, College of Construction and Development, Feng Chia University, Taichung City, Taiwan

Abstract

Identifying relevant location determinants is a good starting point for shop operators, help to increase profitability and, thus, avoiding business failure. Traditional Analytic Hierarchy Process (AHP) or the Analytic Network Process (ANP) have shortages that require improvement. Herein, Decision-Making Trial and Evaluation Laboratory (DEMATEL), ANP based on DEMATEL (DANP), and modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (modified VIKOR) are used to construct a hybrid multiple-attribute decision making (MADM) model, encompassing three dimensions and thirteen criteria in exploring the location determinants of Asia’s unique Bubble Tea Shops (BTSs) and to evaluate three preselected alternatives in Nanjing, China. The empirical findings of the DEMATEL method reveal that traffic traits (D1) and site traits (D2) are critical to BTSs, and that once these are enhanced, shop traits (D3) are also improved. Criteria deemed as important, based on the DEMATEL and DANP methodology, are (in descending order): proximity to a street corner (C2), proximity to public transportation systems (C1), road width (C3), proximity to communities (C5), proximity to commercial areas (C6), types of shop (C9), and proximity to schools (C7). Different decision-making rankings among alternatives are indicated based upon the modified VIKOR method and corresponding strategies for improvement are presented.

Publisher

Vilnius Gediminas Technical University

Subject

Strategy and Management

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