Regional Leading Industry Selection Based on an Extended Fuzzy VIKOR Approach

Fuli Zhou, Guiyan Wang, Tianfu Chen, Panpan Ma and Saurabh Pratap
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Fuli Zhou: Zhengzhou University of Light Industry, China
Guiyan Wang: Zhengzhou University of Light Industry, China
Tianfu Chen: Zhengzhou University of Light Industry, China
Panpan Ma: Zhengzhou University of Light Industry, China
Saurabh Pratap: Indian Institute of Technology, Varanasi, India

International Journal of Decision Support System Technology (IJDSST), 2022, vol. 14, issue 1, 1-14

Abstract: To improve the deployment and optimization of the industrial structure, researchers and practitioners have performed a variety of researches in terms of regional leading industry selection based on AO Hirschman, Rostow, and Miyohei's principles. The criteria and methods employed in previous studies are mainly based on the mass industrial development data, leading to the limitation of study on the application in new high-tech district and underdeveloped regions. Due to lack of industrial data and detail industry information, it is difficult to employ the deterministic regional industry selection model. Therefore, an extended fuzzy-VIKOR approach that the expert-based and trapezoidal fuzzy number decision-making techniques embedded into the VIKOR steps is proposed. It is developed to solve the regional leading industry selection problems concerning industrial, economic, social, and environmental dimensions. Finally, a case study for the industrial planning of a high-tech zone is applied to verify the proposed decision-making approach.

Date: 2022
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