Analysis of Innovation Drivers of New and Old Kinetic Energy Conversion Using a Hybrid Multiple-Criteria Decision-Making Model in the Post-COVID-19 Era: A Chinese Case

Chun-Chieh Tseng, Jun-Yi Zeng, Min-Liang Hsieh () and Chih-Hung Hsu
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Chun-Chieh Tseng: School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, China
Jun-Yi Zeng: Institute of Industrial Engineering, College of Transportation, Fujian University of Technology, Fuzhou 350118, China
Min-Liang Hsieh: School of Economics and Management, Weifang University of Science and Technology, Weifang 262700, China
Chih-Hung Hsu: Institute of Industrial Engineering, College of Transportation, Fujian University of Technology, Fuzhou 350118, China

Mathematics, 2022, vol. 10, issue 20, 1-25

Abstract: To overcome the continuous decline in its gross domestic product growth rate, China has advocated new and old kinetic energy conversion (NOKEC) as a policy for sustainable economic development in the post-COVID-19 era. The innovation drivers of NOKEC are the key to promoting sustainable economic development. However, the innovation drivers have various orientations, and their selection requires multiple-criteria decision-making (MCDM). This study proposes a modified Delphi method combined with the best–worst method (BWM) as a research framework for selecting and ranking innovation drivers. Our results show the validity of this integrated research framework on a case based in China in the post-COVID-19 era. The results reveal 21 innovation-driven factors of NOKEC with varying levels of relative importance. These results may provide a basis for policymakers and researchers with a useful further understanding of the importance and prioritizing of innovation drivers. In this study, BWM uses 4% fewer pairwise comparisons than AHP, and the consistency ratio is in the range of 0.00 to 0.24.

Keywords: new and old kinetic energy conversion; multiple-criteria decision-making; modified Delphi method; best–worst method; post-COVID-19 (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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