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

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 dev...

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Bibliographic Details
Published inMathematics (Basel) Vol. 10; no. 20; p. 3755
Main Authors Tseng, Chun-Chieh, Zeng, Jun-Yi, Hsieh, Min-Liang, Hsu, Chih-Hung
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.10.2022
Subjects
Art galleries & museums
best–worst method
Business models
Case studies
Coronaviruses
COVID-19
Decision making
Delphi method
Economic development
Economic growth
Energy
Energy conversion
Energy conversion (Power resources)
Factories
GDP
Globalization
Gross Domestic Product
Growth rate
Innovations
Integrated approach
Kinetic energy
Medical research
Methods
modified Delphi method
Multiple criteria decision making
Multiple criterion
new and old kinetic energy conversion
Performance management
Polls & surveys
post-COVID-19
Questionnaires
Subsidies
Supply chains
Sustainability
Sustainable development
China
United States > US
Japan
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Summary: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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math10203755