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.
Funder
Natural Science Foundation of Fujian, China
Society Science Foundation of Fujian, China
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Cited by
2 articles.
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