
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
A key stakeholder-based financial subsidy stimulation for Chinese EV industrialization: A system dynamics simulation

Abstract Successful policy-making for an emerging industry relies on two key factors: adopting a scientific perspective and accurately forecasting the policy's potential effects. By combining Mitchell's score-based approach and expert grading method, this paper identifies the key stakeholders of the Chinese electric vehicle (EV) industry, and proposes a key stakeholder-based policy research framework (G-MIC: Government — Manufacturers, Infrastructure, Consumers). Furthermore, a system dynamics (SD) model is outlined, focusing on financial subsidy (FS) policy and the three groups of programs that are set to simulate level of FS, FS allocation, and the demand for realizing the CAO (Civilian Auto Ownership) goal of the Chinese EV industry by 2020. The findings reveal that the following show that a key stakeholder perspective is a better approach to policy research; the SD model constructed under the G-MIC framework extends the methodology of SD; and a “bottom-up” policy-making path is more likely to improve policy outcomes.
- University of Shanghai for Science and Technology China (People's Republic of)
- Shanghai University China (People's Republic of)
- Shanghai University China (People's Republic of)
- University of Shanghai for Science and Technology China (People's Republic of)
- Institute of Economics China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).64 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
