E3S Web Conf.
Volume 214, 20202020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|Number of page(s)||8|
|Section||Big Data Analysis Application and Energy Consumption Research|
|Published online||07 December 2020|
Research on the Evaluation of Innovation Efficiency and Its Influencing Factors in 11 Eastern Coastal Provinces and Cities: Based on Three-stage DEA and Tobit Models
School of Economics and Management, Dalian University Dalian, China
Based on panel data from 2008 to 2017, a BCC model and a DEA-Tobit model based on a three- stage DEA method are established to study the regional innovation capabilities and their influencing factors of 11 provinces and cities in the eastern coastal areas of China. The research finds that the innovation efficiency in the eastern coastal areas is still far from the frontier of innovation efficiency, and the low scale efficiency is the main factor restricting its development. In terms of influencing factors of innovation efficiency, improving technological level, optimizing market environment, and expanding enterprise scale can improve regional innovation efficiency, while the irrational expansion of the financial industry will hinder the development of innovation capabilities. Based on the research conclusions, policy suggestions such as actively exerting the effects of industrial agglomeration, deepening the reform of old industrial bases, and optimizing the innovation environment are put forward.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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