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| Dynamic Innovation Efficiency Measurement and Influencing Factors of Listed Companies in Strategic Emerging Industries：A Study Based on Two-stage DSBM Model and Tobit Model |
| Zeng Zhuoqi,Wang Yue |
| (School of Business, East China University of Science and Technology, Shanghai 200237, China) |
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Abstract As China's economy enters the new normal, it is essential to speed up the cultivation of innovative industries, improve the quality and efficiency of scientific and technological innovation development, and promote national economic growth through innovation. The strategic emerging industries are the pillar industries and leading industries of the national economy. In recent years, China's R&D investment and R&D scale have been increasing, and the total R&D expenditure in 2019 ranked second in the world. However, according to the assessment of the World Intellectual Property Organization (WIPO) and the global innovation index report, China's innovation index in 2020 only ranked the 14th in the world. The above contrast shows that the innovation input and output have not been increased in proportion, and the innovation efficiency is low. The problem of improving innovation efficiency needs to be solved. Therefore, in order to ensure the sustainable development of China's strategic emerging industries, it is necessary to "open the black box", measure and analyze the innovation efficiency of listed companies in strategic emerging industries and its influencing factors.#br#Enterprises are the main body of innovation, and their innovation ability is closely related to the progress and quality of China's scientific and technological innovation system construction. This paper takes 873 listed companies in strategic emerging industries as the research object. At first, this study uses the DEA method and output-oriented DSBM model to measure the dynamic innovation efficiency of the whole and seven key industries in two stages. From the micro enterprise level, the paper proposes for the first time to take the growth of operating revenue, operating revenue and the growth rate of operating revenue as the innovation output in the transformation stage of technological achievements, measures and compares the corresponding innovation efficiency. The results show that it is more realistic to take the growth of operating revenue as the innovation output; the innovation efficiency of each industry is heterogeneous. Then, on the basis of the measurement results of innovation efficiency, this study further uses the Tobit model to analyze the factors that affect the innovation efficiency of enterprises. It is shown that in the stage of technology research and development, enterprise scale, ROA, R&D intensity, labor quality and enterprise nature have positive impacts on the innovation efficiency, but R&D personnel, R&D investment, enterprise age and government subsidies have negative impacts. While in the stage of technological achievement transformation, the authorized patent for invention, enterprise scale, ROA, R&D intensity and labor quality have a positive impact on innovation efficiency, while the total numbers of employees, R&D expenditure, enterprise age, government subsidies and enterprise type have negative impacts on innovation efficiency.#br#According to the research conclusions, it is essential to improve the innovation mode and stimulate the independent innovation ability of enterprises; the resource integration, growth and development of small and medium-sized enterprises should be greatly supported to improve their overall competitiveness; it is necessary to rationally plan and arrange innovation investment and increase the proportion of high-quality scientific and technological personnel; the government should strengthen supervision and guidance, and introduce preferential policies and measures; lastly, we should it is also significant to improve the system of independent intellectual property rights and build a joint system of industry, university and research.#br#This paper firstly analyzes the innovation efficiency and its influencing factors of listed companies in strategic emerging industries at the enterprise level by using micro data, enriching the research perspective of relevant literature. Second, different from the traditional static model based on input-oriented to measure the static innovation efficiency in the past, it uses the high-order dynamic model based on output-oriented after considering the output maximization when the innovation input is certain and the dynamic innovation efficiency of the carry-over activities in the connected periods. Finally, considering the lag of innovation output and the different stages of innovation activities, this study examines the innovation efficiency of enterprises using different innovation output indicators in different stages and its influencing factors, which deepens the understanding of the innovation efficiency of enterprises in strategic emerging industries and the factors affecting innovation efficiency.#br#
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Received: 09 May 2022
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