Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA-Malmquist model

• Published in: Frontiers in psychology Vol. 14; p. 1100717
• Main Authors: Han, Yanqi, Hua, Minghui, Huang, Malan, Li, Jin, Cheng, Shixiong, Wei, Xihang
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 09.03.2023
• Subjects: convergence trend; DEA-Malmquist; dynamic transition; health industry; innovation efficiency; Psychology; DEA-Malmquist; innovation efficiency; health industry; dynamic transition; convergence trend
• ISSN: 1664-1078; 1664-1078
• DOI: 10.3389/fpsyg.2023.1100717

This study investigates the present situation of and changing trend in the innovation efficiency of health industry enterprises in China. Based on panel data for 192 listed health companies in China from 2015 to 2020, we analyse innovation efficiency using the DEA-Malmquist index and test convergence using σ-convergence and β-convergence models. From 2016 to 2019, comprehensive average innovation efficiency increased from 0.6207 to 0.7220 and average innovation efficiency decreased significantly in 2020. The average Malmquist index was 1.072. Innovation efficiency in China as a whole, North China, South China, and Northwest China showed σ-convergence. Except for the Northwest region, absolute β-convergence was evident, and in China as a whole, North China, Northeast China, East China, and South China, conditional β-convergence was evident. Overall innovation efficiency of these companies has increased annually but needs further improvement, and the COVID-19 pandemic has had a great negative impact on it. Innovation efficiency and trends in it vary across regions. Furthermore, we should pay attention to the impacts of innovation infrastructure and government scientific and technological support on innovation efficiency.