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Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model
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 convergenc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033529/ https://www.ncbi.nlm.nih.gov/pubmed/36968692 http://dx.doi.org/10.3389/fpsyg.2023.1100717 |
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author | Han, Yanqi Hua, Minghui Huang, Malan Li, Jin Cheng, Shixiong Wei, Xihang |
author_facet | Han, Yanqi Hua, Minghui Huang, Malan Li, Jin Cheng, Shixiong Wei, Xihang |
author_sort | Han, Yanqi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10033529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100335292023-03-24 Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model Han, Yanqi Hua, Minghui Huang, Malan Li, Jin Cheng, Shixiong Wei, Xihang Front Psychol Psychology 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. Frontiers Media S.A. 2023-03-09 /pmc/articles/PMC10033529/ /pubmed/36968692 http://dx.doi.org/10.3389/fpsyg.2023.1100717 Text en Copyright © 2023 Han, Hua, Huang, Li, Cheng and Wei. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Han, Yanqi Hua, Minghui Huang, Malan Li, Jin Cheng, Shixiong Wei, Xihang Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title | Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title_full | Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title_fullStr | Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title_full_unstemmed | Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title_short | Change and convergence of innovation efficiency among listed health companies in China: Empirical study based on the DEA–Malmquist model |
title_sort | change and convergence of innovation efficiency among listed health companies in china: empirical study based on the dea–malmquist model |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033529/ https://www.ncbi.nlm.nih.gov/pubmed/36968692 http://dx.doi.org/10.3389/fpsyg.2023.1100717 |
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