Effective Innovation Policy in the Industrial Sector: The Case of Russia

Prodchenko, Igor A.; Gulkova, Elena L.; Karp, Marina V.; Tipalina, M. V.; Rykova, Inna N.

doi:10.1007/978-3-030-80485-5_33

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…With the increasing importance of the biomedical industry, Chinese government has made diversified adjustments and implementation of policy support ( 6 ). In addition, countries around the world have attached great importance to the development of the biomedical industry, in which governments and policies play a crucial role ( 10 , 11 ).…”

Section: Literature Review and Model Constructionmentioning

confidence: 99%

“…Similar to the results of this study, in order to stimuli the innovation performance, several large global countries promote the innovation and development of the biomedical industry by means of policy support ( 47 ). For example, Russian science and technology forecasts do focus sufficiently to promising technologies in biomedical industry, nanotechnology, and medical technology ( 11 ). The United States federal government provides large amounts of research funds for R&D in the biomedical industry.…”

Section: Research Conclusion and Outlookmentioning

confidence: 99%

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The influence of “industry policy” and “financial institution” configuration effect on innovation performance of China’s biomedical industry-based on necessary condition analysis and qualitative comparative analysis

Zhang

2024

Front. Med.

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Biomedical industry is a strategic emerging industry in China, especially the outbreak of the Covid pandemic. The biomedical industry is characterized by high risk, high investment, high technology and long cycle, and each stage contains risks and challenges. How to optimize the policy environment and financial environment, explore the unique “policy” and “finance” model for the development of the biomedical industry, and improve the innovation performance has become an important issue. This paper analyzes the relationship among industry policy, financial institution and innovation performance in the biomedical industry from the configuration perspective, combining necessary condition analysis (NCA) and qualitative comparative analysis (QCA) research methods, using the A-share listed enterprises in Shanghai and Shenzhen in the biomedical industry from 2012 to 2020 as the research objects. It is found that (1) individual policy preference or financial institution dimension cannot constitute a necessary condition for generating high innovation performance of biomedical company, but increasing tax incentive and raising the proportion of equity-based financing method play a significant role in generating high innovation performance; (2) four “political” and “financial “synergistic grouping paths can generate high innovation performance, including tax incentives, financial institutions’ professional level and institutional background synergistic drive type; government subsidy, financing method and financial institutions’ professional level synergistic drive type; tax incentive and financing method synergistic drive type; tax incentive and institutional background drive type. Different synergistic grouping paths represent various ways to achieve high innovation performance of biomedical enterprise. In addition, the results show that the two “political” and “financial” groupings lead to low-to-medium innovation performance, which indicates that industry policy plays a very important role in the innovation performance and that the government’s support for emerging industries through policy is a significant force for the innovation development. This paper introduces the “political” and “financial” aspects to investigate the configuration effect of industry policy and financial institutions on the innovation performance of biomedical enterprise. The findings have important theoretical and practical implications for revealing the synergistic path of high innovation performance in the Chinese biomedical industry.

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Section: Literature Review and Model Constructionmentioning

confidence: 99%

Section: Research Conclusion and Outlookmentioning

confidence: 99%