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Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation

In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses “number of new energy project personnel” and “hours of R&D (research and development) personnel” as design indicators to evaluate the investment of innovative talents in enterprises. This paper...

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Detalles Bibliográficos
Autores principales: Cao, Ziying, Qian, Leren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119422/
https://www.ncbi.nlm.nih.gov/pubmed/37091345
http://dx.doi.org/10.3389/fbioe.2023.1178737
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author Cao, Ziying
Qian, Leren
author_facet Cao, Ziying
Qian, Leren
author_sort Cao, Ziying
collection PubMed
description In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses “number of new energy project personnel” and “hours of R&D (research and development) personnel” as design indicators to evaluate the investment of innovative talents in enterprises. This paper first introduces the supporting factors of the innovation environment in the input of innovation resources, and conducts research from four perspectives: human resources, innovation R&D, technology acquisition, and environmental support. In the construction of the innovation output index system, this paper outlines that the technological innovation (TI) achievements of enterprises are related to factors such as technological capabilities, profits, and market competitiveness of enterprises. Finally, this paper evaluates it from three aspects: the research and development achievements, the economic benefits obtained and the competitive benefits of the enterprise. The results show that from 2018 to 2022, the average technological innovation efficiency of new energy enterprises is 1.06; TI’s efficiency indicators in the past five years are all above 1, and the overall improvement trend of TI is relatively stable. The new energy vehicle collaborative innovation system constructed in this paper will promote the overall development of the new energy vehicle industry.
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spelling pubmed-101194222023-04-22 Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation Cao, Ziying Qian, Leren Front Bioeng Biotechnol Bioengineering and Biotechnology In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses “number of new energy project personnel” and “hours of R&D (research and development) personnel” as design indicators to evaluate the investment of innovative talents in enterprises. This paper first introduces the supporting factors of the innovation environment in the input of innovation resources, and conducts research from four perspectives: human resources, innovation R&D, technology acquisition, and environmental support. In the construction of the innovation output index system, this paper outlines that the technological innovation (TI) achievements of enterprises are related to factors such as technological capabilities, profits, and market competitiveness of enterprises. Finally, this paper evaluates it from three aspects: the research and development achievements, the economic benefits obtained and the competitive benefits of the enterprise. The results show that from 2018 to 2022, the average technological innovation efficiency of new energy enterprises is 1.06; TI’s efficiency indicators in the past five years are all above 1, and the overall improvement trend of TI is relatively stable. The new energy vehicle collaborative innovation system constructed in this paper will promote the overall development of the new energy vehicle industry. Frontiers Media S.A. 2023-04-07 /pmc/articles/PMC10119422/ /pubmed/37091345 http://dx.doi.org/10.3389/fbioe.2023.1178737 Text en Copyright © 2023 Cao and Qian. 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 Bioengineering and Biotechnology
Cao, Ziying
Qian, Leren
Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title_full Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title_fullStr Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title_full_unstemmed Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title_short Crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
title_sort crowding effect of institutional openness based on the big data algorithm on the efficiency of new energy technology innovation
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119422/
https://www.ncbi.nlm.nih.gov/pubmed/37091345
http://dx.doi.org/10.3389/fbioe.2023.1178737
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