Abstract
With the implementation of the “Made in China 2025” plan and the promulgation of the “Renewable Energy Law”, China’s new energy equipment manufacturing industry has developed rapidly. At the same time, it has also revealed that China’s new energy equipment manufacturing enterprises have issues such as a high degree of external dependence on key technologies and low-level international competitiveness. Facing the complex international market environment, Chinese new energy equipment manufacturing enterprises urgently need to improve their independent innovation capabilities. This paper establishes the driving factors of independent innovation by sorting out domestic and international independent innovation-related research and combining the opinions of new energy equipment manufacturing experts. By using the exploratory factor analysis, five dimensions that affect independent innovation capability are extracted: independent innovation input capability, external environmental support, internal environmental support, knowledge management capability, and independent innovation output capability. Finally, it establishes the structural equation model of the driving factors of the independent innovation capability of new energy equipment manufacturing enterprises and proposes the driving path of the independent innovation capability of new energy equipment manufacturing enterprises. The research results show that both independent innovation input ability and knowledge management ability can directly have a positive impact on independent innovation output ability, and the influence of knowledge management ability is more significant; while the external environmental support and internal environmental support influence the enterprise’s knowledge management ability Indirectly affect the output capacity of independent innovation.
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References
Lüthje, B.: Platform capitalism ‘Made in China’? Intelligent manufacturing, Taobao Villages and the restructuring of work. Sci. Technol. Soc. 24(2), 199–217 (2019)
Qu, C., Jun, S., Zhonghua, C.: Can embedding in global value chain drive green growth in China’s manufacturing industry? J. Clean. Prod. 268, 121962 (2020)
Fakhri, A.B., et al.: Industry 4.0: architecture and equipment revolution. Comput. Mater. Continua 66(2), 1175–1194 (2021)
Wang, X., et al.: China’s rare earths production forecasting and sustainable development policy implications. Sustainability 9(6), 1003 (2017)
Lewis, J.I., Ryan, H.W.: Fostering a renewable energy technology industry: an international comparison of wind industry policy support mechanisms. Energy Policy 35(3), 1844–1857 (2007)
Lee, K., Chaisung, L.: Technological regimes, catching-up and leapfrogging: findings from the Korean industries. Res. Policy 30(3), 459–483 (2001)
Mattis, J.: Summary of the 2018 national defense strategy of the United States of America. Department of Defense Washington United States (2018)
Iyapparaja, M.: Fogqsym: an industry 4.0 analytical model for fog applications. Comput. Mater. Continua 69(3), 3163–3178 (2021)
Du, H., et al.: Leader confirmation replication for millisecond consensus in private chains. IEEE Internet Things J. (2021). https://doi.org/10.1109/JIOT.2021.3113835
Chao, L., et al.: Comparison of modernization paths between China and Japan. China Economist 11(2), 51 (2016)
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Ma, R., Du, H., Meng, F., Zhu, D. (2022). Research on Driving Factors of Independent Innovation Capability of New Energy Equipment Manufacturing Enterprises. In: Sun, X., Zhang, X., **a, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2022. Communications in Computer and Information Science, vol 1587. Springer, Cham. https://doi.org/10.1007/978-3-031-06761-7_34
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DOI: https://doi.org/10.1007/978-3-031-06761-7_34
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