Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network
Innovation is the main driving force to promote national technological progress. It is of great significance to explore the optimal path to improve innovation efficiency by using the qualitative method and neural network prediction model to promote the high-quality development of the national econom...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/11/5/233 |
| _version_ | 1797598218198974464 |
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| author | Yuanyuan Kou Huiying Chen Kai Liu Yanping Zhou Huajie Xu |
| author_facet | Yuanyuan Kou Huiying Chen Kai Liu Yanping Zhou Huajie Xu |
| author_sort | Yuanyuan Kou |
| collection | DOAJ |
| description | Innovation is the main driving force to promote national technological progress. It is of great significance to explore the optimal path to improve innovation efficiency by using the qualitative method and neural network prediction model to promote the high-quality development of the national economy. This study focuses on high-tech industries in the eastern, central and western regions of China; a factor-dependent research framework for innovation efficiency improvement in high-tech industries is constructed in China. The fuzzy-set qualitative comparative analysis method (QCA) is used to explore multiple paths to enhance the innovation efficiency of China’s high-tech industries. Then, a GA-PSO-BP neural network is used to construct an optimization model for the enhancement path of technological innovation efficiency, which clarifies the optimal path for the enhancement of innovation efficiency of high-tech industries in the eastern, central and western regions of China. Finally, innovation management strategies for high-tech industries are presented with regional features. The study finds that none of the individual conditions are necessary to promote the innovation efficiency of China’s high-tech industries, and only the linkage effect of the factors can achieve the goal of improving the innovation efficiency level of China’s high-tech industries. There are four configuration paths to improve the innovation efficiency of China’s high-tech industries, which are: “Multinational company (MNC) innovation—economic development—government support”; “MNC innovation—government support”; “economic development—government support”; and “economic development”. The characteristics of regional heterogeneity make differences in the optimal paths of innovation efficiency improvement in high-tech industries in eastern, central and western regions of China. |
| first_indexed | 2024-03-11T03:16:14Z |
| format | Article |
| id | doaj.art-428525b5b3f34980ae233c7e460dc4ef |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-11T03:16:14Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-428525b5b3f34980ae233c7e460dc4ef2023-11-18T03:31:39ZengMDPI AGSystems2079-89542023-05-0111523310.3390/systems11050233Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural NetworkYuanyuan Kou0Huiying Chen1Kai Liu2Yanping Zhou3Huajie Xu4College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, ChinaInnovation is the main driving force to promote national technological progress. It is of great significance to explore the optimal path to improve innovation efficiency by using the qualitative method and neural network prediction model to promote the high-quality development of the national economy. This study focuses on high-tech industries in the eastern, central and western regions of China; a factor-dependent research framework for innovation efficiency improvement in high-tech industries is constructed in China. The fuzzy-set qualitative comparative analysis method (QCA) is used to explore multiple paths to enhance the innovation efficiency of China’s high-tech industries. Then, a GA-PSO-BP neural network is used to construct an optimization model for the enhancement path of technological innovation efficiency, which clarifies the optimal path for the enhancement of innovation efficiency of high-tech industries in the eastern, central and western regions of China. Finally, innovation management strategies for high-tech industries are presented with regional features. The study finds that none of the individual conditions are necessary to promote the innovation efficiency of China’s high-tech industries, and only the linkage effect of the factors can achieve the goal of improving the innovation efficiency level of China’s high-tech industries. There are four configuration paths to improve the innovation efficiency of China’s high-tech industries, which are: “Multinational company (MNC) innovation—economic development—government support”; “MNC innovation—government support”; “economic development—government support”; and “economic development”. The characteristics of regional heterogeneity make differences in the optimal paths of innovation efficiency improvement in high-tech industries in eastern, central and western regions of China.https://www.mdpi.com/2079-8954/11/5/233technological innovation efficiencypath optimizationChina’s high-tech industriesqualitative comparative analysisGA-PSO-BP neural network |
| spellingShingle | Yuanyuan Kou Huiying Chen Kai Liu Yanping Zhou Huajie Xu Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network Systems technological innovation efficiency path optimization China’s high-tech industries qualitative comparative analysis GA-PSO-BP neural network |
| title | Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network |
| title_full | Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network |
| title_fullStr | Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network |
| title_full_unstemmed | Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network |
| title_short | Path Optimization of Technological Innovation Efficiency Improvement in China’s High-Tech Industries Based on QCA and GA-PSO-BP Neural Network |
| title_sort | path optimization of technological innovation efficiency improvement in china s high tech industries based on qca and ga pso bp neural network |
| topic | technological innovation efficiency path optimization China’s high-tech industries qualitative comparative analysis GA-PSO-BP neural network |
| url | https://www.mdpi.com/2079-8954/11/5/233 |
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