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Further Exploration on the Path of Improving Enterprise Innovation Performance through Open Innovation: Based on Quality Management and Binary Learning Perspective
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Yingying Fang1, 2, Zhen Yang3, 4, Ruonan Cao5
Journal of Technology Economics | 2025, 44(5) : 108 - 120
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Journal of Technology Economics | 2025, 44(5): 108-120
Technology Economics Evaluation
Further Exploration on the Path of Improving Enterprise Innovation Performance through Open Innovation: Based on Quality Management and Binary Learning Perspective
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Yingying Fang1, 2, Zhen Yang3, 4, Ruonan Cao5
Affiliations
  • 1 China Center for International Economic Exchanges, Beijing 100008, China
  • 2 Huanghuai University, Zhumadian 463000, China
  • 3 Institute of Industrial Economics of CASS, Beijing 100006, China
  • 4 Research Center for Technological Innovation, Tsinghua University, Beijing 100091, China
  • 5 China Academy of Industrial Internet, Beijing 100872, China
Published: 2025-05-25 doi: 10.12404/j.issn.1002-980X.J24052809
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High-quality development is the theme of China's economic and social development during the 14th Five-Year Plan period and beyond. Quality is the foundation of establishing a business and the strategy for strengthening the country, as well as the key element and necessary condition for achieving high-quality development in China. Accelerating the construction of a quality powerhouse and improving the level and competitiveness of China's quality development are strategic choices to promote high-quality development. Enterprises are the micro-foundation for reshaping high-quality development and the main body responsible for building a quality powerhouse, while enterprise innovation is crucial for solving the aforementioned challenges. Open innovation can help enterprises break through boundary restrictions, broaden resource bases, and promote the improvement of enterprise innovation performance through knowledge sharing and collaborative innovation. Meanwhile, organizational ambidexterity has gradually become a key factor driving enterprise innovation and achieving technological catch-up and surpassing. Based on the 2018 data of Chinese industrial enterprises, stepwise regression, Sobel test, and Bootstrap test methods were used for empirical verification. The results reveal that open innovation effectively promotes enterprise innovation performance through both knowledge sharing and collaborative innovation, with collaborative innovation having a more significant promoting effect. Open innovation also indirectly affects innovation performance by enhancing enterprise quality management capabilities. The research on the mechanism of open innovation's impact on enterprise innovation performance is expanded from the perspective of quality management at the theoretical level. In practice, the mechanisms through which Chinese manufacturing enterprises enhance innovation performance via open innovation are extended, providing important support and guidance for enterprises to optimize quality management and maximize the outcomes of open innovation practices.

open innovation  /  innovation performance  /  quality management  /  binary learning
Yingying Fang, Zhen Yang, Ruonan Cao. Further Exploration on the Path of Improving Enterprise Innovation Performance through Open Innovation: Based on Quality Management and Binary Learning Perspective[J]. Journal of Technology Economics, 2025 , 44 (5) : 108 -120 . DOI: 10.12404/j.issn.1002-980X.J24052809
Year 2025 volume 44 Issue 5
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doi: 10.12404/j.issn.1002-980X.J24052809
  • Receive Date:2024-05-28
  • Online Date:2025-07-04
  • Published:2025-05-25
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  • Received:2024-05-28
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Affiliations
    1 China Center for International Economic Exchanges, Beijing 100008, China
    2 Huanghuai University, Zhumadian 463000, China
    3 Institute of Industrial Economics of CASS, Beijing 100006, China
    4 Research Center for Technological Innovation, Tsinghua University, Beijing 100091, China
    5 China Academy of Industrial Internet, Beijing 100872, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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