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Unpacking Boundary-Spanning Search and Green Innovation for Sustainability: The Role of AI Capabilities in the Chinese Manufacturing Industry

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  • Yutong Sun

    (School of Economics and Management, Taiyuan University of Technology, Jinzhong 030600, China)

  • Meili Zhang

    (School of Economics and Management, Taiyuan University of Technology, Jinzhong 030600, China)

  • Jingping Chang

    (School of Economics and Management, Taiyuan University of Technology, Jinzhong 030600, China)

  • Chenggang Wang

    (School of Economics and Business Administration, Heilongjiang University, Harbin 150001, China)

Abstract

Achieving the dual carbon goal and addressing escalating environmental challenges requires that manufacturing enterprises in China must pursue sustainability via green innovation strategies. A key rationale for green innovation is to overcome boundaries and acquire knowledge through boundary-spanning search. Additionally, leveraging artificial intelligence (AI) capabilities provides technical support throughout the innovation process. Thus, both boundary-spanning search and AI capabilities are crucial for achieving sustainability objectives. Drawing on organizational search and knowledge management theories, this paper aims to analyze how dual boundary-spanning search affects sustainability performance and green innovation. It also examines the moderating role of AI capabilities and constructs a moderated mediation model. We analyzed questionnaire data collected from 171 Chinese manufacturing companies over a 13-month period, employing hierarchical regression and bootstrap sampling methods using SPSS 27.0. Our findings reveal that both prospective and responsive boundary-spanning searches significantly enhance corporate sustainability performance. Furthermore, green innovation acts as a positive partial mediator between dual boundary-spanning search and corporate sustainability performance. Notably, AI capabilities positively moderate the relationship between dual boundary-spanning search and green innovation. They also strengthen the mediating effect of green innovation on the link between dual boundary-spanning search and corporate sustainability performance. Based on these findings, more resources should be allocated to boundary-spanning search while encouraging enterprises to pursue green innovation and develop AI capabilities. These efforts will provide robust support for sustainability performance in the manufacturing sector.

Suggested Citation

  • Yutong Sun & Meili Zhang & Jingping Chang & Chenggang Wang, 2025. "Unpacking Boundary-Spanning Search and Green Innovation for Sustainability: The Role of AI Capabilities in the Chinese Manufacturing Industry," Sustainability, MDPI, vol. 17(14), pages 1-26, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6439-:d:1701311
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