Digital disruption, knowledge and collaborative networks and green innovation in China manufacturing transformation

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-04-16 DOI:10.1016/j.techfore.2025.124120

Yao Xiao , Rong Xiang , Yong-lei Sun , Jin Chen , Yun-hong Hao

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引用次数: 0

Abstract

Green innovation is essential for sustainable development but often incurs high costs, reducing economic returns. Grounded in disruptive innovation and social network theory, this study examines whether disruptive events experienced by Chinese manufacturing firms during their digital transformation can reduce green R&D and manufacturing costs, thereby promoting green innovation. Using patent data from China's high-tech manufacturing sector (2014–2023), the study finds an inverted U-shaped relationship between Digital Disruptive Events (DDE) and Green Innovation (GI). The network structure of knowledge and collaboration plays varying moderating roles in this relationship. Structural holes in a firm's knowledge network negatively moderate the effect of DDE on GI, while degree centrality shows no significant moderation. Conversely, more structural holes and lower degree centrality in collaboration networks positively influence GI. The findings highlight the importance of leveraging multilayered network structures to drive green innovation during digital transformation.

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中国制造业转型中的数字化颠覆、知识与协同网络与绿色创新

绿色创新对可持续发展至关重要，但往往成本高昂，降低了经济回报。本研究以颠覆性创新和社会网络理论为基础，探讨中国制造业企业在数字化转型过程中所经历的颠覆性事件是否能够降低绿色研发和制造成本，从而促进绿色创新。利用2014-2023年中国高技术制造业的专利数据，研究发现数字颠覆事件（DDE）与绿色创新（GI）之间存在倒u型关系。知识和协作的网络结构在这一关系中起着不同的调节作用。企业知识网络的结构孔负向调节DDE对GI的影响，而度中心性无显著调节作用。相反，协作网络中结构孔多、中心性低对GI有正向影响。研究结果强调了在数字化转型过程中利用多层网络结构推动绿色创新的重要性。

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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