Divergent temporal dynamics: Capturing the link between AI investment intensity and green innovation volatility

Shuili Yang, Lixu Li, Yan Hou, Lujie Chen and C.H. Chao ()
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Shuili Yang: XUT - Xi'an University of Technology
Lixu Li: XUT - Xi'an University of Technology
Yan Hou: XUT - Xi'an University of Technology
Lujie Chen: XJTLU - Xi’an Jiaotong-Liverpool University
C.H. Chao: EM - EMLyon Business School

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Abstract: Firms increasingly adopt artificial intelligence (AI) to advance green innovation. However, despite these efforts, firms display markedly heterogeneous dynamics in their green innovation trajectories, with some sustaining stable progress and others experiencing fluctuating paths. Constructing a panel dataset of 1200 Chinese A-share-listed firms covering 2010–2020, we uncover the mechanisms underlying this divergence. Based on organizational inertia theory, we theorize and empirically validate a U-shaped curvilinear relationship between artificial intelligence investment intensity (AIII) and green innovation volatility (GIV). In addition, we find industry risk flattens this curve, whereas industry opportunity steepens it. Our findings are reinforced through mediation analysis and competing hypothesis examinations. By revealing the variation in GIV across firms with varying AIII levels and clarifying the boundary conditions shaped by industry environments, our study enriches the literature on technology-enabled sustainable operations management and provides actionable guidance for managers and policymakers.

Keywords: Green innovation volatility; Industry risk; Industry opportunity; Organizational inertia theory (search for similar items in EconPapers)
Date: 2026-05-01
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Published in Technovation, 2026, 153, ⟨10.1016/j.technovation.2026.103522⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05531915

DOI: 10.1016/j.technovation.2026.103522

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