How Artificial Intelligence Influences the Green Transformation of Manufacturing Enterprises: A Dynamic Capabilities Perspective
TL;DR
Micro-level evidence is provided on AI-driven green transformation in manufacturing enterprises from the dynamic capabilities perspective, offering theoretical and practical insights for advancing high-quality transformation of China’s manufacturing sector in the digital-intelligent era.
Abstract
As a strategic general-purpose technology reshaping the manufacturing landscape, artificial intelligence (AI) holds significant potential to drive green transformation. However, how AI translates into green transformation through organizational capabilities has received limited attention. This study examines how AI drives green transformation in manufacturing enterprises through dynamic capabilities—specifically, absorptive, innovative, and adaptive capabilities. Drawing on the resource-based view and dynamic capabilities theory, we develop a theoretical framework positioning these capabilities as the core mediating mechanisms. Using panel data from Chinese manufacturing firms (2012–2023) and text mining with fixed-effects models, we find that AI significantly accelerates green transformation. Mechanism analysis confirms that dynamic capabilities mediate this relationship through three pathways: enhancing absorptive capability, stimulating innovation capability, and improving adaptive capability. Heterogeneity analysis reveals that the effect is stronger in non-state-owned, large-scale, and non-high-tech firms, suggesting that institutional and resource contexts shape AI’s impact. This article provides micro-level evidence on AI-driven green transformation in manufacturing enterprises from the dynamic capabilities perspective, offering theoretical and practical insights for advancing high-quality transformation of China’s manufacturing sector in the digital-intelligent era.