AI and green transformation: the mediating role of operational efficiency in Chinese manufacturing

How Artificial Intelligence Influences the Green Transformation of Manufacturing Enterprises: A Dynamic Capabilities Perspective

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.

Turning regulation into sustainability performance: the role of AI-enabled absorptive capacity in manufacturing firms

This study aims to examine how government regulations are translated into sustainability performance in manufacturing firms by investigating the mediating roles of artificial intelligence (AI) capabilities and absorptive capacity. Drawing on institutional theory and the resource-based view, it explains how regulatory pressure stimulates internal digital capability development and knowledge-processing mechanisms rather than directly improving sustainability outcomes. Data were collected from 297 managers and senior executives in Vietnamese manufacturing firms. The proposed research model was tested using partial least squares-structural equation modeling. The results show that government regulations do not have a significant direct effect on sustainability performance but significantly enhance AI capabilities. AI capabilities, in turn, positively affect sustainability performance and both dimensions of absorptive capacity. Potential absorptive capacity significantly improves sustainability performance, whereas realized absorptive capacity has no significant direct effect. These findings reveal asymmetric effects of absorptive capacity: firms appear better able to acquire and assimilate external knowledge than to convert it into measurable sustainability outcomes. This study contributes to competitiveness and sustainability research by showing that government regulations enhance sustainability performance indirectly through AI-enabled knowledge capabilities. It reconceptualizes AI capabilities as a higher-order strategic resource that strengthens sustainable competitiveness in manufacturing firms, while highlighting possible implementation barriers to converting knowledge into performance.

Unlocking Sustainability in Manufacturing SMEs: Synergizing BDA–AI, Green Supply Chain Practices, Green Innovation, and Organizational Green Culture

Growing pressures for environmental responsibility have intensified the need for manufacturing SMEs to pursue sustainability as a core strategic priority, especially as these firms often operate under severe resource constraints. In this context, firms increasingly adopt advanced digital technologies such as big data analytics–artificial intelligence to strengthen their environmental, social, and economic performance. Guided by the Resource‐Based View (RBV), this study contributes to the ongoing discussion on how digital technologies support sustainable development by proposing the mediating roles of green supply chain management and green innovation in the relationship between BDA–AI capability and sustainable performance. The study further examines whether organizational green culture enhances the ability of BDA–AI to foster green capabilities. Using survey data from 388 Chinese manufacturing SMEs and structural equation modeling through SmartPLS, the findings show that BDA–AI significantly improves GSCM, GI, and sustainable performance. Mediation results confirm that GSCM and GI act as essential mechanisms through which BDA–AI generates environmental and operational benefits. However, the moderating influence of OGC is uneven: it significantly strengthens the pathway from BDA–AI to GI, whereas its effect on the BDA–AI to GSCM relationship remains insignificant. These insights highlight that digital adoption alone is insufficient; sustainability gains emerge when technological investment is accompanied by strong green capabilities and supportive cultural values.

From compliance to transformation: how ESG performance drives firm green transformation

This study examines whether environmental, social, and governance performance promotes firm green transformation in China's emerging economy context, and explains how ESG engagement moves beyond symbolic legitimacy toward organizational change. It conceptualizes green transformation as a dual process that combines green innovation with efficiency upgrading, thereby linking external sustainability pressures to firms’ internal innovation capabilities and productivity improvements. By focusing on Chinese A-share listed firms, the study aims to clarify the firm-level mechanisms through which ESG performance affects independently developed green technologies, collaborative green innovation, and total factor productivity, while identifying the organizational conditions that strengthen or weaken these effects. The study uses an unbalanced panel of Chinese A-share listed firms from 2015 to 2024. Green transformation is measured through independently filed green patents, jointly filed green patents, and total factor productivity estimated using the Levinsohn–Petrin approach. Baseline fixed-effects models are employed to estimate the relationship between ESG performance and green transformation. To address selection bias and dynamic endogeneity, the analysis further applies propensity score matching combined with fixed effects and system GMM estimations. Robustness tests use alternative ESG ratings and alternative green transformation measures. Mechanism and heterogeneity analyses examine internal channels and conditional firm characteristics in greater empirical detail. The results show that higher ESG performance significantly promotes all three dimensions of firm green transformation: independent green innovation, collaborative green innovation, and productivity upgrading. These findings remain robust across matching-based fixed-effects models, system GMM estimations, alternative ESG ratings, and alternative outcome measures. Mechanism tests reveal that ESG facilitates green transformation by expanding innovation human capital, improving internal control quality, and shaping firms’ financing conditions. Heterogeneity analyses indicate that the positive effect of ESG is stronger among tech-intensive firms and small firms, suggesting that absorptive capacity and marginal legitimacy gains condition the effectiveness of ESG engagement in China’s institutional context. This study offers value by reframing ESG as an internal transformation capability rather than a disclosure or legitimacy device. It advances ESG research by unpacking three firm-level transmission mechanisms—innovation human capital, internal control quality, and financing conditions—through which ESG supports green innovation and productivity upgrading. It also broadens green transformation measurement by combining independent green patents, joint green patents, and Levinsohn–Petrin total factor productivity. Focusing on Chinese A-share firms, the study provides context-sensitive evidence from an emerging economy and shows that ESG effects vary by technological intensity and firm size, offering implications for differentiated sustainability governance and investment.

Driving Green Innovation for Sustainable Manufacturing: The Roles of Dynamic Capabilities, Green Core Competence, and Green Organizational Culture

This study examines how firms convert dynamic capabilities into green innovation (GI) by developing green core competence (GCC). Drawing on resource-based theory and dynamic capability theory and incorporating core competence logic, the study investigates the direct effects of absorptive capacity (AC) and technological capability (TC) on GI, the mediating role of GCC, and the moderating role of green organizational culture (GOC) in the capability-to-competence process. Survey data were collected from 324 managers in China’s electronic information manufacturing industry, a technology-intensive sector facing pressures for technological upgrading and environmental improvement. Partial least squares structural equation modeling was used to test the proposed mediation and moderation model. The results show that AC and TC both positively affect GI and GCC, while TC has stronger effects. GCC positively affects GI and partially mediates the relationships between AC and GI and between TC and GI. GOC further strengthens the positive effects of AC and TC on GCC. These findings suggest that GI depends not only on the possession of dynamic capabilities but also on their conversion into a green-specific competence base. The study offers a contextualized explanation of how technology-intensive manufacturing firms organize internal capabilities to support sustainable manufacturing practices.

Smarter factories, greener futures: does intelligent manufacturing enhance ESG performance in Chinese firms?