Green technology transfer for firms in a multi-layer network perspective: The dual impact of knowledge resources and regional environment

Green technology transfer has become a critical approach for energy conservation and emission reduction. This study examines how micro-level knowledge resources and macro-level regional environments jointly influence firms' green technology transfer processes. Drawing on social network theory, resource-based theory, and regional innovation system theory, this study constructs a multi-layer network model that integrates knowledge elements, firms, and cities. We employ the Exponential Random Graph Model (ERGM) to analyze the mechanisms influencing inter-firm green technology transfer. The findings show that, at the micro level, knowledge diversity promotes technology adoption but hinders technology output; specialized knowledge enhances technology adoption; firms' knowledge combined potential and knowledge uniqueness weaken their ability to absorb external technology but facilitate outbound technology transfer. At the macro level, geographical distance significantly hinders technology transfer. In summary, firms' green technology transfer is constrained by both knowledge resources and geographical proximity. This study provides a theoretical foundation for enterprises to optimize knowledge management strategies and for policymakers to enhance technology transfer support systems. By integrating micro-level knowledge resource systems and macro-level regional environments into a unified network model, the study overcomes the limitations of traditional single-level analyses and broadens the scope of technology transfer research by incorporating a multidimensional perspective. • A multi-layer network links knowledge, firms, and cities in green tech transfer. • Knowledge traits have dual impacts on green technology transfer. • Geographical distances constrain green technology transfer. • A multi-level framework reveals green technology transfer mechanisms.