Networked evolutionary game analysis of low-carbon technology diffusion

Developing and deploying low carbon technology is essential for alleviating energy poverty and mitigating environmental pressures, with enterprises serving as critical actors in this transition. To explore the determinants of low carbon technology adoption and diffusion among enterprises, this study constructs a complex network evolutionary game model that integrates behavioral mechanisms and incentive structures. The model examines how behavioral factors, including herd behavior and organizational inertia, together with incentive factors such as policy, economic, social, and technological drivers, shape the diffusion dynamics. The results reveal three key findings: (1) Direct policy incentives and demand-side drivers, such as subsidies and consumer green preferences, exert a stronger and more immediate influence on low-carbon technology adoption than indirect regulatory measures, particularly in the early stages of diffusion. (2) Behavioral factors exhibit asymmetric effects: herd behavior can impede early adoption when participation is low, whereas moderate organizational inertia stabilizes long-term adoption once diffusion takes hold. (3) Policy incentives, market demand, and social supervision interact in a nonlinear and partially substitutable manner, indicating that coordinated policy mixes can significantly accelerate diffusion across enterprise networks. The results suggest that policy and demand-side drivers play a dominant role in accelerating LCT diffusion, while behavioral and social factors primarily influence the timing and stability of adoption. Overall, the study provides an analytical perspective on the role of LCT diffusion in supporting enterprise-level green transformation.