Sustainable ripples: Unveiling contractor knowledge-state transitions and group consensus based on environmental sanction violations.

Sustainable development in the construction industry requires the reduction of ecological disturbances and energy consumption, control of pollution, and adherence to environmental regulations to avoid environmental sanctions. Green knowledge affiliated with environmental compliance spreads from the relationship network to the whole group of contractors, and knowledge gaps are filled via mutual learning and dissemination to promote the implementation of environmentally friendly behavior. This study examined the transfer-diffusion dynamics and evolution of knowledge on environmental violations derived from environmental sanctions in different contractor states. The contributions of different elements to the diffusion process were compared to identify the key factors that reduce the time until contractors reach a green consensus and achieve sustainable construction. Using an improved susceptible–exposed–infectious–recovered model, contractors were characterized as non-informed, informed, spreaders, and forgetters to construct state-transfer paths. In addition, a cellular automaton model was used to demonstrate the diffusion of green knowledge in contractor groups and analyze how state-transfer paths, spreader layouts, and knowledge-reachability neighborhoods affect the diffusion efficiency. Simulations indicated that once knowledge diffusion stabilized, the spreader state was the only remaining state; moreover, differences in the scenario parameters affected the transition rates between each state but not the final proportions of the states. Discrete distribution and spreader influence were positively and significantly correlated to knowledge-diffusion efficiency, whereas the state-transition path had little influence. These findings provide guidance for facilitating the diffusion of green knowledge in the contractor community to reduce environmental damage while avoiding environmental risks to meet the green transformation needs of the construction industry. [Display omitted] • Key factors accelerating reaching a green consensus by contractors were identified • A cellular automaton model was used to demonstrate the diffusion of green knowledge • State-transfer paths were based on non-informed/informed/spreader/forgetter classes • Once knowledge diffusion stabilized, only the spreader state remained • Distribution and spreader influence drove knowledge-diffusion efficiency [ABSTRACT FROM AUTHOR]