Allocation of Environmental Responsibilities in the Prefabricated Construction Supply Chain: Exploring the Influence of Government Subsidies

Abstract

Prefabricated construction has shifted a portion of environmental responsibilities (ERs) from on-site to off-site, prompting a focus on the entire supply chain. As an issue emerging alongside the prefabricated construction, ERs are yet to be clearly allocated along the supply chain. This study aims to explore the optimal allocation of ERs between the agents involved in a prefabricated construction supply chain (PCSC), considering two distinct types of government subsidies, namely, subsidies based on ER levels (EL subsidy) and subsidies based on ER incremental costs (EC subsidy). Additionally, it aims to compare the influence of two types of government subsidies on this allocation process. A three-stage supply-chain Stackelberg model involving the government, a supplier, and a contractor was established to analyze their optimal decisions and a numerical analysis based on a case was further exploited to validate the results. The study revealed a positive correlation between ER levels of the entire supply chain and the ER managerial efficiency of both agents under each type of subsidy. The ER allocation between the two agents varied depending on the subsidy type. With EL subsidies, the allocation of one’s ER level was contingent on its own ER managerial efficiency, while under EC subsidies, the optimal allocation of ERs between the two agents was equal. No subsidy could simultaneously render both agents more profitable than the alternative subsidy, but optimal profits were largely determined by the ER managerial efficiency of the involved agents. By comparing subsidy effectiveness indicators, it was found that EL subsidies are deemed more beneficial for the construction environment than EC subsidies. The findings can serve as a valuable reference for government authorities to incentivize ER behaviors and help enterprises in the supply chain achieve a win-win situation.