LAUSR

In the context of “double carbon”, constructing green supply chains is the only way to implement sustainable development strategies in the manufacturing industry. This paper, therefore, examines the manufacturing supply chain for low-carbon products. More recently, the lack of technical information flow due to data barriers up and down the supply chain has led to high energy consumption, the serious waste of raw materials, and the substandard production of green products. Therefore, the level of supply chain data governance must be improved to enhance the sustainability of the supply chain. By studying blockchain-based data governance and government policy incentives for manufacturing supply chains, this study constructed an evolutionary game model based on prospect theory for the tripartite relation of government, manufacturers, and retailers. The difference between the perceived and actual value was introduced into a three-way evolutionary game model based on prospect theory to optimize the practical implications of the model. The model was then simulated using system dynamics. Through the simulation, it could be concluded that the ability of the three-way evolutionary game to reach the optimal stability point is only related to the sensitivity of the retailer’s perceived value. Additionally, the outcome of the three-way evolutionary game can be unstable, with changes in perceived value sensitivity. Finally, relevant policy recommendations are made. The innovation of this study is establishing a data governance platform that uses data governance to build green supply chains. Additionally, the government was added to the subjects of the game to explore the role of government policy in data governance and sustainable development. In addition, the evolutionary game model was incorporated with prospect theory and traditional expected utility theory, and the rational deficits and preferences of decision makers were taken into account, which brings the results closer to the reality of the situation.