Evolution of residents' cooperative behavior in neighborhood renewal: An agent-based computational approach

Abstract

The cooperative behavior of residents is complex and influenced by their complicated social relationships. This complexity is especially noticeable in neighborhood renewal, so the government does not know how to promote residents' cooperative behavior. Therefore, this study proposes an agent-based model (ABM) to investigate the development of residents' cooperative behavior in neighborhood renewal. Based on a questionnaire survey among residents of old neighborhoods in China, the parameters of ABM were determined in this study. Then, controlled experiments were conducted to investigate the effects of general trust among residents and government control of neighborhood renewal on cooperation patterns in renewal projects. In addition, this study examines the effects of different types of social network structures (small-world, scale-free, and random networks) on the evolution of residents' cooperative behaviors. The simulation results show that when residents' initial willingness to agree to renewal projects is high, their close social relationships need to be managed by the government to achieve better outcomes. Conversely, if initial willingness is low, residents' close relationships may pose a challenge to the government. In addition, government-led renewal projects should be encouraged to a greater extent. This study confirms that the different social network structures have an influence on the development of residents' cooperative behavior. The results of this study provide concrete evidence for understanding the factors that contribute to the emergence of residents' cooperative behavior and for studying the effects of government intervention on neighborhood renewal projects. In addition, the results of this study provide theoretical support for future studies of residents' social network structures.