Agent-based simulation model of panic buying behavior in urban public crisis events: A social network perspective

With the rapid growth of urban economies, accelerated urbanization has resulted in increasing urban public crisis events. The panic buying behavior of the public triggered by these events can seriously endanger social stability and the safety of the urban environment. Therefore, this study aims to explore the evolution of public panic buying behavior in complex urban systems with the intervention of multiple social actors. Based on information filtered from actual cases, this paper identifies 15 stakeholders associated with panic buying in complex urban systems. The complex urban network between the stakeholders is formalized using social network analysis (SNA). To more accurately reflect the evolutionary process of panic buying behavior, this paper proposes an agent-based model (ABM) that simulates five different behavioral states of public and the transition of states to explore the evolutionary process of panic buying behavior under other behavioral decisions of the government and the social media. The model explanation follows the ODD (Overview, Design concepts, Details) protocol. The findings suggest that, prioritizing limited government resources to enhance supply monitoring and responsive attitudes to the public can positively influence public panic buying behavior. At the same time, the social media's willingness to assume its social responsibility and improve information disclosure can further reduce the negative social impact of panic buying.