An evolutionary game-based simulation study of a multi-agent governance system for smart senior care services in China - Qiannan Shi; Shumian Yang; Na Wang; Shu-e Zhang; Yanping Wang; Bing Wu; Xinyuan Lu; Yining She; Zhihao Yue; Lei Gao; Zhong Zhang (BMC Geriatrics, 2023)
Abstract Background The competing interests of the government, smart senior care technology service providers, and older adults have led to a serious fragmentation of governance in China. This study aims to identify the collaboration mechanisms and evolutionary stabilization strategies for these agents. Methods An evolutionary game model is developed to analyze the strategic decisions made by the government, smart senior care technology service providers, and older adults. A sensitivity analysis is conducted using data from Anhui Province, China, to verify the effects of relevant parameters on the strategy decisions of each agent. Results The results of the simulation and sensitivity analysis indicated that, first, despite changes in the initial willingness values of the tripartite agents, the system eventually converges on 1. Second, the collaboration mechanism of the tripartite agents in the smart senior care system is related to government incentives, penalties, and subsidies, smart senior care service costs, and the additional benefits provided to smart senior care technology service providers. Conclusion The strategy decisions of the government, providers, and older adults interact with each other. To promote collaboration among the tripartite agents and improve governance effectiveness, the government should strengthen the regulations for providers, increase penalties for providers that engage in a breach of trust, provide moderate incentives and subsidies, and control smart senior care service costs.