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As China is characterized by a large ageing population, and its rapid speed of ageing, urbanization, and socio-economic transformation, the senior service issue is both typical and urgent. To support the urban planning and decision-making of relevant policies for senior services, which is significantly challenging, this research employs the multi-agent simulation (MAS) approach to simulate the complicated process of Chinese senior service provision. The approach defines the elderly, day-care centers, and residential aged care facilities (RACF) as the kernel agents, determines the behavior rules of different agents, and confirms the interaction between agents, individual agents and urban environments. Altogether nine simulation modules were designed and integrated. This study focuses on the diversifying elderly population, complexity of the senior services system, and the uncertainty of the developing background. Seniors’ socio-economic attributes such as income, family structure, education and hukou status, day-care center, and RACF agents’ characteristics, such as price, location, service standard, public /private status, were emphasized at a microscopic scale. Using a bottom-up approach, neighborhood differentiation was considered the main determinant of senior service needs. Through the design of different policy-scenarios, critical parameters were determined to have the most important influence on senior service needs and their provision. The regulation of these crucial indicators will be a great scientific support to the planning of provisions for senior service facilities and to the decision-making of environmental improvement policies in different urban neighborhoods. The MAS approach is recognized as a modelling paradigm for capturing the dynamics of complex systems. This research is especially useful for supporting the provision of elderly service facilities and the environmental improvement of livable urban neighborhoods through future urban planning.

Prospective living arrangement of China's urban elderly and development of an Agent-based Simulation (ABS) model for elderly care needs