On Feasible and Stable Spatial Matching Of Urban Healthcare Facilities and Population

Abstract: As an essential type of public facility for quality urban living, healthcare facilities in cities face an optimal utilization problem for their services. The nature of this problem is primarily due to mismatch between healthcare facilities and their intended population, leading to unstable healthcare services to underserved or overserved population. This research establishes a novel methodology for stable spatial matching from a behavioral perspective and applies the well-known two-sided matching theory considering key factors, such as location, level, price, and preference, to better analyze and plan healthcare facilities for population. Various feasible and stable spatial matching results based on utility trade-offs among factors are investigated with respect to healthcare services and population choices. The methodology and matchings are empirically tested for the City of Hangzhou, China, with 588 primary healthcare facilities and 320 residential communities. The results show that feasible and stable spatial matchings reflecting trade-offs do exist, yet vary depending on specific factors and preferences. The overall utility of feasible and stable spatial matching is greater for the population side when the substitutability among choices increases. Furthermore, while most matched pairs change due to the shifting of preferences, some pairs are consistently matched after at least five rounds of matching. Compared with all feasible matchings, these unchanged pairs are relatively concentrated in central urban areas with shorter spatial distances, lower housing prices per unit of living space, and comparable total utilities for corresponding communities. Accordingly, sound spatial planning strategies are proposed for healthcare facilities and residential communities in Hangzhou.

Recommended citation: Huang, Lepeng and Shen, Guoqiang and Zhang, Kexun and Coursey, David, On Feasible and Stable Spatial Matching Of Urban Healthcare Facilities and Population (January 30, 2024). Available at SSRN: https://ssrn.com/abstract=4751132 or http://dx.doi.org/10.2139/ssrn.4751132
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