Application of Gale-Shapley algorithm in optimal matching for healthcare facilities to elderly population: the case of Hangzhou, China

This paper serves as the first empirical research applying the Nobel Prize winning Gale-Shapley algorithm to study optimal stable matching of healthcare facilities to elderly population living in residential neighbourhoods in main urban districts of Hangzhou, China. Through bilateral considerations of supply side attributes of healthcare facilities and demand side preferences of elderly population, this research shows that the Gale-Shapley matching is superior to unilateral spatial or non-spatial utility matching and can optimize stable matching for elderly population in a way similar to the Pareto optimal. Further, this study provides a conceptual model classifying urban spaces for healthcare services at various levels.