Satisfying the growing care demands of the elderly has become a major policy issue under the trend of rapidly aging of the population, especially in developing countries. Although the market-oriented transformation on the supply side is a sustainable way to cope with the pressing demands of elderly care in the long term, the conflict between private and public interests seriously impedes the transformation process in its early stage. From the perspective of maximizing social welfare, this study took the specific situation of China as an example and applied a Stackelberg game model to explore the optimal transformation policy that can balance such conflict of interests. By comparing the effects of two forms of subsidy in China, the results first theoretically verified the importance of subsidy in stimulating the private supply of elderly care, and then emphasized that the size of the gap between supply and demand is the fulcrum of differentiated subsidy, which determines the optimal policy for the development of the elderly care market (ECM) in each aging region. Additionally, the study showed that in the process of market-oriented transformation, the government’s positive response to the demands and preferences of the public, the establishment of market supervision measures, and the increase in the elderly’s affordability all play important roles in improving social welfare. These findings not only have policy implications for the marketization of elderly care in China, but also provide meaningful references for other developing countries in the word that are experiencing or about to experience elderly care problems.

Education has become one of the important drivers of residential mobility. The school district system in China has transformed school choice into a competition for housing ownership based on family capital, resulting in the capitalization of education and gentrification. Understanding the patterns of education-driven residential mobility is therefore of significant importance for urban planning, educational policy and social equity research. In this study, we depicted and analyzed the heterogeneity of residential mobility formed by the interaction of schooling choice, diversity of family characteristics, and housing preferences. Based on the household questionnaire survey conducted in Tianjin, we identified five typical education-driven residential mobility patterns by using the K-Prototype clustering algorithm. The empirical results implied that in China, particularly in megacities like Tianjin with a strict school district system tied to housing, wealthy families approach high-quality education through their socio-economic advantages for cultural reproduction; families sacrifice living conditions to access leading schools by acquiring old second-hand housing or smaller new-commercial housing; lower-income families relocate to within a short distance of the city center to change home ownership status for basic school eligibility; and families opting out of school districts achieve residential improvements and display greater locational diversity in relocation. Education-driven residential mobility is reshaping urban space, and may intensify socio-spatial stratification, even influencing long-term urban sustainability through patterns of resource allocation, neighborhood stability, and social equity. While this study focuses on Tianjin, the impacts of such school-housing-linked policies hold broader relevance for global cities facing similar challenges.