Smart community enables a sustainable and livable community future, in which residents’ demands play an important role in its success. Though great efforts have been made to encourage residents’ participation in the implementation of smart communities, inefficient service supply still exists. Thus, this study aimed to classify residents’ demands for community services in smart communities and to explore relevant influencing factors based on the developed conceptual framework. Data from 221 respondents in Xuzhou city of China were analyzed by using binary logistic regression. The results indicated that more than 70% of respondents had demands for all community services in smart communities. Moreover, the demands were influenced by distinct factors, including sociodemographic characteristics, living characteristics, economic characteristics, and individual attitude characteristics. The types of community services in smart communities are clarified and fresh insights are provided into associated factors related to residents’ demands for these services in this study, through which enhanced provision of community services and effective implementation of smart communities can be achieved.

Resource-dependent development worldwide imposes considerable environmental costs and challenges to regional sustainability, particularly through forming coal mining subsidence areas (CMSAs). Nonetheless, villagers’ relocation intentions within the CMSA remain underexplored. Additionally, previous research on individuals’ relocation intentions has predominantly conceptualized it as a dichotomous variable, overlooking its intrinsic elements. This work aims to explore constitutive elements of relocation intention by developing a universal conceptual framework from the perspective of individuals’ subjective preferences and establishing an integrated model for empirical evaluation. This model combines the analytical hierarchy process (AHP), exploratory factor analysis (EFA), technique for order of preference by similarity to ideal solution (TOPSIS), and obstacle degree model (ODM). Data were collected from the Pan’an Lake CMSA in Xuzhou, China. Results identified core elements of villagers’ relocation intentions, including indicators about houses/farmland destruction at origin and housing quality/services at destination. Notably, we discovered a paradox: aspects expected to deter relocation garner greater attention as intention strengthens. This study advances sustainable relocation governance by exploring internal constitutive elements of individual relocation intention rather than defining it as a dichotomous variable. Additionally, it enhances the evaluation efficiency by determining objective indicator weights from the exploratory factor analysis.