Exploration of Smart Elderly Service Supply and Demand Matching for Multi-source Data

Under the background of population aging, the rational use of resources for senior care services has more difficulty, leading to increasingly prominent conflicts between supply and demand. This paper uses the Gini coefficient, cohort effect, and other methods to build a matching supply and demand model for innovative senior care services based on the multi-source data of senior care services. The probabilistic linguistic term set is used for evaluation and a calculation method is proposed to match satisfaction. The model’s feasibility is demonstrated by analyzing arithmetic examples. Five types of senior care demand groups can be obtained through clustering analysis, with three kinds of intelligent senior care, namely, competent institutions, smart communities, and smart homes, in which the Gini coefficient value of community senior care facilities in X city is 0.4203, and there is an imbalance between supply and demand. The method proposed in this paper identifies five types of elderly groups, which can be matched with different innovative senior care services for elderly groups with distinct characteristics.