A-Kano and BCXmotifs-based Biclustering of Services and Elders in Smart Home Elderly Care

Smart home-based elderly care is a novel approach for China to actively respond to population aging and address the growing demand for large-scale and high-quality elderly care. Under this mode, the service population is vast and the needs are complex and diverse. Accurately identifying the types of needs and effectively segmenting the elderly population are key to addressing the current mismatch between supply and demand in smart home-based elderly care services. To this end, this paper proposes a biclustering analysis method for elderly population and services based on the A-Kano model and the BCXmotifs algorithm. First, to address the subjectivity issue of the traditional Kano model in demand classification, A-Kano indicators and classifiers are developed to achieve precise identification of demand types for smart home-based elderly care services. Second, to overcome the limitations of existing biclustering algorithms such as BiMax and BCCC, which either only handle binary data or rely on similarity-based clustering, a BCXmotifs algorithm is designed for biclustering analysis to obtain elderly groups with the same demand structures and types. Finally, taking the elderly residents in a city of Shandong Province as the study object, effectiveness of the proposed model and method is empirically verified and a sensitivity analysis is conducted.