Research on Identifying and Optimizing Elderly Needs for Smart Elderly Care Service Platforms—An Empirical Analysis of Elderly Users Based on the Kano Model

Abstract To identify, classify, and prioritize elderly users’ perceived needs for smart elderly care service platforms, this study applies the Kano model, mixed category analysis, and the Better-Worse coefficient method to systematically analyze 27 functional requirements. The findings reveal a clear hierarchy among elderly users’ needs. Essential requirements mainly involve basic safety and operational functions and serve as fundamental conditions for user acceptance. Expectant requirements show a linear relationship with user satisfaction and play an important role in improving service experience. Attractive requirements provide additional value by generating positive surprises and enhancing user engagement, whereas indifferent requirements currently have limited effects on user satisfaction. Based on these findings, this study proposes a four-stage optimization framework: ensuring the stability of essential functions, improving the quality of expected services, exploring the potential of attractive features, and reducing redundant functions with limited user value. This study provides empirical evidence and practical guidance for the targeted optimization of smart elderly care service platforms and contributes to a deeper understanding of elderly users’ differentiated needs in the context of digital transformation.