Design Evaluation of Smart Shopping Carts for the Elderly

As global population aging intensifies, elderly users are increasingly becoming an important focus in retail service design. However, most existing smart shopping carts fail to fully consider the behavioral characteristics, cognitive limitations, and operational demands of older adults, resulting in reduced usability and adoption rates. To address this issue, this study proposes a design evaluation method based on Cumulative Prospect Theory (CPT), aiming to integrate psychological mechanisms such as reference dependence, loss aversion, and probability weighting into product assessment. By combining the Analytic Hierarchy Process (AHP) with the entropy weight method, a hybrid multi-criteria evaluation framework is constructed to enhance both subjective rationality and data-driven objectivity. Expert scoring, user testing, and CPT-based evaluation were conducted to compare three elderly-oriented smart shopping cart design concepts, and the findings were further validated using the Post-Study System Usability Questionnaire (PSSUQ). Results indicate that the proposed method effectively reduces subjective bias, improves evaluation reliability, and provides practical guidance for optimizing age-friendly product design. This study therefore offers both theoretical insights and methodological support for advancing inclusive design practices.