Consumer-expressed needs concerning age-friendly products in China: a computational grounded theory analysis of online reviews.

PURPOSE: As population aging in China continues to intensify, age-friendly products play an increasingly important role in supporting older adults' quality of life and advancing the smart senior care industry. However, existing studies predominantly rely on traditional methods, such as questionnaires and interviews, to identify user needs, with limited systematic investigation of needs expressed in real-world product contexts. To address this gap, this study analyzes consumer expressions in online reviews from Chinese e-commerce platforms and adopts computational grounded theory to identify and conceptualize user needs concerning age-friendly products. METHODS: A total of 17,133 reviews concerning 66 age-friendly products were collected from Taobao and Tmall. The corpus may include reviews written by older product users, family purchasers, caregivers, institutional staff, and other consumers. After data preprocessing, a computational grounded theory approach was applied through a three-stage analytical procedure comprising pattern detection, pattern refinement, and pattern confirmation. RESULTS: The analysis identified 8 main categories and 28 basic categories of user needs derived from consumer reviews concerning age-friendly products. These categories were organized into a four-layer conceptual framework comprising the foundational assurance layer, core utility layer, adaptation support layer, and value-oriented vision layer. CONCLUSION: By analyzing naturally occurring online reviews, this study broadens the data sources and contextual scope of user needs research concerning age-friendly products. The four-layer framework distinguishes the complementary roles of assurance, practical utility, adaptation support, and value evaluation across product acquisition, everyday use, caregiving, and service contexts. The application of computational grounded theory to user-generated content not only provides a systematic approach for uncovering latent user needs, but also offers actionable insights for the design and optimization of age-friendly products, as well as for the advancement of the smart senior care industry.