With the intensification of urbanization across China, the underutilization of rural housing resources has emerged as a pressing socio-economic and spatial challenge. To enhance the efficiency of shared rural housing transformation and support rural revitalization strategies, a data-driven framework was developed to identify and prioritize hierarchical user demand attributes. Demand items were initially derived through an extensive literature review and subsequently refined using a modified Kano model, informed by structured questionnaire surveys. To strengthen attribute prioritization and functional alignment, the Importance-Satisfaction (I-S) model and the Configuration Index Model were employed for triangulated classification. Findings revealed that structural safety (A11) constitutes a highly attractive attribute, exerting a strong influence on user satisfaction when addressed, yet inducing minimal dissatisfaction when absent. Smart home (A4) and green materials (A7) were identified as key quality attributes, essential for functional enhancement and user experience optimization. In contrast, cost-effectiveness (A1) and investment return (A2) were classified as high-value-added attributes, playing a pivotal role in decision-making among economically motivated users. New energy utilization (A8) and green design (A9) were categorized as fundamental, non-negotiable attributes, reflecting evolving sustainability expectations. Meanwhile, cultural inheritance (A15) and cultural display (A17) exhibited characteristics of low-attractiveness attributes, indicating limited influence on user satisfaction. Salvage (A10) emerged as a potential quality attribute with latent user recognition. The resulting demand classification elucidates a structured pathway for functional optimization, offering a robust analytical lens for the adaptive transformation of idle rural properties into shared accommodation assets. The applicability of the refined Kano model in rural spatial redevelopment was thereby validated. By integrating multidimensional user preferences and sustainability considerations, this study contributes an empirically grounded decision-support tool for policymakers, designers, and stakeholders engaged in rural land use regeneration and housing innovation. The proposed framework holds significant implications for the sustainable utilization of dormant rural infrastructure within broader urban-rural integration agendas.
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