A Data-Driven Design Framework for a Smart Wooden Dressing Mirror Integrating PESTEL-Kano-FBS Models

Abstract

In response to the growing demand for smart household products, this study focused on the intelligent design optimization of a wooden dressing mirror that integrates traditional wood craftsmanship with smart home technologies. A data-driven design framework was developed by combining the PESTEL model, Kano demand analysis, and the Function-Behavior-Structure (FBS) model to address the personalized requirements of young single adults. PESTEL analysis identified market opportunities in sustainable wooden products and digital home integration, while the Kano model quantified and categorized user demands. The FBS model then transferred these demands into functional attributes, forming a comprehensive demand–function mapping framework. An empirical study with 16 young single adults employed semi-structured interviews and questionnaires. The results showed that (1) the Kano questionnaire had high reliability and validity (KMO > 0.92, Bartlett’s p < 0.001, Cronbach’s α > 0.92); (2) seventeen needs were classified as Must-be, One-dimensional, Attractive, and Indifferent, with “virtual fitting” showing the highest satisfaction sensitivity (0.734), and (3) the FBS model effectively guided the functional translation into hardware and software. The proposed PESTEL–Kano–FBS framework provides a practical approach for developing sustainable, user-centered smart wooden household products.