A proposed Human-AI collaborative Kansei Engineering methodology for heritage-inspired designs: a study using surveying and eye-tracking with Africans and Asians

Product design extends beyond functionality, acting as a visual and emotional interface that shapes customer perception and decision-making. Aligning product conceptual design with users’ demographic identity through Kansei Engineering enhances emotional engagement and appeal. This study explores the impact of integrating heritage-inspired elements into product design on socio-psychological perception, engagement, and preferences. Two hypotheses are examined: (1) customer-centric designs aligned with national identity are more engaging and preferred by their community, and (2) natural motifs are perceived as simpler and more appealing than cultural themes in daily-use products. The study began with questionnaire-based surveys to verify demographic-emotional preferences and establish study’s relevance. Subsequently, AI-generated heritage designs were created using demographic motifs and validated through Probability Match Ratio, guided by Kansei Engineering principles. Eye-tracking metrics; fixation frequency, fixation duration, and scan paths assessment are conducted to assess visual engagement, cognitive processing, and design preferences. A full factorial experiment was conducted to assess the effect of nationality, gender, design demography, and themes revealing a significant impact on visual behaviour and purchasing decisions across Africans and Asians. This study contributes to the Human-AI collaborative generative design by integrating Kansei Engineering principles to demonstrate how co-creation grounded in sociopsychology can enhance user engagement and product acceptance.