Exploring Kansei Perceptions in Lifestyle and Purchasing Priorities

Abstract

This study explores the relationship between lifestyle and purchasing priorities among Chinese consumers. The participants were segmented into four lifestyle types through a survey, and machine learning models were applied to investigate the Kansei factors influencing purchasing decisions. Statistical analysis using multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) identified significant differences in purchasing priorities across lifestyle types. Furthermore, classification models, including tandom forest and shapley additive explanations (SHAP) revealed the key features affecting the decision-making process of each type. These findings provide valuable insights into designing marketing strategies tailored to consumer lifestyles.