Group consumers' preference recommendation algorithm model for online apparel's colour based on Kansei engineering

Abstract

The sales growth rate of men's plain-colour shirts dropped significantly online in China. Consumers first pay attention to the appearance design of clothing online. It only takes 7 seconds for consumers to determine a product, and the colour in its appearance design accounts for about 67% of the role. Thus, this study took the colour design of men's plain-colour shirts as an example in China, established the basic colour calculation scale and an algorithm model of group consumers' product preferences based on Kansei Engineering and scientific mathematics, to provide new sales ideas and methods for retailers and markets online. Firstly, this study obtained the crucial Kansei word pairs (emotional preferences) and colour design elements through interviews, literature, magazines and websites, word frequency statistics, card sorting and cluster analysis. Then, researchers established a basic colour calculation scale of cross-loading through Kansei Engineering and partial least squares (PLS). Finally, a recommendation set of products is obtained using the analytic hierarchy process (AHP), the weight of Kansei word pairs, and the distance calculation of comprehensive evaluation value based on consumers' emotional needs. That is, this study obtained consumers' aesthetic emotional preference for men's plain-colour shirts in China, colour design elements of shirts that are widely recognized and accepted, basic colour calculation scales, recommendation preferences algorithms and models for group consumers, and verified their effectiveness by PCA.