A fuzzy logic apparel size decision methodology for online marketing

Abstract

Purpose Beside the development of technology and accessibility, ease of use, ability to reach various products and compare many products at the same time make online shopping even more popular. Despite the great advantages provided by online shopping for either consumers or retailers, there are certain issues that must be solved to improve online shopping advantages. Finding right size is one of the biggest barriers against apparel online retailing. Since the use of apparels is directly related with fitting, choosing right size is becoming more critical for retailers and consumers. The purpose of this paper is to contribute to the solution of the problem. Design/methodology/approach For the study, the specific size measurements of male shirts (collar, shoulder, chest, waist, arm length in cm) from four different sizes (small, medium, large, x-large) and from eight different brands were collected and stored in a database. Totally, weight, height and body measurements (collar, shoulder, chest, waist and arm length in cm) of 80 male candidates, between the ages of 18 and 35, were measured individually. These data were then used for experiments. Findings Any product with known measurements can be compared with users’ body measurement based on fuzzy logic rule and the best-fitted size can be selected for users. Similarly, using the proposed web design, users are able to see desired products on users with similar body type. Originality/value In this study, a new mathematical method based on fuzzy relations for apparel size finder is proposed. Beside, this method can group users based on body measurements in order to find people with similar size.