Modelling children's choice decisions of clothing

Abstract

PurposeThis paper aims to identify the key factors in children's choice of clothing from six to 11‐year‐olds.Design/ methodology/ approachThis exploratory study was developed through a questionnaire answered by 313 children, between the ages of six and 11, from four different schools in Porto (Portugal), covering the private/ state and the rural/urban dimensions. The Logit and Probit binary choice models have been chosen to evaluate the factors that influence children's choice of clothing (proxy), based on a mix constituted by “brand name, functionality and fashion”.FindingsThe results showed that choice is positively related to age, sex, environment, parents' income, self‐esteem, susceptibility to interpersonal influence and utilitarian value (functional value). On the contrary, susceptibility to reference group influence, materialism (materialistic attitudes), ostentatious value and involvement are negatively related to choice.Research limitations/implicationsThe results of the research are limited by the specific sample chosen for this purpose. It is very difficult to generalize the results taking into account all children. The translation and adaptation of the original scales to the case of children and to the Portuguese context may have caused some deviation. The determination of choice was not done directly, as it resulted from a proxy related to the choice of clothing.Practical implicationsRetailers and manufacturers of children's clothing can benefit from the findings of this study. The model developed was applied to the children's choice of clothing. However, it may be tested for a wider universe and applied to other product types.Originality/valueThis study contributes to the literature by studying key factors that affect children's choice of clothing. Based on these results, indications for future research are pointed out: a change in the mix of clothing products available and a characterization of choice types through free, conditional, ordered and multinomial models.