Drivers of successful luxury fashion brand extensions: cases of complement and transfer extensions

Abstract

Purpose In recent years, brand extension has become a popular and fundamental strategy of most luxury brands. The purpose of this paper is to clarify the factors that affect the success of luxury brand extensions by incorporating luxury brand value perceptions, parent brand attitude, fit perceptions and consumers' product category involvement and innovativeness in a holistic model. The model is tested for two hypothetical luxury brand extensions types: complement and transfer. Design/methodology/approach This study employs a fuzzy-set qualitative comparative analysis (fsQCA) technique to identify the variables that combine to produce a positive or a negative attitude towards luxury brand extensions. The research was conducted on 555 young women professionals (254 for brand extension Type 1 - complement (umbrella); and 301 for brand extension type - transfer (seating furniture), respectively). Findings The results show that perceived fit between the parent brand and extension is a necessary condition for a positive evaluation of both extension types. Other than perceived fit, hedonic and symbolic values and consumer involvement are proven to be necessary antecedent conditions for the evaluation of transfer extensions. This study also proposes several configurations for forming a positive attitude towards each brand extension type and makes implications for luxury managers and further research. Originality/value The results of the research are significant in several ways. First, this study adds to the extant literature by exploring a somehow neglected subject: luxury fashion brand extensions. The study tests a more holistic model than those of previous studies on luxury brand extensions and utilises two different extension contexts adapted from Aaker and Keller (1990). Second, this study is the first to apply fsQCA to identify the factors of luxury brand extension evaluations. fsQCA is highly applicable to large-scale data without the loss of detail or the potential for complexity.