Modeling consumers’ intention to use fashion and beauty subscription-based online services (SOS)
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Abstract
Abstract This study examined one of the new consumption styles of modern consumers, subscription-based online services (SOS), which is often called as box retailing. The purpose of this study was to empirically test six antecedents—utilitarian motivations, hedonic motivations, fashion consciousness, consumer innovativeness, desire for unique products, and online transaction self-efficacy—as predictors of consumers’ attitude toward and intention to use fashion/beauty SOS. The theory of reasoned action was used as a theoretical foundation. With responses from 385 American consumers on an online survey, the theoretical model was tested in the fashion/beauty SOS context using structural equation modeling on LISREL. Results indicated that utilitarian and hedonic motivations, fashion consciousness, and online transaction self-efficacy indirectly influence intention to use fashion/beauty SOS, mediated by attitude towards fashion/beauty SOS. Instead of being mediated by attitude towards fashion/beauty SOS, consumer innovativeness and desire for unique products directly influence intention to use fashion/beauty SOS. Subjective norm positively influences intention to use fashion/beauty SOS. By identifying the factors that can predict consumers’ attitude towards and intention to use this new type of fashion/beauty consumption, this study addresses an evolving trend in home-based shopping behavior. Theoretically, as one of the earliest studies in this phenomenon, this study lays the theoretical groundwork paving way for further exploration in this area. Managers of fashion and beauty SOSs also can utilize these findings to more accurately target the appropriate consumer segment and streamline their marketing messages in accordance.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Consumer Retail Behavior Studies · Consumer Behavior in Brand Consumption and Identification · Digital Marketing and Social Media
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (44)
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