Exploring the effectiveness of fashion recommendations made by social media influencers in the centennial generation
Source abstract
Abstract
Previous literature has highlighted the social media influencer’s (SMI’s) credibility as a crucial factor in explaining the persuasive power of recommendations. To date, however, there have been very few studies that have shed light on the role of the audience’s product involvement in mitigating risk and enhancing the authenticity of SMIs’ messages. The present analysis sought to fill this gap, checking whether the relationship between involvement (fashion consciousness), perceived risk, and perceived message authenticity among SMIs’ had an impact on the audience’s attitude and purchase intention. To do so, we present a new exploratory model using an extension of the theory of planned behavior, and we focus on fashion recommendations aimed at the centennial generation. The empirical analysis was carried out on a sample of 690 SMI followers, using partial least squares–structural equation modeling. The results confirmed that high levels of involvement with fashion products improved the perceived authenticity of the recommendations, increased the influence of the social group of belonging, and intensified the power of the recommendations. This paper contributes to the literature by studying a set of variables that have proved relevant to the analysis of influencer marketing. Moreover, as a novelty, the research provides knowledge on the presence of perceived risk and the influence of product involvement on younger consumers. Our results could help managers, marketers, and influencers in the fashion and textile industry. By identifying product involvement as a key construct, we confirmed that the different operators must work on product promotions that appeal to fashion values.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Marketing and Social Media · Consumer Behavior in Brand Consumption and Identification · Environmental Sustainability in Business
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Business Organization, University of Córdoba, Spain
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