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The impact of social media celebrities' posts and contextual interactions on impulse buying in social commerce.
- Source :
-
Computers in Human Behavior . Feb2021, Vol. 115, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- Social commerce has altered the consumption experience due to various interactive factors. Growing evidence stated that users are prone to buy impulsively in such an environment. Prior studies were limited to demonstrate the emerging role of social media celebrities and embedded social interaction in the context of impulse buying though users encounter them concurrently and frequently while browsing. Hence, this study investigated the influence of celebrities' post authenticity, sentiment polarity, observational learning, and impulse buying tendency following the latent state-trait theory. We have used the data of 452 Pakistani respondents to empirically investigate the research model collected via an online questionnaire from celebrities' community on Facebook. This study employed partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze data. The findings revealed that proposed constructs significantly influence the urge to buy impulsively. Further, impulse buying tendency moderates all relationships except negative sentiments. Unexpectedly, the moderation effects of celebrities' authenticity are insignificant. Furthermore, fsQCA results show the robustness of constructs towards urge to buy impulsively. The theoretical and managerial implications with limitations are provided in the paper. • Social media celebrities post and contextual interaction have a significant impact on impulse buying. • Latent state-trait theory was adopted for the research framework. • PLS-SEM was employed to analyze the data of 452 respondents collected via online questionnaire from Facebook.com. • Impulse buying tendency significantly interacts all relationships except negative sentiments. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 07475632
- Volume :
- 115
- Database :
- Academic Search Index
- Journal :
- Computers in Human Behavior
- Publication Type :
- Academic Journal
- Accession number :
- 147604007
- Full Text :
- https://doi.org/10.1016/j.chb.2019.106178