Social Commerce Adoption Predictors: A Review and Weight Analysis

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Abstract

Social commerce is a rapidly growing platform of e-commerce that utilises social media and online social interaction to build brand awareness and increase sales. Buying and selling through social media can create a reliable and sustainable platform for buyers and vendors, offering an alternative platform to traditional online approaches. Research on social commerce began to achieve traction in 2006 and has grown since with a significant focus from academics who have offered new insight to many of the key topics. This study seeks to offer an additional contribution to the literature by analysing the predictors of consumer adoption of social commerce from existing studies by employing a weight analysis technique. The analysis considered seven dependent variables (along with their best and worst predictors) that are most frequently examined and are relevant to consumer adoption. The review presented in this study suggests that the intention to purchase is the most frequently examined dependent variable and that trust in the social commerce context is a key factor.

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Sarker, P., Hughe, L., Dwivedi, Y. K., & Rana, N. P. (2020). Social Commerce Adoption Predictors: A Review and Weight Analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12066 LNCS, pp. 176–191). Springer. https://doi.org/10.1007/978-3-030-44999-5_15

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