Predicting the antecedents of trust in social commerce – A hybrid structural equation modeling with neural network approach

Lai-Ying Leong, Teck-Soon Hew, Keng-Boon Ooi and Alain Yee-Loong Chong

Journal of Business Research, 2020, vol. 110, issue C, 24-40

Abstract: Trust is an essential concern in s-commerce. Though existing research has studied the association between trust and purchasing intention; the determinants of the formation of trust in s-commerce remain largely unexplored. This study examines the determinants of trust in s-commerce based on social presence and social support. Unlike most business research, we applied a hybrid SEM-ANN approach that can detect non-linear and non-compensatory relationships. Linear and compensatory models assume that a shortfall in one factor may be compensated by other factors. However, consumer decision-making processes are complicated and non-compensatory and linear models tend to oversimplify these processes. Criterion sampling was used to gather 462 datasets of social commerce users using a mall intercept technique. Information support has the strongest effect followed by the social presence of interaction with the sellers, income and social presence of others. The integrated model predicts 76.9% trust in s-commerce. Theoretical and managerial contributions are discussed.

Keywords: Trust; Social commerce; Social Presence Theory; Social Support Theory; Artificial neural network (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:110:y:2020:i:c:p:24-40

DOI: 10.1016/j.jbusres.2019.11.056

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