A socio-technical analysis of factors affecting consumer engagement in livestream shopping: Evidence from structural equation modeling and fuzzy set qualitative comparative analysis

Abstract

Both in China and across the rest of the world, livestream shopping is developing at a considerable rate. Non-transactional consumer engagement has been demonstrated to be essential to the long-term growth of livestream commerce; however, few studies have addressed this topic. Using the socio-technical approach, the present study proposes a theoretical framework to explore the antecedents of non-transactional consumer engagement in livestream commerce. To obtain comprehensive insights into these antecedents, we employed structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) for data analysis. According to the SEM results, multiple cues, personal focus, and identification with streamers all have a positive and significant influence on emotional support and informational support, which in turn lead to greater consumer engagement. However, immediate feedback is associated with informational support, but not with emotional support. The results of fsQCA confirm the importance of the proposed antecedents and provide configurations that increase consumer engagement. The study findings not only enrich the literature regarding livestream shopping but also provide practical insights for practitioners to make consumer engagement strategies based on their own strengths. In addition, this paper demonstrates the feasibility of hybrid methods in the livestream shopping research.