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Effect of Social Presence toward Livestream E-Commerce on Consumers’ Purchase Intention

Author

Listed:
  • Li-Ru Chen

    (Department of Industrial Education and Technology, National Changhua University of Education, Changhua 50074, Taiwan)

  • Farn-Shing Chen

    (Department of Automation Engineering and Institute of Mechatronoptic Systems, Chienkuo Technology University, Changhua 500020, Taiwan)

  • Der-Fa Chen

    (Department of Industrial Education and Technology, National Changhua University of Education, Changhua 50074, Taiwan)

Abstract

The booming development of livestream e-commerce has attracted considerable academic attention, but research on how social presence affects consumers’ purchase decisions is limited. To this end, this article proposed a theoretical framework for the influence of social presence on consumers’ purchasing decisions based on social presence theory. In this study, structural equation modeling was carried out on 390 data collected from a questionnaire to verify the mechanisms by which social presence influences purchase intention. The study found that social presence enhances consumer identification, which in turn enhances consumers’ purchase intention. Meanwhile, this study not only verified the mediating role of consumer identification but also tested the positive moderating role of self-improvement by livestream e-commerce. This study found that a live streaming host’s social presence influences the consumers’ purchase behavior, and it provides decision support for companies to sell products through livestreaming platforms, which has important theoretical significance and practical application value.

Suggested Citation

  • Li-Ru Chen & Farn-Shing Chen & Der-Fa Chen, 2023. "Effect of Social Presence toward Livestream E-Commerce on Consumers’ Purchase Intention," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3571-:d:1069144
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    References listed on IDEAS

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    Cited by:

    1. Xiong Xiong & Fan Yang & Li Su, 2023. "Popularity, face and voice: Predicting and interpreting livestreamers' retail performance using machine learning techniques," Papers 2310.19200, arXiv.org.

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