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TAM Model Evidence for Online Social Commerce Purchase Intention

Author

Listed:
  • Zhang Ying

    (School of Economics and Management, Beijing University of Posts and Telecommunications, China)

  • Zeng Jianqiu

    (School of Economics and Management, Beijing University of Posts and Telecommunications, China)

  • Umair Akram

    (Guanghua School of Managment, Peking University, China)

  • Hassan Rasool

    (Department of Business Studies, Pakistan Institute of Develpment Economics, Pakistan)

Abstract

The aim of this research is to use the Technology Acceptance Model (TAM) to investigate the potential antecedents of online purchase intention in social commerce environments. Data were collected from 513 online survey participants in China. Structural Equation Modeling (SEM) techniques was used to test the study hypotheses. The findings reveal that website quality, trust, and electronic Word Of Mouth (eWOM) positively influence online purchase intentions. Furthermore, perceived ease of use and perceived usefulness significantly and positively moderate the relationship between website quality and online purchase intention. These survey results help provide a more comprehensive understanding of online purchase intentions in social commerce in China. The findings and conclusion address notable implications for theory and managers.

Suggested Citation

  • Zhang Ying & Zeng Jianqiu & Umair Akram & Hassan Rasool, 2021. "TAM Model Evidence for Online Social Commerce Purchase Intention," Information Resources Management Journal (IRMJ), IGI Global, vol. 34(1), pages 86-108, January.
    • Handle: RePEc:igg:rmj000:v:34:y:2021:i:1:p:86-108
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    Cited by:

    1. Faruk Ahmeti & Hykmete Bajrami, 2024. "Exploring the Impact of Technology Acceptance Model Constructs on Consumer Behavior in SMEs: with A focus on E-Marketing Strategies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 66-88.
    2. Jorge Serrano-Malebran & Cristian Vidal-Silva & Iván Veas-González, 2023. "Social Media Marketing as a Segmentation Tool," Sustainability, MDPI, vol. 15(2), pages 1-16, January.

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