The impact of social commerce on the purchase intentions of Millennials using Facebook

  • Received January 31, 2023;
    Accepted May 9, 2023;
    Published June 16, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.19(2).2023.18
  • Article Info
    Volume 19 2023, Issue #2, pp. 223-235
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This work is licensed under a Creative Commons Attribution 4.0 International License

This study examined the impact of social commerce on the purchase intentions of Millennials who use Facebook by exploring how social commerce constructs influence consumer trust. A quantitative research approach was used and data were collected via an ‘online’ survey. The target population was 386 young adults aged 25 to 34 residing in KwaZulu-Natal, South Africa, referred to as Millennials, and comprises the largest group of users on Facebook. Convenience sampling, namely snowball sampling, was used to target participants. It was found that social commerce constructs significantly influence trust, which positively influences consumer purchasing decisions. The results of the study showed that trust explained 68% of the variance in purchasing intentions. Since trust is an integral and vital component of social commerce, the role of social commerce constructs and social support is to build trust in the ‘online’ context and consumers’ intention to buy. This suggests that businesses should monitor the quality and content of the engagements around their brands on social media, as information sharing in social commerce has a significant impact on consumer decisions, i.e., purchase intentions.

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    • Figure 1. Number of hours spent on Facebook within the past month
    • Figure 2. Diagrammatic representation of the structural model
    • Table 1. Factor loadings for purchase intentions
    • Table 2. Factor loadings for social commerce constructs
    • Table 3. Factor loadings for social capital constructs
    • Table 4. Factor loadings for the trust variable
    • Table 5. Fit indices for the initial and the final measurement model
    • Table 6. Fit indices for the structural model
    • Table 7. Reliability of the composite variables of the structural model
    • Table 8. Summary of regression model analyses
    • Table 9. Summary of regression model analyses for mediators
    • Conceptualization
      Krishna K. Govender
    • Methodology
      Krishna K. Govender, Ramnarain Yavisha
    • Resources
      Krishna K. Govender, Ramnarain Yavisha
    • Supervision
      Krishna K. Govender
    • Visualization
      Krishna K. Govender
    • Writing – original draft
      Krishna K. Govender
    • Data curation
      Ramnarain Yavisha
    • Formal Analysis
      Ramnarain Yavisha
    • Investigation
      Ramnarain Yavisha
    • Project administration
      Ramnarain Yavisha
    • Writing – review & editing
      Ramnarain Yavisha