The S-O-R framework in action: The impact of source credibility, interactivity, and perceived usefulness on consumer engagement and trust in live streaming commerce

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The emergence of live-streaming commerce has significantly altered the purchasing patterns of consumers, and it has become a critical component of e-commerce and marketing, specifically during the pandemic. This study investigates how customer engagement and trust are impacted by perceived utility, platform interaction, and source credibility, as well as how these factors affect purchase intention and actual purchasing behavior. Data were gathered from 247 regular live streaming platform users in Chennai, Tamil Nadu, India, employing purposive sampling and a standard questionnaire. From August to November 2024, the survey was administered during periods of significant online purchasing events and increasing live commerce activities. Participants were selected among technology-savvy, digitally engaged shoppers at major metropolitan shopping malls to generate a representative sample. Using Partial Least Squares Structural Equation Modeling, results indicate that source credibility, platform interactivity, and perceived usefulness significantly affect consumer engagement (β = 1.376, p < 0.001). The results indicate that source credibility, platform interactivity, and perceived utility strongly affect trust (β = 1.198, p < 0.001, β = 0.351, p < 0.001, β = 0.224, p = 0.010). The findings also showed that customer engagement has a favorable impact on both purchase intention and the actual purchase (β = 1.272, 0.404; p = 0.001, 0.003). Trust positively affects both purchase intention (β = 0.994, p = 0.002) and actual purchase (β = 0.546, p = 0.001). Marketers and e-commerce platforms could apply these results to create more authentic and dynamic live streaming experiences that boost consumer engagement and trust.

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    • Figure 1. Conceptual framework
    • Figure 2. Results from PLS_SEM
    • Table 1. Measurement scales
    • Table 2. Participants’ demographic data
    • Table 3. Validity statistics
    • Table 4. Fornell and Larcker cross-loadings
    • Table 5. Model estimations
    • Table 6. Test of hypothesized relationships
    • Table А1. Questionnaire
    • Investigation
      K. Subathra
    • Project administration
      K. Subathra
    • Resources
      K. Subathra
    • Supervision
      K. Subathra
    • Writing – review & editing
      K. Subathra, Paul Arun Kumar J
    • Conceptualization
      Paul Arun Kumar J
    • Data curation
      Paul Arun Kumar J
    • Formal Analysis
      Paul Arun Kumar J
    • Methodology
      Paul Arun Kumar J
    • Software
      Paul Arun Kumar J
    • Validation
      Paul Arun Kumar J
    • Visualization
      Paul Arun Kumar J
    • Writing – original draft
      Paul Arun Kumar J