Factors affecting bridge employment behavior: Surveying Chinese older adults as anchors in social media

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Social media has brought new opportunities to bridge employment and has become an essential channel for addressing the issue of an aging society. This study aims to explore the factors influencing bridge employment behavior among older adults on social media platforms. This analysis collected 757 older adults from China who continue to work as anchors in social media after retiring. Data collection was conducted over ten days via structured questionnaires divided into eight sections. Furthermore, this study conducts structural equation modeling (SEM) to process the data. The results indicate that social capital (beta = 0.183, p = 0.004) and bridge employment policies (beta = 0.123, p = 0.031) have a significant positive impact on intention to bridge employment. Subjective norms (beta = 0.197, p < 0.001), attitudes (beta = 0.204, p < 0.001), and perceived behavioral control (beta= 0.147, p = 0.004) also positively and significantly influence intention to bridge employment. Subjective norms, attitudes, and perceived behavioral control serve as crucial mediators in the relationship between social capital, bridge employment policies, and intention to bridge employment. Finally, intention (beta = 0.480, p = 0.001) is a strong predictor of bridge employment behavior and acts as a mediator within the model. The findings suggest that enhancing social capital and well-structured employment policies can significantly influence older adults’ acceptance and sustained participation in bridge employment on social media platforms.

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    • Figure 1. Empirical framework
    • Figure 2. SmartPLS output of SEM
    • Table 1. Demographics
    • Table 2. Reliability statistics
    • Table 3. KMO and Bartlett’s test
    • Table 4. Convergence validity
    • Table 5. Discriminant validity test
    • Table 6. Reliability statistics
    • Table 7. Structural equation model
    • Table 8. Bootstrap test of mediation effect
    • Table A1. Measurement scale
    • Conceptualization
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Data curation
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Formal Analysis
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Funding acquisition
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Investigation
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Methodology
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Project administration
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Resources
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Software
      Lingzhi Liu, Songyu Jiang
    • Supervision
      Lingzhi Liu, Jirawan Deeprasert
    • Validation
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Visualization
      Lingzhi Liu, Songyu Jiang
    • Writing – original draft
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang
    • Writing – review & editing
      Lingzhi Liu, Jirawan Deeprasert, Songyu Jiang