Understanding the women’s digital employment intentions: The role of policies and values

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The digital economy has enforced women’s employment and provided more possibilities for promoting employment for gender equality (SGD5). In order to achieve SDG5, the study aims to explore the role of digital employment policy and digital employment value on digital employment intention based on the support alliance theory and employment behavior theory and to build a model of digital employment for gender equality. 492 women with digital work experience from China participated in the survey. The results reveal that digital employment policy (β = 0.327, p < 0.001) and digital employment value (β = 0.454, p < 0.001) predict digital employment intention. Digital employment policy plays an active role in determining digital employment value (β = 0.546, p < 0.001). At the same time, the study claims the intermediary role of digital employment value in the structural model. This study can inspire the government and relevant departments to design more scientific and diversified employment policies for women, including policy support in economic, educational, and social aspects. Furthermore, women in the digital era should actively participate in training, improve their digital skills, understand the possibilities that digitalization brings to their work and life, and adapt themselves to the development of the digital society. This study encourages women to integrate into the digital society and actively improve their values, thus achieving SDG5.

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    • Figure 1. Confirmatory factor analysis
    • Figure 2. Structural equation model of digital employment for gender equality
    • Table 1. Demographics of the respondents
    • Table 2. Reliability statistics
    • Table 3. KMO and Bartlett’s test
    • Table 4. Aggregate validity test
    • Table 5. Differentiation validity test
    • Table 6. Modification indices
    • Table 7. Confirmatory factor analysis model fitting index
    • Table 8. Aggregate validity test (after deletion and correction)
    • Table 9. Differentiation validity test (after correction)
    • Table 10. Structural equation model path test
    • Table 11. Summary of mediation effect
    • Conceptualization
      Wei Wang, Songyu Jiang, Lin Li
    • Data curation
      Wei Wang, Songyu Jiang, Lin Li
    • Formal Analysis
      Wei Wang, Songyu Jiang, Lin Li
    • Funding acquisition
      Wei Wang, Songyu Jiang, Lin Li
    • Investigation
      Wei Wang, Songyu Jiang, Lin Li
    • Methodology
      Wei Wang, Songyu Jiang, Lin Li
    • Project administration
      Wei Wang, Songyu Jiang
    • Resources
      Wei Wang, Songyu Jiang
    • Supervision
      Wei Wang, Songyu Jiang
    • Validation
      Wei Wang, Songyu Jiang
    • Visualization
      Wei Wang, Songyu Jiang
    • Writing – original draft
      Wei Wang, Songyu Jiang
    • Writing – review & editing
      Wei Wang, Songyu Jiang
    • Software
      Songyu Jiang