Determinants of turnover intention in the context of SMEs: Do generational differences matter?

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Type of the article: Research Article

Abstract
This study examines the interplay among organizational justice, perceived organizational support (POS), job embeddedness, and the intention of employees in SMEs to leave their positions with generations (Gen Y and Gen Z) as a moderator. The sample of this study includes SME employees in Indonesia, consisting of several sectors, such as handicrafts, culinary, fashion, and accommodation. The data collection involved the distribution of questionnaires, both in person and online, from January to March 2024, employing a purposive sampling, resulting in 268 valid responses. The hypotheses were subsequently validated utilizing PLS-SEM and MGA. The findings demonstrate that organizational justice (β = –0.397, p = 0.000), POS (β = –0.202, p = 0.000), and job embeddedness (β = –0.285, p = 0.000) negatively affect turnover intention. Conversely, organizational justice (β = 0.405, p = 0.000) and POS (β = 0.314, p = 0.000) positively affect job embeddedness. Ultimately, the results of the moderation analysis of generations revealed differences between Gen Y and Gen Z in the effects of organizational justice (β = –0.189, p = 0.019) and POS (β = 0.180, p = 0.070) on turnover intention, and also in the effects of organizational justice (β = 0.195, p = 0.024) and POS (β = –0.241, p = 0.013) on job embeddedness. Contrarily, there is no significant difference between Gen Y and Gen Z in the relationship between job embeddedness and turnover intention (β = 0.089, p = 0.228). This paper offers substantial insights into the existing body of knowledge, particularly in addressing the issue of SMEs’ employee turnover intention.

Acknowledgments
The authors would like to thank all the subjects who helped a lot during the preparation of this article, especially the Institute for Research and Community Service, Khairun University, which funded this research.

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    • Figure 1. Conceptual model
    • Table 1. Demographic data of respondents
    • Table 2. Convergent validity and reliability results
    • Table 3. Discriminant validity results (HTMT)
    • Table 4. Structural model results
    • Table 5. Multi-group analysis results
    • Table A1. Measurement Items
    • Conceptualization
      Abdullah W. Jabid, Dudi Amarullah, Sulfi Abdul Haji
    • Data curation
      Abdullah W. Jabid, Dudi Amarullah, Ahmad Yani Abdurrahman, Sulfi Abdul Haji
    • Funding acquisition
      Abdullah W. Jabid
    • Investigation
      Abdullah W. Jabid, Ahmad Yani Abdurrahman, Sulfi Abdul Haji
    • Methodology
      Abdullah W. Jabid, Dudi Amarullah
    • Resources
      Abdullah W. Jabid, Ahmad Yani Abdurrahman
    • Supervision
      Abdullah W. Jabid, Sulfi Abdul Haji
    • Validation
      Abdullah W. Jabid, Dudi Amarullah, Ahmad Yani Abdurrahman, Sulfi Abdul Haji
    • Writing – original draft
      Abdullah W. Jabid, Dudi Amarullah
    • Writing – review & editing
      Abdullah W. Jabid, Ahmad Yani Abdurrahman, Sulfi Abdul Haji
    • Formal Analysis
      Dudi Amarullah, Ahmad Yani Abdurrahman
    • Project administration
      Dudi Amarullah, Sulfi Abdul Haji
    • Software
      Dudi Amarullah, Ahmad Yani Abdurrahman, Sulfi Abdul Haji
    • Visualization
      Dudi Amarullah, Ahmad Yani Abdurrahman