Factors influencing attitudes toward aging workforce: Evidence from college students in Southern Thailand

  • Received September 20, 2023;
    Accepted December 12, 2023;
    Published January 12, 2024
  • Author(s)
    Medina Adulyarat
    ORCID ,
    Najmee Adulyarat
    ORCID ,
    Long Kim
    ORCID , Laura Poskin ,
    Suchita Manajit
    ORCID
  • DOI
    http://dx.doi.org/10.21511/ppm.22(1).2024.15
  • Article Info
    Volume 22 2024, Issue #1, pp. 170-181
  • TO CITE АНОТАЦІЯ
  • Cited by
    3 articles
  • 359 Views
  • 102 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

As the aging population grows, examining attitudes and intentions toward joining the aging workforce is of greater importance. This study examines factors influencing Southern Thai college students’ attitudes and intentions to join the aging workforce. A cross-sectional survey was conducted among 412 undergraduate students from three universities in the region. The survey measured attitudes, subjective norms, perceived behavioral control, and intention to be older workers based on the theory of planned behavior using a 5-point Likert scale. The data were analyzed using the path analysis technique. The findings indicated significant associations between attitudes, subjective norms, perceived behavioral control, and intentions to be older workers among college students. Attitudes toward older workers positively influenced subjective norms (β = 0.71, p = 0.001), and perceived behavioral control also had a significant impact on subjective norms (β = 0.11, p = 0.05) and on the intention to be older workers (β = 0.23, p < 0.05). Subjective norms, in turn, positively influenced intentions to be older workers (β = 0.42, p < 0.001). In conclusion, this study highlights the importance of attitudes, subjective norms, and perceived behavioral control as factors in influencing college students’ intention to join the aging workforce.

Acknowledgment
This study is supported by the Research and Innovation Institute of Excellence, Walailak University, under Grant No. WU66251.

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    • Figure 1. Theoretical model
    • Figure 2. Regression results of path analysis
    • Table 1. Demographic information of respondents
    • Table 2. Content reliability and convergent validity
    • Table 3. Discriminant validity
    • Table 4. Model fitness
    • Table 5. Results summary
    • Conceptualization
      Medina Adulyarat, Suchita Manajit
    • Data curation
      Medina Adulyarat, Long Kim, Laura Poskin
    • Funding acquisition
      Medina Adulyarat, Najmee Adulyarat
    • Project administration
      Medina Adulyarat, Long Kim
    • Resources
      Medina Adulyarat
    • Writing – original draft
      Medina Adulyarat, Najmee Adulyarat
    • Writing – review & editing
      Medina Adulyarat, Najmee Adulyarat, Long Kim, Laura Poskin, Suchita Manajit
    • Methodology
      Najmee Adulyarat, Laura Poskin
    • Software
      Najmee Adulyarat, Long Kim
    • Investigation
      Long Kim, Suchita Manajit
    • Validation
      Long Kim
    • Visualization
      Laura Poskin
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