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Social media for talent selection? a validity test of inter-judge agreement and behavioral prediction

Author

Listed:
  • Zheng Wenzhi

    (Huaqiao University China)

  • Wu Yenchun

    (National Taiwan Normal University
    National Sun Yat-Sen University)

  • Shen Chuangang

    (Huaqiao University China)

  • Wen Hao

    (Huaqiao University China)

Abstract

Individuals have a large amount of personal information on social media (SM), which provides companies with new opportunities for talent selection. However, researchers’ understanding of the effectiveness of assessments based on SM is relatively ambiguous, and the conclusions of empirical studies remain controversial. The Realistic Accuracy Model provides theoretical and methodological support for the application of SM information in zero-acquaintance contexts. Accordingly, we collected and matched 160 sets of Chinese SM assessment (other-assessment) and employee self-assessment data. Through a two-step data analysis, we conducted a consistency check and verification of behavioural predictions. The results suggested that in terms of general suitability, as well as knowledge, skills, abilities, and other characteristics (KSAOs), the other-assessments and self-assessments were consistent. Furthermore, the general suitability and KSAOs of the other-assessments were predictive of behavioural intention (i.e., openness to change). This study empirically tested the accuracy of SM talent assessments, and finally, the research limitations and future trends were discussed.

Suggested Citation

  • Zheng Wenzhi & Wu Yenchun & Shen Chuangang & Wen Hao, 2021. "Social media for talent selection? a validity test of inter-judge agreement and behavioral prediction," Information Technology and Management, Springer, vol. 22(1), pages 1-12, March.
    • Handle: RePEc:spr:infotm:v:22:y:2021:i:1:d:10.1007_s10799-021-00321-z
    DOI: 10.1007/s10799-021-00321-z
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    References listed on IDEAS

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    1. Wu He & Feng-Kwei Wang & Yong Chen & Shenghua Zha, 0. "An exploratory investigation of social media adoption by small businesses," Information Technology and Management, Springer, vol. 0, pages 1-12.
    2. Michelle Richey & Aparna Gonibeed & M. N. Ravishankar, 2018. "The Perils and Promises of Self-Disclosure on Social Media," Information Systems Frontiers, Springer, vol. 20(3), pages 425-437, June.
    3. Lievens, Filip & Van Iddekinge, Chad H., 2016. "Reducing the Noise From Scraping Social Media Content: Some Evidence-Based Recommendations," Industrial and Organizational Psychology, Cambridge University Press, vol. 9(3), pages 660-666, September.
    4. Girish N. Punj, 2019. "Understanding individuals’ intentions to limit online personal information disclosures to protect their privacy: implications for organizations and public policy," Information Technology and Management, Springer, vol. 20(3), pages 139-151, September.
    5. Wu He & Feng-Kwei Wang & Yong Chen & Shenghua Zha, 2017. "An exploratory investigation of social media adoption by small businesses," Information Technology and Management, Springer, vol. 18(2), pages 149-160, June.
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    Cited by:

    1. Jie Tang & Wenyue Cui, 2024. "Does the Internet trigger an innovative spatial revolution: evidence from China," Information Technology and Management, Springer, vol. 25(4), pages 305-318, December.

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