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Whistleblowing in Emerging Financial Systems: Model Development and Mixed-Methods Evidence from Banks in Qatar

Author

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  • Najla Al-Thani

    (College of Humanities and Social Sciences, Hamad bin Khalifa University, Qatar Foundation, Doha 34110, Qatar)

  • Steven Wright

    (College of Humanities and Social Sciences, Hamad bin Khalifa University, Qatar Foundation, Doha 34110, Qatar)

Abstract

Whistleblowing is a key mechanism of financial governance; however, its effectiveness varies across institutional and cultural contexts. This study examines the factors influencing whistleblowing effectiveness in Qatar’s banking sector, employing an integrated model grounded in the Stimulus–Organism–Response framework and Prosocial Behavior theory. A mixed-methods design combined survey data from 354 banking employees with qualitative text analysis. Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that Training and awareness were the strongest predictors of whistleblowing effectiveness, followed by Transparency and Accountability, and Reporting and Monitoring Mechanisms. At the same time, Legislative and Policy Framework were not significant. Fear of Retaliation partially mediated these relationships, underscoring the importance of psychological safety and trust. Thematic analysis confirmed these findings, highlighting leadership credibility, anonymity, and independent reporting as key enablers, while cultural norms such as hierarchy and loyalty remained barriers. The results indicate that effective whistleblowing in Qatar is less dependent on formal regulation and more on cultivating trust, transparency, and credible protection mechanisms. The study extends behavioral theory to financial ethics, offering practical insights for strengthening integrity systems in emerging financial sectors.

Suggested Citation

  • Najla Al-Thani & Steven Wright, 2026. "Whistleblowing in Emerging Financial Systems: Model Development and Mixed-Methods Evidence from Banks in Qatar," JRFM, MDPI, vol. 19(1), pages 1-33, January.
  • Handle: RePEc:gam:jjrfmx:v:19:y:2026:i:1:p:33-:d:1832490
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