Journal of Business Ethics

, Volume 117, Issue 3, pp 615–634

Prediction of Whistleblowing or Non-reporting Observation: The Role of Personal and Situational Factors

Article

DOI: 10.1007/s10551-012-1548-3

Cite this article as:
Cassematis, P.G. & Wortley, R. J Bus Ethics (2013) 117: 615. doi:10.1007/s10551-012-1548-3

Abstract

This study examined whether it was possible to classify Australian public sector employees as either whistleblowers or non-reporting observers using personal and situational variables. The personal variables were demography (gender, public sector tenure, organisational tenure and age), work attitudes (job satisfaction, trust in management, whistleblowing propensity) and employee behaviour (organisational citizenship behaviour). The situational variables were perceived personal victimisation, fear of reprisals and perceived wrongdoing seriousness. These variables were used as predictors in a series of binary logistic regressions. It was possible to identify whistleblowers on the basis of individual initiative, whistleblowing propensity (individual and organisational), fear of reprisals, perceived wrongdoing seriousness and perceived personal victimisation. It was concluded that whistleblowers are not markedly dissimilar to non-reporting observers. Based on the two most influential variables (perceived personal victimisation and perceived wrongdoing seriousness), the average Australian public sector whistleblower is most likely to be an ordinary employee making a good faith attempt to stop what they perceived to be a serious wrongdoing that was initially identified through personal victimisation.

Keywords

Australian public sector organisationsNon-reporting observationPersonal victimisationWhistleblowerWhistleblowingWrongdoing seriousness

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Key Centre for Ethics, Law, Justice and GovernanceGriffith UniversityMt Gravatt, BrisbaneAustralia
  2. 2.UCL Jill Dando Institute of Security and Crime ScienceLondonUK