Whistleblowing Intentions Among Public Accountants in Indonesia: Testing for the Moderation Effects
- 1.3k Downloads
Our study contributes by providing new insights into the relationship between the individual levels of the antecedents and how the intention of whistleblowing is moderated by perceived organizational support (POS), team norms (TNs), and perceived moral intensity (PMI). In this paper, we argue that the intention of both internal and external whistleblowing depends on the individual-level antecedents [attitudes toward whistleblowing, perceived behavioral control, independence commitment, personal responsibility for reporting, and personal cost of reporting (PCR)] and is moderated by POS, TNs, and PMI. The findings confirm our predictions. Data were collected using an online survey on 256 Indonesian public accountants who worked in the audit firm affiliated with the Big 4 and non-Big 4. The results support the argument that all the antecedents of individual levels can improve the auditors’ intention to blow the whistle (internally and externally). The nature of the relationship is more complex than analysis by adding moderating variables using the Partial Least Squares-Structural Equation Modeling approach. We found that POS, TNs, and PMI can partially improve the relationship between the individual-level antecedents and whistleblowing intentions. These findings indicate that the POS, TNs, and PMI are a mechanism or that attribute is important in controlling behavior.
KeywordsWhistleblowing Audit firms Individual-level antecedents Perceived organizational support Team norms Perceived moral intensity
This article uses the statistical software SmartPLS 3 (http://www.smartpls.com). Ringle acknowledges a financial interest in SmartPLS.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
We aware of the contents and consent to the use of our names as an author of manuscript entitled “Whistleblowing Intentions Among Public Accountants in Indonesia: Testing for the Moderation Effects.”
- Ajzen, I. (2005). Attitudes, personality and behaviour (2nd ed.). Berkshire: Open University Press.Google Scholar
- Archambeault, D. S., & Webber, S. (2015). Whistleblowing 101. The CPA Journal, 85(7), 62–68.Google Scholar
- Clements, L. H., & Shawver, T. (2011). Moral intensity and intentions of accounting professionals to whistleblow internally. Journal of Forensic Studies in Accounting and Business, 3(1), 67–82.Google Scholar
- Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed mode surveys: The tailored design method (4th ed.). Hoboken, NJ: Wiley.Google Scholar
- Graham, J. W. (1986). Principled organizational dissent: A theoretical essay. Research in Organizational Behavior, 8, 1–52.Google Scholar
- Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: Sage.Google Scholar
- Henseler, J., Hubona, G., & Ray, P. A. (2017). Partial least squares path modeling: Updated guidelines. In H. Latan & R. Noonan (Eds.), Recent developments in PLS-SEM. New York: Springer.Google Scholar
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy Marketing Science, 43(1), 115–135.Google Scholar
- Jöreskog, K. G., & Wold, H. (1982). The ML and PLS techniques for modeling with latent variables: Historical and comparative aspects. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation: Causality, structure, prediction (Vol. 1, pp. 263–270). Amsterdam: North Holland.Google Scholar
- Latan, H., & Ghozali, I. (2015). Partial least squares: Concepts, techniques and application using program SmartPLS 3.0 (2nd ed.). Semarang: Diponegoro University Press.Google Scholar
- Miceli, M. P., & Near, J. P. (1984). The relationships among beliefs, organizational position, and whistle-blowing status: A discriminant analysis. Academy of Management Journal, 27(4), 687–705.Google Scholar
- Oppenheim, A. (2001). Questionnaire design, interviewing and attitude measurement (2nd ed.). New York: Basic Books.Google Scholar
- Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH. http://www.smartpls.com.
- Robertson, J. C., Stefaniak, C. M., & Curtis, M. B. (2011). Does wrongdoer reputation matter? Impact of auditor wrongdoer performance and likeability reputations on fellow auditors’ intention to take action and choice of reporting outlet. Behavioral Research in Accounting, 23(2), 207–234.CrossRefGoogle Scholar
- Vandekerckhove, W. (2006). Whistleblowing and organizational social responsibility: A global assessment. Burlington, VT: Ashgate.Google Scholar
- Vroom, V. H. (1964). Work and motivation. New York: Wiley.Google Scholar
- Webber, S., & Archambeault, D. S. (2015). Whistleblowing: Not so simple for accountants. The CPA Journal, 85(8), 62–68.Google Scholar
- Wold, H. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation: Causality, structure, prediction (Vol. 2, pp. 1–54). Amsterdam: North Holland.Google Scholar