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Determinants of Ethics Auditing: Structural Equation Model Approach

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Abstract

It is generally accepted that behaving ethically is essential to the success of organizations. The failure to behave ethically in the eyes of key stakeholders can impair the health of organizations. This is particularly the case with organizations who are potentially vulnerable to direct consumer action and also the state agencies who provide various services for their citizens. In this paper, we analyze the involvement of internal audit in the provision of assurance in relation to the ethics implementations in organizations. Internal audit is expected to conduct an effective ethical audit as a high priority in a risk-based internal audit planning process which is required by the International Professional Practices Framework (IPPF) of the Institute of Internal Auditors (IIA). The provision of assurance concerning successful implementation of an ethics policy as a contribution to the achievement of organizational objectives is becoming increasingly critical. That’s why, it is examined whether internal audit is ready for responding to this challenge globally. The Common Body of Knowledge (CBOK) data of IIA are used for analyzing the current situation about determinants of ethics auditing all over the world. We propose a structural equation model (SEM) utilizing a worldwide dataset of CBOK data with responses from internal auditors. The determinants of ethics auditing is estimated by using SEM with 20 observed variables loaded to six factors namely, Audit Policy Documents, Auditor Integrity, Audit Policy Documents, Ethics Standards, Ethics Audit, and Corporate Governance. Finally, policy recommendations are made based on empirical findings to add value to internal audit profession and stakeholders.

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Notes

  1. 1.

    Melé (2012) argue that stakeholders are people affected by or who can affect the activity of the organization.

  2. 2.

    Ferell, O. C., Fraedrick, J., and Ferell, L. (2011). Business Ethics: Ethical Decision Making and Cases. Mason: South-Western—Cengage Learning.

  3. 3.

    Institute of Internal Auditors-IIA. (2014). The IIA Global Internal Audit Competency Framework. https://na.theiia.org/careermap/Public%20Documents/Framework.pdf.

  4. 4.

    Institute of Internal Auditors-IIA. Standards For The Professional Practice Of Internal Auditing (Standards). (2016). pp. 1–3.

  5. 5.

    Ronald Francis and Anona Armstrong. (2003). Ethics as a Risk Management Strategy: The Australian Experience. Journal of Business Ethics. Vol. 45. No. 4 (Jul 2003). pp. 375–385.

  6. 6.

    Victor and Cullen (1987) are first in the literature to introduce the concept of “ethical climate” to explain and predict organizational ethical behavior.

  7. 7.

    Although the number of questionnaires is equal to 14,500, we could not use them all, and depending on the validity checks, we eliminate them up to 2025. We consider the surveys with fully answered for the same set of questions, in other words, we did not select the questionnaires without any answer. We rely on these 2025 questionnaires to estimate determinants of ethics auditing. At the beginning of our empirical tests, we try to establish a different hypothesis, and in that case, the number of relevant questionnaires decreased up to 100 which is relatively small to make reliable estimations. For this reason, we did not want to decrease the sample size even lower, and due to empty lines with N/A indicating “not applicable,” we only eliminate 14,500 questionnaires to 2025. According to MacCallum et al. (1996), if the sample size is small and the number of estimated parameters is large, the confidence interval will be broad. Given a complex model (i.e., a large number of estimated parameters), a considerable sample size would be required in order to obtain a reasonably narrow confidence interval. On the other hand, if the number of parameters is small, then the probability of obtaining a narrow confidence interval is high, even for samples of somewhat moderate size.

  8. 8.

    Barbara M. Byrne. (2010). Structural Equation Modelling with AMOS. Basic Concepts, Applications, and Programming. Second Edition. Taylor & Francis Group. pp. 275–276.

  9. 9.

    If skewness is positive, the data are positively skewed or skewed right, meaning that the right tail of the distribution is longer than the left. If skewness is negative, the data are negatively skewed or skewed left, meaning that the left tail is longer.

  10. 10.

    A distribution with kurtosis >3 (excess kurtosis >0) is called leptokurtic. Compared to a normal distribution, its tails are more extended and fatter, and often its central peak is higher and sharper.

  11. 11.

    Barbara M. Byrne. (2010). Structural Equation Modelling with AMOS. Basic Concepts, Applications, and Programming. Second Edition. Taylor & Francis Group. pp. 67–68.

  12. 12.

    Barbara M. Byrne. (2010). Structural Equation Modelling with AMOS. Basic Concepts, Applications, and Programming. Second Edition. Taylor & Francis Group. p. 73.

  13. 13.

    In larger samples (as in this research), the chi-squared test almost always leads to rejection of the model because the difference between sample covariance’s and implied population covariance would lead to a higher chi-squared value if sample size increases.

  14. 14.

    Hu and Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives”, 1999, Structural Equation Modeling 6, pp. 1–2.

  15. 15.

    Although this index, and the conceptual framework within which it is embedded, was first proposed by Steiger and Lind in 1980, it has only recently been recognized as one of the most informative criteria in covariance structure modeling.

  16. 16.

    Barbara M. Byrne. (2010). Structural Equation Modelling with AMOS. Basic Concepts, Applications, and Programming. Second Edition. Taylor & Francis Group. pp. 73–100.

  17. 17.

    If an increase in one variable results in an increase in the other variable, both variables are said to have a positive covariance. Decreases in one variable also cause a decrease in the other.

  18. 18.

    A competency is the ability of an individual to perform a job or task correctly, being a set of defined knowledge, skills, and behaviors. The Framework provides a structured guide, enabling the identification, evaluation, and development of those competencies in individual internal auditors. The core competencies are as follows: I. Professional ethics: promotes and applies professional ethics. II. Internal audit management: develops and manages the internal audit function. III. IPPF: applies the International Professional Practices Framework (IPPF). IV. Governance, risk, and control: applies a thorough understanding of governance, risk, and control appropriate to the organization. V. Business acumen: maintains expertise in the business environment, industry practices, and specific organizational factors. VI. Communication: communicates with impact. VII. Persuasion and collaboration: persuades and motivates others through collaboration and cooperation. VIII. Critical thinking: applies process analysis, business intelligence, and problem-solving techniques. IX. Internal audit delivery: delivers internal audit engagements. X. Improvement and innovation: embraces change and drives improvement and innovation.

  19. 19.

    The IIA Standards and the code of ethics are “mandatory” guidance components of the IPPF. The IPPF also comprises practice advisories, “advisory” guidance, which is available free of charge to IIA members, and development and practice aids that provide “practical, how-to” guidance for the professional practice of internal auditing. The practice advisories consist of detailed, step-by-step guidance for adhering to the Standards. For example, Standard 2600 is about risk communication process such that when the chief audit executive (CAE) concludes that management has accepted a level of risk that may be unacceptable to the organization, the CAE must discuss the matter with senior management. If the CAE determines the matter has not been resolved, the CAE must communicate the matter to the board.

  20. 20.

    García-Marzá Domingo. (2005). Trust and Dialogue: Theoretical Approaches to Ethics Auditing. Journal of Business Ethics. Vol. 57. No. 3 (Mar. 2005), p. 205.

  21. 21.

    Trevino, L.K. and Weaver, G.R. (2003). Managing Ethics in Organizations: A Social-Scientific Perspective on Business Ethics. Stanford University Press. California. pp. 267–270.

  22. 22.

    Piet van Montfort, Ina de Haan, Ruud Hogendoorn and Brenda Vermeeren. (2010). Measuring effectiveness of integrity management: A Study Comparing the effectiveness of value-based and compliance based approaches of integrity in Dutch public sector organizations by measuring employee perceptions. pp. 5–6. https://www.law.kuleuven.be/integriteit/egpa/egpa2010/de-haan-et-al_measuring-effectiveness-integrity.pdf.

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Correspondence to Sezer Bozkuş Kahyaoglu .

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Kahyaoglu, S.B., Balkan, B., Balkan, O. (2019). Determinants of Ethics Auditing: Structural Equation Model Approach. In: Çalıyurt, K. (eds) Ethics and Sustainability in Accounting and Finance, Volume I. Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application. Springer, Singapore. https://doi.org/10.1007/978-981-13-3203-6_6

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