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Measuring Audit Task Complexity Using Structural Equation Modeling

Document Type : Research Paper

Authors

1 PhD Student in Accounting, University of Mazandaran, Babolsar, Iran.

2 Associate Professor, Accounting Dept., University of Mazandaran, Babolsar, Iran.

Abstract

Audit task complexity, as one of the important and effective factors on the auditors' judgment and decision-making, is one of the controversial concepts in the audit field, which, due to its multidimensional nature, has led to many researches in the audit field. Despite the provision of individual indicators to measure audit task complexity in these studies, explaining a multidimensional model to measure of this fundamental concept in auditing is a problem that requires to research. It is expected that the explanation of such an index can lead to a better understanding of this concept and its dimensions and help auditors in planning audit task as well as ways to increase the quality of judgment and decision making. Accordingly, the current research purpose is to explain a model to measure for audit task complexity concept. For this purpose, information related to 128 companies in Tehran Stock Exchange during 2010-2019 was collected and tested through Partial Least Squares Structural Equation Modeling. Findings based on Constructive-Constructive measurement model and second-order Confirmatory Factor analysis showed that twenty-one factors effect on audit task complexity. Also, the results showed that audit task complexity is influenced by three dimensions of input, processing and output complexity. These findings, in addition to explaining the concept of audit task complexity, have helped to understand the effective factors and dimensions of this concept and can be useful in auditor's tasks planning and policy making and provide a more powerful tool to increase audit judgment quality.

Keywords

Main Subjects

References
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Empirical Studies in Financial Accounting
Volume 19, Issue 75
October 2022
Pages 125-164
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History
  • Receive Date: 06 September 2022
  • Revise Date: 27 November 2022
  • Accept Date: 27 November 2022
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