Design and Validation of a Native Conceptual Model for Evaluating and Improving Internal Audit Performance in the Iranian Petrochemical Industry Using a Mixed-Methods Approach
Keywords:
Native model for evaluating internal audit performance, mixed-methods approach, Iranian petrochemical industry, meta-synthesis, structural equation modelingAbstract
This study was conducted with the aim of designing and validating a native conceptual model for evaluating the performance of internal auditing in the Iranian petrochemical industry and identifying existing gaps. In the qualitative phase, using meta-synthesis and a systematic review of 157 studies published between 2000 and 2024, a total of 25 selected studies were coded. In the quantitative phase, data were collected from 100 petrochemical complexes and analyzed using structural equation modeling and paired t-tests. The results indicated that the input, process, and output dimensions have a significant effect on internal audit quality, and a considerable gap exists between the current and the desired state. The largest gap was observed in independence and objectivity, and the smallest gap in training and development. The innovation of this study lies in presenting a native model tailored to the structure and conditions of the Iranian petrochemical industry, which can serve as a foundation for the continuous improvement of internal audit units.
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Copyright (c) 2024 Mozhgan Heidari (Author); Ali Akbar Chaharmahali; Mehran Matinfard (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
