Document Type : Original Article
Authors
- Fatemeh Khodadad Hatkehposhti 1
- Reza Fallah 2
- Hamid Reza Gholam nia Roshan Gholam nia Roshan 1
- Kaveh Azinfar 1
1 Department of Accounting, Babol Branch, Islamic Azad University, Babol, Iran
2 Department of Accounting, Chalos Branch, Islamic Azad University, Chalos, Iran
Abstract
Introduction: Accounting software constitutes a critical tool for financial managers. This study was conducted to develop an evaluation model for computer audit tools aimed at assessing data gaps in hospitals.
Methods: This mixed-methods research was conducted based on the systematic approach of Strauss and Corbin. Using snowball sampling, 15 financial and audit experts were selected for semi-structured interviews, which continued until theoretical saturation. In the quantitative phase, data were purposively collected from 143 individuals in target groups across public and private hospitals in Tehran. Data were analyzed using structural equation modeling (SEM) with Smart PLS-3 software.
Results: To evaluate hospital data gaps, potential strategies were first extracted (including staff training, information disclosure, benchmarking, public awareness campaigns, patient education, allocation of digitalization budgets, and the use of experienced consultants). To prioritize and select the most effective strategies under conditions of uncertainty, fuzzy decision-making models were used. A comparison of three fuzzy approaches (Type 1, 2, and 3) revealed significant differences in their efficacy. Fuzzy Type 3, which demonstrated a superior capacity to process the inherent ambiguity in hospital data, was selected as the final analytical framework.
During the data modeling and fuzzification stage, the performance of various membership functions was examined. Results indicated that composite functions possessed higher overall accuracy compared to basic functions. Among basic functions, sinusoidal-shaped functions showed a better ability to cover the range of uncertainty and account for data ambiguity. Integrating these findings to achieve maximum accuracy, the final fuzzification process was designed and implemented using a Type 3 sinusoidal-logistic composite membership function (for inputs) and a Type 4 Sheffer implication operator (for rule inference). Finally, the proposed model was evaluated with a fit index of 0.711, confirming a desirable fit and the reliability of the final model.
Conclusion: Internal audit plays a valuable role in the organizational strategic pillars, risk management, and internal controls. Leveraging its specialized understanding of the organization’s risks and internal controls to mitigate them, it assists management and provides recommendations for improvement.
Keywords
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