Presenting the acceptance model of computer-based auditing tools and techniques with the ISM technique

Document Type : Research Paper

Authors

1 Department of Accounting, Kerman Branch, Islamic Azad University, Kerman, Iran

2 Department of Accounting, Shahid Bahonar University, Kerman, Iran

Abstract

The objective of this study is to introduce a model for assessing the acceptance of computer-based audit tools and techniques using the ISM technique and to assess its effectiveness through structural equations. The study follows a mixed research approach and employs a survey-cross-sectional design for data collection. The research methodology is primarily exploratory. Conducting two-stage exploratory studies allows for the qualitative findings from the first stage to inform and enhance the results and analysis of the quantitative phase. The target population for the qualitative portion consists of accounting experts and professionals. This study utilized the viewpoints of 20 accounting experts and professors. The surveyed community is primarily composed of professionals, including auditors who hold a bachelor's degree in accounting and auditing. Additionally, these auditors have achieved at least the rank of senior auditor within auditing institutions. Therefore, given the unlimited number of professionals in the quantitative sector, Cochran's formula was employed for unlimited sampling, resulting in the consideration of a certain 384 individuals. Written information and articles were utilised to explore the theoretical aspects and review the existing literature on the research topic. In the qualitative phase, data collection involved conducting library studies and expert interviews. For the quantitative research phase, a questionnaire was employed to gather data. The qualitative data was analyzed using the thematic analysis method. The research findings revealed that the research model comprised a comprehensive theme, three constructive themes, and twelve primary themes. Subsequently, the research model was presented based on the final categories. Interpretive structural modelling was employed to identify and design the pattern of relationships among indicators.

Keywords

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Volume 15, Issue 12
December 2024
Pages 297-310
  • Receive Date: 27 June 2023
  • Accept Date: 18 September 2023