Presenting an Integrated Model of Psychological Factors, Digital Empowerment, and Internal Audit Quality in Organizations Based on Emerging Technologies

Document Type : Original Article

Authors

1 PhD, Department of Accounting, Zanjan Branch, Islamic Azad University, Zanjan, Iran.

2 PhD, Department of Accounting, Payam Noor University, Tehran, Iran.

Abstract
This study aimed to develop and empirically examine an integrated model linking psychological factors, digital empowerment, and internal audit quality in organizations operating in environments shaped by emerging technologies. The research was applied in purpose and employed a descriptive–analytical, cross-sectional field design. In the qualitative phase, the fuzzy Delphi technique was used to identify and refine the components of the proposed model. Purposive sampling was followed by theoretical sampling until data saturation was achieved. After reviewing the 28 experts’ opinions, four additional specialists were included to address conceptual gaps. The three-round fuzzy Delphi process showed that all identified indicators exceeded the acceptance threshold and were retained in the final model. The proposed framework comprised sense of worth, autonomy, perceived impact, trust and psychological security, independence, integrity, confidentiality, objectivity, professional competence and due care, and idealism. In the quantitative phase, robust structural equation modeling with resampling and quantile structural equation modeling were employed to examine the associations among the proposed constructs. Gender, membership in the Iranian Association of Certified Public Accountants, education level, and work experience were included as control variables. The findings revealed statistically significant associations between education level, work experience, digital empowerment, and internal audit quality. Furthermore, the quantile structural equation modeling results indicated that the strength of these associations varied across different levels of internal audit quality, suggesting heterogeneous relationships among the study variables. Model assessment based on SRMR and NFI indicated an acceptable overall model fit, supporting the adequacy of the proposed conceptual framework.

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Subjects

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  • Receive Date 02 July 2025
  • Revise Date 27 July 2025
  • Accept Date 25 August 2025