Designing an Earnings Management Improvement Model for Iranian knowledge-based Firms

Document Type : Original Article

Authors

• Khadijeh Ghasemi
• Hosein Jabbari
• Meysam Arabzadeh
• Hosein Panahian

Department of Accounting, Faculty of Humanities, Islamic Azad University, Kashan Branch, Kashan, Iran

10.22067/ijaaf.2022.42175

Abstract

The present study designs an earnings management improvement model appropriate for Iranian knowledge-based firms (KBFs). This study is interpretive in the model exploration phase and positivist in the model testing phase, and in general, this is applied research. The research sample in the qualitative phase comprises the experts in the field of earnings management, including accounting faculty members (8), senior managers of KBFs (7), and members of the Iranian National Tax Administration (INTA) (5); thus, a total number of 20 experts were interviewed to collect the qualitative data. The research questionnaire for collecting the quantitative data was designed according to the exploratory factor analysis (EFA). In the quantitative phase, using the sample size calculator (the G*Power software) at the alpha level of 0.1 and test power of 0.85, the final research sample comprises 153 participants. The research approach uses mixed methods, and the employed strategy is grounded theory. The constant comparative method in the three stages of open, axial, and selective coding based on the Strauss et al. (1996) method and the MAXQDA software was employed to analyse the data. The path analysis of the explored model was carried out based on the variance-based structural equation modeling (SEM) using SPSS version 24 and Smart PLS 3.0. The study results indicate 53 indicators, including more than 18 components and 7 latent variables.

Keywords

• Designing
• Earnings Management
• G*Power Software
• Variance-based Structural Equation Modeling

Main Subjects

• Accounting

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©2022 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

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