Designing an earnings management improvement model for Iranian knowledge-based firms

Iranian Journal of Accounting, Auditing and Finance

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 16 اردیبهشت 1401  

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.22067/ijaaf.2022.75349.1110

نویسندگان

Hosein Jabbari ¹؛ Khadijeh Ghasemi²؛ Meysam Arabzadeh²؛ Hosein Panahian²

¹Department of Accounting, Faculty of Humanities, Islamic Azad University, Kashan Branch, Kashan, Iran

²Department of Accounting, Faculty of Humanities, Islamic Azad University, Kashan Branch, Kashan, Iran

چکیده

The present study designsan earnings managemen timprovement model appropriate for Iranian knowledge-based firms (KBFs).This study isinterpretive in the model exploration phase and positivist in the model testingphase, and in general, this is applied research.The research sample in the qualitative phase comprisesthe 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 is mixed methods,and the employed strategy is the grounded theory.The constant comparative method in the three stages of open, axial, and selective coding based on the Strauss and Corbin method and using the MAXQDA software was employed to analyse the data.The path analysis of the explored model was carried out based on the variance-basedstructural 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.

کلیدواژه‌ها

Earnings management؛ Designing؛ G*Power software؛ Variance-based structural equation modeling