Designing a Model for Evaluating Managers’ Compensation Based on Financial Reporting Transparency (Case Study: National Iranian Oil Products Distribution Company) - Maleki, Alireza; Ahmady, Fatemeh; Mohammadi yarijani, Forouzan; Nouraie, Maryam (Management Strategies and Engineering Sciences, 2026)
Managers’ compensation and its evaluation, particularly in state-owned enterprises, constitute one of the major challenges in the economies of developing countries, and the application of approaches such as financial reporting transparency in this regard can be beneficial. Accordingly, the present study was conducted with the aim of designing a model for evaluating managers’ compensation based on financial reporting transparency in the National Iranian Oil Products Distribution Company. The research employed a mixed-methods approach (qualitative–quantitative). In the qualitative phase, the required data were collected through interviews with 20 academic and organizational experts. In the quantitative phase, in order to design the model, the relationships and interactions among the extracted indicators were initially determined using a self-interaction matrix with the assistance of experts. The quantitative data were analyzed using MATLAB software. Following the qualitative data analysis, 21 indicators for evaluating managers’ compensation based on financial reporting transparency were identified and extracted. Subsequently, the analysis of the quantitative results led to the development of a five-level model comprising these 21 indicators, in which training for enhancing reporting transparency and the alignment of financial reporting with international financial reporting standards were identified as the most influential indicators. The originality and contribution to knowledge: The findings of the study demonstrated that, within the proposed model for evaluating managers’ compensation based on financial reporting transparency in the National Iranian Oil Products Distribution Company, two indicators function as the most influential factors, nine indicators are the most influenced factors, and ten indicators serve as linkage variables within the model.