System Dynamics of Profit Forecasting of Oil Refining Companies Listed on the Tehran Stock Exchange with a Quantum Mechanics Approach

Document Type : Original Article

Authors
1 PhD Student, Department of Accounting, Sa.C., Islamic Azad University, Sanandaj, Iran.
2 Associate Professor, Department of Accounting, University of Ilam, Ilam, Iran
3 Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, University of Ilam, Ilam, Iran
4 Department of Accounting, Sa.c., Islamic Azad University, Sanandaj, Iran
Abstract
Profit and its forecasting using modern approaches and methods in a way that takes into account unpredictable conditions has always been one of the challenges of companies and their managers. The turbulent and unreliable environment in the oil industry has a special look at profit forecasting. Therefore, this research was conducted with the aim of system dynamics of profit forecasting of oil refining companies listed on the Tehran Stock Exchange with a quantum mechanics approach. The method of conducting this research is mixed (qualitative-quantitative). In the qualitative part of the research, 97 reputable scientific and research articles were examined using a meta-synthesis approach, and finally 39 articles were selected to extract profit forecasting indicators with a quantum mechanics approach. After detailed analysis, 19 indicators were identified and extracted for profit forecasting with a quantum mechanics approach. However, ultimately, seven underlying components were identified for predicting the profits of oil refining companies in the qualitative section. Then, in the quantitative section, first, using a fuzzy Delphi questionnaire, the opinions of 14 experts on the effectiveness of the extracted underlying components were approved. Next, to apply dynamics, first, two causal-cyclic models were determined by analyzing and explaining the relationships between the underlying components, and then, with the help of these two models, the main model was developed with a dynamics approach, which consisted of two causal-cyclic models.

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