International Journal of Finance & Managerial Accounting

International Journal of Finance & Managerial Accounting

Designing an optimal supply chain model for price determination in the steel industry based on market structure with a Neural Network approach and game theory

Document Type : Original Article

Authors
Mohammad Ali Afsharkkazemi 1
Mina Kazemian 2
1 Professor, Faculty of Management, Islamic Azad University Central Tehran Branch, Tehran, Iran
2 PhD in Industrial Management, Graduated from Islamic Azad University, Science and Research Branch
10.22034/ijfma.2025.77998.2187
Abstract
The main issue in the steel industry and supply chain management is to identify and model fluctuations in this market. Considering the vertical chain in this industry and the interaction between players, game theory is used to model the optimal price. On the other hand, players need to interact with and repeat the game to reach a balance, for which neural network models were employed. In the following, according to the specific conditions of the country that is facing severe sanctions in the metal industry, the sanctions variable is considered as an adjustment factor in the price modeling of this industry.
The research method is practical in terms of purpose. The research period of seasonal data is from 2011 to 2020, and MATLAB software is used.
Based on the explanations, a hybrid model based on neural networks and game theory was presented. To predict steel prices, three Bayesian neural networks, support vectors, and cross diffusion were used. The results indicate that the cross-emission model of Grossberg is more accurate in predicting steel prices Then the predicted price was entered into the game theory process and the Nash equilibrium point of the model was determined. The results indicate that the presence of sanctions in the model has increased the price and decreased production in the steel industry.
Keywords
Optimal Price, Neural Network, Game Theory, Steel Industry

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