Industrial management
Mina Kazemian; Mohamad Ali Afshar Kazemi; Kiamars Fathi Hafshejani; Mohammad reza Motadel
Abstract
IntroductionThe field of supply chain management has focused on crucial topics such as coordination, cooperation, and competition among chain members. Game theory has emerged as a valuable tool for examining supply chain management issues, as it analyzes various situations and their impact on supply ...
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IntroductionThe field of supply chain management has focused on crucial topics such as coordination, cooperation, and competition among chain members. Game theory has emerged as a valuable tool for examining supply chain management issues, as it analyzes various situations and their impact on supply chain performance (Naimi Sediq et al., 2013; Shafi'i et al., 2018). While every action and performance within the supply chain influences the outcomes of the game, it does not solely determine them. The goal is to balance the parties involved in the supply chain and create satisfaction for the end customer (Metinfer et al., 2018).Although extensive research has been conducted in supply chain management within the steel industry, the impact of sanctions on Nash equilibria and the application of three approaches (Cournot, Stackelberg, and collusion) to achieve game balance in different scenarios have not been thoroughly investigated. This research aims to fill this gap by addressing the mentioned research question. The current study focuses on determining the optimal price using an intelligent decision-making system based on game theory within the steel industry, considering the presence or absence of the sanctions variable.Our country currently possesses several relative advantages in terms of steel production conditions, including abundant and affordable energy, iron ore and refractory raw materials, considerable steel production experience, and a skilled and cost-effective workforce. By acquiring new production technology, these advantages enable our country to play a competitive and influential role in the global steel market. However, the steel industry faces significant challenges such as price fluctuations, extreme price disparities across regions, and delayed delivery due to a lack of efficient supply chain management. Therefore, the main research question aims to provide a model that incorporates key variables, such as the supply and demand of final and intermediate products in the steelmaking industry and the future trends in production and quantity changes.Research methodThis article introduces a composite model that combines artificial neural networks and game theory to assist stakeholders in the steel industry in determining optimal production levels and price levels. To predict the price of steel, three techniques were employed: Bayesian neural networks, support vectors, and Grassberg anti-diffusion. Additionally, to address the issue of binary identification in the neural network, three different network structures were introduced: feedforward network structure, competitive network structure, and backward associative memory network structure.Research findingsThe first scenario is the non-cooperative game (Cournot model scenario) where each participant aims to maximize their profit and would not deviate from their strategy as it would lead to a reduction in their profits. The second scenario is the sequential non-cooperative game (Stackelberg model scenario), in which two chains engage in a confrontation of the Stackelberg game type. The leader's goal is to determine the best strategy while considering all rational strategies that follower players can employ to maximize their income. This scenario demonstrates that the rate of price and profit increase is lower compared to sequential and cooperative game modes. The third scenario is the cooperative game (collusion model scenario). In this scenario, the allocation of profits among the cooperating members is crucial to ensure the stability of their cooperation. The Grassberg anti-diffusion method exhibits higher accuracy due to its higher true positive (TP) and true negative (TN) values compared to other algorithms. Additionally, it has fewer false positives (FP) and false negatives (FN) because a higher TP and TN indicate more accurate predictions in the tested dataset, while FP and FN represent incorrect predictions. The inclusion of the sanctions variable as a moderating factor in the steel price forecasting model accounts for the potential reduction in production and increased cost price. Through the model, it was discovered that the Grossberg method yields more accurate steel price forecasting. Consequently, price forecasting in the model is based on the Grossberg method.Research resultsThe results indicate that transitioning from the Cournot game to the Stackelberg game and from the Stackelberg game to the collusion game in the steel industry's supply chain leads to a $6 increase in price per ton and a product supply ranging from 1500 to 4000 tons. In other words, as collusion in the steel market intensifies, more products are introduced into the market, resulting in an increase in product prices and a decrease in the welfare of steel consumers. According to the findings, increased competition in the industry reduces the profitability and production levels of producers while enhancing consumer welfare. Conversely, higher levels of monopoly exhibit the opposite effect. To maintain a balanced supply chain in the steel industry and prevent potential problems, it is recommended to adopt the Stackelberg game approach, which aligns more closely with reality. It is worth noting that the order in which players enter the game impacts the Nash equilibrium. Therefore, exploring market entry monitoring regulations and rules in this industry becomes crucial since the steel industry involves high entry and exit costs. Policymakers and industry managers should consider monitoring the entry and exit of players, formulate game standards and rules among market participants. Based on the results, the primary recommendation of this research is to increase competition intensity and adopt the Cournot approach in the industry to reduce prices and increase production. Additionally, enhancing international relations and diplomatic efforts will mitigate the impact of sanctions on the industry, leading to cost price improvements and an increase in the level of comparative advantage at the international level.
supply chain management
mohammadreza monjazeb; Mohammadkazem Sayadi; Mohammadjavad Farsayad
Abstract
Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between ...
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Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between chains, the environment and social welfare. This article presents three different models. In the first model the two green and non-green supply chains are competing with each other and the government is not present. In the second model, the government creates a culture to use the green supply chain and in the third model, is taxing the non-green supply chain. The objective of government is social welfare. In both models of government intervention, the game is in the form of a Stackelberg. Backward analysis method is used to solve the model. This method is a backward inference process in problems with limited steps, with the aim of obtaining optimal action in each step. MATLAB and Maple software are used for mathematical calculations and obtaining decision variables. The results show that if the government intervenes in a cultural way, environmental damage will decrease. Another result is that the conditions for increasing social welfare in the state of culture are determined. It is also possible for the green supply chain to increase its price if certain relationships are established between the parameters. In the tax collection model, if the government aims to maximize social welfare, social welfare will increase under any circumstances compared to the absence of the government.
Mohsen Tabatabaei; Abbas Afrazeh; Abbas Seifi
Abstract
This paper aims to propose a knowledge sharing optimization model based on the game theory that optimizes both employer and employee(s) decisions simultaneously. This model is a bi-level programming model. The upper-level problem includes employer decision about the reward, and the lower-level problem ...
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This paper aims to propose a knowledge sharing optimization model based on the game theory that optimizes both employer and employee(s) decisions simultaneously. This model is a bi-level programming model. The upper-level problem includes employer decision about the reward, and the lower-level problem contains employee(s) decisions about time and effort allocation to knowledge sharing activity. Mathematical formulation of the model designed based on previous literature and in the framework of Motivation-Opportunity-Ability. The proposed bi-level programming model provides a foundation to investigate more different parameters comparing with previous models introduced in the literature. This model considers opportunity and ability factors in addition to the motivation. Also, payoff functions in this model are non-linear and therefore is more consistent with real cases relative to previous linear models. Additionally, this model analysis the effects of available time as a key factor. The bi-level model coded in GAMS using EMP syntax and solved for a set of randomly generated data using BARON algorithm. Results show that the increase of applicability of codified knowledge and impact coefficient of social comparison could improve organizational performance and also save the cost of reward system. Therefore, neglecting these two parameters in designing a reward system could lead to non-optimized decision making. This research provides a basis to consider more parameters simultaneously and help to improve organizational decisions. However, based on the results, BARON algorithm is not efficient to solve big problems, so developing a more efficient algorithm is needed
Javad Behnamian; Mohammad Mehdi Bashar
Abstract
Cooperation in supply chain, due to conflicts in goals, is one the most important topics in SCM. With cooperation, players in supply chain echelons have agree with each other to play in supply chain game as a whole. To reach highest profit in the whole supply chain in cooperation condition, using game ...
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Cooperation in supply chain, due to conflicts in goals, is one the most important topics in SCM. With cooperation, players in supply chain echelons have agree with each other to play in supply chain game as a whole. To reach highest profit in the whole supply chain in cooperation condition, using game theory concept and side-contract of partnership in profits and considering marketing cost between manufacture and retailer, a cooperative multi-echelon supply chain is designed. In this paper, for the first time, mathematical modeling in fuzzy environment is presented, taking into account a discount that is approximated to the actual situation where the marketing cost is considered as triangular fuzzy number. The proposed model has been solved using Genetic algorithm (GA), simulated annealing algorithm (SA) and a hybrid algorithm based on GA-SA, for some random examples, and the model has been validated using GAMS software.
Ameneh Khadivar; Adel Azar; Fatemeh Mojibian
Abstract
By applying fuzzy set theory in game theory, player’s strategies are determined by fuzzy variable with a definite membership function, where the degree of non-membership is stated by supplement of degree of membership, while determining the value of uncertain parameters of decisions may be associated ...
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By applying fuzzy set theory in game theory, player’s strategies are determined by fuzzy variable with a definite membership function, where the degree of non-membership is stated by supplement of degree of membership, while determining the value of uncertain parameters of decisions may be associated with a hesitation degree. Therefore, in this paper, intuitionistic fuzzy variables are used to better describe vague and imprecise information, and also deals with uncertainty and ambiguity in product pricing process. To provide the proposed model, a two-echelon supply chain with one manufacturer and one retailer is considered. For Designing the proposed pricing game, we have considered structure of two-level programming in a Stackelberg game form. Finally, using a numerical example, structural validation and the effectiveness of proposed model is shown in product pricing process
