game theory

this research, with the aim of evaluating the green innovation ecosystem and the way of green science and technology policy of selected European countries in order to ensure that Europe is moving towards minimizing Carbon, holistic sustainable development, and the green, innovative and competitive economy are on the move. This research is trying to provide a set of useful input, mediator and output indicators to determine the model indicating the stages affecting the performance of the green innovation ecosystem of the selected countries by examining the background of similar research. By collecting the available data through data banks, and preparing the ground for mathematical modeling, the mathematical model was designed by combining methods of network data envelopment analysis and game theory with the help of Lingo software to combine relative efficiency in functional areas and create a Calculate the final weighted score to evaluate the performance of the green innovation ecosystem for EU member states. The results indicate that according to the designed conceptual model including four stages of knowledge creation and development, knowledge implementation, financial and economic transformations and environmental protection, with the change in the performance of countries in the stage of financial and economic transformations, efficiency The total number of countries increases significantly;

The purpose of this research is to model the behavior of the government and the contractor in the early termination of BOT projects for the construction of suburban pedestrian bridges, using game theory. The case study includes BOT projects for the construction of pedestrian bridges in the Tehran-Semnan highway. By applying game theory and analyzing the behavior of the parties in the form of a bargaining game, the consequences of the decisions of the government and the contractor in the conditions of early termination of projects have been investigated and a model has been presented to predict these behaviors and their economic results. The data used in this research were extracted from the experts of the General Department of Highways and Road Transport of Tehran and the managers of BOT projects, as well as related documents. The proposed model provides three key features for the analysis of parties' behaviors, and using a practical example, these features have been calculated and verified. The results show that the amount of compensation and the decisions around it are directly related to the behavior of the government and the contractor; High compensation could lead to a government counteroffer or construction of a new bridge, but may delay negotiations, while low compensation would cause the project to continue inefficiently and harm the public interest. Finally, managed anticipated behaviors in the public and private sector and reaching an agreement on compensation is suggested as a suitable solution to reduce behavioral conflicts and maintain public interests.

The main problem in the steel industry and value chain management is identifying and modeling fluctuations in this market. Considering the vertical chain in this industry and the interaction between players, we will use game theory to model the optimal price. On the other hand, considering that to achieve equilibrium, player interaction, and game repetition are needed, deep learning models were used to repeat the game. The research method is quantitative, descriptive in terms of philosophy, positivism, in terms of nature, and applied in terms of results. The data collection method is the library. The research period is seasonal data from 2011 to 2020 and the software used is MATLAB software. This research presents a hybrid model based on deep learning networks and game theory to help steel industry activists determine the optimal price level and production. To predict the price of steel, CNN, LST, and RNN algorithms were used in deep mode. The results show the fact that by moving from the Cornot game to the Stackelberg game and from the Stackelberg game to the collusion game in the supply chain, it increases the price and production in the steel industry. The exclusivity of the steel market in Iran assures the producers that the price will not decrease with the increase in supply.

One of the fundamental challenges in Iran's banking system is the conflict of interest, which plays a critical role in public trust. This issue points to situations where individual personal interests are at odds with their duties and responsibilities. Without addressing the actors involved in conflicts of interest, achieving and controlling these conflicts cannot be assured. Therefore, this study employs content analysis, interviews with experts, and the identification of their desires and actions. Through the application of game theory and graph models, the equilibrium status among stakeholders such as banks, customers and borrowers, legislators and regulatory bodies, investors and market analysts, and consumer rights organizations has been identified. The equilibrium state among the actors was determined through interviews regarding their preferences and with the help of evolutionary path analysis, tracing the actors' movements from the current state to the equilibrium state. The study found that this equilibrium does not represent an ideal state for the community and policymakers, indicating a need for a shift in stakeholders' preferences. Through backward game analysis, it has been determined that legislators and regulatory bodies should strengthen oversight and transparency, and consumer rights organizations should initiate awareness campaigns and collaborate with lawmakers and supervisory bodies to enhance protective regulations, aiming to achieve an optimal state for the national economy. This research can assist the Islamic Consultative Assembly in developing more effective legislative strategies through a better understanding of the interactions between stakeholders.

In the current era, the competition between organizations has also been transferred to the supply chain. The stability of the supply chain is a necessary and sufficient condition for the stability of companies. The most basic condition for the sustainability of an organization is its profitability. Therefore, the aim of this research is to present a mathematical model based on game theory in order to maximize profit in the closed loop supply chain. The main goal in the closed loop supply chain is to eliminate waste and optimize the consumption of products in such a way that the products are separated into two groups, new product and used product, and there is the possibility of returning used product and reproduced products in the consumption cycle. has it. However, all members of the chain benefit. But the fact is that it is not clear which factors can maximize the benefits of the closed loop supply chain members. For this purpose, in the current research, a mathematical model based on game theory is designed in which cooperation between upstream and downstream members occurs. Finally, it is clear what effective factors such as demand, returned products, recycled products and remanufactured products have on the profit of the chain members. In other words, how can the total profit of chain members and the share of individual members be increased and under what conditions this increase is achieved.
The general results from the analysis of this research show that demand is a factor that can increase the profit of all members of the chain, and returned products have a positive effect on the profit of all members, while recycled products and remanufactured products, in If it increases, it only increases the profit of the reproducer and recycler and reduces the profit of other members significantly at different levels.
In this research, the profitability of the closed loop supply chain has been investigated using game theory and the parameters of demand, returned products, recycled products and remanufactured products affecting the profitability of the closed loop supply chain have been simultaneously investigated. Therefore, the innovation of this research includes the simultaneous examination of demand, returned products, recycled products and remanufactured products affecting the profitability of the closed loop supply chain.

One of the fundamental challenges of Iran's banking system is the activity of unlicensed technology companies. With the emergence of new technologies and the redefinition of banking, this issue has become more significant. Achieving desirable goals is impossible without considering the actors in the banking technology sector. This study employs content analysis and expert interviews to identify the needs and necessary actions. Using game theory and graph models, the equilibrium among key actors such as traditional banks, financial technology companies, customers and users of banking services, the government and regulatory bodies, and investors and market analysts is examined. The equilibrium state among these actors was identified through interviews and determining their preferences regarding the game states. Evolutionary path analysis determined the movements of actors from the current state to the equilibrium state. The results indicate that the current equilibrium is not desirable for society and policymakers, and changes in the actors' preferences are necessary to achieve the desired equilibrium. Reverse game analysis revealed that the government and regulatory bodies need to formally recognize this sector and implement stringent laws and regulations. This research helps policymakers gain a better understanding of the dynamics and interactions among actors and design more effective policies for managing stakeholders in the regulation of banking.

EXTENDED ABSTRACT
In the bargaining process, most people follow their usual procedures when faced with issues and disputes and seek to find a solution that satisfies the interests of the parties. But in this process, problems such as lack of effective interaction, instability of decisions, lack of clarity in the understanding of parties and specialties are often seen. Bargaining and negotiation in the supply chain are essential components of decision-making processes that have wide-ranging implications for various individuals engaged in the global business landscape. With increasing emphasis on achieving fair outcomes and efficient allocation of resources, the application of game theory, especially the Nash negotiation solution, has attracted more attention in the field of supply chain negotiations. As global markets become more complex and intertwined, understanding the dynamics of supply chain negotiations is essential for organizations to optimize their operations. In dealing with complex issues and a large number of people and different aspects, Nash negotiations allow the parties to reach agreements that satisfy all parties in the shortest possible time. The Nash negotiation solution developed by Nash (1950) provides a powerful framework for analyzing negotiations and incorporates the concept of "fair sharing" between the parties involved. This tool has proven to be valuable for modeling and understanding negotiation processes in supply chains. By considering individual preferences, relative negotiation power and feasible agreements, Nash's negotiation solution tries to establish optimal and fair results. Understanding the application and implications of the Nash negotiation solution in supply chain negotiations can provide valuable insights in reaching mutually beneficial agreements and enhancing cooperation between supply chain partners. However, in the field of negotiations and bargaining, there have not been enough studies and researches regarding the use of the "Nash" negotiation solution; Therefore, the main purpose of this research is to use the solution of "Nash" negotiations to improve the bargaining process, so that by examining the effects of "Nash" negotiations on the quality of decision-making, the psychology of people and the agreements reached, a pattern of improvement and improvement in the bargaining process in the supply chain can be obtained.
From the perspective of the research strategy, this research is a qualitative method, and from the perspective of the paradigm, it is classified as an interpretive paradigm. In this method, the researcher uses the method of qualitative data analysis, which is specifically used in this research, to make patterns. The meta-synthesis research method is one of the types of meta-study methods and is considered a qualitative research method. In fact, meta-synthesis is a type of qualitative study that uses the information of findings extracted from other studies in the field of a related topic. In the meta-synthesis method, the researcher combines the secondary data of the results of other studies to respond to the results of his study and obtains new results. The current research includes two primary stages: initial planning and implementation of a systematic review, followed by reporting and publication of findings, and finally a model that shows the improvements that can be made in the supply chain bargaining process by adopting Nash's approaches with the meta-synthesis is presented. In order to achieve the goal of the research, the seven-step method of Sandelowski and Barroso was used. Sandelowski and Barroso's method is a structured model for qualitative text analysis and extracting concepts. This method uses a seven-step model for document analysis. The main method of data collection is also library studies.
 In order to evaluate the reliability of the interview, the within-subject agreement method was used with a two-pass code, in which a researcher colleague (coder) who was a PhD student registered. Collaboratively, the researcher and research associate coded the four articles and subsequently calculated the percentage of within-theme agreement, indicating the agreement between the two transfer codes. To facilitate the coding process and save time, a checklist containing two values (yes/no) was used to cover the entire task or all necessary items. When the opinions were obtained through the formula presented below, the kappa coefficient of agreement was calculated, a numerical value between 1 and +1. A rate close to 1 indicates high reliability, while a rate close to -1 indicates disagreement and a rate close to zero indicates no reliability. A kappa coefficient between 0.6 and 0.8 indicates good reliability. In the context of the current research, a part of the article was presented to two professors and based on their evaluation and comments, the kappa coefficient (K) was calculated using the P0-PE formula divided by P0-1, and its value was 0.84. The results showed that there was a total of 6 dimensions, 18 components and 90 indicators that showed changes in terms of repetition and frequency.
The findings of this study showed that Nash negotiations are effectively able to form agreements that support a fair balance between the negotiating parties. This equality resulting from Nash solutions, in addition to strengthening long-term cooperation, also plays a role in reducing potential negotiation tensions. Structuring the negotiation based on the theoretical framework of Nash negotiations paves the way for the development of more favorable and insightful relations between the parties. Psychologically, Nash techniques can help reduce negative emotions and increase mutual trust. Negotiators who feel their interests are properly understood and established are more willing to cooperate and enter into long-term contracts. This issue not only affects the individual relationships between experts, but also has an effect on the entire structure and performance of the supply chain. Nash solutions also improve the quality of decisions. By focusing on sustainable and win-win outcomes, parties are more motivated to explore innovative and progressive solutions. Innovative perspectives can lead to improved processes, reduced costs, and increased efficiency and effectiveness. At the theoretical level, the application of Nash solutions in this study has benefited from the realistic simulated dynamics that we have achieved a more accurate understanding of the complex dynamics of supply chains. Understanding these complexities has enabled researchers and managers to implement more insightful strategies to guide negotiations and find efficient and successful agreements

Uncertainty in the supply chain is considered as a fundamental and important issue in order to make appropriate decisions for supply chain managers and designers. In this article, in order to deal with this issue, a three-level supply chain under random demand is proposed using two decentralized and coordinated models, in which the profit increase of each actor in the chain (supplier-manufacturer-retailer) considered. In the decentralized model under the scenario-based stochastic demand, the retailer and the manufacturer separately decide on the order quantity and investment by considering the scenario-based stochastic CSR-sensitive demand. A wholesale price contract with two adjustable levels is proposed to persuade three levels to enter into a coordination scheme. According to the comparisons made between the results of the algorithms, it was found that the coordinated model performed better than the other algorithm in reducing chain costs and increasing profits. In particular, it can be acknowledged that the coordinated model performed better than the decentralized model by about 144.39% and was able to increase the profit of the chain.

Designing a multi-level supply chain network with efficient product flow management is an important issue in supply chain management. Determining the price of products, which can be affected by different factors such as environmental uncertainty, will have a significant impact on the strategic decision of designing the supply chain network. In recent research on dynamic pricing, the majority focused on two-level supply chains, exploring the impact of advertising on the supply chain. In this study, the levels of the supply chain are upgraded to three levels, and the advertising and inventory variables as well as the pricing issue in the supply chain are investigated. Hence, the overarching objective is to scrutinize the coordination of a supply chain involving three variables: advertising, warehouse inventory, and a comparison between static and dynamic pricing. Given the accelerated expansion of e-commerce, dynamic pricing emerges as a potent strategy for profit augmentation within the supply chain, an aspect that has received comparatively less attention. The supply chain in this research includes three levels: producer, supplier, and retailer. In addition, many sources, including Chen et al, 2018, have indicated that dynamic pricing is being used in many innovative businesses, that 60% of market development managers around the world are familiar with dynamic pricing methods, and that 35% of CEOs and business managers plan to base all their pricing models on dynamic pricing methods in the next three years. This research initially aims to provide a stable model for dynamic pricing and compare it with static pricing in multi-level supply chains using a game theory approach. Secondly, it examines the theoretical foundations, thirdly, the research methodology is presented, and fourthly, the discussion and conclusions are discussed.

The present research falls under the category of applied research. It considers discount-oriented models to examine the planning horizon, the use of dynamic pricing in some actors at one level of the chain from the concept of dynamic pricing, and the use of static pricing by others at the same level and considering the demand in a non-deterministic (stable) manner. Finally, the use of Stackelberg’s game is presented to examine the core of the game and the Nash equilibrium point. The robust optimization model is presented by Malloy et al. Initially, the model introduces symbols: x as the vector of design variables, and y as the vector of control variables. Parameters A, B, and C are coefficient parameters, while b and e are parameter vectors. Values for A and B are predetermined, and B, C, and e involve uncertainty. A particular understanding of the parameter is called scenario uncertainty, which is assigned the symbol s, and its probability is specified by ps. K retailers operate in the supply chain, and each retailer supplies the desired product from only one manufacturer. In general, the outcome for each retailer is the disparity between their income and expenses. In such a situation, the retailer faces ordering, holding, and marketing costs for each product. The profit margin of each retailer is the difference between the price paid to the manufacturer for the bulk purchase and the selling price to the customer. It is worth noting that considering that the final product of each manufacturer is sent to only one retailer, the number of manufacturers and retailers is equal. For data analysis, a genetic algorithm, particle accumulation optimization, and MATLAB software were employed. Initially, the model underwent analysis in static mode, followed by dynamic mode analysis using Games software. Ultimately, the outcomes of the two pricing methods were compared.

This article introduces the development of a stochastic demand function utilizing genetic algorithms and particle optimization. It presents two distinct single-period models designed for a competitive environment. In the first model, retailers have only an intermediary role and do not decide on pricing or optimal order quantity. In the mentioned model, it is assumed that retailers transfer the demand exactly and to the same extent as it is from the customers to the suppliers. Based on the amount of their production, suppliers face shortages and excess supply. The purpose of this model is to determine the optimal and desirable amount of production as well as the price for each supplier. In addition, routing costs are approximated. The results indicate that the presented approximation is very accurate and evaluates the equilibrium point in much less time than the original model. In the second model, retailers are assumed to incur shortage or maintenance costs according to the number of orders they send. Here, the suppliers determine the final price, and the goal of the retailers is to determine the optimal amount of the order. In this model, it is assumed that suppliers’ production is customized, and inventory costs are considered only for retailers. A noteworthy aspect of this model is the emphasis on dynamic pricing—an inherently crucial and intricate element within the domain of supply chain dynamics theory

The results underscore the substantial efficacy of the proposed combination in addressing the multi-level supply chain network design model with both dynamic and static pricing. The sensitivity analysis of the manufacturer’s profit showed that the changes indicating an increase in the market base of a manufacturer will lead to an increase in profit for both manufacturers. The graph of the change in the producer’s profit compared to the change in the costs showed that a decrease in the production cost leads to an increase in the profit for the producer, while the profit of the next producer decreases in these conditions. Like the producer’s profit, the distributor’s profit also increases with the market base. Expanding the market base not only leads to an increase in the distributor's profit through collaboration with producers but also occurs through two distinct mechanisms. Firstly, there's a profit increase due to raising retailer prices. Although wholesale prices increase with the expanded market base and heightened demand, the distributor, to maintain balance, can elevate retail prices at a higher ratio. Consequently, the value of the pi-wi term increases. Secondly, there's a profit increase resulting from boosting sales volume. The distributor's profit is positively influenced by the increase in sales volume, thereby reinforcing the overall financial outcome.

Implementing the "Vendor-Managed Inventory" strategy and sharing inventory information among retailers and manufacturers play crucial roles in reducing holding costs, shortage costs, transportation costs, and excess inventory costs. This leads to enhanced coordination in the decision-making processes of supply chain members. Therefore, this research delves into the investigation of the supply chain coordination mechanism by combining the vendor-managed inventory strategy and revenue-sharing contracts. Additionally, in the developed model, the demand function incorporates a multiplicative factor of elements influencing the profit function, such as retail price, retailer, and manufacturer advertising investments.
 

In this article, we study the coordination in a two-level supply chain including one manufacturer and multiple retailers under a revenue-sharing contract, where the pricing and advertising investment strategy of each member of the supply chain is implemented despite vendor-managed inventory in a centralized supply chain. Subsequently, in the decentralized state, we employ the Stackelberg game with manufacturer leadership to determine the optimal variables for both manufacturers and retailers. Finally, to reach coordination and achieve the maximum benefit of the supply chain, we proposed a revenue-sharing contract so that the retailer compensates a part of the costs incurred by the manufacturer by sharing a proportion of the revenue.
 

A numerical example is presented to show the implementation impact of the revenue-sharing contract on the profit of the chain members. Costs and profit functions are calculated in the Iranian Rial and this system is planned for one year. In this example, it is clear that this contract has been worked successfully and the profit of the supply chain in the coordinated state is equal to the profit under the centralized state. The sensitivity analysis of the model showed that the profit of each member of the chain in a coordinated state is more than their profit in a decentralized state. In addition, advertising investment increases the profits of manufacturers and retailers significantly. As a managerial insight, it is recommended that both levels of the chain place special emphasis on investing in advertising activities.
 

This research was conceived based on a real-world scenario, where a single manufacturer engages with multiple retailers within a market. The findings of this study have broad applicability across various retail industries, including but not limited to fruit and vegetable markets, grocery stores, protein supply chain outlets, health and beauty product suppliers, drugstores, pharmaceutical supply chains, as well as industries such as automotive and petrochemical. The results of this research proved that the vendor-managed inventory strategy increases the interaction between manufacturers and retailers and helps manufacturers access the retailer information to charge products as soon as possible and also avoid excess production.

The aim of this research is to design scenarios based on cooperative game theory models to investigate the observed rewards and penalties resulting from knowledge sharing or non-sharing among companies. The research population includes managers and experts from 30 top private companies active in the field of oil and gas projects. The research methodology is based on Kumar's classification, which is applied, interpretive, exploratory, and includes both quantitative and qualitative aspects. This study underscores the importance of efficient knowledge sharing as a means to foster collaboration among investors in the portfolios of the National Iranian Oil Company to compete with foreign competitors during sanctions.Upon reviewing the results of four scenarios derived from the game, it is observed that the rewards perceived by companies from knowledge sharing depend on the behavior resulting from knowledge sharing by other companies. The more capable an organization is in the influential factors of knowledge transfer and higher innovation, the greater the returns companies will obtain through cooperation. Sensitivity analysis regarding the costs of project cooperation, which arises due to the difficulty of implementing joint projects, shows that as costs increase, companies shift from a cooperation strategy towards a retaliation strategy and then towards a non-cooperation strategy. These strategies are determined based on aligning the results of the profit equation designed with three interrelated cooperative games: the prisoner's dilemma, the hawk-dove game, and assurance game.

Supply chain management is a modern organizational management mode that organizes and plans information, capital flow, and business partnerships in the supply chain and requires complete business and market information (Quinn et al., 2012). However, the cost of acquiring supply chain companies and product information by traditional methods is very high. Information technology provides the power for companies to implement supply chain management and share the supply chain easily, and all companies in the supply chain can create value through information management (Shawaki et al., 2023). The utilization of intelligent approaches to predict prices and demand quantities enhances supplier delivery performance. It also refines demand forecasting accuracy, improves factory planning precision, forecasts demand for new products, and minimizes supplier risks, transportation costs, inventory, operational expenses, and time (Tirklai et al., 2021). In supply chain management, accurate forecasting of demand reflects the price. It is a critical issue that can reduce inventory costs and achieve the desired service level (Zouqaq et al., 2020). Intelligent supply chain pricing approaches can help supply chain companies to adapt the quality of their product offerings in supply chain management according to the knowledge gained (Kotsiopoulos et al., 2021). Identifying and modeling steel market fluctuations is very important in the steel industry and supply chain management. Considering the vertical chain in this industry and the interaction between the players of this industry, game theory has been used to model the optimal price. Neural network models were employed to replicate the game, as interaction and repeated gameplay are required for achieving balance among players. Taking into account Iran's unique circumstances, notably its confrontations with substantial sanctions in the metal industry, the sanctions variable was integrated as an adjusting factor in the pricing model for this sector.

This is a practical study. The research time frame for predicting steel prices and calculating the sanctions index spans from 2011 to 2020, with quarterly data. The MATLAB software was used.

Three Bayesian neural networks, support vectors, and Grassberg's anti-diffusion were used to predict the price of steel. The results showed that the Grossberg anti-diffusion model is more accurate in predicting steel prices. Next, the predicted price entered the game theory process and the Nash equilibrium point of the model was determined. According to the country's specific conditions, the sanctions variable was introduced in the game theory model. The results showed that the inclusion of sanctions in the model led to price increases and production reductions within the steel industry. The present study delved into price fluctuations resulting from shifts in supply and demand, particularly in the context of sanctions. The findings reveal that a reduction in supply coupled with escalated sanctions led to substantial price hikes, surpassing the impact of supply changes. Consequently, steel exhibits a heightened susceptibility to input constraints, where any disruption in its supply chain triggers significant price spikes, thus unsettling the market. This amplifies the sensitivity of supply chain management for steel. Consequently, a systemic and dynamic approach is essential for market regulation policies, raw material supply, transportation strategies, and warehousing considerations. It should be noted that the use of intelligent approaches and machine learning can play a significant role in coordinating such issues.

Considering that Stackelberg's approach was used in the current research, the sequence of players' entry into the game holds significance with respect to the Nash equilibrium. The development of market entry monitoring rules and regulations in this industry should be investigated because the steel industry is one of the industries that face high entry and exit costs. As a result, Policymakers and industry managers should monitor the entry and exit of players within this sector. They should endeavor to establish norms and regulations governing interactions among market participants to foster a structured and well-defined competitive environment.

The globalization of the economy and the improvement of data innovation has caused the supply-oriented market to alter to the demand-oriented market. Furthermore, organizations ought to prioritize the desires of clients to proceed and survive in the competitive market, which requires the presence of supply chain management. Considering the wide assortment of products and today's competitive market, choosing the correct strategies to provide the required services according to a few primary components such as price, quality level, and the warranty period is one of the most concerns of company managers and dealers. This study sought to consider the increase in the profit of each part of the chain along with providing appropriate services and keeping up product quality, extracting and applying suitable implementation strategies. It also tried to present pricing strategies in a two-echelon supply chain comprised of one manufacturer and two competing retailers, with warranty period, quality, and price-dependent demands.
The strategies presented and discussed in this research have several implications; in addition; their improvements are practical. The profit functions of the manufacturer and the retailers were maximized under centralized and decentralized approaches. Mathematical models were developed in four distinctive cases (i) two non-cooperative frameworks, (ii) a channel-cooperative framework, and (iii) a global-cooperative framework. The producer intended to maximize his benefit by setting a diverse wholesale price for each of the retailers and the length of the common warranty period. On the other hand, retailers maximized their profit by setting the selling price for consumers. This can be explained through the models related to general cooperation strategies, cooperation within the channel, and non-cooperation (Stackelberg of the leading producer and Stackelberg of the leader retailers), furthermore; the profit function of each case and its formula is presented.
For each case, the values of the main decision variables and the profit of each member of the supply chain were calculated and appeared in a numerical case. Moreover, the total profit was compared with each other through two solution methods i.e., the Mathematica computer program and the Championship Algorithm in sports leagues (LCA). The championship algorithm in sports leagues was presented as a population-based algorithm for worldwide search in continuous space and inspired by sports competitions within the real world. During this algorithm, distinctive solutions that can be given to a problem were compared and each one was improved based on its suitability, last; a solution close to the optimum was selected.
A research gap was recognized by studying the research conducted within the field of pricing, warranty, and product quality using the game theory approach. On the other hand, the models were developed by considering all decision variables at the same time as well as between a manufacturer and two competitive retailers deciding on the retail price to maximize their profit. In this regard, four models of Stackelberg manufacturer leader, Stackelberg retailer leader, participation within the channel, and overall cooperation were considered. In all models, the LCA algorithm resulted in better answers compared with Mathematica software. In this study by investigating four techniques, we realized that the best reply can be achieved through the cooperation strategy which is more profitable than the others. Finally, sensitivity analyses were also performed on various model parameters.

One of the challenges faced by the steel industry is supply chain management. Based on this, inthe present research, based on the three scenarios of non-cooperation and simultaneousmovement (Cournot), non-cooperation and sequential movement (Stackelberg) and cooperativebehavior (collusion) will be discussed in the steel supply chain.The research method is applied in terms of purpose. The research period is seasonal data from2011 to 2020 and the software used MATLAB softwareIn this paper, a hybrid model based on artificial neural networks and game theory was presentedto help steel industry activists in determining the price level and optimal production. To predictsteel prices, three Bayesian neural networks, support vectors and cross-emission anti-emissionwere used. The results indicate that the cross-emission model of Grossberg is more accurate inpredicting steel prices. Also, the results show that by moving from the Cournot game to theStackelberg game and from the Stackelberg game to the Collusion game In the supply chain, itwill increase the price in the steel industry by 6 dollars per ton and the amount of product supplywill be in the range of 1500 to 4000 tons In other words, with the increase in the level ofcollusion in the steel market, more products have been offered in the market and at the sametime, the price level of the product will also increase, which will reduce the welfare of steelconsumers in the market.

Cooperation is the cornerstone of social life. Lack of cooperation would lead to a wide range of social, moral, cultural and economic disasters. Altruistic punishment is found to be the major strategy to maintain and to encourage people to adhere to cooperation. The aim of the present study was to separate altruistic punishment from other seemingly similar forms of behavior. For the purpose of study, 60 male students of Shahid Beheshti University participated, were recruited. Their performance at both Dictator Game (DG) and Ultimatum Game (UG) where assessed in a computerized setting. Generally, %75 of participants rejected unfair offers in UG; whilst the same number of participants behaved unfairly in DG. Only, %25 of participants rejected unfair offers in the UG and acted fairly in the DG, which is considered an altruistic punishment. About %50 of participants rejected unfair offers in the UG, but they acted unfairly in the DG. This pattern of behavior is defined as spiteful punishment, which is a form of antisocial punishment. Eventually, %25 of participants accepted the unfair offers in the UG and behaved unfairly in the DG. This behavior pattern shows individual profit seeking at the cost of accepting injustice. A pattern that has not been reported in other studies so far. Although rejecting any unfair offer in the UG cannot be interpreted as altruistic punishment. However, the low rate of this behavior pattern in contrast to the high rate of spiteful punishment predicts a growing lack of social cooperation because the minority of people who behave cooperatively, gradually learn that cooperation is not beneficial. Instead, those who behave selfishly, monopolistically and profit-seeking, get a lot of advantages. In this way, individual profit-seeking surpasses cooperation and becomes the dominant paradigm. This situation is the bane of social life.

Due to the increasing number of competitors, organizations are increasingly looking for aperformance evaluation system that is effective and dynamic In addition to clarifying an organization's current situation, performance evaluation and management can be an organization's strategic plan that could also determine the organization's future. The purpose of this article is to provide a model for evaluating the performance management of oil and gas companies with a game theory approach. The present research is applied and descriptive research, and its branch of survey. The study population of this research includes all companies which act in the field of oil and gas. The statistical sample of this study consists of 280 people who were randomly selected. In the Recent study, multirariate statistical analysis software was used for analysis in to part: descriptive and inferential, mathematical modeling and shapley value. The results showed that paying attention to the customer's perspective will create the most desirability to achieve the vision, and penetration in new markets with a beta of 0.774 directly affects revenue growth.

Supply chain sustainability is necessary for businesses today, so organizations pay attention to social and environmental goals in addition to economic goals. Therefore, to ensure the realization of these goals, measuring the sustainability efficiency of the supply chain is considered inevitable. The problem of assessing the performance of supply chain sustainability, on the one hand, is affected by the inherent conflicts of interest among sustainability goals, which increase the complexity of the problem, and on the other hand, it should be configured in a way that can simultaneously provide sufficient knowledge of the efficiency of overall supply chain sustainability and sustainability goals. In this study, a combined mathematical model of data envelopment analysis and game theory is presented to evaluate the sustainability efficiency of the supply chain and the efficiency of sustainability goals by considering the trade-offs among sustainability goals. The trade-offs among sustainability goals are formulated using the Nash bargaining game in such a way that the ability to provide simultaneous results is related to the overall efficiency of supply chain sustainability and the efficiency of each sustainability goal. The proposed model was evaluated under a case study for appraising the efficiency of supply chain sustainability of an Iranian pharmaceutical company. The results of the model implementation indicate that the proposed model is firstly capable of simultaneously providing efficiency values of supply chain sustainability and each sustainability goal, and secondly, it provides the necessary and sufficient knowledge in comparison of these values for efficient and inefficient products.