Game Theory Methods Research Articles

GAME THEORY AND FINANCIAL COMPONENTS FOR DETERMINING THE BUDGET PLACES OPTIMAL DISTRIBUTION IN THE HIGHER EDUCATION SYSTEM OF UKRAINE

The complexity and interdependence of management and decision-making problems in the system of higher education require new ideas and approaches, which necessitates the search for new management solutions using modern approaches and methods of economic and mathematical modeling. The article is devoted to the problem of optimal allocation of budget places for higher education institutions by specialty. The conducted research shows that the priorities of the state, labor market and consumers do not coincide. In this situation, the university, as a provider of educational services, must balance the demand of the consumer (applicants, students and their parents) with the offers of the customer (the state, entrepreneurs, the labor market), taking into account the forecast of demand in the labor market. The purpose of the study is to determine the optimal allocation of budget places for higher education institutions considering financial constituents, system analysis and the game theory method. A solution to the problem is offered by building an economic-mathematical model using game theory techniques and methods of analyzing hierarchies, which have a powerful apparatus for considering many different models, approaches and concepts for solving the same problem. The presented mathematical model allows to obtain a balanced optimal distribution of budget places by university specialties, which harmonizes the demands of applicants and employers. The budgetary expenditures for higher education are an effective regulator of direct action on the training of specialists with higher education and an instrument of state regulation of the number of state-ordered students. Based on the results of the study, the model of distribution of the institution's budget expenditures for decision-making management is proposed, which allows redistributing funds to expenditure items that are included in the development expenditures of higher education institutions. Further development of the described model in the direction of researching the impact on existing restrictions on the market of educational services will allow offering powerful mechanisms and technologies for managing the process of forming optimal strategies for the development of higher education institutions.

Analyzing the effects of government policy and solar photovoltaic hydrogen production on promoting CO2 capture and utilization by using evolutionary game analysis

This study aims at proposing a public-private partnership project including the government (GOVT), coal-fired power plant (CTPP) and solar photovoltaic power plant (PVPP) toward carbon emission reduction and neutralization in China. The project is formed using the CO2 capture and utilization (CCU) and solar PV hydrogen production technologies. When all the participators cooperate, the influence of typical factors on the project is evaluated using the evolutionary game theory method. The results show that increasing the CCU subsidy can strengthen the participating intention of the CTPP but will reduce that of the GOVT. Improving the green electricity subsidy can strengthen the participating intention of the PVPP but will decrease that of the GOVT. To ensure the smooth running of the project, a relatively higher carbon emission penalty and a higher sales price of methanol should be ensured, the PVPP should control its daily working hours appropriately, and the proportion of electricity quantity of the PVPP used for hydrogen production should be increased. In this study, the suggested ranges of CCU and green electricity subsidy coefficients are 0.03–0.05 $/kWh and 0.0035–0.0045 $/kWh, the carbon emission penalty coefficient should be greater than 11 $/t, and the suggested range of daily working hours of the PVPP is 7–8 h.

DIGITAL TRANSFORMATION OF THE COUNTRIES OF THE CENTRAL ASIAN REGION: PROSPECTS OF PUBLIC ADMINISTRATION IN KAZAKHSTAN

Scientific interest in the research topic is due to the fact that effective public administration in the modern world is largely determined by the development of digital transformation. It is worth noting that the issue of digitalization of the sphere of public administration has been studied by the authors, including through the use of the method of game theory. To this end, the article analyzed data on the digitalization of public administration in all five countries of the Central Asian region (CAR). Based on open data on the spread of innovation published by the World Bank (WB), this study was mainly focused on the GovTech indicator. We believe that in the context of the accelerated development of the economies of the countries of the region, the study of the development of digitalization in the field of public administration is of particular importance.

Game theory analysis of biometric systems market: Users choice VS service providers revenue

This paper represents a study of the interaction between users' choice and the service providers revenue in the biometric system market. This study is based on the game theory method, in which the authors assumed that all service providers are offering systems with the same quality that respects users' privacy. The authors presented service providers utility and users choice with two functions that takes into consideration the price of the service and the degree of irrationality of users. The results have shown that there is an equilibrium point between service providers utilities. Moreover, service providers revenue increases with the augmentation of their client's irrationality. Therefore, in term of maximizing their revenues, service providers prefer irrational customers rather than rational customers. And this result has been achieved when representing the graph of the price of Anarchy which reaches the value 1 as the degree of irrationality of customers increases.

Optimizing the Interaction Between Two Closed-Loop Supply Chains Based on Inverse Logistics Using the Game Theory Method

Abstract Over the past few years, attention to environmental problems, legal necessities, and economic advantages emerging from reproduction activities has attracted attention to reverse logistics activities in the form of a closed-loop supply chain, whether in industry or scientific research. The current study aims to model competitiveness and comparison between two closed-loop three-level supply chains, each of which includes a manufacturer, a retailer, and a third party to collect the products used by the customer, taking into account the concepts of game theory and the existence of aggregates. Moreover, a separate supplier for each chain is considered. In the forward supply chain, the manufacturer produces new products using new components or re-used products that have been collected from the consumer, then sells these products mainly to the retailer, and the retailer sells them. In the reverse chain, the collector provides the used products to the manufacturer after collection. The study utilized the definitions and concepts of game theory to model this closed loop chain as a Stackelberg game to obtain the optimal value of wholesale and retail price and the optimal value of the product return coefficient for the collector. Finally, the models based on some numerical examples are solved. Given the results, the remanufacturing costs have a significant role in making more profits for all members in such chains, and competitive chains should attempt to remanufacture the products at lower costs.

Stable control algorithms for non-stationary objects based on game methods

The paper considers the issues of constructing stable control algorithms for non-stationary objects based on the concepts of game methods. According to the principle of dynamic programming, control is defined when there are or are no restrictions on control actions. A.N.Tikhonov’s regularization method is used for stable estimation of the perturbation vector using the principle of the least residual estimate, as well as the method for compiling and solving an extended regularized normal system of equations. The obtained expressions make it possible to form control algorithms for linear non-stationary objects, which are stable when the control actions are limited, taking into account the feedback channel signal. At the same time, the use of game theory methods makes it possible to optimize management decisions under the conditions of inefficiency of classical management methods under conditions of a high level of a priori uncertainty of processes in the system under consideration.

Bargaining Power in Cooperative Resource Allocations Games

Cooperative game theory provides an appropriate framework to assess the likelihood of conflict resolution, encourage cooperation among parties, and determine each party’s share in resource sharing conflicts. In calculating the fair and efficient allocation of the incremental benefits of cooperation, cooperative game theory methods often do not consider the exogenous bargaining powers of the players based on factors, that are external to the game, such as their political, economic, and military powers. This study reformulates three well-known cooperative game theory methods, namely, Nash-Harsanyi, Shapley, and Nucleolus, to account for the exogenous bargaining powers of the players in cooperative games. Using the Caspian Sea international conflict as an example, this paper shows how the negotiators’ exogenous bargaining power can change the outcome of resource sharing games. The proposed weighted cooperative game theory approach can help determine practical resolutions for real-world conflicts in which the exogenous powers of players can have a significant influence on the outcome of negotiations.

Macro-site selection and obstacle factor extraction of biomass cogeneration based on comprehensive weight method of Game theory

Biomass energy can reduce the consumption of fossil fuels and reduce environmental pollution. The project site selection affects the production efficiency and economic benefits. Firstly, this study proposes a macro-site selection decision framework for biomass cogeneration considering carbon emission reduction. Secondly, this paper innovatively uses Nash equilibrium as the coordination goal, and introduces Game Theory to determine the optimal combination weight of Best-Worst Method (BWM) and Criteria Importance Though Intercriteria Correlation (CRITIC). Further thinking is needed to improve the comprehensive closeness measurement method, establish a Technique for Order Preference by Similarity to an Ideal Solution and Grey Relational Analysis (TOPSIS-GRA) site selection model that reflects distance and curve shape, and sort the plans. And then explore the barriers to improving the site selection environment. Finally take five cities in China as an example. The feasibility and the stability of the site selection decision-making framework in practical applications are verified by comparative analysis and weight sensitivity analysis. The results show that carbon emission is the primary barrier factor in the criterion layer. In the sub-criterion layer, transportation costs, carbon emission pressure, carbon benefits, industrial policies, and heating rate are the common obstacle factors in each region. To promote the long-term healthy development of the project, this study provides a theoretical reference for the new construction and expansion of biomass cogeneration projects, and has guiding significance for improving the location suitability of the project.

Optimizing hydropower generation and sediment transport in Yellow River basin via cooperative game theory

The complicated relationship between water and sediment in the Yellow River Basin (YRB) makes it imperative for reservoir stakeholders to game with each other to balance the short-term and long-term benefits. This paper proposes an integrated model to analyze the cooperation opportunities for major reservoir stakeholders engaged with the Longyangxia, Liujiaxia, Wanjiazhai, Sanmenxia, and Xiaolangdi reservoirs on the YRB mainstream. Multiple benefits are considered, including flood control, water supply, hydropower generation, and sediment trapping. Non-cooperation and cooperation scenarios are compared in this study. The effect of flow and sediment conditions on the incremental benefit of cooperation is examined, which shows that the systematic incremental benefit is larger when the YRB is dryer and sediment concentration is higher. Basin-wide cooperation is especially beneficial when the inflow peak comes earlier and the streamflow process is more fluctuating. Cooperation of reservoir stakeholders in a normal year (2019) can bring more incremental benefit (i.e., $22.57 million) in contrast to the non-cooperation scenario. Longyangxia, Liujiaxia, and Wanjiazhai reservoirs contribute most to the grand cooperation by implementing optimal operation for downstream stakeholders. Three cooperative game theory methods (Shapley value, Gately point, and Nash–Harsanyi solution) are employed to find possible benefit-sharing solutions. Based on cooperative game theory, the results demonstrate the core of basin-wide cooperation in the Yellow River is negligible due to the negative externality effect, implying more measures are needed by the government or non-profit organization to maintain the stability of grand coalition, i.e., water resources utilization control and external compensation. The results also show that Shapley value could be used to reallocate the incremental benefits in the grand cooperation.

Economic Evaluation of Drought Resistance Measures for Maize Seed Production Based on TOPSIS Model and Combination Weighting Optimization

In order to optimize the appropriate drought resistance measures in the implementation of high-efficiency and intensive production of maize seed, in 2018 and 2019, maize cultivation experiments with different drought resistance measures were carried out in the arid area of northwest China, including water retention agent (SA), white plastic film mulch (WF), black plastic film mulch (BF), straw mulch (SM), and open ground flat seed as control (CK). A total of five treatments were conducted. Ten specific indicators contained four types of attributes, namely the yield, quality, water use efficiency (WUE), and economic benefit of maize seed production, aimed at constructing a multilevel evaluation system. To improve the reliability of evaluation results, subjective and objective weights of indexes were calculated using the analytic hierarchy process (AHP) and entropy weight method (EWM), respectively. Then, based on the integrated weighting method of game theory (GT), the combined weights of subjective and objective unity were obtained. Finally, with the help of the technique for order preference by similarity to ideal solution (TOPSIS), a comprehensive benefit evaluation model was established to screen out the optimal drought resistance measures. Compared with CK, different drought resistance measures significantly improved the grain quality of seeds-production corn, and the average annual yield and WUE of black and white film treatments were improved by 49.57% and 42.97% and by 65.67% and 58.21%, respectively. This proved that black film mulching (BF) could significantly increase the yield and WUE of maize seed production and effectively improve grain quality, which could be used as the best drought-resistant cultivation mode for maize seed planting in Hexi and similar areas.

Comprehensive Evaluation Model of Coal Mine Safety under the Combination of Game Theory and TOPSIS

At present, the frequent occurrence of coal mine accidents in China is a key concern in the field of safety. Although the coal mine accident rate is decreasing due to the progress of technology and the improvement of management, there is still a lack of comprehensive evaluation of the role of various factors in the coal mine. Therefore, the purpose of this study is to establish a game theory combination weight-TOPSIS comprehensive evaluation model based on the analysis of various factors affecting coal mine safety. The model combines the weights obtained from fuzzy analytic hierarchy process (FAHP), entropy weight method (EWM), and back propagation neural network (BP-NN) by using the combination method of game theory and then combines with the TOPSIS method to evaluate 20 indicators in four aspects of a coal mine: personnel, equipment, environment, and management. Taking five mines under Zheng Coal Group as an example, the evaluation results of the game theory combination weight-TOPSIS comprehensive evaluation model are compared with those of the fuzzy analytic hierarchy process and the improved composite weight-TOPSIS method. The results show that the safety grade of the five mine samples under Zhengmei Group is ranked as follows: mine 4 > grade II (relatively safe) > mine 2 > mine 5 > grade III (moderately safe) > mine 3 > mine 1 > grade IV (generally safe). The evaluation result of the game theory combination weight-TOPSIS method is basically consistent with the actual safety situation of the coal mine, which reflects the superiority and practicality of the evaluation model. The model has greater differentiation in the process of determining the coal mine safety grade, and the evaluation results are more intuitive and reasonable, which can provide a more effective evaluation tool for the comprehensive evaluation of coal mine safety. Finally, based on the evaluation results, corresponding policy recommendations to improve the status quo of coal mine safety are proposed, aiming to provide decision-making reference for coal mine safety management personnel.

Discovering biomarkers of hepatocellular carcinoma from single-cell RNA sequencing data by cooperative games on gene regulatory network

Effective and reliable biomarker is a promising means to achieve early diagnosis of cancer. The availability of high-throughput single-cell RNA sequencing (scRNA-seq) data opens an unprecedented opportunity of discovering biomarkers by developing machine learning and feature selection methods. At present, the existing biomarker screening methods, such as recursive feature elimination (RFE), often treat genes as isolated features, ignoring their embedding complex network relationship. In addition, the interpretability of a cancer biomarker discovery model is as important as its classification accuracy. To address these problems, we propose a game theoretic method to discover gene modules serving as biomarkers on gene regulatory network (GRN) that can better distinguish hepatocellular carcinoma (HCC) samples with healthy ones. Specifically, the network-based game theory method, called NGTM, is an interpretable module exploration of supervised feature selection procedure. We regard the process of gene-to-model selection as a cooperative game. The contribution of each feature in combination is evaluated by cooperative game theoretic metrics, that is, Shapley values. The extension strategy of gene module is conducted on GRN in the form of subnetwork, and NGTM makes the biomarker recognition easily interpretable. Furthermore, our method is statistically verified by Akaike information criterion (AIC) in model selection. There is a strong correlation between AIC and the area under curve in classification. In comparison study, we test the wrapper RFE and random feature extraction methods on random forest under the same conditions. NGTM achieves relatively better classification performances which prove its advantage. The enriched dysfunctions in biomarkers are also consistent with prior knowledge of the occurrence and development of HCC.

Evolutionary Game Analysis of Non-Governmental Organizations Participating in Garbage Management under the Background of Internet of Things

In the context of the information age, due to the development trend of information technology and the increasingly prominent position of economic activities, Internet of Things technology, as an important part of the new generation of information technology, stands out in the management of municipal solid waste collection and transportation management. At the same time, it has also become an efficient management means to realize waste treatment and construct high-quality urban green infrastructure in the environmental protection industry. Under this reality, environmental non-governmental organizations are becoming increasingly important as an organized social force in limiting national environmental power. It has become a crucial force in municipal solid waste management. Within this context, this study aimed to evaluate the strategic choice relationship among environmental non-governmental organizations, local governments, and garbage disposal enterprises, as well as the impact of environmental non-governmental organizations participating in the supervision of the implementation of information waste classification and management systems. In this study, the game theory method is used to construct the tripartite evolutionary game model of local governments, garbage disposal enterprises, and environmental non-governmental organizations, and the Matlab simulation model is established. The results of model analysis and simulation show that direct supervision, financial support, and punishment from non-governmental organizations, as well as pressure measures by non-governmental organizations, can promote the implementation of Internet of Things technology behavior. High-intensity financial support, low-intensity punishment and pressure measures, and moderate direct supervision have the most significant effect on the implementation of Internet of Things technology.

Improved Bayesian Network and Its Application in Autonomous Capability Evaluation

The Bayesian network (BN) is a new intelligent evaluation technology, which has become one of the effective methods to solve uncertainty problems and deal with asymmetric information. However, its application is limited in the case of complex indicator systems and interrelated variables. To solve these problems, an improved BN model based on game theory is proposed. First, an IHORAFA attribute reduction algorithm is used to optimize the index system. Then, a weighted BN evaluation model is proposed for the problem of correlation among indicators, which uses the improved combination weighting method of game theory to determine the optimal weight and improve the accuracy of weight calculation. Finally, the improved BN is applied to the autonomous capability evaluation of ground attack UAVs. The simulation results show that the improved BN model can be used for assessment and reasoning under uncertain conditions and variable correlation.

A Study on College Students’ Cognitive Intention and Path Choice of Entrepreneurship from the Perspective of Individual and Group Cooperation

In order to study the overall low entrepreneurial enthusiasm of college students, a method was proposed based on the cognitive intention and path choice of college students’ entrepreneurship from the perspective of individual and group cooperation. The method briefly introduces the achievement motivation theory, entrepreneurial intention theory, entrepreneurial cognition theory, classical game theory, computer simulation, and experimental methods. Then, the research hypothesis and model construction method are elaborated, and a questionnaire is designed to study the cognitive intention and path of entrepreneurship of college students. Finally, data analysis and hypothesis testing are described to provide a guarantee for college students’ entrepreneurship. The results show that the fundamental driving force for the great progress of entrepreneurship education in colleges and universities is to meet the needs of both the collective and the individual in the top-level design and to realize the mechanism through which entrepreneurship education can achieve common development.

Evolution of cooperation with time-varying tags and heterogeneous immigration dynamics

Cooperation in an open dynamic system fundamentally depends upon information distributed across its components. Yet in an environment with rapidly evolving complexity, this information may need to change adaptively to enable cooperative interactions. Combining the methods of evolutionary game theory, agent-based simulation, and statistical physics, we develop a model of the evolution of cooperation in an ageing population of artificial decision makers playing spatial tag-mediated prisoner’s dilemma games with their ingroup neighbors and with genetically unrelated immigrant agents. We introduce the concept of time-varying tags such that the phenotypic features of ‘new’ agents can change into ‘approved’ following variable approval times. In the standard 4-strategy model with fixed tags, we identified a critical cost [Formula: see text] above which cooperation transitioned abruptly into the phase of pure defection. In our generalized 6-strategy model with time-varying tags, the maintenance of elevated cooperation was observed for a much wider region of the parameter space, peaking at intermediate approval times and cost values above [Formula: see text]. Our findings reveal the existence of optimal approval times leading to high levels of cooperation if a fraction of the population adopts the strategy with an egalitarian generosity directed towards both native and approved agents, regardless of their actual origin.

Optimal Decisions in a Multi-Party Closed-Loop Supply Chain Considering Green Marketing and Carbon Tax Policy

Global warming and e-waste pollution are two major environmental pollution issues that have attracted widespread attention. The government has adopted various measures to reduce carbon emissions from businesses and to make manufacturers responsible for recycling e-waste. In the face of external pressures, more and more companies are implementing sustainable closed-loop supply chain (CLSC) management to reduce environmental pollution and achieve sustainable development. Therefore, it is essential to study the operational decisions of CLSC enterprises. This paper considers a sustainable CLSC consisting of two competing manufacturers and a dominant retailer. The government imposes a carbon tax on the retailer, and two manufacturers collect used products directly from their customers. We separately examine whether implementing green marketing by the retailer and the collaboration between the two manufacturers can improve their profits. By building decentralized CLSC mathematical models and applying game theory methods, we obtain that green marketing can increase profits for all CLSC members and improve return rates. The collaboration may yield higher total profits for two manufacturers than a decentralized solution, while the retailer’s profits may be lost under certain conditions. Finally, we perform several numerical analyses to find the relationship between unit carbon emission tax and social welfare and gain some managerial insights. The study gives key factors that CLSC companies should consider when making decisions to help them achieve sustainability and provides recommendations for the government to set a reasonable unit carbon tax.

Evolutionary Game Analysis of Carbon Emission Reduction between Government and Enterprises under Carbon Quota Trading Policy.

As one of the most efficient means of emission reduction policies, carbon quota trading has a far-reaching impact on the carbon emission reduction of enterprises. Firstly, a two-party evolutionary game model of enterprise and government and a three-party evolutionary game model of enterprise–enterprise–government are constructed based on the multi-agent driving mechanism, evolutionary game theory, scenario simulation, and other methods. Then, we conduct a series of policy simulations for carbon emission under different scenario models and various enforcement strengths. Lastly, the behavioral strategies and system evolution trajectories in enterprises and government carbon trading are comprehensively investigated. The results show that in the two-party and three-party evolutionary game models, the carbon trading behavior is affected by the joint action of the enterprise and the government. The difference in initial willingness mainly affects the speed of the subject’s convergence to the steady state. Based on this, policy suggestions are proposed, such as reducing the cost of carbon emission of enterprises, enhancing the vitality of carbon emission reduction of enterprises, and stimulating the power of government regulation and responsibility performance, which can provide suggestions for the development of the carbon market.

Legal Regulation of E-commerce Credit

In last years, China's online economy has developed rapidly, but the imperfect credit mechanism has become one of the important factors restricting the healthy development of e-commerce. This paper discusses the characteristics of e-commerce credit mechanism and uses the method of Game Theory to analyze the important point of the legal regulation. At the meantime, this paper proposes countermeasures to improve our country's legal system of e-commerce credit from the e-business credit information legal system, credit evaluation legal system, credit supervision legal system and disciplinary legal system.

Modelling closed-loop dual-channel supply chain: A game-theoretic approach to maximize the profit

The essentials of clean environment and sustainable development witnessed the rise in closed-loop supply chains. From past two decades, the studies on digitalization of supply chain activities considering resource scarcity, reuse and remanufacturing have engrossed attention from academia about fundamentals of Closed-Loop Dual-Channel Supply Chain (CLDSC). In this paper, a two-level CLDSC consisting of a manufacturer, a retailer, and an e-tailer is considered as a formal buyer and used product collector. The study's main idea is to evaluate optimal pricing and effort decisions for CLDSC scenarios namely; vertically integrated, decentralized, partial retail, partial direct and horizontally integrated scenarios. A Stackelberg game theory and backward induction method is used to get the optimum values of decision parameters (selling price, buyback price, sales effort, and collection effort). Their relations are established, measured and compared to show managerial insights and proportional measures. A numerical illustration with sensitivity investigation is furthermore presented to simulate the effects of channel preferences, price coefficients, sales, and collection effort coefficients for price and effort optimization on decision parameters. As a managerial implication, this analysis helps the channel members to make strategic decisions about CLDSC and choose the best fit channel structure. The findings of this research elucidates partially integrated scenario executes optimum performance in terms of cost and effort both; one can compare the optimum values and predict the outcomes.