Game Theory Model Research Articles

Quantitative easing rules as a means to achieve optimal levels of structural reforms and government deficits in a monetary union

AbstractThis paper uses a tractable game theory model to study the interactions of structural reforms and fiscal and monetary policies in the European Monetary Union (EMU). Considering the externalities that arise when interest rates have hit the lower bound and monetary policy is carried out through quantitative easing (QE), we show that the subgame perfect equilibrium is suboptimal when structural reforms and fiscal policy are implemented at a national level. Then, we prove that the optimal outcome cannot be obtained if structural reforms are dictated by a supranational institution. By contrast, we establish that the first best can be obtained either by a full‐fledged fiscal union or a rule on QE. Given the practical difficulties that the first of these two solutions have encountered in the EMU, a rule over QE provides a clear, easier and more credible way to make structural reforms and fiscal deficits achieve the levels that maximise the union's welfare.

How a Game Theoretic Approach Can Minimize the Cost of Train Passenger Services: An Intermodal Competition between Rail and Road Transport

Game theory models provide very powerful tools for evaluating strategies that are beneficial to both rail and road operators competing for passengers on parallel routes. This study examines how game theory can help rail operators who are incurring losses on passenger transport to identify strategies that can minimise costs, using the methodology of dual linear programming to analyse strategies. In identifying the best strategies for minimising costs for the railway operator, the best strategies for maximising profits for the road operators are also identified. The game model is set up between two passenger transport operators (rail and road) and is based on the income earned by the road operators from passengers. This study illustrates the following: how the strategies of the two competitors (rail and road) are determined; the formation of the payoff matrix and the presentation of the mathematical problem for the two competitors; and the results and verification of the best strategies for both competitors. The Leonid Hurwicz criterion was used to verify the optimal strategies.

A game theory-based analysis of merchants’ mobile payment adoption using hybrid SEM-neural network approach

PurposeDriven by the evidence from the literature on the significance of mobile (m-)payment in economic growth and productivity and at the same time the relative dismal adoption of this service, the purpose of present paper is to elucidate the merchants’ m-payment adoption from the perspective of trust, drawing upon the game theory framework, in the Malaysian context.Design/methodology/approachAn online survey consisting of 302 respondents was carried out to investigate the impact of trust and opportunism on merchants’ perceived trustworthiness using a two-staged structural equation modeling–neural network approach to determine the significance and relative importance of variables. This study also applies a game-theoretic approach to analyze the impact of trust on the relationship between merchants and m-payment service providers.FindingsThe results indicate a positive and statistically significant relationship between merchant trust, merchant opportunism and perceived trustworthiness, and a statistically significant negative relationship was found between m-payment provider opportunism and perceived trustworthiness. The findings from the prisoner’s dilemma two-player model indicate that the scenarios of mutual trust and mutual opportunism as paradigmatic of cooperation and defection produce the best and worse outcomes, respectively. An intriguing result was the positive impact of merchant opportunism on perceived trustworthiness, which indicates a very calculative orientation of merchants in m-payment contracting.Originality/valueTo the best of the authors’ knowledge, this is among the first attempts to propose a game theory approach to the interaction between merchants and m-payment providers under the framework of trust and opportunism. A game theory study in the context of m-payment adoption can contribute to the theoretical literature by providing insights into the decision-making processes of merchants. By incorporating trust and opportunism into the game theory model, we can gain a better understanding of how they affect the decision-making process and overall adoption rates. The conclusions and implications provide useful insights for managers of both m-payment platforms and merchants in this relational exchange. The results of the present research can provide insights into the factors that influence merchant decisions and guide them toward suitable partnerships for successful adoption and can guide authorities for policy interventions and supporting adoption efforts.

Vertical transmission does not always lead to benign pathogen-host associations.

Understanding the capacity of pathogens to cause severe disease is of fundamental importance to human health and the preservation of biodiversity. Many of those pathogens are not only transmitted horizontally between unrelated hosts but also vertically between parents and their progeny. It is widely accepted that vertical transmission leads to the evolution of less virulent pathogens, but this idea stems from research that neglects the evolutionary response of hosts. Here, we use a game-theory model of coevolution between pathogen and host to show that vertical transmission does not always lead to more benign pathogens. We highlight scenarios in which vertical transmission results in pathogens exhibiting more virulence. However, we also predict that more benign outcomes are still possible (a) when generating new horizontal infections inflicts too much damage on hosts, (b) when clearing an infection is too costly for the host, and (c) when vertical transmission is promoted by a greater growth rate of the host population. Though our work offers a new perspective on the role of vertical transmission in pathogen-host systems, it does agree with previous experimental work.

Post financial forecasting game theory and decision making

This paper examines the post-forecasting issue where predictions influence behavior and render original forecasts obsolete. Using game-theory models, we analyze two player types: econometricians with predictions and normal individuals. Our study suggests that late-moving individuals should not participate, while early-mover probabilities in Bayesian games are beneficial. Improved prediction accuracy benefits econometricians but has little impact on normal individuals. Obtaining prediction information incurs a positive cost, overlooked with high accuracy. These findings, supported by preference, uncertainty, information price, and market efficiency analyses, have important implications for investors using forecasting information in financial markets.

Optimal Decisions of Electric Vehicle Closed-Loop Supply Chain under Government Subsidy and Varied Consumers’ Green Awareness

The emerging operating mode of new automobile forces in the context of China brings up new problems for the development of the EV CLSC, which are the market position shift inside the loop and government policy and consumer awareness of changes outside it. Aiming at promoting the development of the EV CLSC, this study integrates the influence of internal and external factors, analyzes their joint impact on the performance of the EV CLSC, and explores the optimal CLSC structure. Specifically, this study develops five game theory models considering different CLSC structures and consumers’ green awareness under government subsidy and varied channel leaderships. Combining theoretical analysis with numerical simulation, the study reveals the performance of the EV CLSC and indicates the optimal CLSC decisions for different players. The result suggests that an EV manufacturer should develop an EV CLSC by itself considering the elimination of double marginalization. When a third-party player is incorporated, the EV manufacturer should undertake the collection effort by itself to optimize the benefit for both the EV manufacturer and the third-party player, especially considering the increasing green awareness of consumers. And a lift of each player’s channel power would always be a wise choice for each other. For the government which has the goals of promoting both the EV industry and the end-of-life treatment of obsolete EVs, a series of trade-offs including the CLSC structure and channel leadership should be considered prudently. This study contributes to the comprehensive understanding of the optimal decisions of the EV CLSC, and will benefit the development of the EV CLSC.

Platform information sharing and selling contract strategies with blockchain adoption

The recent rapid development of blockchain technology has drawn considerable attention. To examine the impact of blockchain on platform supply chains, we construct a supply chain consisting of two suppliers and an e-commerce platform. Each supplier may use either a reselling or an agency selling contract; therefore, three scenarios are possible: pure agency selling, pure reselling, or hybrid contracts. Considering blockchain’s role in eliminating transaction costs and achieving demand information transparency, we apply a game theory model to study each player’s pricing strategy and profits when blockchain and selling contract strategies vary. We find that the platform’s optimal selling contract and blockchain strategies strongly depend on commission rates, competition intensity, and transaction costs. Suppliers are willing to join the blockchain to gain demand information and reduce transaction costs. With low transaction costs and high competition intensity, the platform may ally itself with the agency supplier and authorize him to join the blockchain to maximize profits, which may ruin social welfare. From a social welfare perspective, we find that a pure agency contract is optimal, whereas the optimal blockchain strategy varies. Specifically, blockchain adoption may not benefit social welfare even when its operations costs are negligible. We further explore a scenario in which two suppliers can choose their selling contracts to derive insights into suppliers’ contract choices and government subsidy policies. Moreover, we explore the impact of marginal production costs on the optimal strategy for platforms.

Modelling the emergence of synchrony from decentralized rhythmic interactions in animal communication.

To communicate, an animal's strategic timing of rhythmic signals is crucial. Evolutionary, game-theoretical, and dynamical systems models can shed light on the interaction between individuals and the associated costs and benefits of signalling at a specific time. Mathematical models that study rhythmic interactions from a strategic or evolutionary perspective are rare in animal communication research. But new inspiration may come from a recent game theory model of how group synchrony emerges from local interactions of oscillatory neurons. In the study, the authors analyse when the benefit of joint synchronization outweighs the cost of individual neurons sending electrical signals to each other. They postulate there is a benefit for pairs of neurons to fire together and a cost for a neuron to communicate. The resulting model delivers a variant of a classical dynamical system, the Kuramoto model. Here, we present an accessible overview of the Kuramoto model and evolutionary game theory, and of the 'oscillatory neurons' model. We interpret the model's results and discuss the advantages and limitations of using this particular model in the context of animal rhythmic communication. Finally, we sketch potential future directions and discuss the need to further combine evolutionary dynamics, game theory and rhythmic processes in animal communication studies.

Applications of evolutionary game theory in urban road transport network: A state of the art review

A sustainable transport infrastructure is one of the pillars of a sustainable city. However, the literature indicates that urbanization, population growth, changes in population density, and motorization make it difficult for the current road transport system to meet mobility needs for a sustainable city. Traffic crashes and congestion on roads are common as a result of increasing travel times, fuel consumption, and carbon emissions, thereby reducing efficiency and sustainability of mobility systems. Managing these issues involves the interaction of multiple decision-makers, such as vehicles, pedestrians, traffic system operators, and authorities. Accordingly, these are well-suited to being analyzed under the guise of game theory. While classical game theory possesses multiple limitations, it can be argued that evolutionary game theory (EGT) models are more effective for real-world scenarios. This manuscript presents a state-of-the-art review on EGT applied to the road transportation network. The manuscript has divided the application of EGT in advancing the transportation network into multiple categories, i.e., choice-based analysis, traffic management, behavioral interactions, routing operation, and transport safety. This manuscript provides an in-depth analysis and a comparative criticism of the various proposed evolutionary game models. Finally, the manuscript discusses the challenges and provides recommendations for future research on evolutionary game models in transportation networks. These insights aim to facilitate targeted activities based on current research needs.

Low-Carbon Supply Chain Operation Decisions and Coordination Strategies Considering the Consumers’ Preferences

Implementing the low-carbon transformation strategy has become an inevitable choice for manufacturing enterprises. However, suppliers often overlook the impact of consumers’ preferences for low-carbon products (LCPs) on their own low-carbon strategies. Based on this idea, this study uses game theory models to analyze how consumer preferences affect suppliers’ decision-making and coordination strategies in low-carbon supply chains (LCSCs). Results show that (1) manufacturers and retailers are more likely to produce and promote LCPs as consumers become more sensitive to carbon emission reduction (CER); (2) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to promotional rates; and (3) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to retail prices. This study concludes that consumer preferences play a crucial role in determining suppliers’ decisions and coordination strategies in LCSCs.

Visualization service investment strategies for a self-operated fresh agricultural product e-tailer

Motivated by the fact that numerous fresh agricultural product e-tailers utilize the visualization technology to improve service quality, this paper examines visualization service investment strategies for a fresh agricultural product e-tailer. A supply chain comprised of one manufacturer and one self-operated e-tailer is constructed. We first investigate two service investment strategies in the game theory model: the manufacturer investment and the e-tailer investment. Our analysis reveals that there are two investment cases in the supply chain: one member intends to the service investment (a “win-win” situation) and neither is willing to offer the service (a “lose-lose” dilemma). Then we extend the theory model. The impacts of consumer preference heterogeneity, demand uncertainty and consumer preference for the product quality difference on the investment strategies are explored by the method of multi-agent modelling. We find that: (i) when consumer preference heterogeneity is small, the e-tailer should invest in the service; (ii) if consumer preference or demand uncertainty is moderate, it is difficult to reach an agreement between two players. Further, the government subsidy factor is considered. The issue of how the government subsidy affects service investment strategies is discussed. In fact, it is not necessary to provide a subsidy all the time. Only when the free-riding behavior happens, the government should grant a moderate amount of subsidy to coordinate the supply chain members. An excessive subsidy hurts two sides’ benefits instead.

Role of carbon emission linked financial leasing in shipping decarbonization

ABSTRACT Carbon emission-linked financial leasing (CFL) is a type of financial service that encourages commitment by borrowers to pursue decarbonization for greener operations. The main difference between CFL and traditional financial leasing (TFL) is that the financial lease hire is dynamically linked to the actual carbon emissions. This study investigates a green shipping operations system comprising a capital-constrained shipping firm providing green shipping services to shippers and a financial leasing firm providing the financial leasing business of green ships. By imposing a hard constraint on carbon emissions, we construct game theory models for CFL and TFL. The optimal equilibrium solutions in CFL and TFL are obtained, as well as comparisons of the profits and price of shipping services in different financial leasing models. Results corroborate that CFL is more effective for decarbonization. The participants need to sacrifice their profits, even if carbon reduction cost can be shifted to shippers through the price of shipping services. Tighter carbon emissions constraints can reinforce the effects of shipping decarbonization. Furthermore, we extend our study to cap-and-trade scheme for application. Most of the results derived in the models with a hard constraint on carbon emissions are applicable in the situation with cap-and-trade scheme

Tractable Choice

Models in economics and game theory often assume that people behave as if they can solve very complex problems, which can lead to misleading conclusions. To address this, I propose that we supplement the theory of rational choice with a theory of tractable choice. Tractable choice asks what an individual can accomplish using resources like time, memory, or data, which are often in short supply. The field of economics has been disciplined when it comes to insisting that choices in models be rational, but is less diligent in requiring that choices be tractable under reasonable assumptions about what resources are available. Fortunately, theoretical computer science has developed deep insights and powerful frameworks for understanding tractability. Using a recent paper as a case study, I argue that tractability is a first-order concern when studying behavior.

A Game Theory Study of Big Data Analytics in Internet of Things

With the rapid development of Internet of Things (IoT), big data analytics (BDA) has gradually stepped into the spotlight of IoT research. However, existing research mostly focused on improving the efficiency of data mining, the wishes and profits of the participants in BDA are largely ignored. In real systems, it is always supposed that the IoT data owners accept the big data analytics in IoT (BDA-IoT), the theoretical modeling of BDA-IoT is needed to be constructed urgently. In this paper, aiming to provide theoretical modeling of the practical application of BDA-IoT, we prove the feasibility of participants voluntarily participating in BDA-IoT for the first time. Subsequently, a non-cooperative game theory model with incentive and payment mechanisms is constructed, and the multi-parties interaction process in BDA-IoT is simulated. The overall benefits of all participants are then discussed, the rationality and feasibility of our study are proved. Simulation results show the feasibility of our model in improving the benefits of all stakeholders in a non-cooperative game, and the best choice for all participants is to accept BDA-IoT.

The supportability evaluation of cross-regional major infrastructure projects based on the combination weighting of the game theory–cloud model

PurposeThis study aims to establish an evaluation method for cross-regional major infrastructure project (CRMIP) supportability. The focus is to identify evaluation indicators from a complexity perspective and develop an evaluation model using qualitative and quantitative methods. Case studies are carried out to verify the reliability of the evaluation model, thereby providing theoretical and practical guidance for CRMIP operations and maintenance (O&M).Design/methodology/approachGuided by the idea of complexity management, the evaluation indicators of CRMIP supportability are determined through literature analysis, actual O&M experience and expert interviews. A combination of qualitative and quantitative methods, consisting of sequential relationship analysis, entropy weighting, game theory and cloud model, is developed to determine the indicator weights. Finally, the evaluation model is used to evaluate the supportability of the Hong Kong–Zhuhai–Macao Bridge (HZMB), which tests the rationality of the model and reveals its supportability level.FindingsThe results demonstrate that CRMIPs' supportability is influenced by 6 guideline-level and 18 indicator-level indicators, and the priority of the influencing factors includes “organization,” “technology,” “system,” “human resources,” “material system,” and “funding.” As for specific indicators, “organizational objectives,” “organizational structure and synergy mechanism,” and “technical systems and procedures” are critical to CRMIPs' O&M supportability. The results also indicate that the supportability level of the HZMB falls between good and excellent.Originality/valueUnder the guidance of complexity management thinking, this study proposes a supportability evaluation framework based on the combined weights of game theory and the cloud model. This study provides a valuable reference and scientific judgment for the health and safety of CRMIPs' O&M.

The mystery of choice of equity incentive model: based on the game theory analysis between shareholders and top executives

PurposeBased on the background of the restricted stock has gradually replaced stock option and has become the mainstream equity incentive model in China, this paper aims to investigate the which factors affect the choice of equity incentive model, and the impacts of equity incentive model.Design/methodology/approachThe theoretical analysis is based on the game theory between shareholders and top executives. The empirical analysis is based on the detailed data of equity incentives in China’s listed companies from 2006 to 2017; the logit method and least square method are implemented to estimate the regression coefficients and Black–Scholes options pricing model to estimate the value of restricted stock/option granted to the CEO.FindingsThis paper documents that enterprises with serious agency problems, high investment risks, high stock price synchronicity and great executive power are significantly and positively related to restricted stock. The main empirical findings still hold after several robust tests. In addition, restricted stock can significantly improve corporate performance when the performance evaluation index is strict and the validity period is long, while for the sample group with loose performance index and short validity period, restricted stock significantly reduces corporate performance.Originality/valueThis paper analyzes the “black box” of equity incentive model selection from the stakeholders’ game perspective by constructing a game theory model to investigate the reasons for the choice of equity incentive model in various situations, which enriches the research in this field. Moreover, this paper finds that restricted stock has both incentive and welfare characteristics, and the rationality of performance appraisal goals is the key factor leading to the difference in incentive effects. Overall, the research indicates that only well-designed equity incentive plans can improve corporate performance, which contributes to regulators and practitioners to form a rational understanding of restricted stock model and provides a reference for their decision-making.

A tripartite evolutionary game model for the hydrogen fuel cell vehicle industry development under government regulation in China

The development of the hydrogen fuel cell vehicle (HFCV) industry constitutes a necessary advancement in the transformation and upgrading of the automotive industry as a whole and is also an important strategic route to help China achieve the objectives of carbon neutrality. How to effectively promote the production of HFCV enterprises and the purchase of HFCVs by consumers has become a critical problem that needs to be solved. Taking into consideration the limited rationality of the government, enterprises and consumers, we applied a tripartite evolutionary game theory (EGT) model to analyze the impact of government regulation on the development of the HFCV industry. The simulation results show that: (1) medium-intensity supervision can promote robust and regulated HFCV industry development; (2) the higher the penalty, the more likely enterprises are to transition to HFCV production; (3) the larger the research and development (R&D) subsidy, the more beneficial it is for enterprises to overcome technical obstacles; (4) higher investment in infrastructure stimulates consumers to purchase HFCVs. Based on these results, some recommendations have provided to support the sustainable development of HFCV industry in China.

Applied Research Analysis of Game Theory and Markov chain

Since probability theory was put forward, it has been applied in all aspects of life and many science and technology. A good use of probability thinking can make a more rational, wise, and correct judgment and improve the probability of winning. Among them, game theory and Markov chain are the most influential. They have become one of the important theoretical foundations of various industries and fields, and gradually mathematize various fields, playing a vital role in their applied research field, promoting the development of society and science and technology. The prisoner's dilemma model of game theory was analyzed in various situations and explained how to apply it to economics, how to affect the social economy, and how to solve some social economic problems. By analyzing and utilizing the integrability, constant return, periodicity, and ergodicity of Markov chain, it is applied to signal transmission, traffic management, and bad debts of banks. Markov chain is used to model various transmission processes to facilitate the application field.

인질범죄에 대한 형의 임의적 감경 규정의 실효성 분석 연구

In order to protect the life and safety of hostages in hostage-taking crimes, Criminal Law stipulates provisions for reducing the sentence in Articles 295-2 and 324-6. The purpose of the regulation is to deter secondary crime against hostages as an incentive for actors to safely release hostages. However, it is somewhat questionable whether the preferential treatment of criminal policy at the level of arbitrary mitigation is an effective motive for the hostage offenders to safely release the hostage. Accordingly, using the sequential game model of game theory, this study analyzes what selective strategies are carried out under the interdependence between hostage criminals and law enforcement authorities.
 In the game model, the compensation vector of each participant used Becker's equation of criminal utility theory. First, the strategic choices of hostage offenders, law enforcement authorities, the general public, and law enforcement authorities were examined separately to derive the limit and general deterrence effects of the hostage release reduction regulations respectively. In addition, in the strategic choice analysis between hostage offenders and law enforcement authorities, the tendency of hostage offenders was divided into risk avoidance, risk neutrality, and risk preference type, and in each case, the hostage offender made a choice between necessary reduction or arbitrary reduction. In order to promote the safety of hostages, necessary reduction or exemption was found to be the most effective incentive. However, it should be noted that this result may give the wrong signal as an incentive for hostage crimes to the general public, who are potential criminals.
 Furthermore, this study also examines the possible improvements of the current liberation reduction regulations by reflecting the golden time in relation to the age of hostages. Given that the purpose of the liberation and mitigation regulations is to protect the lives and security of hostages, it is highly likely that the law enforcement authorities' attempts to negotiate after the golden time will be meaningless. It was confirmed that the golden time, which can guarantee the safety of the hostages, has a large time difference depending on the age of the hostages. As a result, in order to ensure the safety of hostages and to ensure the fair exercise of national punishment rights, the temporal application of the liberation and mitigation regulations should be more precisely defined by reflecting the golden time. In order to safely release hostages within the period by applying the golden time, the average time after victims are robbed and attracted, the need to define greater incentives for compensation than the current arbitrary reduction should be considered.
 Finally, this study suggests that the method of statistics collection and crime analysis on hostage crimes needs to be completely reorganized as a premise to reflect the difference in golden time in legislation.

Research on Firm Recruitment on Adverse Selection under the Game Theory Model

In the era of global economic integration, economy and science and technology have in-creasingly become the decisive factors of international competition, and among them, enter-prises have increasingly become the main body of competition. Therefore, in recent years, major enterprises have increasingly improved the core competitiveness of their enterprises, and the research on human resources has become more and more in-depth. To maximize the benefits, in recent years, companies around the world have gradually realized the im-portance of high-level talent to their company's capabilities. However, due to various prob-lems, such as information asymmetry caused by adverse selection, it is increasingly difficult for companies to select real talents to contribute more to themselves. Through the estab-lishment of the game theory model, this paper discusses the benefits and losses for employ-ers and applicants and finds the best employment recruitment scheme. The research results show that the information asymmetry in the recruitment process will greatly reduce the effi-ciency of enterprises to find talents, and cause losses to both recruiters, so this paper puts forward relevant suggestions for the problem of information asymmetry to make up for the information asymmetry of the double-reverse, to promote the absorption of outstanding tal-ents by enterprises and drive the development of enterprises and economic recovery.