Game Theory Approach Research Articles

Game Theory Approach for Autonomous Mobility-Assisted Piggyback Network with mm-Wave Links

Game Theory Approach for Autonomous Mobility-Assisted Piggyback Network with mm-Wave Links

Erratum for “Game Theory Approach for Concurrent Delay Analysis”

Erratum for “Game Theory Approach for Concurrent Delay Analysis”

Shared recycling model for waste electrical and electronic equipment based on the targeted responsibility system in the context of China

The formal recycling of waste electrical and electronic equipment (WEEE) has long faced collection difficulties owing to the inadequate recycling system and insufficient collection capacity under China’s fund-based recycling model. The government has introduced the recycling Target Responsibility System (TRS) to motivate producers to develop and share recycling systems, yet without clear incentive mechanisms. In this study, we provide a “1 + N” shared recycling model referring to the theory of the sharing economy, and we propose a credit mechanism with a deposit system and a penalty mechanism for dishonesty to constrain the opportunistic behavior of sharing. In addition, according to the TRS, we design a “reduction-penalty-subsidy” fund policy to incentivize producers and recyclers to achieve recycling targets. On this basis, we apply evolutionary game theory and system dynamics approach to analyze the collaborative mechanism of shared recycling and the incentive effect of the funding policy. Game analysis yields the evolution of shared recycling from the developing stage to the mature stage. The system simulation results indicate that the government’s “penalty” and “subsidy” strategies provide evident incentives for producers and recyclers, respectively, in the developing stage, whereas endogenous dynamics derived from economies of scale under market mechanisms promote the multi-agent collaborative implementation of shared recycling in the mature stage.

Producing Green or Brown? A Game of Green Innovation in an Asymmetric Oligopoly

As consensus grows for low-carbon development, innovation becomes vital for green growth, given the substantial technology adoption needed for long-term environmental targets. This paper explores market-driven incentives for green product innovation in an asymmetric duopoly using a game theory approach without relying on direct government intervention. The roles that market dynamics and rivalry have on the supply of green or brown products are explored in simultaneous and sequential scenarios, considering technology costs, demand-creating effects, rivalry gains, and information availability. Results reveal that a fully green market is contingent on low innovation costs, depending especially on the magnitude of demand creation effects. Notably, product differentiation occurs only under extreme cost asymmetry. Recommendations underscore the importance of incentivising low-cost innovations, assessing the impact of product differentiation and diversity, especially concerning lower-income consumers, and proposing measures to improve the transparency of firms’ strategic choices.

An evolutionary analysis of supply chain collaborative information sharing based on prospect theory.

In order to delve into the dynamic evolution process and influencing factors of information sharing decisions among stakeholders under supply chain collaboration, this study constructs an evolutionary game model with suppliers and retailers as the primary entities. Within this model, a combined approach of game theory and prospect theory is employed, integrating prospect value functions and weight functions to create an information sharing prospect value matrix. A comprehensive analysis is conducted on the strategic choices and benefits of entities considering the psychological perception of information sharing, and critical factors influencing the stability of information sharing evolution results are explored through numerical simulations using Matlab. The key findings of this study are as follows: Firstly, from the perspective of supply chain collaboration, the probability of entities evolving into information sharing is negatively correlated with the cost of information sharing and positively correlated with the benefits generated by information coordination. Secondly, looking at supply chain collaboration, entities are more likely to engage in information sharing behavior when they exhibit a lower level of risk aversion, indicating greater rationality, when facing profits; conversely, they are more likely to participate in information sharing when they display a higher degree of risk preference, indicating less rationality, in the face of losses. Furthermore, the lesser sensitivity of suppliers and retailers to losses is more likely to drive the system towards an information-sharing state. Based on the primary findings mentioned above, this study offers recommendations for enhancing trust, constructing information exchange platforms, and adjusting psychological awareness. These suggestions contribute to improving information sharing among entities within the supply chain, thus enhancing the overall efficiency and collaboration of the supply chain.

Promoting strategy of rural energy consumption electrification: a network game theory approach

Promoting strategy of rural energy consumption electrification: a network game theory approach

Vibration based single-objective finite element model updating using cooperative game theory approach

This paper introduces a novel approach that focuses on application of cooperative game theory model for automated finite element model updating. The approach involves transforming the conventional single-objective optimization finite element model updating problem into a game theory problem. Among the different alternatives, a cooperative game model is considered to solve the transformed updating problem. This new approach overcomes the limitations of the conventional single-objective optimization formulation, which include challenges related to selecting appropriate weighting factor of residuals and analysing their influence on optimization results. To demonstrate the effectiveness of the proposed approach, an ultralight fibre reinforced polymer footbridge is considered. The numerical model of the footbridge is updated using the experimentally determined inherent properties (natural frequencies and mode shapes) using the proposed approach. A comparison with the conventional sensitivity-based weighted single objective method reveals that the inclusion of the weighting factor in the optimization process under the cooperative game model method allows for more efficient solution of the single-objective updating optimization problem, while maintaining accuracy and quality in the updated model.

Improving performance evaluation based on the balanced scorecard with data envelopment analysis and game theory approaches: a case study

PurposeThis paper aims to propose an integrated use of balanced scorecard (BSC), data envelopment analysis (DEA) and game theory approach as an enhanced performance measurement technique to determine and rank the importance of manufacturing indicators of a steel company as a real case study.Design/methodology/approachAn efficiency change ratio is defined to examine the characteristic function of each coalition which is super-additive. Then, the Shapley value index is used as the solution of the cooperative game to determine the importance of the BSC indicators of the company and rank order them.FindingsThe results reveal that “profitability rate” is the most important BSC indicator, whereas “customer satisfaction” is the least significant one. The ranking order of the importance of all BSC indicators makes it possible for the senior managers of the organization to realize the importance of each index separately and to improve the profitability and the number of customers by presenting programs according to the budget and time constraints.Originality/valueThe main contribution of this paper lies in the adoption of a game theory approach to performance measurement in the industrial sector that determines and ranks the importance of manufacturing indicators.

Power control in LTE based on heuristic game theory for interference management

In the conventional LTE homogeneous network, sufficient transmit power of user equipment (UE) is determined by open-loop power control (OL-PC) and closed-loop power control (CL-PC) schemes. However, in a Het-Net environment, setting the UE’s transmit power requires delicate responsiveness to handle the severe and complicated uplink interference. In this paper, an interference-aware uplink power control mechanism based on Heuristic game theory approach is proposed for devices coexisting in a heterogeneous wireless network. Various wireless constraints like channel response, path loss, fading, shadowing, interference and metrics like SNR, SINR, throughput and bit rates are considered. Uplink power is controlled by suitably selecting the penalization factor (β) based on a simple Heuristic game theory approach considering the possible wireless constraints of each user depending on its location in the cell under consideration. The algorithm is framed in such a way to reduce inter-cell interference, limit transmit power, enhance bit rates and throughput of users. A significant improvement of 5.2% in the user coverage/distribution is achieved as a result of interference management compared to conventional power control scheme and power control with convex pricing.

Stakeholder interactions of government intervention in construction and demolition waste recycling market: A game theory approach

To acquire an in-depth understanding on how government intervention affects C&DW recycling market, this study develops four game models consisting of three main categories of stakeholders, e.g., the government, contractors, and C&DW receivers (recycling enterprises and landfills) to reveal stakeholder interactions of government intervention. Taking China's C&DW recycling market as an example, four different scenarios are established to examine and compare the effects of government intervention policies on C&DW recycling, illegal dumping, and stakeholder profits. Finally, numerical simulations are performed to gain further insights into the impact of government intervention on stakeholders' behaviors with a case study from Shenzhen, China. Results indicate: (1) government intervention policies can always lead to an increased amount of C&DW recycled and a reduced amount of C&DW illegally dumped compared to no any measure; (2) government subsidy can improve the market competitiveness of recycling enterprises and weaken the competitiveness of landfills. Both subsidy-only and subsidy-plus-penalty policies help reduce economic burden on contractors compared to no interventions, but penalty policy increases contractors' expenditures. Finally, penalty policy can significantly reduce the amount of illegally dumped C&DW, while subsidy policy can significantly increase the amount of recycled C&DW. This study provides valuable theoretical support and practical guidance for decision-making of governments in developing economies to develop C&DW recycling by formulating targeted intervention policies.

Branding fashion through gameplay: the branded gaming and the cool dynamics in the fashion markets. A game-theory approach

PurposeThe aim of this study was to investigate the role of immersive gaming on brand coolness and brand equity, with particular emphasis on fashion gaming collaborations. We used game theory as a theoretical framework to analyse immersive branding strategies and gain a deeper understanding of fashion consumers’ decision-making process in gaming environments. Gender, as a significant factor affecting gamers, has been studied as a moderator that impacts the overall proposed framework.Design/methodology/approachA quantitative method was used to assess the significance of relationships within the proposed model empirically. The partial least squares structural equation modelling technique was implemented to assess the relationships of the framework with a sample size of 160 active Malaysian gamers.FindingsThe findings indicate that brand equity is positively associated with perceived brand coolness. Furthermore, of the three core values of online games, perceived enjoyment is most strongly associated with perceived brand coolness, ahead of the values of self-expression and perceived emotional challenge. The results of the multigroup analysis further suggest that in the fashion industry, building brand equity through online games is strongly related to perceived brand coolness among female respondents, the role of perceived brand coolness being weaker among male respondents.Originality/valueThe study contributes to the existing literature by providing a deeper understanding of the impact of immersive gaming branding practices on the overall equity of the fashion brand. The results provide insight for fashion brand managers into the significant effect on consumer behaviour outcomes of fashion-gaming collaborations.

Relationship between the College Student and the Campus Club: An Evolutionary Game Theory Analysis.

In this paper, we use an evolutionary game theory approach to build a relationship model of students and clubs for the purpose of improving student enthusiasm for participating in club activities. First, the process of the model building is introduced, which mainly includes the basic assumptions and the equilibrium point stability analysis. Based on this analysis, we find that the motivation adjustment of students and clubs is a dynamic process and that unilateral efforts alone cannot achieve an ideal result. Then, we use real data from Yanshan University to evaluate the model, the results of which indicate that the model can analyze the relationship between students and clubs effectively. Finally, we provide relevant suggestions based on the model established in this study, whereby we contribute a theoretical basis and practical guidance for how students can actively participate in clubs, as well as how clubs can better develop themselves.

Security and Privacy Issues in Deep Reinforcement Learning: Threats and Countermeasures

Deep Reinforcement Learning (DRL) is an essential subfield of Artificial Intelligence (AI), where agents interact with environments to learn policies for solving complex tasks. In recent years, DRL has achieved remarkable breakthroughs in various tasks, including video games, robotic control, quantitative trading, and autonomous driving. Despite its accomplishments, security and privacy-related issues still prevent us from deploying trustworthy DRL applications. For example, by manipulating the environment, an attacker can influence an agent’s actions, misleading it to behave abnormally. Additionally, an attacker can infer private training data and environmental information by maliciously interacting with DRL models, causing a privacy breach. In this survey, we systematically investigate the recent progress of security and privacy issues in the context of DRL. First, we present a holistic review of security-related attacks within DRL systems from the perspectives of single-agent and multi-agent systems and review privacy-related attacks. Second, we review and classify defense methods used to address security-related challenges, including robust learning, anomaly detection, and game theory approaches. Third, we review and classify privacy-preserving technologies, including encryption, differential privacy, and policy confusion. We conclude the survey by discussing open issues and possible directions for future research in this field.

Multi-agent collaborative management of coastal pollution from land-based sources from the perspective of emissions trading: An evolutionary game theory approach

Emissions trading has been playing a very important role in addressing pollution of estuarine and coastal waters. This paper aims to explain mechanism of the multi-agent collaborative management of coastal pollution from land-based sources from the perspective of emissions trading and identify its influencing factors. Given the current participation of polluting enterprises in emissions trading, this paper constructs a tripartite evolutionary game model consisting of local governments, polluting enterprises, and the public. Drawing on this model and the ABM (agent-based modeling) for simulation and using artificial neural networks for error corrections, the numerical simulation of the data of Dongying, a pilot city of emissions trading is conducted, to examine the influence of different factors on the evolutionarily stable strategy. The results show that: ➀ increasing each agent’s initial willingness of participating in collaborative management can facilitate the evolution of their behavioral strategies towards collaborative management. Specifically, compared with the public, polluter’s stronger willingness for emission reduction and the government’s more proactive willingness for regulation can better promote collaborative management in land-based pollution; ➁ the increase in the reward standard for emissions cutters has a positive impact on enterprises and the public’s proactive participation in collaborative management, yet a negative impact on local governments; ➂ higher reward from the provincial government and the increase in the emissions trading price have a positive impact on the enthusiasm of local governments, enterprises and the public in collaborative management; ➃ the increase in the unit cost of emission reduction will undermine polluting enterprises’ enthusiasm in emission reduction. Policy suggestions are thus proposed, such as increasing the subsidies for emission reduction, promoting and perfecting the emission trading market, cutting the emission reduction cost of enterprises and the supervision cost of local governments, and increasing the public’s concern on the governance of marine pollution from land-based sources. The conclusion will provide a theoretical underpinning for and guide related practice of future preservation of coastal ecologies and management of coastal pollution from land-based sources.

Game theoretic centrality of a directed graph vertices

The paper considers a game theory approach to calculating the centrality value of the vertices in a directed graph, based on the number of vertex occurrences in fixed length paths. It is proposed to define vertex centrality as a solution of a cooperative game, where the characteristic function is given as the number of simple paths of fixed length in subgraphs corresponding to coalitions. The concept of integral centrality is introduced as the value of a definite integral of the payoff function. It is shown that this centrality measure satisfies the Boldi-Vigna axioms.

Game-Theoretic Centrality of Directed Graph Vertices

The paper considers a game theory approach to calculating the centrality value of the vertices in a directed graph, based on the number of vertex occurrences in fixed length paths. It is proposed to define vertex centrality as a solution of a cooperative game, where the characteristic function is given as the number of simple paths of fixed length in subgraphs corresponding to coalitions. The concept of integral centrality is introduced as the value of a definite integral of the payoff function. It is shown that this centrality measure satisfies the Boldi-Vigna axioms.

Water Resources Conservation in Bali: A Non-cooperative Game Theory Approach

Entering the 21st century, the world faces a global water crisis threat, due to increasing competition for freshwater which is an implication of economic growth, population growth, and climate change. Therefore, institutions that can secure the availability of water resources sustainably are urgently needed. In contrast to the tendency of research in the last two decades, which was dominated by experimental methods, this research studies local institutions in Bali called Subak using game theory as a reasoning method. Water management was analyzed using three economic frameworks namely, institutions, transaction costs, and contracts, to reveal how water institutions in Bali are managed. This study found that there are strong social norms that can maintain trust, act as a coordinating medium, eliminate transaction costs, and enforce contracts. Furthermore, the study also discusses the failure possibility of the current government intervention system because the capitalist production function alienates the value of water from its production system. Empirical research through experiments is very important, however, economics has a set of theories that can be used to predict or develop incentive mechanisms within an institution. The social norms that were found in this study can be used as a basis for the design of clean water management institutions at the village or community level with public participation.

Patent pricing under incomplete information

ABSTRACT Patent pricing is fundamental for patent industrialisation. This article aims to capture the patent price under incomplete information with game theory approaches. The results show first, patent industrialisation with a high technology level promotes outputs and reduces the prices of final goods. Second, competition decreases the price of patents, while asymmetric information deters patent industrialisation. Finally, a new type of risk function is established to merit the risk of cheap information, and we show that exaggerated technology amplifies the risks of both cost and profit. The policy implication is to strengthen information disclosure and supervision about patents. Finally, numerical examples are illustrated with the sensitivity analysis of the key parameters to justify the proposed model.

Evolutionary game analysis of online game studios and online game companies participating in the virtual economy of online games.

In the context of the new economic development in the post-pandemic era, "play" labor as an important component of digital work has become an inexhaustible driving force for the growth of the digital economy. Previous research has shown that "play" labor, as an emerging business model, can effectively promote the growth of the digital economy. However, there is a relative lack of research on the dynamic evolutionary game between "play" labor suppliers represented by game studios and online gaming companies. In this study, we applied the theoretical approach of dynamic evolutionary game theory to establish a game model depicting the evolution of both parties involved in the virtual economy of online gaming. The aim was to investigate the strategic selection mechanisms and influencing factors for game studios and online gaming companies participating in the virtual economy of online gaming. By analyzing the evolutionary game path, equilibrium points, and factors influencing the evolutionary game outcome, as well as conducting numerical simulation analysis using Matlab software, we found that the incremental gains and costs resulting from the strategic choices of online gaming companies and game studios in engaging in the virtual economy of online gaming affect the evolutionary outcomes. In addition, for the probability ratio of online game studios and online game companies choosing to participate in the virtual economy of online games, whether it is online game studios or online game companies, the larger the initialization ratio, the more likely the evolution result is to develop in a mutually beneficial direction. After an in-depth analysis and discussion of the evolutionary game results, relevant policy recommendations were proposed. We hope to provide a reference for promoting online game companies to strengthen the adequate supervision of online game studios' participation in the virtual economy of online games and optimize and improve the virtual economic environment.

Additional Income Distribution between Small Hydropower Plant and Public Trader Using Shapley Value

The small rivers energy usage and regime optimization is considered in the paper. Possibility of additional income reception in case of cooperative behavior of the power plant owners is demonstrated. Cooperative game theory approach is used for the additional income distribution and the small-scale hydro power plants (SHPP) regime planning and management. The obtained results demonstrate the possibility of the current supporting schemes revision, in case if SHPP regime optimization is made taking into account the market conditions.