Game Theory Analysis Research Articles

Strategic dynamics of local governments in regional collaborative governance: An evolutionary game theory analysis of haze pollution response in the Fen-Wei Plain, China

Regional collaborative governance has become a key strategy for environmental protection, especially in reducing transboundary pollution transfer. This study, set against the backdrop of environmental governance in China's Fen-Wei Plain, employs evolutionary game theory to deeply analyze the strategic choices of local governments in managing haze pollution. We developed a model incorporating 14 key variables to systematically explore the emission reduction strategies of local governments under various policy environments. Through numerical simulations, we not only validate the effectiveness of the model but also focuses on how incentives and punishments from the central government influence the stability of local governments adopting a “strict enforcement” strategy. We find that appropriate incentives from the central government can significantly enhance the tendency of local governments to choose a “strict enforcement” strategy for emission reduction. Under certain conditions, whether adopting “strict enforcement” or “superficial enforcement,” both can lead to an Evolutionarily Stable Strategy (ESS). Moreover, the intensity of rewards and penalties from the central government and the benefits of collaborative governance by local governments are key factors determining the stability of strategies. Our findings underscore the importance of establishing performance-oriented incentive mechanisms, refining reward and punishment measures, and focusing on sustainable and adaptable governance strategies. The strategic recommendations provided by this study offer important guidance for balancing incentives and punishments, thereby stimulating local government enthusiasm for governance, which supports high-quality environmental protection and sustainable development goals.

Small-business owners and their choice of banks: Some lessons from the banking literature and game theory in the aftermath of the COVID-19 pandemic

ABSTRACT Finance textbooks treat banks as homogenous institutions. Intuition suggests that small businesses should interact with large banks, given the latter’s ability to diversify risk. Large banks are involved in transactional banking as part of their business relationships, and small and community banks use soft information and value long-term relationships with borrowers. During the recent COVID-19 pandemic and the subsequent Paycheck Protection Program lending, large banks supported bigger businesses while small and community banks supported small businesses. To investigate this phenomenon, we focus on the U.S. experience and conduct a game theory analysis. Based on the results, we recommend that small businesses develop long-term relationships with small and community banks, which are more likely to use soft information and support the small businesses during a crisis.

Game Theory Analysis of Competitive Dynamics in the Streaming Industry: A Comparative Study of Netflix and Disney+

Game Theory Analysis of Competitive Dynamics in the Streaming Industry: A Comparative Study of Netflix and Disney+

A game theory analysis of regional innovation ecosystems

A game theory analysis of regional innovation ecosystems

Study on Chinas Homemaking Service Credit Optimization in Perspective of Game Theory

In recent years, the homemaking service industry in China has developed rapidly, with a market size of trillions RMB. However, conflicts and poor trust between homemaking service provider (companies and practitioners) and consumers remain prominent. Credit issues have become the main bottleneck for the high-quality development of the homemaking service industry. These credit issues are mainly caused by factors such as intermediary enterprise model, low capability and bad service quality for practitioners, information asymmetry, lack of industry credit system, etc. This article uses game theory to analyze the integrity mechanism in the homemaking service industry and proposes a targeted optimization method for the credit system of homemaking service. The case study shows that the enterprises credit has decreased, and its production and operation have fallen into difficulties due to the dishonest operation during the game between the enterprise and consumer. Through game theory analysis, it can be found that information disclosure mechanisms and reward and punishment mechanisms play an important role in optimizing the credit of homemaking services. Cooperative games help build stable trust relationships and improve service quality.

How does the power structure affect the acquisition price and inventory decisions in the reverse supply chain

With growing concerns about environmental sustainability, reverse supply chains play a crucial role in recycling, remanufacturing, and reducing waste. Investigating the power structure’s impact on decisions related to acquisition prices and inventory management can provide insights into the integration of sustainable practices. This study analyzes a reverse supply chain with a supplier and a remanufacturer, in which the supplier provides the remanufacturer with sorted used cores. We investigate the acquisition pricing and inventory decisions under different power structures (supplierled Stackelberg model, remanufacturer-led Stackelberg model) through game theory analysis. We first establish the centralized model to explore optimal acquisition decisions and profit of the total system. Then we evaluate the acquisition quantity, wholesale prices, the profit of supplier and remanufacturer in the supplier-led model and in the remanufacturer-led model. Finally, the impact of power structure on the performance of supplier and remanufacturer are explored by numerical analysis, as well as the supply chain system. Our significant findings show that (i) the total profit of the supplier-led and remanufacturer-led reverse supply chain are less than the centralized model due to the double marginalization; (ii) the remanufacturer-led reverse supply chain is superior to the supplier-led model reverse supply chain; (iii) the selected grades in the supplier-led model is proved the same as that in the remanufacturer-led model, which could not been affected by the wholesale price; (iv) the greater the inventory risk (the uncertainty in demand), the greater the profit share for the remanufacturer (supplier) in the supplier-led (remanufacturer-led) model.

Implications of risk-averse manufacturer on coordination of green supply chain with mixed carbon policies

PurposeThis paper intends to address the decision-making and coordination of green supply chain (GSC) considering risk-averse manufacturers under mixed carbon policy.Design/methodology/approachThis paper focuses on a GSC consisting of a manufacturer and a retailer, in which the manufacturer is risk-averse (R-A). This paper employs Stackelberg game theory and mean variance analysis to assess the pricing decision-making process under various scenarios. Furthermore, cost-sharing contracts are introduced to coordinate the GSC.FindingsThe research results suggest that the green level of the product and the profit of the GSC under a centralized scenario are higher than those under a decentralized scenario, while the retail price is lower. Under the decentralized scenario, the green level of product, wholesale price and manufacturer’s profit in the R-A scenario are lower than the values in the risk-neutrality scenario, while retailer's profit is higher. In addition, when a cost-sharing contract is utilized for coordination in the GSC, it can lead to Pareto improvement, regardless of whether the manufacturer makes risk-neutrality or R-A decisions.Originality/valueThis research provides a deeper understanding of GSC decision-making and coordination strategy under mixed carbon policy with consideration of R-A from a theoretical perspective and provides decision support for enterprises to choose strategies in practice.

Economic and environmental evaluation of different collection models for spent power batteries

The efficient collection of spent batteries is important for the recycling of power batteries and the sustainable advancement of electric vehicles (EVs). This study introduces and evaluates 14 power battery collection models, encompassing single-channel, dual-channel, and triple-channel scenarios, which encapsulate the dynamics of competition, cooperation, and co-opetition among key stakeholders. Employing Stackelberg game theory and simulation analysis, this study assesses the economic and environmental benefits of these models, with particular attention to the impact of consumer environmental awareness and competition intensity. Findings indicate that the collaborative collection model involving battery manufacturers, EV companies, and third-party recyclers (Model MVTP) delivers superior economic outcomes, with benefits ranging from 20.3 to 20.31 billion RMB. Meanwhile, the competitive three-party collection model (Model M-V-TP) stands out for its environmental benefits, achieving collection rates between 14.95 % and 25.65 %. Intriguingly, while competition intensity does not influence the outcomes of single-channel models, it diminishes both economic and environmental benefits in dual- and triple-channel scenarios. Moreover, enhanced consumer environmental awareness consistently elevates the economic benefits of all models, though its effect on environmental benefits varies—enhancing collection rates in single- and dual-channel models but detrimentally impacting the triple-channel model.

Enhancing Transshipment Decision-making in Transportation Companies through Computational Intelligence: A Bayesian Game Model with Data-Driven Simulations at Guangzhou Port

The challenge of port congestion significantly impedes the efficiency of global trade flows and the economic vitality of hinterland regions. Addressing this issue, our study harnesses computational intelligence to construct a sophisticated Bayesian game model between the government and multiple transportation companies, where the transshipment costs, considered as private information to the companies, play a pivotal role. This research integrates data analytics and machine learning techniques to analyze the strategic decision-making processes of transportation companies, which decide on transshipment based on a critical cost threshold influenced by government subsidies and a probabilistic assessment of transshipment costs. Utilizing backward induction, the study outlines how the government can leverage computational models to devise an optimal subsidy strategy for transshipment, taking into account the anticipated responses of the transportation companies. The Bayesian Nash equilibrium identified through our model suggests that companies with costs below a predefined threshold are incentivized by government subsidies to opt for transshipment. This conclusion is further validated through evolutionary game theory analysis, enriched by data-driven simulations. Employing real-world data from Guangzhou Port, we conducted extensive computational simulations to quantify the impact of transshipment subsidies. The findings reveal a substantial alleviation in port congestion, with a 33.7% reduction in congestion levels and a 35% decrease in congestion-related costs, alongside a notable 1.9% increase in government revenue. These simulations, powered by advanced computational algorithms and data analytics, not only underscore the effectiveness of informed subsidy strategies in mitigating port congestion but also demonstrate the potential of integrating computational approaches in logistical and transportation decision-making. This study contributes a novel computational framework to the logistics and transportation literature, offering practical insights for policymakers to tackle the enduring problem of port congestion through data-driven strategies.

Game Theory Analysis of Indihome and Biznet in the Salatiga Internet Market

Game Theory Analysis of Indihome and Biznet in the Salatiga Internet Market

The role of social capital in community development: Insights from behavioral game theory and social network analysis

AbstractThis study examined the multifaceted nature of Social Capital (SC) in community development projects by using Water, Sanitation, and Hygiene (WASH) interventions in three urban Bangladeshi slums as a case study. Despite its recognized importance, the ambiguity surrounding SC has led to mixed outcomes, necessitating a more theorized approach to quantitatively assess SC. To address this, a comprehensive methodology was developed, specifically crafted for a community development context and incorporating standard SC questions, social network analysis indices, and an adherence to social norms through behavioral game theory. The analysis revealed varied SC profiles, with one slum achieving successful community toilet management through strong reciprocal ties. The other slums faced challenges due to community division and weakened SC among key individuals. These findings underscore the necessity of tailoring interventions to community‐specific SC characteristics. The streamlined approach derived from the study provides guidance for both enhancing the effectiveness of community interventions and advancing sustainable development.

A Comprehensive Analysis of Game theory on Multi-Agent Reinforcement

In recent years, reinforcement learning has gradually emerged as a popular research field in artificial intelligence. However, for multi-agent systems, due to their complex environment and an abundance of agents, the learning target of maximizing the anticipated value of cumulative rewards for specific agents frequently fails to converge. Introducing game theory into reinforcement learning can effectively address the interactions among intelligent agents, provide a rationale for convergence points corresponding to strategies. To address the issue of non-existence of optimal solutions for certain tasks in multi-agent settings, this paper takes a game-theoretic perspective and summarizes classical reinforcement learning algorithms developed in recent years. The basic theory of multi-agent reinforcement learning, essential game theory, categorization of reinforcement learning using multiple agents game strategies, primary worries are addressed in the study. It also analyzes the challenges that game-theoretic multi-agent reinforcement learning algorithms may encounter in the future, along with the relevant optimization directions.

Win-Loss-Win in the US–China Game: A Cross-cultural Analysis of a TV Anchor Debate Between Trish Regan and Liu Xin

Abstract Guided by the cultural game theory, WGTICC and cultural analysis model, this study has found such game intentions and communication strategies as shaming the invited counterpart versus correcting the host calmly, turning a debate into a Q&A versus using the Q&A as a meaningful presentation, and getting ready to listen versus demonstrating courage, sincerity, and cogency have been adopted during the 3 rounds of debate, thus illustrating and expanding the third assumption in the water and game theory from a win-loss to a win-loss-win result. In terms of cultural roots, Fox Business News, as an example of Western media, has been shifting from objective, accurate, and fair journalism ethics to unilateralism, catalyzed by prioritizing the US interests. In contrast, the Chinese media, like CGTN, have been reshaping themselves for survival and performance employing and developing multiple online platforms while converging with social media.

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.

Exploring effective incentive policies for sustainable development of green buildings in China: based on evolutionary game theory and numerical simulation analysis

PurposeThis study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.Design/methodology/approachFirst, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.Findings(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.Practical implicationsThe expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.Originality/valueThe model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

Virtual influencers and corporate reputation: from marketing game to empirical analysis

PurposeThis study delves into how corporations make decisions about influencer marketing. Specifically, it examines the differences between human influencers, who carry the risk of scandals, and virtual influencers, a new and unpredictable realm, regarding their integration with social media platforms.Design/methodology/approachUsing game theory and empirical data, the study explores crucial factors in influencer marketing, including influencer quality, reputation repair costs and the probability of R&D failures.FindingsThis study suggests that companies favor human influencers when the risk of scandal is low. However, competing companies switch to virtual influencers at different intervals as this risk increases. The costs, likelihood of scandals and competition intensity all play a role in a company's decision-making regarding technology management. Additionally, a higher chance of R&D failure can motivate a company to invest more in R&D to gain a competitive advantage over rivals that may suffer failures.Research implications/implicationsThis study provides insights into how corporations manage social media influencer marketing in the digital age. It contributes to marketing theory and technology management decisions by offering a fresh perspective on the relationship between corporate reputation and influencer marketing strategy.Originality/valueThis study offers valuable perspectives into a relatively uncharted area of marketing strategy. It employs game theory and empirical analysis to introduce a fresh method of comprehending the dynamics of influencer marketing, its impact on corporate reputation management and its interaction with social media.

Game Theory Analysis of Algebraic Content Selection in Middle School Mathematics Curricula

The algebra section of middle school math textbooks is indispensable. The characteristics of the textbook and the rationality of its elements need to be algebra content of middle school math textbooks mainly consists of algebraic formulas, equations and inequalities, functions and other elements. This paper focuses on modeling the analysis based on game theory and then exploring the rationality of the algebra textbook study is conducted by reviewing the literature and constructing an analytical model based on cooperative game and Nash equilibrium theory. It is obtained that in the strategy where all three elements are used at the same time, the one that focuses on the orchestration function can maximize the reorganization of unit algebra content design is needed to achieve rational weighting of individual algebra selection of elements needs to fully reflect the articulation between the individual algebra elements. Algebraic elements are designed to spiral in difficulty to match the needs of teachers and students using them.

Using Game Theory to Analyze the Effects of Different News Communication Strategies on Public Opinion Formation

Abstract In this paper, the public opinion game model is introduced through the analysis of game theory and news dissemination theory. According to the basic assumptions to form the payment matrix, the mathematical derivation of the benefit expectation function, to get the replication of the main body of the dynamic equations, and its equilibrium point of the stability of the test, so as to complete the construction of the public opinion game model under different news dissemination strategies. The model of this paper is validated and analyzed when the news dissemination to the public economic loss Lg is higher, leading to the rise of the probability of strict government regulation, prompting the public judgment and self-opinion ability to improve. If the government does not intervene in the news media, the gray gains of the news media Re 2 gradually increase, resulting in the lack of relevant, correct knowledge of the public. In this paper, we study the impact of different news communication strategies on the formation of public opinion and promote the formation of public opinion.

Game theory implementation in business strategy analysis for railway ticket reservation services

This study aims to analyze competition between two railway ticket reservation services from users’ perspective. The existence of many services makes them compete to acquire users, with KAI Access and Traveloka being the most popular. To determine appropriate business strategies for fair competition, a game theory analysis was carried out. For preparing the model, their business strategies were identified. A survey was conducted to collect 156 users' preferences. The survey results then used to calculate each strategies’ value by using game theory model. The game value obtained was 15.33, which produced two appropriate strategies for KAI Access and Traveloka.

Dilemma and Countermeasures of Antitrust Regulation in the Field of Internet Platform Economy

Abstract This study addresses the issue of monopolies in the Internet platform economy by analyzing their causes and evaluating effective antitrust measures to maintain market fairness and encourage economic prosperity. Focusing on monopoly dynamics, including the network effect, capital influence, and market dominance, we apply evolutionary game theory and empirical analyses to devise a game theoretical model. This model helps simulate monopoly evolution and the potency of antitrust strategies. Our findings illustrate a direct correlation between monopoly growth and factors such as user base size, capital consolidation, and market control, with platforms frequently adopting monopolistic tactics for revenue maximization. Following antitrust regulatory actions, industry concentration shows a notable decrease, with metrics of total assets and net sales concentration dropping by 0.059 and 0.069, respectively. The study outlines critical regulatory strategies for enhancing market regulation, competition facilitation, and encouraging innovation. Effective antitrust enforcement is vital for optimizing market structures, spurring industry innovation, ensuring consumer welfare, and supporting the healthy progression of the Internet platform economy.