Game Theory Model Research Articles

Buying from a Competitor: A Model of Knowledge Spillover and Innovation

This paper builds a game theory model that shows how buying from a competitor affects incentives to invest in innovation.

Generalization Increases the Adaptive Value of Mate Choice Copying When Immediate Copying Is Costly

When assessing potential mates is costly, there will be selection for copying others. Mate choice copying, which is the increased chance of mating with another individual after observing them mating with someone else (i.e., individual-based copying), has been documented in several species, including humans. It is touted as an example of the influence of culture on animal and human mating, but alone it is unlikely to lead the cultural evolution of mating. Rather, it requires mate choice copying with generalization (i.e., trait-based copying), which is the effect of immediate observations on future mating. This sort of mate choice copying has been documented in six species, including humans. Here, I extend an existing game theory model of mate choice copying to include generalization (Extension 1), a cost to immediate copying (Extension 2), and both previous extensions (Extension 3). The results show that Extensions 1 and 2 decrease the adaptive value of mate choice copying when compared to the original model. Extension 3 suggests that adding generalization to mate choice copying with a cost to immediate copying is a more likely evolutionary trajectory than adding it to mate choice copying without this cost. These results have implications for illuminating the emergence of the cultural evolution of mating preferences.

Inventory pledge financing decisions based on a permissioned blockchain by controlling fraudulent risk

Inventory pledge financing (IPF) is a crucial financing way for small and medium-sized enterprise (SMEs). But banks are reluctant to finance SMEs due to fraudulent risk in practice. This paper discusses the application of blockchain in IPF, particularly its impact on mitigating fraud risks. Utilizing game theory models, we illustrate how the finance and operation decisions of participants, along with supply chain efficiency, are influenced by the introduction of blockchain. Meanwhile, equilibrium outcomes are analysed and numerical study is given. Our analysis reveals that under certain conditions, blockchain integration can lead to reduced loan interest rates, lower wholesale prices, increased order quantities by buyers, and enhanced supply chain efficiency. Lastly, we develop a protocol to demonstrate the transfer of digital warehouse receipt on a permissioned blockchain to avoid fraudulent risk. This study provides a theoretical foundation, and a guidance for decisions-making in blockchain-enabled IPF schme.

Sustainable digital fashion in a metaverse ecosystem

The fashion industry ranks among the top polluters globally, yet the emergence of virtual worlds offers a chance for brands to switch to digital clothing as a greener option. This research explores whether the metaverse can enhance sustainability in fashion or worsen environmental issues, especially those linked to non-fungible tokens (NFTs). We introduce a game theory model to analyze the strategic dynamics between brand manufacturers and digital fashion platforms, factoring in platforms' abilities to reduce emissions. The model uncovers how these uncertainties influence pricing, investment, and performance outcomes. Our analysis is supported by a case study on DressX, a prominent digital fashion platform, showing that digital fashion brings technological innovation and environmental advantages. Platforms with greater emission reduction capacities and their collaborators witness increased revenues. However, information asymmetry complicates strategic decision-making, and the environmental implications of digital technologies underpinning the metaverse remain a critical concern. Platforms with advanced capabilities gain a competitive edge by managing costs effectively, whereas manufacturers profit at the platforms' expense. However, there is a strategic equilibrium that benefits both sides. Our study indicates that maximizing the environmental benefits of digital fashion demands responsible actions from all stakeholders, including careful technology selection, clear communication of capabilities, cost management, and strategic cooperation. Our game theory approach, combined with a real-world case study, provides a unique perspective on the strategic and environmental dynamics of digital fashion in the metaverse, contributing to the growing body of literature on sustainable fashion and digital ecosystems.

Evolutionary game theoretical approach for reducing carbon emissions in a complex supply chain organization

PurposeOur research explores the intricate behavior of low-carbon supply chain organizations in an ever-evolving landscape, emphasizing the profound implications of government-mandated low-carbon policies and the growing low-carbon market. Central to our exploration is applying a combined game theory model, merging Evolutionary Game Theory (EGT) with the Shapley Value Cooperative Game Theory Approach (SVCGTA).Design/methodology/approachWe establish a two-tier supply chain featuring retailers and manufacturers within this novel framework. We leverage an integrated approach, combining strategic Evolutionary Game Theory and Cooperative Game Theory, to conduct an in-depth analysis of four distinct low-carbon strategy combinations for retailers and manufacturers.FindingsThe implications of our findings transcend theoretical boundaries and resonate with a trinity of economic, environmental and societal interests. Our research goes beyond theoretical constructs to consider real-world impacts, including the influence of changes in government low-carbon policies, the dynamics of consumer sensitivities and the strategic calibration of retailer carbon financing incentives and subsidies on the identified ESS. Notably, our work highlights that governments can effectively incentivize organizations to reduce carbon emissions by adopting a more flexible approach, such as regulating carbon prices, rather than imposing rigid carbon caps.Originality/valueOur comprehensive analysis reveals the emergence of an Evolutionary Stability Strategy (ESS) that evolves in sync with the phases of low-carbon technology development. During the initial stages, our research suggests that manufacturers or retailers adopt low-carbon behavior as the optimal approach.

Selling mode choice and return policy for advance selling in an e-commerce platform with social influence

Advance selling is increasingly employed to mitigate demand uncertainty, raise consumer awareness of products, and even exert social influence on subsequent sales. However, consumers may hesitate to pre-order products due to uncertainty about product valuation. As a response, sellers have begun implementing return policies and utilizing online retail platforms to alleviate the uncertainty. This study aims to investigate the interaction between return policies for advance selling and selling formats of e-commerce platforms considering the impact of social influence. We examine a two-period platform supply chain that includes agency selling, reselling, and hybrid selling formats with and without return policies. Using game theory models, we analyze pricing decisions and profits of each player under six possible scenarios. The results indicate that the manufacturer consistently prefers adopting a Money-Back Guarantee (MBG) return policy regardless of the selling format. However, the MBG return policy is not always advantageous for the platform, except in the case of low social influence. In such a case, the platform may implement the MBG return policy to boost advance sales, thereby enhancing the penetration power from advance sales to regular sales. Regarding selling formats, the platform and the manufacturer opt for the reselling and agency selling, respectively, when the commission rate is low; otherwise, they adopt the agency selling and hybrid selling, respectively. Furthermore, we explore the impact of critical drivers on the pricing decisions and profits within the platform supply chain. Our study offers valuable insights into implementing return policies and determining selling formats.

Can subsidy policies achieve fuel cell logistics vehicle (FCLV) promotion targets? Evidence from the beijing-tianjin-hebei fuel cell vehicle demonstration city cluster in China

Fuel cell logistics vehicle (FCLV) plays a pillar role in achieving carbon neutrality in the freight sector. Due to high costs and imperfect infrastructure, millions of subsidies are granted to develop FCLV and fulfill promotion targets set by the government. To examine the effectiveness of this action, the study proposes a tripartite evolutionary game theory (EGT) model to simulate the interactions between local governments, private investors, and consumers, and explores the fulfillment of promotion targets in the Beijing-Tianjin-Hebei fuel cell vehicle demonstration city cluster. The obtained results show that: (i) the FCLV promotion targets of demonstration cities except Tangshan could be substantially achieved under the current subsidy; (ii) purchase subsidies for consumers can help achieve promotion targets at a faster pace, while construction subsidies for investors have a limited incentive effect, so more non-financial incentives need to be provided to investors, such as innovative operating models and priority approval of land for hydrogen refueling station construction; (iii) a comparison of subsidies in different cities reveals that Beijing's subsidies are the most efficient and that there is an optimal allocation between consumers and private investors that allows for the faster accomplishment of promotion targets without increasing the fiscal burden.

Value-Positivity for Matrix Games

Matrix games are the most basic model in game theory, and yet robustness with respect to small perturbations of the matrix entries is not fully understood. In this paper, we introduce value positivity and uniform value positivity, two properties that refine the notion of optimality in the context of polynomially perturbed matrix games. The first concept captures how the value depends on the perturbation parameter, and the second consists of the existence of a fixed strategy that guarantees the value of the unperturbed matrix game for every sufficiently small positive parameter. We provide polynomial-time algorithms to check whether a polynomially perturbed matrix game satisfies these properties. We further provide the functional form for a parameterized optimal strategy and the value function. Finally, we translate our results to linear programming and stochastic games, where value positivity is related to the existence of robust solutions. Funding: This research was supported by Fondation CFM pour la Recherche, the H2020 European Research Council [Grant ERC-CoG-863818 (ForM-SMArt)], the Austrian Science Fund [Grant 10.55776/COE12], ANID Chile [Grant ACT210005], and Agence Nationale de la Recherche [Grant ANR-21-CE40-0020].

The analysis of evolutionary strategies to facilitate the transformation of traditional buildings into prefabricated buildings

This paper establishes a two-party evolutionary game theory model comprising of the governments and prefabricated components suppliers as the players; and uses the replicator dynamic equations to analyze the evolution mechanisms each player’s strategy choices. Results from numerical simulations indicate that the evolution trajectory of the model is significantly influenced by not only the initial strategies of the players, but also by government incentives and regulatory penalties, as well as the costs and benefits resulted from each strategy choice. Also, prefabricated components suppliers exhibit greater responsiveness to variations in cost-related factors. When the subsidy and penalty respectively remain constant at 15% and 5% of the additional cost, the model exhibits both rapid and stable evolutionary trend towards the optimal evolutionarily stable strategy of full cooperation between the two players. This article proposes a suitable threshold for government incentives and penalties, besides serving as a guide for the steady and sustainable growth of the prefabricated buildings sector.

Platform Information Sharing Decisions Considering Supplier Delivery Services and Encroachment Strategies

The platform often has private information about uncertain demand and determines whether to share the information with the supplier. And the supplier’s choice of delivery services and encroachment may depend on the platform’s information sharing policy. This paper examines the two-dimensional information sharing strategies in a supply chain where the supplier provides delivery services. Based on the game theory model, we find that when the platform shares unfavorable information, the motivation for the supplier’s encroachment decreases firstly. Encroachment does not reduce the level of delivery service from the supplier. Second, delivery services levels of supplier increase with channel substitution rate. Although platform sharing information lowers profits in a supply chain where the supplier provides delivery services, the platform can share information on behalf of delivery services improvement under certain conditions interestingly. Previous papers that ignore a supplier’s decision on delivery services may have underestimated the scope for platform profitable information sharing. Third, the equilibrium profits of supply chain entities present non-monotonous with respect to encroachment cost. The platform often faces a tradeoff. Sharing information, on the one hand, enables the supplier to gain a better understanding of the impact on demand and encourages enhancements to delivery services, which is advantageous to the platform. However, sharing information allows the supplier to absorb the impact of demand information by making modifications to the wholesale price and delivery services, which benefits the supplier but hurts the platform. This makes the negative effects of double marginalization worse.

Security, QoS and energy aware optimization of cloud-edge data centers using game theory and homomorphic encryption: Modeling and formal verification

Privacy and efficient data processing are crucial research areas in the field of outsourcing computing. Thus, the contribution of the paper is twofold. First of all, we develop a secure offloading technique that can process data while preserving privacy. Although RSA and Paillier cryptosystems are highly beneficial for mathematical operations on basic encrypted data due to their homomorphic properties, images are processed using permutation-ordered binary (POB) and Shamir's secret sharing (SSS). Second, a non-cooperative game theory model was formulated to examine the interactions between service providers, characterizing each edge as an M/M/1 system with an infinite queue. Through formal verification using rigorous mathematical reasoning, the suggested strategies for task offloading and resource allocation are shown to be effective in terms of security, quality of service (QoS), and energy consumption. The best-response dynamics approach is used to calculate the final strategy for each participant and assess how fairly resources are allocated. Finally, the potential of our approach is demonstrated numerically, revealing a faster convergence towards attaining Nash equilibrium in a duopoly cloud-edge data center market, granted that the necessary and sufficient conditions are met.

Optimal supply chain green innovation and subsidy strategy: producer subsidy versus consumer subsidy

PurposeConsidering two types of subsidies for producers (supplier and manufacturer) and one for consumers based on product greenness and sales quantity, this study aims to formulate optimal supply chain green innovation and subsidy strategies, and to achieve this goal with the support of information systems.Design/methodology/approachThis study introduces a composite green-product supply chain where suppliers focus on green innovation for component greenness and manufacturers focus on green innovation for manufacturing process greenness. Game theory modeling is applied to investigate the differences of product greenness, supply chain members’ profit and social welfare under different government subsidy strategies.FindingsIncreasing the unit greenness subsidy coefficient can boost product greenness and supply chain members’ profits, but does not always raise social welfare. When the government exclusively offers subsidies to producers, subsidies should be allocated to suppliers when there is a significant disparity in supply chain green innovation costs. Conversely, it is more beneficial to subsidize manufacturers. Consumer subsidies have the potential to enhance both environmental and economic performance in the supply chain compared with producer-exclusive subsidies, but may not always maximize social welfare when supply chain members have low unit costs associated with green innovation.Originality/valueThis study examines the optimal decisions for green supply chain innovation and government subsidy strategies. Supply chain members and the government can use the information system to collect and evaluate the cost of upstream and downstream green innovation, and then develop reasonable collaborative green innovation and subsidy strategies.

Evolution of a bistable genetic system in fluctuating and nonfluctuating environments

Epigenetic mechanisms can generate bacterial lineages capable of spontaneously switching between distinct phenotypes. Currently, mathematical models and simulations propose epigenetic switches as a mechanism of adaptation to deal with fluctuating environments. However, bacterial evolution experiments for testing these predictions are lacking. Here, we exploit an epigenetic switch in Salmonella enterica, the opvAB operon, to show clear evidence that OpvAB bistability persists in changing environments but not in stable conditions. Epigenetic control of transcription in the opvAB operon produces OpvABOFF (phage-sensitive) and OpvABON (phage-resistant) cells in a reversible manner and may be interpreted as an example of bet-hedging to preadapt Salmonella populations to the encounter with phages. Our experimental observations and computational simulations illustrate the adaptive value of epigenetic variation as an evolutionary strategy for mutation avoidance in fluctuating environments. In addition, our study provides experimental support to game theory models predicting that phenotypic heterogeneity is advantageous in changing and unpredictable environments.

Valuation of Project Managers to Enhance Project Performance in Nigeria’s Construction Industry

Construction project management is critical to the success of construction projects, with the performance of project managers (PMRs) playing a central role. Despite its importance, previous studies have highlighted the poor performance of construction organizations in Nigeria, such as project delays and cost overruns and the need for proper project management practices. However, the specific performance of PMRs in the Nigerian construction industry (NCI) has not been extensively studied. To address this issue, this study aims to identify the causes of underperformance among PMRs in the NCI by examining the tasks where PMRs underperform and the extent of this underperformance and its effect on motivational support from organizations. Data were collected through 206 questionnaires and 36 semi-structured interviews with organizations and project managers. Descriptive analysis was conducted to evaluate project management (PM) practices as well as the level of motivational support provided to PMRs. The analysis revealed that PMRs underperform in more than 60% of tasks but outperform in 20%. Underperformance refers to the tasks in which PMRs performed less than the expected contributions set by the organization, while outperformance describes tasks where PMRs exceeded the organization’s expectations. The analysis also revealed low motivational support of PMR. Correlation analysis was conducted to investigate whether motivational support influences PMR performance, and the results indicated a two-way causal relationship between underperformance and low motivational support. This study integrated a game theory model with regression analysis to show that (stay, support) is the dominant solution for project managers and organizations, provided the net contribution of support is positive. In this context, “stay” refers to PMRs continuing working with their current organization, while “support” refers to the motivational support provided by the organization to enhance the commitment and performance of the PMRs. However, current support levels may not be enough to cause PMRs to begin to outperform. In addition, regression analysis was conducted between the degree of underperformance and motivational factors, and we conducted a preliminary simulation by increasing these values of regression coefficients. The results indicated that while motivational support from organizations can improve PMRs performance, its effectiveness is limited. Factors such as corruption, political pressures, and organizational culture have a greater impact on performance. Addressing these factors may be more crucial for enhancing performance and project outcomes than focusing only on motivational support. Therefore, the Nigerian construction industry needs to implement institutional changes alongside motivational strategies to improve PMRs performance and project success.

Understanding the oscillations of an epidemic due to vaccine hesitancy.

Vaccine hesitancy threatens to reverse the progress in tackling vaccine-preventable diseases. We used an $ SIS $ model with a game theory model for vaccination and parameters from the COVID-19 pandemic to study how vaccine hesitancy impacts epidemic dynamics. The system showed three asymptotic behaviors: total rejection of vaccinations, complete acceptance, and oscillations. With increasing fear of infection, stable endemic states become periodic oscillations. Our results suggest that managing fear of infection relative to vaccination is vital to successful mass vaccinations.

Why Abusive Supervision Pervades College Sports: A Game Theory Model About Games

Why Abusive Supervision Pervades College Sports: A Game Theory Model About Games

The Prisoner’s Dilemma game as a tool to investigate cooperation and undergraduate education in evolution

Evolutionary theory is based on the conflict that arises when certain heritable variants out-compete others. Given this foundational conflict, a central question for evolutionary biologists concerns the presence of cooperation found throughout all levels of biological organization; from biochemical pathways to complex animal societies. Human behavior is often distinguished from other animal behavior by the presence of acts of cooperative behavior called altruism. Altruism is a cooperative act that penalizes the actor for actions that benefit the recipient. Any other form of cooperation, one that does not penalize the actor, is formally not considered altruistic. How can costly altruistic behavior evolve? This question was the basis for development of a web application tool incorporating a game theory model to investigate conditions affecting cooperative behavior. The game theory model described as Prisoner’s Dilemma incorporates acts of cooperation and non-cooperation (defection). Computer simulations of Prisoner’s Dilemma were developed and online applications were administered for five semesters at Georgia Gwinnett College, using two simulation environments referred to as Random and Non-random. Data collected from simulation runs were used to evaluate the effect of environment on student cooperative behavior and actively engage students in concepts associated with the evolution of cooperation and game theory. Results from student game play suggest group simulation environment played a significant role in the likelihood of observing cooperative behavior. Educational content and attitudinal surveys suggested that PD game play in the undergraduate evolution class at Georgia Gwinnett College improved student knowledge and self-confidence.

Solar–Hydrogen-Storage Integrated Electric Vehicle Charging Stations with Demand-Side Management and Social Welfare Maximization

The reliable operation of a power system requires a real-time balance between supply and demand. However, it is difficult to achieve this balance solely by relying on supply-side regulation. Therefore, it is necessary to cooperate with effective demand-side management, which is a key strategy within smart grid systems, encouraging end-users to actively engage and optimize their electricity usage. This paper proposes a novel bi-level optimization model for integrating solar, hydrogen, and battery storage systems with charging stations (SHS-EVCSs) to maximize social welfare. The first level employs a non-cooperative game theory model for each individual EVCS to minimize capital and operational costs. The second level uses a cooperative game framework with an internal management system to optimize energy transactions among multiple EVCSs while considering EV owners’ economic interests. A Markov decision process models uncertainties in EV charging times, and Monte Carlo simulations predict charging demand. Real-time electricity pricing based on the dual theory enables demand-side management strategies like peak shaving and valley filling. Case studies demonstrate the model’s effectiveness in reducing peak loads, balancing energy utilization, and enhancing overall system efficiency and sustainability through optimized renewable integration, energy storage, EV charging coordination, social welfare maximization, and cost minimization. The proposed approach offers a promising pathway toward sustainable energy infrastructure by harmonizing renewable sources, storage technologies, EV charging demands, and societal benefits.

Root foraging strategies and niche segregation of three mediterranean shrub species

Shrubs are usually adapted to stressful environments in which soil resources are limited, and thus, roots are fundamental for their biological success. However, root measures are challenging to collect, especially in field conditions and at the individual level. For this study, we collected data on the three‐dimensional distribution of fine root biomass of twenty‐three individuals belonging to three shrub species in a mediterranean shrubland in central Spain: gum rockrose Cistus ladanifer, rosemary Salvia rosmarinus, and hairy‐fruited broom Cytisus striatus. Our goal was to determine the soil‐foraging strategies adopted by the plants. We hypothesized that plants would show stabilizing niche differences explaining the high plant biodiversity characteristic of mediterranean shrublands and that they would follow the game theory model's prediction of exploitative segregation of roots behaving territorially but also over‐proliferating roots close to their stem and engaging in a root tragedy of the commons. We found that two‐thirds to three‐fourths of the biomass was belowground, and the system's productivity was roughly 500–600 g C m−2 year−1. Only rosemary plants competed with neighbors following the exploitative segregation predictions. Broom plants had the shallowest and most widespread root systems but significantly reduced their root range toward competing neighbors. Gum rockrose presented deep, narrow root systems avoiding extensive overlap with neighbors but did not appear to respond to competitive pressure levels. Shrubs appeared to stratify their roots at different soil depths, supporting the niche segregation hypothesis.

Towards a Sustainable Blockchain: A Peer-to-Peer Federated Learning based Approach

In the rapidly evolving digital world, blockchain technology is becoming the foundation for numerous applications, ranging from financial services to supply chain management. As the usage of blockchain is becoming more prevalent, the energy-intensive nature of this technology has raised concerns about its long-term sustainability and environmental footprint. To address this challenge, we explore the potential of Peer-to-Peer Federated Learning (P2P-FL), a distributed machine learning approach that allows multiple nodes to collaborate without sharing raw data. We present a novel integration of P2P-FL with blockchain technology, aimed at enhancing the sustainability and efficiency of blockchain networks. The basic idea of our approach is the use of distributed learning mechanisms to find the optimal performance parameters of blockchain without relying on centralized control. These parameters are then used by a load-balancing mechanism that prioritizes energy efficiency to distribute loads on different blockchains. Furthermore, we formulate a non-cooperative game theory model to align the individual node strategies with the collective objective of energy optimization, ensuring a balance between self-interest and overall network performance. Our work is exemplified through a case study in the renewable energy sector, demonstrating the application of our model in creating an efficient marketplace for energy trading. The experimentation and results indicate a significant improvement in the execution times and energy consumption of blockchain networks. Therefore, the overall sustainability of the network is enhanced, making our framework practical and applicable in real-world scenarios.