Game-theoretic Model Research Articles

Marketing and Sustainable Economic Development of the Energy Complex: A Case Study of the Administrative And Legal Planning of a Public-Private Partnership

The main purpose of the article is to present a modern methodological approach to choosing the most optimal model of administrative and legal planning of public-private partnership in the context of sustainable development of the energy complex, taking into account various aspects, including issues of security and rational resource use. The object of the study is a system of administrative and legal planning public-private partnership models in the context of sustainable development and security of the energy complex. The research methodology involves the use of the method of strategizing of administrative and legal planning for the sustainable development of public-private partnerships, the method of the vector of efficiency of public-private partnerships, as well as the method of game-theoretic modeling. As a result, a methodological approach was formed to strategies of administrative and legal planning for the sustainable development of public-private partnerships in the energy sector. The optimal interaction model between the state and the private sector in this context was selected.

Information Collection and Personalized Service Strategy of Monopoly under Consumer Misrepresentation

To decrease privacy risks, consumers may choose to misrepresent themselves when they are asked to offer personal information. Using a game theoretic model, this study examines the impact of consumer misrepresentation on both a monopolistic firm and consumers. The results show that consumer misrepresentation may benefit the firm, but hurt consumers under certain conditions. In addition, we find that when the unit cost of personalized service is low, consumer misrepresentation may encourage the firm to provide a higher personalized service level. Moreover, when consumers misrepresent themselves and the firm only covers part of the market, a greater unit value of consumer private information will reduce the firm’s profit, while a greater unit cost of personalized service will increase the firm’s profit. The analysis reported here provides important insights regarding the application of consumer information in online personalized marketing and consumer privacy protection.

Logistics service decision for e-commerce supply chain with fairness concern under uncertain environment

In this paper, we construct a two-echelon supply chain composed of an e-commerce platform and a manufacturer. We investigate the impact of manufacturer’s fairness concern (MFC) on e-commerce supply chain logistics service decisions under an uncertain environment. Given the uncertainty of the market environment, we depict unit cost of product and logistics service elasticity as uncertain variables. We construct four game-theoretical models, i.e. the manufacturer or the platform undertakes logistics service without and with considering the MFC, and compare the equilibrium solutions through numerical analysis. The results demonstrate that providing logistics services through an e-commerce platform increases the profits of all supply chain participants, regardless of whether the MFC is considered or not. Furthermore, we discover that the manufacturer will not always benefit from the MFC, the MFC can decrease the expected profits of supply chain participants. Interestingly, an increase in the level of environmental uncertainty does not necessarily imply a threat to the interests of supply chain participants. Under an uncertain environment, every supply chain participant needs to consider its fairness concern behavior and coordinate with logistics service strategies.

A game theoretic conflict analysis model with linguistic assessments and two levels of game play

In a conflict scenario, the domestic and international stake holders vye to safeguard their specific vested interests and objectives, like in the Syrian and Afghan conflicts. Knowledge about the position of domestic players can help both domestic and international players determine the root causes of conflict and work in groups to resolve the divergent issues. Due to complex nature of conflicts, it is pertinent to study conflict at domestic and international levels separately. For this purpose, we design a two-level conflict analysis model based on game theory and linguistic assessments of players. The first level deals with local players by playing a game between each of them in view of local issues and taking into account the local grouping. At the second level, game is played between local groups and international players regarding multiple issues. In this way, all the parties calculate the gains or losses of comparable actions of each other. Thus, the proposed model provides a comprehensive study of conflict. This paper studies Syrian conflict to validate the conflict analysis algorithm and explain the computations and results.

The evolution of brood parasitism from host egg predation

Abstract Obligate brood parasites pass all their parental duties to foster parents of a host species. While best understood in birds and hymenopteran insects, obligate brood parasitism has evolved independently at least 59 times across many lineages. The ancestors of brood parasites often provided no parental care to their offspring. Instead, a trophic association with their eventual hosts commonly appears to precede the origin of a brood parasitic strategy. Here, we used a game theoretical model to explore the conditions under which brood parasitism can evolve from predation and be maintained in the population. Our model was inspired by the relationship between the cuckoo catfish (Synodontis multipunctatus) parasitizing mouthbrooding cichlid fishes in the African Lake Tanganyika. Our model demonstrates the facilitatory role of host egg predation on the origin and evolutionary maintenance of brood parasitism through the exploitation of the host response to egg predation by brood parasites. We found no conditions under which brood parasitism as a pure strategy is evolutionarily stable, but we describe a range of evolutionarily stable equilibria when predators and parasites coexist. While our model is tailored to the cuckoo catfish, it generally applies to other systems where brood parasitism has evolved from other antagonistic behavior.

Newsvendor Competition with Endogenous Biases

Extensive studies have revealed that newsvendor decisions by human decision-makers are often biased by cognitive limitations, and, therefore, fail to achieve optimal profits prescribed by normative models. These biases are typically considered as liabilities in individual inventory decision-making, and much research has focused on developing methods to debias the decision-maker—for example, by providing decision support tools. However, in competitive settings biases can provide a competitive advantage, such that a biased newsvendor may earn a higher profit than an unbiased one. This raises the question of whether and when firms should debias their decision-makers. In this paper, we analyze decision biases that are endogenous rather than exogenous in competing newsvendor games. Specifically, we develop a two-stage game-theoretic model in which competing firms first select their decision-makers typefied by their bias levels, and then engage in a classic inventory competition game. Our analysis confirms the positive effect of the decision-maker’s bias on a firm’s economic outcome. However, this effect only appears in competitions in which decision biases are exogenously given. When biases are endogenously selected, firms are always (weakly) worse off than if they all had rational decision-makers. Our results suggest that debiasing at the industry level (e.g., adopting advanced inventory planning software) could benefit all players; however, individual firms do not have the incentive to do so in the absence of coordination mechanisms.

Improving Recycling: How Far Should We Go?

We analyze, in a game-theoretic model, the strategic interaction between competing firms that source their inputs from either primary or recycled material. Because the manufacturers’ primary production today serves as input for the recyclers’ production tomorrow, manufacturers can limit the recyclers’ scale of operation by reducing their output. Improving the recycling process generates then two opposite effects: it reduces primary production tomorrow by exposing manufacturers to stronger competition from recyclers, but it also lowers the manufacturers’ incentives to reduce their primary production today. If primary production exerts a negative externality on the environment, then making the recycling process too efficient might be counterproductive. This intuition equally applies to remanufacturing.

Punching above One’s Weight–On Overcommitment in Election Campaigns

In this paper, we develop a game-theoretic model to study how candidates compete in elections when voters care about the winner’s ability to implement policies. In our model, the candidates make commitments before the election regarding the plans they will try to implement if elected. These commitments serve as a signal of ability. In equilibrium, candidates make overambitious promises. While the candidate with the highest ability wins, the electorate may be better off having a random candidate implement her best plan, rather than seeing the winner implementing an overambitious plan.

Blockchain adoption and mode selection strategies for remanufacturing supply chain under cap-and-trade policy

Environmental conservation and economic advantages have propelled the swift expansion of the remanufacturing industry. Many original equipment manufacturers (OEMs) delegate remanufacturing operations to third-party remanufacturers (TPRs) through outsourcing and authorization. Furthermore, blockchain technology enhances consumers’ intention to purchase remanufactured products by disclosing more product information. To investigate the impacts of blockchain on remanufacturing mode selection, this paper focuses on a competitive remanufacturing supply chain comprising an OEM and a TPR under a cap-and-trade policy. Further, four game-theoretic models are derived from whether to adopt blockchain technology and which remanufacturing mode to select. Three major findings are obtained by solving and comparing the four models: (1) Adopting blockchain does not consistently result in advantages for both the OEM and TPR, and they should adopt blockchain for information disclosure in instances where the unit blockchain adoption cost is low, and the disclosure degree of remanufactured product information is also low. (2) Compared with not adopting blockchain technology, if the unit blockchain adoption cost is low, blockchain technology will increase the remanufactured product sales, thereby fostering the advancement of remanufacturing and contributing to reducing the environmental impact. (3) Whether blockchain is adopted or not, the OEM always tends to be in the outsourcing remanufacturing mode. The TPR only opts for the outsourcing remanufacturing mode when consumers’ preference for remanufactured products is high. More importantly, adopting blockchain will likely enhance consumers’ preference for remanufactured products, potentially shifting the TPR’s inclination for remanufacturing mode from authorization to outsourcing in some instances.

Strategic Queueing Behavior of Two Groups of Patients in a Healthcare System

Long waiting times and crowded services are the current medical situation in China. Especially in hierarchic healthcare systems, as high-quality medical resources are mainly concentrated in comprehensive hospitals, patients are too concentrated in these hospitals, which leads to overcrowding. This paper constructs a game-theoretical queueing model to analyze the strategic queueing behavior of patients. In such hospitals, patients are divided into first-visit and referred patients, and the hospitals provide patients with two service phases of “diagnosis” and “treatment”. We first obtain the expected sojourn time. By defining the patience level of patients, the queueing behavior of patients in equilibrium is studied. The results suggest that as long as the patients with low patience levels join the queue, the patients with high patience levels also join the queue. As more patients arrive at the hospitals, the queueing behavior of patients with high patience levels may have a negative effect on that of patients with low patience levels. The numerical results also show that the equilibrium behavior deviates from a socially optimal solution; therefore, to reach maximal social welfare, the social planner should adopt some regulatory policies to control the arrival rates of patients.

Blockchain adoption to eliminate dispute in platform-supplier cooperative delivery

Inefficient delivery services undermine consumers’ online shopping experience, posing a crucial challenge for e-commerce platforms and suppliers. In a platform-supplier cooperative delivery system, the issue of unclear responsibility for quality defects often arises. By utilizing real-time traceability enabled by blockchain, the platform can promptly identify supplier delivery accidents and return defective products directly to the supplier. This blockchain-enabled return mechanism could significantly reduce disputes in cooperative delivery processes. We develop a game theoretical model to analyze delivery strategies in supply chains with and without blockchain, and further examine the impact of blockchain on members’ delivery services and their profits. Our analysis indicates that blockchain incentivizes the platform to conduct high-level delivery services. However, it may either encourage or discourage the supplier’s provision of high-level delivery services. Moreover, blockchain acts as a double-edged sword in the supply chain, enhancing consumer satisfaction while also increasing wholesale prices. The interaction between these two effects determines whether blockchain negatively impacts on the supply chain’s profit, with the disposal cost of returned products by the supplier playing a crucial role. When the supplier’s disposal cost is relatively high, blockchain may result in supply chain members being worse off, despite its enhancement of consumer satisfaction. Furthermore, we find that blockchain enhances both the delivery service level and the profit of the supply chain if neither the supplier’s disposal cost nor the platform’s cost of high-level service are high. This study provides valuable insights into the potential benefits and challenges associated with blockchain adoption in cooperative delivery systems.

Verifiable Crowd Computing: Coping with bounded rationality

In this paper we use the repeated-games framework to design and analyze a master-worker (MW) mechanism, where a master repeatedly outsources computational tasks to workers in exchange for payment. Previous work on MW models assumes that all workers are perfectly rational and aim to maximize their expected utility. Perfect rationality is a strong behavioral assumption because it requires that all workers follow the prescribed equilibrium. Such a model may be unrealistic in a practical setting, where some agents are not perfectly rational and may deviate from the equilibrium for short-term gains. Since the correctness of these MW protocols relies on workers following the equilibrium strategies, they are not robust against such deviations.We augment the game-theoretical MW model with the presence of such bounded-rational players or deviators. In particular, we show how to design a repeated-games based MW Verifiable Crowd Computing mechanism that incentivizes the rational workers (or followers) to effectively punish such deviators through the use of terminal payments. We show that the master can use terminal payments to obtain correct answers to computational problems even in this more general model. We supplement our theoretical results with simulations that show that our mechanism outperforms related approaches.

A game theoretic decision forest for feature selection and classification

Abstract Classification and feature selection are two of the most intertwined problems in machine learning. Decision trees (DTs) are straightforward models that address these problems offering also the advantage of explainability. However, solutions that are based on them are either tailored for the problem they solve or their performance is dependent on the split criterion used. A game-theoretic decision forest model is proposed to approach both issues. DTs in the forest use a splitting mechanism based on the Nash equilibrium concept. A feature importance measure is computed after each tree is built. The selection of features for the next trees is based on the information provided by this measure. To make predictions, training data is aggregated from all leaves that contain the data tested, and logistic regression is further used. Numerical experiments illustrate the efficiency of the approach. A real data example that studies country income groups and world development indicators using the proposed approach is presented.

Should competing sellers adopt the data analytics service to enable product improvement in online marketplace

More and more marketplace platforms choose to use the data gathered from consumers (e.g., customer search terms, demographics) to provide a data analytics service for third-party sellers, both encouraging innovations and improving the operations of the latter. Through adopting the data analytics service, a seller can enhance its competitiveness by improving the quality of its products when there is more than one seller offering substitutes. This study develops a game-theoretic model to characterize a scenario with a marketplace platform and two competing sellers that sell substitutable products and decide whether to adopt the data analytics service provided by the platform. Then, we find that a seller's decision of whether or not to purchase the service depends on the competitor's decision and the two sellers' absorptive capacities of knowledge. Furthermore, a seller can benefit from adopting the data analytics service only if the seller has a high absorptive capacity, which can help increase product quality. When only one seller adopts, the platform and competing sellers can benefit from the adoption if this seller's absorptive capacity is high and the other's is moderate. The sellers' interests and social welfare can be aligned unless both sellers' absorptive capacities are low or high.

When ownership and copyright are separated: Economics of non-fungible token marketplaces with secondary markets

Creators have long strived to secure royalties for their works but with little success. In the digital realm, monetization presents an even greater challenge, as traditional digital assets frequently suffer from piracy issues, primarily due to the lack of verifiable ownership. Recently, non-fungible token (NFT), a blockchain-enabled tradable digital asset, has aroused great public attention for its potential to address this long-standing issue. Specifically, NFTs empower creators by enabling them to earn resale royalties from post-primary-sale transactions and by providing verifiable ownership that facilitates consumer trading in a secondary market. In this paper, we employ a two-stage game-theoretic model to examine this innovative business model. Here, an NFT creator makes optimal pricing and royalty rate decisions, while consumers make their purchase and resale decisions accordingly. Our study reveals that the creator inevitably reduces the selling price when a secondary market is introduced, even without imposing royalties. Moreover, contrary to conventional wisdom that NFT-enabled royalties always benefit creators, our research uncovers that the introduction of a secondary market leads to unintended revenue loss for the creator, particularly when most consumers only engage in secondary transactions. Furthermore, we find that the platform's profitability diminishes with the introduction of a secondary market, especially when most consumers are uninformed and the platform relies primarily on the primary market for commission collection. Finally, we find that the introduction of a secondary market may leave consumers worse off, despite the resale opportunities it offers. Our findings carry crucial managerial implications for platforms, creators, consumers, and policymakers.

How power structure and markup schemes impact supply chain channel efficiency under price-dependent stochastic demand

Although considerable attention has been separately given to factors such as power structures, price-dependent demand, and markup pricing schemes, there has been limited exploration of the combined effects of these factors on supply chain efficiency and the leader’s advantage. We propose a game theoretic model in which a manufacturer sells a single product to a newsvendor retailer who sets both optimal order quantity and selling price under uncertain price-dependent demand. Furthermore, we examine a supply network wherein a single retailer fulfills orders using a global manufacturer for regular orders and a local manufacturer to clear any shortages. Through numerical analysis, we show that the retailer always prefers to charge a percentage markup. In a two-player game, channel efficiency is higher when the retailer is the leader under linear demand; however, under iso-elastic demand, the manufacturer being a leader brings a higher channel efficiency. When a local manufacturer is involved as a second manufacturer, channel efficiency is higher when the retailer remains a follower, as this induces more fierce wholesale price competition between the two manufacturers. Additionally, when demand uncertainty is high in the two-player game with linear demand, the retailer as a follower can achieve higher profits, whilst high uncertainty under iso-elastic demand decreases both players’ profits. Moreover, it becomes advantageous for the retailer to have a local manufacturer as demand uncertainty increases, even when the local manufacturer announces the wholesale price first.

Competition between New Energy and Fuel Vehicles with Behavior-Based Pricing Strategies When Considering Environmental Concerns and Green Innovation

Environmental sustainability is an important issue in supply chain management (SCM). New energy vehicles (NEVs) have significant environmental value when compared to traditional fuel vehicles (FVs). Currently, there is intense competition between fuel and new energy vehicles, owing to differentiated pricing strategies. This paper focuses on behavior-based pricing (BBP) strategies between energy vehicles and fuel vehicles in a two-echelon supply chain wherein consumers are environmentally conscious. A two-period game-theoretic model is built to examine the effect of consumers’ environmental concerns on competition between fuel and energy vehicles, behavior-based pricing strategies, supply chain efficiency, and social welfare. The analytical results indicate that consumers’ environmental concerns facilitate the market share competition by new energy vehicle firms in the second period. If consumers care more about the environment, supply chain efficiency is improved in cases of retail as well as wholesale-and-retail behavior-based pricing strategies. Wholesale-and-retail behavior-based pricing strategies benefit all members of the supply chain, but this is not the case for retail behavior-based pricing strategies. If consumers are sufficiently concerned about the environment and new energy vehicle firms are more efficient, a win–win–win scenario for firms, consumers, and social welfare occurs in the two behavior-based pricing strategies. Counterintuitively, green innovation improves new energy vehicle, fuel vehicle as well as overall supply chain efficiency, in three cases.

Game theoretical analysis in two-echelon sustainable supply chains to manage and coordinate strategic decisions

Business firms and consumers are increasingly and rapidly realizing the benefits of adopting environmental responsibility. The business firms stress including it in their supply chain strategy and/or operations. This paper explores the environmental consciousness and quality attentiveness of consumers in a supply chain. Demand for the product depends on its price, eco-friendly level, and quality of the product. Three decentralized models are developed under three different game theoretical settings. A comparative study of the three game-theoretical models reveals several characteristics. It determines conditions under which channel members can decide the policy for the best possible benefit. The present work explores the effect of customer environmental awareness on the optimal decision. Production of eco-friendly items is also the prime consideration of our paper. It reveals that the manufacturer gets the most profit in the manufacturer Stackelberg game model, but the retailer gets the maximum profit from the retailer Stackelberg game model. Although channel members prefer their leading position to make the game theoretical decision-making process, the most decentralized channel profit is obtained from the Nash game model. Thus, consumers will also benefit, and the best channel profit can be obtained if the channel members agree to make decentralized decisions using the Nash game model. The centralized channel profit outperforms all three decentralized channel profits. The paper applies the concepts of sub-game perfect equilibrium and alternating offer bargaining to coordinate the channel and distribute surplus profit. Finally, analytical results are verified using numerical examples.

Nonlinear dynamics and game-theoretic modeling in economics and finance

In this foreword to the Special Issue “Nonlinear dynamics and game-theoretical modeling in economics and finance” we review the contributions in the issue highlighting the economic results and the connections with aspects of dynamic analysis. Indeed, the common theme of the contributions is the focus on system dynamics and the latest analytical techniques. This issue is devoted to celebrating the 70th birthday of Professor Laura Gardini, who inspired a generation of scholars in the study of discrete-time systems and global methods of analysis.

Committing to the wrong artificial delegate in a collective-risk dilemma is better than directly committing mistakes

While autonomous artificial agents are assumed to perfectly execute the strategies they are programmed with, humans who design them may make mistakes. These mistakes may lead to a misalignment between the humans’ intended goals and their agents’ observed behavior, a problem of value alignment. Such an alignment problem may have particularly strong consequences when these autonomous systems are used in social contexts that involve some form of collective risk. By means of an evolutionary game theoretical model, we investigate whether errors in the configuration of artificial agents change the outcome of a collective-risk dilemma, in comparison to a scenario with no delegation. Delegation is here distinguished from no-delegation simply by the moment at which a mistake occurs: either when programming/choosing the agent (in case of delegation) or when executing the actions at each round of the game (in case of no-delegation). We find that, while errors decrease success rate, it is better to delegate and commit to a somewhat flawed strategy, perfectly executed by an autonomous agent, than to commit execution errors directly. Our model also shows that in the long-term, delegation strategies should be favored over no-delegation, if given the choice.