Static Game Models Research Articles

How to Reshape the Selection Boundaries between Traditional and Digital Supply Chain Finance Based on the Pledge Rate and Default Loss: Two Tripartite Game Models

The development of digital technologies such as blockchain has provided new possibilities for solving the financing difficulties of small and medium-sized enterprises (SMEs). In order to explore the mutual influence of the participants in the supply chain, this paper constructs two static tripartite game models for traditional and digital supply chain finance, including a small and medium-sized enterprise (SME), a core enterprise (CE), and a financial institution (FI). The conditions for SME, CE, and FI to participate in digital supply chain finance, and the equilibrium strategy (repayment, repayment, loan) after participating in digital supply chain finance, are figured out. It is found that compared with the traditional supply chain, the digital supply chain expands the probability range of repayment for SME and CE by the change of pledge rate and default loss and broadens the probability range of repayment for CE by the change of default loss. Further, compared with the traditional supply chain finance, the greater the pledge rate of digital supply chain finance and the smaller the default loss, the stronger the willingness of the SME and CE to participate in the digital supply chain and the lower the willingness of the FI. After the three parties participate in the digital supply chain, however, the conclusion is the opposite. The smaller the pledge rate and the greater the default loss, the stronger the repayment willingness for the SME and CE and the stronger the loan willingness of the FI. Therefore, it is suggested to find the critical values of pledge rate and default loss and raise these two variables to an appropriate range to encourage all parties to voluntarily and consistently participate in digital supply chain financing.

Strategies to Mitigate Cutthroat Competition in E-Commerce: Insights from Game Theory

As e-commerce industries advanced irresistibly in recent years, some platforms chose to reduce prices again and again to seize the market, which lead to vicious competition and price war. So, this article tried to find out the best method for different companies to deal with price war. Based on several articles about how to avoid price war for enterprises, this article analyzes price war from the game theory perspective by establishing static game models to analyze the feasibility of each method. The result show that the main reason of this phenomenon is people are trapped in a prisoner's dilemma, and price war is an economic necessity behavior. As a result, government is suggested to establish market superior department and companies are suggested to produce differential products and cooperate with each other to deal with price war. For different kind of enterprises, oligopolies can produce products suit for different people and collaborate with influential companies in different areas while supply chain companies should reach a cooperation treaty with upstream and downstream enterprises achieve win-win cooperation.

Modeling the exploitation of common oil and gas resources under different conditions of resource distribution and extraction power: A game theory approach

Oil and gas are the driving forces behind many economic and productive activities, so they hold a crucial place in economic growth and development. The South Pars/North Dome field, the world's largest gas field, needs to be adequately developed and utilized. Iran and Qatar jointly own this field, and they have the responsibility of developing appropriate strategies for oil and gas exploitation. This study analyzes four static game models of the Nash equilibrium and optimal strategies between the two countries to exploit their shared resource. It assumes that a country's extraction power relies on international sanctions, which leads to unequal extraction power. The various conditions of the model include “equal resource distribution and equal extraction power”, “unequal distribution with equal extraction power”, “equal distribution with unequal extraction power”, and “unequal distribution with unequal extraction power”. The study's findings indicate that in the first two scenarios in which no country faces sanctions, both countries should adopt a non-commitment to cooperation. However, in the latter two scenarios in which one country is under sanctions and has weaker extraction power, the sanctioned country should commit to a cooperative policy, while the other country should adopt a non-cooperative approach. Therefore, the decision of a country to participate in the exploitation of common resources depends on its extraction power rather than resource distribution. Consequently, it can be argued that Iran and Qatar's common gas field, which is unequally divided, is significantly affected by sanctions. Due to Iran's sanctions, its extraction power has decreased, and it has adopted a cooperative strategy with Qatar. Meanwhile, Qatar's dominant strategy is non-cooperation. As a result, Iran suffers from the exploitation of shared resources under sanctions.

Solar farm investment game model: A data‐driven case in Florida

AbstractThe most effective approach to subsidizing power producers in order to bolster the penetration of renewable energy is continuously debated. To address this issue, this paper undertakes an in‐depth investigation into a solar farm investment problem, aiming at capturing the common interests and frictions among the government, the solar system developer, and the utility. In this paper, both static and dynamic game models are proposed with the consideration of the uncertainty of solar power generation. Before investing in a solar farm project, a potential solar farm investor takes into account of subsidy rate regulation for utilities enacted by the government, the panel price announced by the solar developer. In this study, we identified two thresholds of solar panel cost, which provide valuable insights for government policymakers when formulating an appropriate subsidy rate for the solar energy industry. Besides, a optimal policy for each stakeholder has been exposed. The finding from the dynamic model discloses the profound influence of various behaviors on the long‐term profitability of each stakeholder. Finally, based on the real‐world solar power data in Orlando, a case study is presented to expose a more tangible prospect for industrial application.

Competition of consumables’ original brand manufacturers and remanufacturers considering the entry of compatible manufacturers

Original brand consumables and remanufactured consumables are provided in the after-sales market, and in recent years the entry of compatible consumables provides a new option for consumers. Compared with original brand consumables, remanufactured and compatible consumables enjoy a cost advantage, but they suffer from different consumer trust discounts in the market. In order to capture the scenarios that before and after compatible products enter, we develop two independent static game models and explore equilibrium market structures for three types of consumables. Surprisingly, we find that (1) the more obscure consumer trust in remanufactured and compatible products, the more favorable to the coexistence of the three products, however, the appropriate distinction between remanufactured and compatible products is beneficial to a remanufacturer; (2) reduction of the failure rate by the remanufacturer will give free-riding opportunities to compatible products that also have non-original brand characteristics; and (3) the entry of compatible products cannot always improve consumer surplus and social welfare. These findings provide management suggestions for three types of manufacturing enterprises to sort out their competitive relationships, and also give policy implications for the government to promote the remanufacturing industry.

Optimal pricing and complex analysis for low-carbon apparel supply chains

Motivated by the low-carbon economic development, we study the competition issues in apparel supply chains considering consumers’ low-carbon preferences. In this paper, we construct static and dynamic decision-making models under different game scenarios based on the centralized and decentralized frameworks. Firstly, we explore the critical conversion conditions between the centralized and decentralized frameworks with the static game models. The centralized model benefits the whole supply chain when the low-carbon investment coefficient is moderate. On the contrary, the decentralized model benefits the supply chain when the low-carbon investment coefficient is smaller or larger. Secondly, combined with the local and global bifurcation theory, we examine the complex effect of adjustment parameters on the dynamic system. The dynamic game systems show bifurcation, chaos, and multi-stability as the adjustment parameters change continuously. Therefore, we apply a hybrid chaos control method to stabilize the dynamic system. Thirdly, we compare the average profits in the dynamic game scenarios and show the complex relationships with the varying parameters. Finally, some management insights and suggestions are presented based on our findings.

Average stochastic games for continuous-time jump processes

We consider nonzero-sum games for continuous-time jump processes with unbounded transition rates under expected average payoff criterion. The state and action spaces are Borel spaces and reward rates are unbounded. We introduce an approximating sequence of stochastic game models with extended state space, for which the uniform exponential ergodicity is obtained. Moreover, we prove the existence of a stationary almost Markov Nash equilibrium by introducing auxiliary static game models. Finally, a cash flow model is employed to illustrate the results.

Static Game Models and Applications Based on Market Supervision and Compliance Management of P2P Platform

This article focuses on the two-party static game between market supervisory organization and peer-to-peer (P2P) lending platform. Considering 4 game modes with both “strong supervision” and “weak supervision” of market supervisory organization and “compliance management” and “noncompliance management” of P2P lending platform, the paper establishes a static game model between P2P lending platform and market supervisory organization and solves the market equilibrium solutions. Based on income, cost, disguised cost, and fine of P2P lending platform and income, cost, and reward of market supervisory organization, it discusses conditional strategies that P2P lending platform selects “compliance management” or “noncompliance management” and that market supervisory organization selects “strong supervision” or “weak supervision,” respectively. Furthermore, the relevant influencing factors are analyzed which come from 18 P2P lending platforms in Guangdong Province of China, and the conclusions were in good agreement with the actual market. The research has scientific guiding significance.

Survive and Thrive: A Stochastic Game for DDoS Attacks in Bitcoin Mining Pools

Mining pools have become dominant in today’s bitcoin mining network, where miners can pool their powers together for reduced variance of block mining and steadier stream of potential income. Along with the continuous evolvement of mining pools are the increasingly intense competitions among them. Recent empirical studies have shown that the distributed denial-of-service (DDoS) attack is one of the most common ways for competing mining pools to sabotage the rivals and earn illegitimate rewards. Existing efforts have been made on using static game models to analyze the interactions between mining pools, and derive the Nash Equilibrium and optimal attacking strategies in a one-time static context. To better understand the impact of such DDoS attacks, in this paper, we take a starkly different approach, and for the first time address the dynamics in mining pool attacks. Specifically, we start by formulating the interactive competition among mining pools as a general-sum stochastic game. Then we propose an efficient Nash learning algorithm to obtain the near optimal attacking strategy that maximizes the expected long-term utility. Our theoretical analysis and extensive experimental results both show that the proposed strategy outperforms the baseline myopic learning algorithm, which only aims at maximizing the revenue in the current time stage. These findings, together with our proposed stochastic game model and learning algorithm, are expected to provide more practical guidelines for mining pools to survive and thrive in the highly-competitive bitcoin ecosystem.

Dynamic Games in Cyber-Physical Security: An Overview

Due to complex dependencies between multiple layers and components of emerging cyber-physical systems, security and vulnerability of such systems have become a major challenge in recent years. In this regard, game theory, a powerful tool for modeling strategic interactions between multiple decision makers with conflicting objectives, offers a natural paradigm to address the security-related issues arising in these systems. While there exists substantial amount of work in modeling and analyzing security problems using game-theoretic techniques, most of the existing literature in this area focuses on static game models, ignoring the dynamic nature of interactions between the main players (defenders vs. attackers). In this paper, we focus only on dynamic game analysis of cyber-physical security problems and provide a general overview of the existing results and recent advances based on application domains. We also discuss several limitations of the existing models and identify several hitherto unaddressed directions for future research.

Nonzero-Sum Expected Average Discrete-Time Stochastic Games: The Case of Uncountable Spaces

In this paper we study nonzero-sum discrete-time stochastic games with an uncountable state space and Borel action spaces under the expected average payoff criterion. The reward functions can be possibly unbounded and the transition law is a convex combination of finitely many probability measures dependent on the state variable and dominated by some probability measure on the state space. We introduce several auxiliary static game models and obtain their properties. Moreover, by a technique of extending the space state, we introduce auxiliary stochastic game models and derive the uniform geometric ergodicity of Markov chains taking values in the extended state space. Furthermore, we show the existence of a stationary almost Markov Nash equilibrium via an approximation method. Finally, we use a resource extraction model to illustrate the main results.

Information structure and statistical information in discrete response models

Strategic interaction parameters characterize the impact of actions of one economic agent on the payo of another economic agent. In this paper we study how the information available to economic agents regarding other economic agents can inuence the ability of an econometrician to recover strategic information parameters from the observed actions. We consider two extreme cases: the complete information case where the information sets of participating economic agents coincide, and the incomplete information case where each agent has a privately observable type. We nd that in models with incomplete information the statistical (Fisher) information for the interaction parameters is zero, implying that estimation and inference become nonstandard. In contrast, in the incomplete information models with any non-zero variance of player types, the statistical information is positive, implying the existence of regular estimators for these parameters converging at the parametric rate. This nding is illustrated in two cases: treatment eect models (expressed as a triangular system of equations), and the static game models. In both types of models the observed discrete outcomes are driven by continuously distributed errors with an unknown distribution (unobserved heterogeneity). We nd that the key factor driving the result in these models is

Game-based strategy for load service entity to level Duck Chart as well as gain EV consumers

Summary With the increasing penetration of unregulated solar energy, a load service entity (LSE) can exert an externality cost to guide the charging behaviors of electric vehicle (EV) users and level the Duck Chart. This paper introduces a dynamic Stackelberg game model between LSE and EV users to analyze consumer behavior, and a complete information static game model to help LSEs increase profits by gaining share of the EV market. These dynamic and static game models are incorporated into a novel theoretic algorithm with mixed integer programming. A case study shows that the models and the proposed algorithm can level the Duck Chart and guarantee an LSE's share of the EV market. Copyright © 2016 John Wiley & Sons, Ltd.

Game Theory Analysis on the Generation Process of Transfer of Rural Construction Land Transfer

At present, as to the rights of using rural collective construction land, our country in most cases adopts policy of limiting its transfer, however, the phenomenon of the transfer of collective construction land still occur in life. From the perspective of game theory, this paper established static game models to conduct analysis on the behavior choices of the village collective, construction land transferee and the government and elaborated the rise of transfer behavior in rural construction land. The final finding concluded that the optimal strategy in the game between the village collective and the government is to choose transference; the transferee's rational behavioral strategy is to transfer construction land to rural collective; and allowing the transfer of collective construction land is the conclusion of the government's rational choice. It theoretically explains the phenomenon that although the laws in our country prohibit the market transference of the rural collective construction land, in practice there is a large amount of such transference.

Defense Expenditures and Allied Cooperation

This article investigates the implications of cooperative and noncooperative defense spending of allied countries in conflicting blocs using static and leader-follower game models. It is well known that in the three-country world with two allies and an adversary, all countries may be worse off when the allies cooperate than when they do not. This article shows that when the number of countries in each separate bloc is large, the countries in one bloc may be better off by cooperating than not, even if the negative spillover from the adversarial bloc is large. Furthermore, cooperative behavior in a leader-follower game by the leader bloc can attain a better outcome than noncooperation.

Static game theory models and their applications in management science

In the present paper, we give a brief review of static game models and their applications in management science. Our intention here is twofold: On the one hand, we would like to provide the reader with an overview of game theory and its applications in management science. On the other hand, we intent to explore the mathematical tractability of management science problems when formulating them as game theory models. To make the paper not too extensive, we restrict our attention to static game theory models and five management science related areas. Our discussion starts by a general description of static game theory models and their solution schemes and follows by an investigation of game theory applications. At the end of the survey, we provide a brief description of some other approaches of game theory.