Multi-stage Game Model Research Articles

Verification and Optimization of Network Security Defense System from the Perspective of Blue Army in Actual Offensive and Defensive Exercises

From the point of view of signal camouflage, this paper proposes an active network defense system. Then, the optimal camouflage target selection scheme is proposed. Its goal is to solve the problems existing in the information constructionof Chinese military equipment support. This method establishes a multistage game model based on weapon support informationnetwork attack and defense. The attack and defense benefits are quantitatively calculated based on the cost of signal concealment. The solution to the refined Bayesian balance problem is given. Then, a multistage optimization algorithm for camouflage signal selection is proposed. Finally, experimental research proves the proposed algorithm to be reasonable and practical.

Optimal channel selection considering price competition and information sharing under demand uncertainty

PurposeThe rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.Design/methodology/approachThis study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.FindingsThis study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.Originality/valueThis research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

Cooperation and investment decisions of one shipping liner to multiple ports under differential pricing

Cooperation between shipping liners and ports has become an inevitable trend in the development of the maritime supply chain. To better understand the investment decisions of one shipping liner for multiple ports and the efforts that ports should make to achieve a large market share and high profitability, we construct a two-stage game model from the perspective of ports and shipping liner and summarize the conditions under which the shipping liner invests in different ports. The results show that the greater the difference in initial capacity between two ports under no-investment, the more likely it is that the shipping liner chooses the High-capacity port to call. Interestingly, investment in ports by the shipping liner may not necessarily help ports expand their market share but may instead damage the market share they already have, and the loss effect is positively related to port size. Additionally, with the shipping liner investment, a stronger discount decided by the Flexible port does not attract the shipping liner to cooperate with it. In this study, a multi-stage game model is used to characterize the changes in the decision-making of the maritime supply chain under different strategies, which can not only provide decision-making suggestions for the cooperation choices of shipping liners but also provide a theoretical basis for ports to attract investment from shipping liners.

Flipit Game Deception Strategy Selection Method Based on Deep Reinforcement Learning

The existing cyber deception decision-making model based on game theory primarily focuses on the selection of spatial strategies, which ignores the optimal defense timing and can affect the execution of a defense strategy. Consequently, this paper presents a method for selecting deception strategies based on a multi-stage Flipit game. Firstly, based on the analysis of cyber deception attack and defense, we propose a concept of moving deception attack surface and analyze the characteristics of deception attack and defense interaction behaviors based on the Flipit game model. The Flipit game model is then utilized to create a single-stage deception spatial-temporal decision-making model. Additionally, we introduce the discount factor and transition probability based on a single-stage game model and construct a multi-stage cyber deception model. We provide the utility function of the multi-stage game model, and design a Proximal Policy Optimization algorithm based on deep reinforcement learning to compute the defender’s optimal spatial-temporal strategies. Finally, we utilize an application example to validate the effectiveness of the model and the advantages of the proposed algorithm in generating the multi-stage cyber deception strategy.

Logistics mode selection and information sharing in a cross-border e-commerce supply chain with competition

Selecting an appropriate logistics mode is crucial for overseas suppliers (OSs) who enter new markets through the cross-border e-commerce platform (CEP), but it is challenging because OSs are unfamiliar with the local markets. Thus motivated, we aim at a supply chain where an OS sells its product through a CEP that holds demand information advantages, and the OS faces competition from the domestic supplier (DS). By constructing a multi-stage game model, we study the OS's logistics mode selection between direct-mail and bonded-warehouse, which has different logistics costs and inventory risks. Moreover, the influence of the CEP's information sharing decision on the logistics mode selection is investigated. Our results show that with information sharing, the OS always selects the bonded-warehouse logistics mode; while without information sharing, the OS makes a choice between direct-mail and bonded-warehouse mode according to the tax rate and market fluctuation. Particularly, under a high tax rate, with the increase in market fluctuation, the uninformed OS not only needs to adjust the logistics mode choice but also change the inventory strategy. We also reveal that information sharing could lead to the OS changing the logistics mode from direct-mail to bonded-warehouse, and then cause fierce competition between the OS and DS. Therefore, sharing information does not always benefit the CEP. Under certain conditions, it is more beneficial for the OS to choose the direct-mail mode when the information is shared, as doing so can help chain members escape the prisoner's dilemma and thus lead to a “win-win-win” outcome.

Marketplace or reseller: the channel strategy analysis for e-commerce platforms considering brand differentiation

PurposeThe paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand.Design/methodology/approachThe paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy.FindingsThe results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high.Research limitations/implicationsThis study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment.Practical implicationsThe paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets.Originality/valueThis paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.

A differential privacy based multi-stage network fingerprinting deception game method

As an active deception defense mechanism, network fingerprint obfuscation plays an important role in deceiving the attacker's fingerprinting actions. However, the existing methods show increasing limitations in coping with strategic multi-stage fingerprinting behavior in resource constrained situations. In order to solve this problem, we propose a Differential Privacy based Multi-stage fingerprinting deception Game method (DPMG). DPMG uses the multi-stage game model and the belief update mechanism to give a better description on the continuous fingerprinting interaction process. Besides, the equilibrium existence of such a game model is analyzed. Then a defender strategy optimization mechanism under the resource constraints is designed and a Recursive Algorithm Solving Equilibrium algorithm (RASE) to solve the equilibrium strategy is implemented. Experiment results show that DPMG can deceive the network fingerprinting behavior effectively under the defense resources constraints, and scale well to different network size.

Multistage Game Model Based Dynamic Pricing for Car Parking Slot to Control Congestion

Car parking has become expensive both in terms of money and the time to search for a free parking slot, especially in metropolitan cities. The parking lots nearer to shopping complexes or corporate buildings often get occupied, leaving the farther parking lots empty and leading to traffic congestion near these already busy areas. With a dynamic pricing strategy, the prices of high-demand parking lots can be surged up during peak hours, deviating the traffic towards the unoccupied, cheaper parking lots. A dynamic pricing strategy for car parking slots helps in fairly distributing the traffic among all the parking lots and helps in increasing the revenue of the parking lot management as well. However, increasing the prices unconditionally will affect the drivers. In this paper, a game-theory-based dynamic pricing strategy is proposed that aims to optimize the benefits for both the car parking management and the drivers. The goal is to find the Nash equilibrium price for peak hours and off-peak hours where the car parking management’s revenue is maximized while the price paid by the drivers is minimized. Simulation results show that the proposed model manages to reduce the congestion at peak hours and the profits of parking lot owners are increased.

Demand information sharing of fresh produce supply chain considering competing suppliers’ freshness‐keeping effort

AbstractThis paper considers a fresh produce supply chain in which a retailer sources alternative produce from two competing suppliers. The suppliers make efforts to preserve product freshness, while the retailer, with demand forecast information, can share it with none, one or both of the suppliers strategically. By constructing a multistage game model, the optimal demand information sharing strategy in the supply chain is explored. The results show that the retailer has the willingness to disclose demand information only when the freshness elasticity is high. Significantly, with the improvement of the freshness elasticity, the retailer will transform from sharing information with both suppliers to one supplier. The suppliers are always willing to accept the information disclosed by the retailer. However, complete transparency of demand information may hurt the supply chain under certain conditions. To improve the supply chain performance, the retailer can charge both suppliers for information fees and adjust from sharing information with no suppliers to both suppliers with a relatively low freshness elasticity. Conversely, the retailer can change from sharing information with both suppliers to sharing information with one supplier through a charging contract with a relatively high freshness elasticity.

Investment and Production Strategies of Renewable Energy Power under the Quota and Green Power Certificate System

In order to study the impact of a renewable energy quota and green power certificate system on the strategies of energy suppliers, this paper constructs a multi-stage game model of renewable energy power investment and production from the renewable energy interest chain and its stakeholders. Through the calculation and solution of the model, the optimal renewable energy utilization level, pricing and production strategies of renewable energy power of energy suppliers are calculated under the scenarios of direct sale of power and purchase and sale by power grids. The results show that the quota ratio, green certificate price and investment cost are the key influencing factors of energy suppliers’ strategies, and changes in the values of the three factors will completely change the renewable energy investment, pricing and production levels of energy suppliers in equilibrium. In addition, the study found that the impact of the renewable energy quota on renewable energy utilization levels of energy suppliers depends on the relative size of investment cost and green power certificate price. At the same time, it was also found that with a change in investment cost, green power certificate price and user preference, the market share and renewable energy utilization level of traditional energy suppliers and new energy suppliers also change.

A multi-stage game model for the false data injection attack from attacker’s perspective

With the rapid development and widespread application of information and communication technology, power system has gradually become a cyber physical power system (CPPS) in which the cyber space and physical space are deeply coupled. The continuous interaction between information flow and power flow renders power grid confronted with potential cyber attack risks. As a typical attack approach, false data injection attack (FDIA) interferes with control decisions making by weakening information integrity. In this paper, regarding the phasor measurement unit (PMU) as the attack-defense target in power system, a multi-stage game model for FDIA is proposed based on attacker’s perspective, putting particular emphasis on data tampering, strategic adjustments, and multi-path attacks in a multi-stage game. Firstly, from the perspective of the attacker, the false data is constructed based on the PMU configuration, the attack range is optimized, and the attack consequences are quantified. Secondly, based on two-player zero-sum game theory, take the overall revenue and multi-path attacks in multi-stage game into consideration, the optimal attack-defense strategy is obtained by solving the Nash equilibrium point. Finally, experiment results of multi-stage game and one-stage game are discussed. The simulation results demonstrate that the proposed multi-stage game strategy owns better effect and applicability for attackers.

Study on Online Dispatching Defensive Strategy for Power Grid Considering Expected Circuit Breaker Fault Set

In order to prevent serious blackouts caused by cascading faults, a defense strategy which considers the expected circuit breaker fault set is proposed for online despatching that is applied to power grid protection. In this paper, the multi-stage game model has been established to study the online defense strategy of circuit breaker failure from the perspective of attacker and defender. From the perspective of attacker in the power grid, the initial expected fault set based on the circuit breaker defect prediction is taken as the initial action. Considering the two factors that the removal of the power flow transfer branch and the incorrect operation of the zone III distance protection because of hidden fault. Then, a strategic space for the attacker is formed by using the risk theory predict the operation of power grid. From the perspective of the defender, a method for adjusting the power system using sensitivity control and adaptive adjustment of the backup protection setting is proposed. The paper finds the optimal strategy for both parties through defining the profit function. Finally, the IEEE 39-bus system is taken as an example to analyze the model, and the simulation results verify the feasibility of the article model.

The Value of Traded Target Information in Security Games

Ample evidence has confirmed the importance of information in security. While much research on security game has assumed the attackers' limited capabilities to obtain target information, few studies consider the possibility that the information can be acquired from a data broker, not to mention exploring the attackers' profit-seeking behaviors in the shrouded underground society. This paper studies the role of information in the security problem when the target information is sold by a data broker to multiple attackers. We formulate a novel multi-stage game model to characterize both the cooperative and competitive interactions of the data broker and attackers. The attackers' competition with correlated purchasing and attacking decisions is modeled as a two-stage stochastic model, and the bargaining process between the data broker and the attackers is analyzed in a Stackelberg game. The study contributes to the literature by exploring the behaviors of the attackers with labor specialization, and providing quantitative measures of information value from an economic perspective. The proposed frameworks characterize both the attackers' competitive equilibrium solutions and the data broker's pricing strategies under different market parameters. We also show how factors such as the quality of information, the heterogeneity in attackers' utilities, and their cooperative purchasing strategy would have an impact on the results.

A game theoretic approach for the duopoly pricing of energy-efficient appliances regarding innovation protection and social welfare

Recent developments in energy consumption ‘management’ have heightened the need for energy efficiency considerations in energy-intensive supply chains, according to the sustainable development framework. Therefore, policy-makers need to find out how they can improve these conditions, considering the resource limitations and energy requirements. According to these issues, we address a novel pricing model for new energy-efficient products, conventional models, and relative energy consumption under a tax-subsidy system. The products and energy services are made in a product supply chain consisting of an energy supplier and two manufacturers in a duopoly. Furthermore, the protection costs of innovation process such as copyright are investigated for the first time in this problem. Then, a multi-stage game model is developed considering two scenarios, based on different game structures. Finally, we solve the problem and provide a comprehensive analysis of the optimal values of variables and players’ profit. The results show that the first scenario has more advantages than the leader-follower competition. However, the second scenario results in less energy consumption than the first one. The findings also suggest that energy policies applied on the producer side are more effective than the consumer-side energy policies to improve energy-saving.

A game theoretic approach for pricing policies in a duopolistic supply chain considering energy productivity, industrial rebound effect, and government policies

Nowadays, due to environmental issues sustainability becomes more popular among industrial firms. In this regards, governments follow the energy-efficiency programs (EEPs) to control and reduce energy consumption in all the world. In this paper, we investigate a novel sustainable supply-chain consists of an energy-efficient manufacturer, inefficient manufacturer, and energy supplier that participation in an EEP. Also, we propose an extended utility function for household energy consumers, besides assuming industrial energy productivity as government's utility function and energy rebound of the technological efficiency improvement of the production process, for the first time. To design an effective program, a multi-stage game model is proposed under two scenarios, i.e. tax deduction and subsidy scheme. Then, we present equilibrium decisions as well as a sensitivity analysis in details. The results indicate that considering energy rebound can close profit calculations to the reality. Additionally, the tax deduction is a more effective policy than subsidy scheme to support the energy-efficient manufacturer in competition with similar manufacturers. However, subsidy policy provides better conditions for the government to control the energy consumption of the household sector using energy price reform. The present study clears the application of sustainable development participation in an industrial EEP.

A game theoretic approach for assessing residential energy-efficiency program considering rebound, consumer behavior, and government policies

In recent years, due to the sustainability concerns, energy-efficiency programs that address eco-friendly issues such as energy efficiency and clean production have increased in the world. Furthermore, eco-efficient appliances, as the direct result of research and development (R&D) activities have become a popular topic in the sustainability programs of the most developed countries due to their high-tech features. In this paper, we discuss a residential energy-efficiency program for the new energy-efficient appliances and related energy consumption, simultaneously, in a sustainable supply chain consists of the energy supplier, manufacturer, and the government. Also, we consider the technological rebound effect of the efficiency improvement, consumer behavior, and ability to innovate of the manufacturer in the problem, as the novel assumptions. To solve the problem, we propose a multi-stage game model using the Bertrand model. Also, we investigate three structures, based on the Nash and leader-follower games as the scenarios. The findings reveal the equilibrium pricing decisions for the supply-chain players to maximize their profits, besides the best energy policy and supply-chain structure for the efficient management of household energy consumption. More precisely, the first scenario with the Nash structure between the manufacturer and energy supplier has the most advantages and the least disadvantages than the other scenarios. Also, the manufacturer subsidy has the most performance in the discussed energy-efficiency program. Finally, the present study shows the significant effects of considering the energy rebound, innovation abilities of the manufacturer, and consumer behavior assumptions in the household energy problems.

An Empirical Study on Optimal Strategies of Industry-University-Institute Green Innovation with Subsidy

With the increasing awareness of environmental protection and the complexity and rapid change of technological innovation, more and more enterprises seek to develop and research (R&D) institutions to cooperate with green innovation. In order to promote the cooperation efficiency of green innovation, this paper develops a multi-stage game model to analyze the optimal strategies of the enterprise, the university and the policy-maker with consumer learning and government subsidy. Then the paper compares the difference of optimal subsidy between the single-stage green innovation cooperation and the multi-stage green innovation cooperation. The research shows that consumers’ initial learning factors and green innovation cooperation cycle have a significant impact on the optimal input level of the enterprise and the university and also have a significant impact on the optimal subsidy of the government. The specific government subsidy and subsidy ratio depend on the comprehensive role of consumer learning factors and the green innovation cooperation cycle. In the end, we propose that the government should subsidize the university at times when the initial consumer learning factor is low; the government subsidy should be properly lagged when the initial consumer learning factor is high.

Dynamic trust game model between venture capitalists and entrepreneurs based on reinforcement learning theory

It has been extensively demonstrated that the trust between venture capitalists and entrepreneurs plays an important role in improving the success rate of entrepreneurship. However, little research has been performed concerning the dynamic nature of the trust between venture capitalists and entrepreneurs. Therefore, we attempt to reveal the motivations and process of trust between VCs and entrepreneurs from the perspective of dynamics. First, the theoretical model of dynamic trust was proposed. Second, reinforcement learning was introduced to design the multi-stage game model of dynamic trust, and the algorithm was illustrated. Reinforcement learning theory can reveal the reasons for dynamic changes in trust from a psychological perspective. Finally, the action strategies of venture capitalists and entrepreneurs were simulated. We observe that the dynamic characteristics of trust between venture capitalists and entrepreneurs are determined by entrepreneurs’ efforts. Venture capitalists can prevent investment risks and maintain trust stability when fewer funds are invested in the early stage and when more funds are invested in the later stage. Since the dynamic process of trust is also the process of learning about the other, the dynamic process of trust is non-linear, and the relationship is adaptive.

Choice of Strategic Industry-protecting Policies Amidst Uncertainty in Demand and Supply: A Multi-stage Game Model

It has been shown how trade policy can be strategically chosen while demand uncertainty significantly arises for the exporting market. As an extension, we will show how industry-protecting policy can be strategically chosen while uncertainty arises in both demand and supply. In summary, demand uncertainty is important to determine trade policy while supply uncertainty important to industry-protecting policy. Some countries enact an industry-protecting policy of either subsidy or price control despite arguments about inefficiency. This paper aims to explore which policy can be strategically chosen. To do so, we will use a multi-stage game model. One finding is that subsidy is clearly better when supply uncertainty is significant. This is largely because subsidy induces domestic firms to internalize the supply uncertainty. When demand uncertainty is significant, the number of firms and the elasticity, of demand and supply, should be taken into account when making a choice. This paper contributes to the body of knowledge in terms of industrial policy and strategic choice.

Platform Governance in the Sharing Economy: Interplay Between Public and Private Regulators

We built a multi-stage dynamic game model to analyze how to effectively regulate opportunistic behaviors in the sharing economy. We elaborate this under three different scenarios: sellers under (1)...