scholarly journals The service pricing strategies and the strategic behavior of customers in  an unobservable  Markovian queue with unreliable server

2021 ◽  
Author(s):  
Kamel Meziani ◽  
Fazia RAHMOUNE ◽  
Mohammed Said RADJEF
Keyword(s):  
Strategic Behavior ◽  
Stackelberg Game ◽  
Stackelberg Equilibrium ◽  
Pricing Strategies ◽  
Behavioral Strategies ◽  
System Parameters ◽  
Service Pricing ◽  
Markovian Queue ◽  
Proposed Model ◽  
The Social

A Stackelberg game is used to study the service pricing and the strategic behavior of customers in an unreliable and totally unobservable M/M/1 queue under a reward-cost structure. At the first stage, the server manager, acting as a leader, chooses a service price and, at the second stage, a customer, arriving at the system and acting as a follower, chooses to join the system or an outside opportunity, knowing only the service price imposed by the server manager and the system parameters. We show that the constructed game admits an equilibrium and we give explicit forms of server manager and customers equilibrium behavioral strategies.  The results of the proposed model show that the assumption that customers are risk-neutral is fundamental for the standard approach usually used. Moreover, we determine the socially optimal price that maximizes the social welfare and we compare it to the Stackelberg equilibrium. We illustrate, by numerical examples, the effect of some system parameters on the equilibrium service price and the revenue of the server manager.

scholarly journals Does Information Asymmetry Impact Sub-Regions’ Cooperation of Regional Water Resource Allocation?

2019 ◽  
Vol 16 (21) ◽  
pp. 4292
Author(s):  
Li Pan ◽  
Xudong Chen ◽  
Lu Zhao ◽  
Anran Xiao
Keyword(s):  
Information Asymmetry ◽  
River Basin ◽  
Water Allocation ◽  
Stackelberg Game ◽  
Regional Cooperation ◽  
Economic Benefits ◽  
Allocation Model ◽  
Proposed Model ◽  
The Social ◽  
Regional Water

Water resources allocation is an urgent problem for basin authorities. In order to obtain greater economic benefits from limited water supplies, sub-regions must cooperate with each other. To study the influence of cooperation among sub-regions and the symmetry of cooperation information on the interests of the basin authority and each sub-region, this study proposes a regional water allocation model in three different situations: (1) non-cooperation; (2) cooperation and information symmetry; (3) cooperation and information asymmetry. The proposed model clearly reflects the Stackelberg game relationship between the basin authority and sub-regions. Finally, the model is applied to the Qujiang River Basin in China, and the decisions of the basin authority and sub-regional managers of the Qujiang River Basin under three different situations are discussed. The results show that regional cooperation benefits both the cooperative regions and the social welfare value of the entire river basin, when compared with non-cooperation.

scholarly journals A Game Model for Medical Service Pricing Based on the Diagnosis Related Groups

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinli Duan ◽  
Zhibin Lin ◽  
Feng Jiao
Keyword(s):  
Social Welfare ◽  
Medical Service ◽  
Stackelberg Game ◽  
Diagnosis Related Groups ◽  
Equilibrium Price ◽  
Stackelberg Equilibrium ◽  
Game Model ◽  
Second Stage ◽  
Medical Institutions ◽  
Service Pricing

Background: Currently there are various issues that exist in the medical institutions in China as a result of the price-setting in DRGs, which include the fact that medical institutions tend to choose patients and that the payment standard for complex cases cannot reasonably compensate the cost.Objective: The main objective is to prevent adverse selection problems in the operations of a diagnosis-related groups (DRGs) system with the game pricing model for scientific and reasonable pricing.Methods: The study proposes an improved bargaining game model over three stages, with the government and patients forming an alliance. The first stage assumes the alliance is the price maker in the Stackelberg game to maximize social welfare. Medical institutions are a price taker and decide the level of quality of medical service to maximize their revenue. A Stackelberg equilibrium solution is obtained. The second stage assumes medical institutions dominate the Stackelberg game and set an optimal service quality for maximizing their revenues. The alliance as the price taker decides the price to maximize the social welfare. Another Stackelberg equilibrium solution is achieved. The final stage establishes a Rubinstein bargaining game model to combine the Stackelberg equilibrium solutions in the first and second stage. A new equilibrium between the alliance and medical institutions is established.Results: The results show that if the price elasticity of demand increases, the ratio of cost compensation on medical institutions will increase, and the equilibrium price will increase. The equilibrium price is associated with the coefficient of patients' quality preference. The absolute risk aversion coefficient of patients affects government compensation and total social welfare.Conclusion: In a DRGs system, considering the demand elasticity and the quality preference of patients, medical service pricing can prevent an adverse selection problem. In the future, we plan to generalize these models to DRGs pricing systems with the effects of competition of medical institutions. In addition, we suggest considering the differential compensation for general hospitals and community hospitals in a DRGs system, in order to promote the goal of hierarchical diagnosis and treatment.

scholarly journals Optimally Deceiving a Learning Leader in Stackelberg Games

2021 ◽  
Vol 72 ◽  
pp. 507-531
Author(s):  
Georgios Birmpas ◽  
Jiarui Gan ◽  
Alexandros Hollender ◽  
Francisco J. Marmolejo-Cossío ◽  
Ninad Rajgopal ◽  
...  
Keyword(s):  
Strategic Behavior ◽  
Stackelberg Game ◽  
Learning Algorithm ◽  
Stackelberg Equilibrium ◽  
Stackelberg Games ◽  
Main Challenge ◽  
Interesting Connection ◽  
Finite Set ◽  
Payoff Matrices ◽  
Best Responses

Recent results have shown that algorithms for learning the optimal commitment in a Stackelberg game are susceptible to manipulation by the follower. These learning algorithms operate by querying the best responses of the follower, who consequently can deceive the algorithm by using fake best responses, typically by responding according to fake payoffs that are different from the actual ones. For this strategic behavior to be successful, the main challenge faced by the follower is to pinpoint the fake payoffs that would make the learning algorithm output a commitment that benefits them the most. While this problem has been considered before, the related literature has only focused on a simple setting where the follower can only choose from a finite set of payoff matrices, thus leaving the general version of the problem unanswered. In this paper, we fill this gap by showing that it is always possible for the follower to efficiently compute (near-)optimal fake payoffs, for various scenarios of learning interaction between the leader and the follower. Our results also establish an interesting connection between the follower’s deception and the leader’s maximin utility: through deception, the follower can induce almost any (fake) Stackelberg equilibrium if and only if the leader obtains at least their maximin utility in this equilibrium.

Strategic behavior in the constant retrial queue with a single vacation

2020 ◽  
Vol 54 (2) ◽  
pp. 569-583 ◽  
Author(s):  
Yu Zhang
Keyword(s):  
Social Welfare ◽  
System Parameter ◽  
Strategic Behavior ◽  
Retrial Queue ◽  
Cost Structure ◽  
Social Planner ◽  
System Parameters ◽  
Single Vacation ◽  
The Social ◽  
System Characteristics

We study customers’ joining strategies in an M/M/1 constant retrial queue with a single vacation. There is no waiting space in front of the server and a vacation is triggered when the system is empty. If an arriving customer finds the server idle, he occupies the server immediately. Otherwise, if the server is found unavailable, the customer enters a retrial pool called orbit with infinite capacity and becomes a repeated customer. According to the different information provided for customers, we consider two situations, where we investigate system characteristics and customers’ joining or balk decisions based on a linear reward-cost structure. Furthermore, we establish the social welfare of the system and make comparisons between the two information levels. It is found that there exist thresholds of system parameters such that the social planner would prefer revealing more information when the system parameter is greater than or less than the corresponding threshold.

Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li
Keyword(s):  
Resource Allocation ◽  
Incomplete Information ◽  
Stackelberg Game ◽  
Superior Performance ◽  
Channel Gain ◽  
Mobile Users ◽  
Pricing Strategies ◽  
Game Equilibrium ◽  
Allocation Process ◽  
Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

scholarly journals Pricing Policies in a Retailer Stackelberg O2O Green Supply Chain

2020 ◽  
Vol 12 (8) ◽  
pp. 3236
Author(s):  
Gan Wan ◽  
Gang Kou ◽  
Tie Li ◽  
Feng Xiao ◽  
Yang Chen
Keyword(s):  
Supply Chain ◽  
Stackelberg Game ◽  
Good Combination ◽  
Green Supply Chain ◽  
Game Model ◽  
Mathematical Function ◽  
Pricing Strategies ◽  
Direct Channel ◽  
Retail Channel ◽  
Offline Channels

Due to the popularization of the concept of “new retailing”, we study a new commercial model named O2O (online-to-offline), which is a good combination model of a direct channel and a traditional retail channel. We analyze an O2O supply chain in which manufacturers are responsible for making green products and selling them through both online and offline channels. The retailer is responsible for all online and offline channels’ orders, and the manufacturer gives the retailer a fixed fee. We construct a mathematical function model and analyze the greenness and pricing strategies of centralized and decentralized settings through the retailer Stackelberg game model. Due to the effects of the double marginalization of supply chain members, we adopt a simple contract to coordinate the green supply chain. The paper’s contributions are that we obtain pricing and greening strategies by taking the cooperation of offline channels and online channels into consideration under the O2O green supply chain environment.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

scholarly journals Demand Subsidy versus Production Regulation: Development of New Energy Vehicles in a Competitive Environment

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1280
Author(s):  
Zixuan Wang ◽  
Xiuzhang Li
Keyword(s):  
Social Welfare ◽  
Stackelberg Game ◽  
Positive Impact ◽  
Consumer Preference ◽  
Social Planner ◽  
Environmental Preferences ◽  
The Social ◽  
New Energy ◽  
Vehicle Market ◽  
New Energy Vehicles

In the competitive market environment, the growth of new energy vehicles (NEVs) faces many obstacles. Demand subsidy or production regulation-related policies are widely used to promote the development of NEVs. A comparative analysis of the effects of the two types of policies on the competitive vehicle market requires further study. To fill this gap, we investigate which type of policy is more preferable from the perspective of the social planner. In this paper, we construct a Stackelberg game with a welfare-maximizing social planner and two profit-maximizing manufacturers producing NEVs and fuel vehicles (FVs), respectively. Interestingly, although both types of policies can increase the quantity of NEVs, demand subsidy also promotes the growth of total vehicles at the same time; in contrast, production regulation reduces the total vehicles. Moreover, compared with the benchmark that no policy intervention, demand subsidy generally improves social welfare, while production regulation improves social welfare only with high consumer preference for NEVs. Nevertheless, production regulation always has a positive impact on the environment, whereas demand subsidy may have a positive impact only when the NEV is very environment friendly. The numerical results show that consumer environmental preferences and the regulation of environmental impact determine which type of policy dominates the other.

scholarly journals Diversity Balancing for Two-Stage Collaborative Filtering in Recommender Systems

2020 ◽  
Vol 10 (4) ◽  
pp. 1257 ◽  
Author(s):  
Liang Zhang ◽  
Quanshen Wei ◽  
Lei Zhang ◽  
Baojiao Wang ◽  
Wen-Hsien Ho
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Social Relationships ◽  
Two Stage ◽  
Proposed Model ◽  
The Social ◽  
Item List ◽  
Ranking Strategy ◽  
High Prediction ◽  
Optimization Mechanism

Conventional recommender systems are designed to achieve high prediction accuracy by recommending items expected to be the most relevant and interesting to users. Therefore, they tend to recommend only the most popular items. Studies agree that diversity of recommendations is as important as accuracy because it improves the customer experience by reducing monotony. However, increasing diversity reduces accuracy. Thus, a recommendation algorithm is needed to recommend less popular items while maintaining acceptable accuracy. This work proposes a two-stage collaborative filtering optimization mechanism that obtains a complete and diversified item list. The first stage of the model incorporates multiple interests to optimize neighbor selection. In addition to using conventional collaborative filtering to predict ratings by exploiting available ratings, the proposed model further considers the social relationships of the user. A novel ranking strategy is then used to rearrange the list of top-N items while maintaining accuracy by (1) rearranging the area controlled by the threshold and by (2) maximizing popularity while maintaining an acceptable reduction in accuracy. An extensive experimental evaluation performed in a real-world dataset confirmed that, for a given loss of accuracy, the proposed model achieves higher diversity compared to conventional approaches.

scholarly journals Shared Partisanship, Household Norms and Turnout: Testing a Relational Theory of Electoral Participation

2016 ◽  
Vol 48 (3) ◽  
pp. 807-823 ◽  
Author(s):  
Edward Fieldhouse ◽  
David Cutts
Keyword(s):  
Party Identification ◽  
Household Survey ◽  
Relational Theory ◽  
Civic Duty ◽  
Proposed Model ◽  
The Social ◽  
Empirical Tests ◽  
Partisan Identification ◽  
Consumption Benefits ◽  
The Individual

Previous research shows that the household context is a crucial source of influence on turnout. This article sets out a relational theory of voting in which turnout is dependent on the existence of relational selective consumption benefits. The study provides empirical tests of key elements of the proposed model using household survey data from Great Britain. First, building on expressive theories of voting, it examines the extent to which shared partisan identification enhances turnout. Secondly, extending theories of voting as a social norm, it tests whether the civic norms of citizens’ families or households affect turnout over and above the social norms of the individual. In accordance with expectations of expressive theories of voting, it finds that having a shared party identification with other members of the household increases turnout. It also finds that the civic duty of other household members is important in explaining turnout, even when allowing for respondent’s civic duty.

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