Security Service Pricing Model for UAV Swarms: A Stackelberg Game Approach

2021 ◽  
Author(s):  
Gaurang Bansal ◽  
Biplab Sikdar
Keyword(s):  
Stackelberg Game ◽  
Pricing Model ◽  
Security Service ◽  
Service Pricing

scholarly journals PV value-added service pricing model of stand-alone Stackelberg game

2019 ◽  
Vol 592 ◽  
pp. 012161
Author(s):  
Wenfeng Li ◽  
Hongkun Bai ◽  
Yuanpeng Hua ◽  
Feifei Bu ◽  
Ding Han ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Value Added ◽  
Pricing Model ◽  
Service Pricing ◽  
Value Added Service

scholarly journals Pricing Decisions of Two Complementary Products in a Fuzzy Environment

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Li Wang ◽  
Jing Zhao ◽  
Jie Wei
Keyword(s):  
Closed Form ◽  
Stackelberg Game ◽  
Reference Model ◽  
Optimal Pricing ◽  
Pricing Model ◽  
Complementary Products ◽  
Nash Game ◽  
Retail Pricing ◽  
Pricing Decisions ◽  
Fuzzy Environment

Pricing decisions of two complementary products in a fuzzy environment are considered in this paper. The purpose of this paper is to analyze the changes of the optimal retail pricing of two complementary products under two different decentralized decision scenarios (e.g., Nash game case and Stackelberg game case). As a reference model, the centralized pricing model is also established. The closed-form optimal pricing decisions of the two complementary products are obtained in the above three decision scenarios. Some interesting management insights into how pricing decisions vary with decision scenarios are given.

An enhanced network service pricing model considering network externalities

2007 ◽  
Vol 6 (1) ◽  
pp. 5-24
Author(s):  
Valbona Barolli ◽  
Heihachiro Fukuda ◽  
Leonard Barolli ◽  
Makoto Takizawa
Keyword(s):  
Network Externalities ◽  
Pricing Model ◽  
Network Service ◽  
Service Pricing

scholarly journals A Negotiation Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

2020 ◽  
Author(s):  
Yan Zhou ◽  
Yue Li ◽  
Yunxing Zhang
Keyword(s):  
Genetic Algorithm ◽  
Learning Strategy ◽  
Negotiation Process ◽  
Final Decision ◽  
Pricing Model ◽  
Multiobjective Genetic Algorithm ◽  
Multiobjective Problem ◽  
Service Pricing ◽  
Pricing Process ◽  
Service Efficiency

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

The Influence of Third-party E-Commerce Platform Price Limits on the Dual-Channel Strategy of Manufacturers

2019 ◽  
Vol 7 (2) ◽  
pp. 173-186
Author(s):  
Cong Wang ◽  
Huifang Yang ◽  
Deli Yang
Keyword(s):  
Stackelberg Game ◽  
Third Party ◽  
Pricing Model ◽  
Price Limits ◽  
Pricing Models ◽  
Partial Loss ◽  
The Third ◽  
Dual Channel ◽  
Channel Strategy ◽  
And Performance

Abstract Powerful platform operators always set price limits for sellers on the platform. This paper establishes Stackelberg game models according to two pricing models when the manufacturer enters the third-party e-commerce platform and sells products online. The first is a seller-pricing model in which the manufacturer decides the online price. The second is a platform-pricing model in which the platform decides the online price. We obtain the equilibrium results for these two models and the condition that allows the manufacturer to adopt the dual-channel strategy by comparing the operation decisions and performance of supply-chain members in the two models. Results show that the dual-channel strategy of the manufacturer always decreases the profit of the traditional retailer. In comparison with the seller-pricing model, the platform-pricing model always erodes parts of the manufacturers profit obtained by the dual-channel strategy. The manufacturer will pass on the partial loss to the retailer using relative leadership in the platform-pricing model, which renders the profit of the retailer lower than that in the seller-pricing model. Also, price limits do not always bring the platform more profits; sometimes the platform is forced to set a low price.

Cooperative Pricing of Apparel Supply Chain Based on API

2011 ◽  
Vol 58-60 ◽  
pp. 28-35
Author(s):  
Ge Fu Zhang ◽  
Dong Hui Wang
Keyword(s):  
Supply Chain ◽  
Optimization Model ◽  
Stackelberg Game ◽  
Research Result ◽  
Response Strategy ◽  
Quick Response ◽  
Pricing Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Excess Profit

The purpose of this paper is to construct a multi-objective optimization model for cooperative pricing in the management of apparel supply chain. Firstly, by using Apparel Popularity Index (API) model, a kind of pricing model for supply chain has been built. Then, by introducing cooperation and other constraint conditions, a kind of cooperative pricing model was constructed. This model is a kind of Stackelberg game. The manufacturer and the retailer obtained their excess profits through the game. Lastly, this paper gave a numerical example which demonstrated that the excess profit of the cooperative supply chain was constant, and when the constraint conditions changed, the excess profit space would change at the meantime. This research result can help partners on apparel supply chain to practice Quick Response strategy.

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.

Effective Power Allocation with Uniform Pricing Model Based on Game Theory in Nano-Computing Environment of Cognitive Radio Network

2017 ◽  
Vol 14 (1) ◽  
pp. 291-298 ◽  
Author(s):  
Shyamala Bharathi ◽  
Dhananjay Kumar
Keyword(s):  
Game Theory ◽  
Resource Allocation ◽  
Nash Equilibrium ◽  
Power Allocation ◽  
Cognitive Radio Network ◽  
Stackelberg Game ◽  
Radio Network ◽  
Pricing Model ◽  
Computing Environment ◽  
Uniform Pricing

Efficient resource allocation in cognitive radio network (CRN) remains a challenge due to dynamic nature of available spectrum in working band and implementation in nano-computing environment. Adoption of game theory in power allocation based on pricing model requires the formulation of strategy of the players as profit/loss function which may lead to Nash equilibrium. Earlier research focuses on the impact of game models such as Cournot, and Bertrand in formulating the utility function under the constraint power and service quality. In Cournot and Bertrand game the users play simultaneously that may not be acquainted with the other user’s action. It suits for common regimes such as all user are to be unlicensed (SU) and they may simultaneously try to access a set of available channels. In this paper, we formulate the condition for optimal power allocation in CRN using Stackelberg game where the previous user decides its output and then the erstwhile user does so, knowing the output characteristics by the former user. Based on the profit of PU (as a leader) and SU (as a follower), the optimized solution is formulated for power and interference price and it is modelled as a convex function of transmission power achieved by Nash equilibrium which involves backward induction. By means of a uniform pricing scheme every PU aims to maximize its profit under channel data rate and interference power constraint. The proposed Resource Allocation using Stackelberg Game (RASG) algorithm tries to optimize uniform pricing and power allocation among SUs such that maximizing throughput and fairness. The simulation results show a significant enhancement in throughput and fairness compared to power optimization based on Bertrand and Cournot game theory.

scholarly journals Subsidy and Pricing Model of Electric Vehicle Sharing Based on Two-Stage Stackelberg Game – A Case Study in China

2019 ◽  
Vol 9 (8) ◽  
pp. 1631 ◽  
Author(s):  
Jun Yang ◽  
Yangjia Lin ◽  
Fuzhang Wu ◽  
Lei Chen
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Stackelberg Game ◽  
Operation Mode ◽  
Pricing Strategies ◽  
Pricing Model ◽  
Key Factors ◽  
Car Sharing ◽  
Two Stage ◽  
The Government

Electric vehicle sharing provides an effective way to improve the traffic situation and relieve environmental pressure. The government subsidy policy and the car-sharing operator’s pricing strategy are the key factors that affect the large-scale application of electric vehicle sharing. To address this issue, a subsidy and pricing model for electric vehicle sharing based on the two-stage Stackelberg game is proposed in this paper according to the current situation in China. First, an electric vehicle sharing operation mode under government participation is constructed. Then, a two-stage Stackelberg game model involving the government, the car-sharing operator and the consumers is proposed to determine the subsidy rates and pricing strategies. The improved particle swarm optimization algorithm is used to obtain the Nash equilibrium of the model. Also, the influence of private car cost and shared travel comfort on subsidy rates and pricing strategies is analyzed. Finally, the simulation of electric vehicle sharing in a town of China is carried out to investigate the performance of the proposed subsidy and price model. The simulation results show that the model rationally formulates subsidy policies and pricing strategies of the electric vehicle sharing to balance the interests of the three participants, mobilizing users’ enthusiasm while guaranteeing the benefits of the government and operator, making the overall benefit optimal.

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