scholarly journals Dynamic Pricing Based on Strategic Consumers and Substitutes in a Duopoly Setting

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Gongbing Bi ◽  
Lechi Li ◽  
Feng Yang ◽  
Liang Liang
Keyword(s):  
Decision Making ◽  
Nash Equilibrium ◽  
Product Differentiation ◽  
Dynamic Pricing ◽  
Dynamic Game ◽  
Solution Concept ◽  
Expected Value ◽  
Decision Making Process ◽  
Pricing Model ◽  
Strategic Consumers

Based on the rational strategic consumers, we construct a dynamic game to build a two-period dynamic pricing model for two brands of substitutes which are sold by duopoly. The solution concept of the dynamic game is Nash equilibrium. In our model, consumers have been clearly segmented into several consumption classes, according to their expected value of the products. The two competing firms enter a pricing game and finally reach the state of Nash equilibrium. In addition, decision-making process with only myopic consumers existing in the market is analyzed. To make the paper more practical and realistic, the condition, in which the myopic and strategic consumers both exist in the market, is also considered and studied. In order to help the readers understand better and make it intuitively more clearly, a numerical example is given to describe the influence of the main parameters to the optimal prices. The result indicates that, to maintain the firms’ respective optimal profits, the prices of the products should be adjusted appropriately with the changes of product differentiation coefficient.

scholarly journals Dynamic Nonlinear Pricing Model Based on Adaptive and Sophisticated Learning

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Wenjie Bi ◽  
Yinghui Sun ◽  
Haiying Liu ◽  
Xiaohong Chen
Keyword(s):  
Adaptive Learning ◽  
Dynamic Pricing ◽  
Dynamic Game ◽  
Nonlinear Pricing ◽  
Decision Problems ◽  
Purchase Behavior ◽  
Pricing Model ◽  
Model Based ◽  
Dynamic Game Model ◽  
Steady State Solutions

Existing dynamic pricing models which take consumers’ learning behavior into account generally assume that consumers learn on the basis of reinforcement learning and belief-based learning. Nevertheless, abundant empirical evidence of behavior game indicates that consumers’ learning is normally described as a process of mixed learning. Particularly, for experience goods, a consumer’s purchase decision is not only based on his previous purchase behavior (adaptive learning), but also affected by that of other consumers (sophisticated learning). With the assumption that consumers are both adaptive and sophisticated learners, we study a dynamic pricing model dealing with repeated decision problems in a duopoly market. Specifically, we build a dynamic game model based on sophisticated experience-weighted attraction learning model (SEWA) and analyze the existence of the equilibrium. Finally, we show the characteristics and differences of the steady-state solutions between models considering adaptive consumers and models considering sophistical consumers by numerical results.

scholarly journals Business Analytics using Dynamic Pricing based on Customer Entry-Exit Rates Tradeoff

2020 ◽  
Vol 8 (1) ◽  
pp. 272-280
Author(s):  
Hamed Fazlollahtabar ◽  
Minoo Talebi Ashoori
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Business Intelligence ◽  
Dynamic Pricing ◽  
Market Analysis ◽  
Business Analytics ◽  
Pricing Model ◽  
Decision Optimization ◽  
Sensitive Parameters

This paper concerns with an integrated business process to be applied as a decision support for market analysis and decision making. The proposed business intelligence and analytics system makes use of an extract, transform and load mechanism for data collection and purification. As a mathematical decision optimization, dynamic pricing is formulated based on customer entry-exit rates in a history-based pricing model. The optimal prices for products are obtained so that aggregated profit is maximized. A case study is reported to show the effectiveness of the approach. Also, analytical investigations on the impacts of the sensitive parameters of the pricing model are given.

Study on Multiobjective Programming Problem under Bifuzzy Environment

2011 ◽  
Vol 204-210 ◽  
pp. 502-507
Author(s):  
Ming Fa Zheng ◽  
Bing Jie Li ◽  
Guang Xing Kou
Keyword(s):  
Decision Making ◽  
Programming Problem ◽  
Solution Method ◽  
Multiobjective Programming ◽  
Expected Value ◽  
Decision Making Process ◽  
Multiobjective Problem ◽  
Expected Value Model ◽  
Multiobjective Programming Problem ◽  
Value Model

In this paper, based on bifuzzy theory, we have studied the multiobjective programming problem under bifuzzy environment, and presented the expected-value model which is a deterministic multiobjective problem. To the expected value model, the concepts of non-inferior solution are defined, and their relations are also discussed. According to practical decision-making process, a solution method, called the method of main objective function, has been studied, whose results can facilitate us to design algorithms to solve the bifuzzy multiobjective programming problem.

Data Analysis for Dynamic Pricing in Airline

2014 ◽  
Vol 16 (1) ◽  
pp. 14-22
Author(s):  
Rahul Bhaskar
Keyword(s):  
Decision Making ◽  
Airline Industry ◽  
Dynamic Pricing ◽  
Pricing Strategy ◽  
External Information ◽  
Decision Making Process ◽  
Short Term ◽  
Ticket Pricing ◽  
Airline Company

The competitors in the airline industry often rely on pricing strategy to capture more sales as a main mean of competition. Thus, dynamic pricing is often utilized to maximize profit while allowing better pricing against competition at the same time. In order for dynamic pricing to be effective, airline company has to take in consideration both internal and external information. Tactical pricing is an important component for airline, for it provides both short term and long term strategies to ticket pricing. The case is an exemplification of how tactical pricing plays an important role in the decision making process of an airline company.

scholarly journals Simulation model of pedestrian flow based on multi-agent system and Bayesian Nash equilibrium

2021 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Yiyu Wang ◽  
Jiaqi Ge ◽  
Alexis Comber
Keyword(s):  
Decision Making ◽  
Nash Equilibrium ◽  
Simulation Model ◽  
Decision Making Process ◽  
Multi Agent System ◽  
Pedestrian Flow ◽  
Time Step ◽  
Agent System ◽  
Bayesian Nash Equilibrium ◽  
Multi Agent

Abstract. Computer-based simulation is a means of exploring complex systems and has become the mainstream method of pedestrian research. In this research, a multi-agent simulation model of pedestrian flow will be established using a multi-agent system (MAS) and Bayesian Nash equilibrium. MAS is used to simulate the crowd movement and the interaction between pedestrians, and Bayesian Nash equilibrium is adopted to analyze the decision-making process of pedestrians. In contrast to previous pedestrian flow simulation modeling methods, this study adopts multi-agent modeling to realize the complete heterogeneity of pedestrians, so as to achieve more accurate simulation and make the research conclusions closer to reality. To be specific, we attempt to determine the cell side length and simulation time step of an initial model parameterized using a dataset of actual pedestrian movements. It allows more than one pedestrian to be in the same cell and stipulates that the utility of pedestrians decreases with the growing number of pedestrians in the cell. The Bayesian Nash equilibrium is applied to analyze the decision-making process of pedestrians and collision avoidance rules and interaction rules of agents are also formulated. A number of areas of further research are discussed.

scholarly journals Dynamic Pricing for Airline Revenue Management under Passenger Mental Accounting

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yusheng Hu ◽  
Jinlin Li ◽  
Lun Ran
Keyword(s):  
Decision Making ◽  
Dynamic Pricing ◽  
Mental Accounting ◽  
Dynamic Programming Method ◽  
Optimal Pricing ◽  
Decision Making Process ◽  
Pricing Strategies ◽  
Human Decision ◽  
Pricing Problems ◽  
Positive Effect

Mental accounting is a far-reaching concept, which is often used to explain various kinds of irrational behaviors in human decision making process. This paper investigates dynamic pricing problems for single-flight and multiple flights settings, respectively, where passengers may be affected by mental accounting. We analyze dynamic pricing problems by means of the dynamic programming method and obtain the optimal pricing strategies. Further, we analytically show that the passenger mental accounting depth has a positive effect on the flight’s expected revenue for the single flight and numerically illustrate that the passenger mental accounting depth has a positive effect on the optimal prices for the multiple flights.

Decisions of Green Supply Chain under Fairness Concerns and Different Power Structures

2018 ◽  
Vol 14 (4) ◽  
pp. 28-53 ◽  
Author(s):  
Guangdong Liu ◽  
Tianjian Yang ◽  
Yao Wei ◽  
Xuemei Zhang
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Nash Equilibrium ◽  
Wholesale Price ◽  
Dynamic Game ◽  
Retail Price ◽  
Green Supply Chain ◽  
Power Structures ◽  
Fairness Concerns ◽  
Dynamic Game Model

This article constructs a two-stage dynamic game model for green manufacturers, retailers, and consumers to address the issue that fairness preference in manufacturing can impact supply chain decision-making. This is done by discussing decision-making under the three power structures of green-manufacturer-dominated, retailer-dominated, and the Nash-equilibrium, and compares the balanced decision under the three power structures. The results show that in the manufacturer-dominated and Nash equilibrium games, product greenness, retailer profits, manufacturer profits, total supply chain profits, and a manufacturer's utility all decrease as the fairness preference increases, whereas the retail price and wholesale price are just the opposite of each other. In the retailer-dominated game, the retail price, product greenness, and total supply chain profits are not impacted by the fairness preference. The wholesale price, manufacturer's profits, and manufacturer's utility increases as the fairness preference increases, whereas the retailer profits decrease.

scholarly journals The Achilles tendon of dynamic pricing –– the effect of consumers' fairness preferences on platform's dynamic pricing strategies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yong Wang ◽  
Tianze Tang ◽  
Weiyi Zhang ◽  
Zhen Sun ◽  
Qiaoqin Xiong
Keyword(s):  
Decision Making ◽  
Dynamic Pricing ◽  
Design Methodology ◽  
Repeated Game ◽  
Decision Making Process ◽  
Pricing Strategies ◽  
Content Type ◽  
Fair Game ◽  
Game Dynamic ◽  
Repeated Game Theory

PurposeIn this paper, the authors study the effect of consumers' fairness preferences on dynamic pricing strategies adopted by platforms in a non-cooperative game.Design/methodology/approachThis study applies fair game and repeated game theory.FindingsThis study reveals that, in a one-shot game, if consumers have fairness preferences, dynamic prices will slightly decline. In a repeated game, dynamic prices will be reduced even when consumers do not have fairness preferences. When fairness preferences and repeated game are considered simultaneously, dynamic prices are most likely to be set at fair prices. The authors also discuss the effect of platforms' discounting factors, the consumers' income and alternative choices of consumption on the dynamic prices.Research limitations/implicationsThe study findings illustrate the importance of incorporating behavioral elements in understanding and designing the dynamic pricing strategies for platforms and the implications on social welfare in general.Originality/valueThe authors developed a theoretical model to incorporate consumers' fairness preference into the decision-making process of platforms when they design the dynamic pricing strategies.

scholarly journals Ex Post Nash Equilibrium in Games for Decision Making in Multi-environments

2018 ◽  
Author(s):  
Abbas Edalat ◽  
Samira Hossein Ghorban ◽  
Ali Ghoroghi
Keyword(s):  
Decision Making ◽  
Nash Equilibrium ◽  
Finite Number ◽  
Convex Combination ◽  
Solution Concept ◽  
Trust Game ◽  
Type Space ◽  
Pure Type ◽  
Ex Post ◽  
Basic Game

We employ the solution concept of ex post Nash equilibrium to predict the interaction of a finite number of agents competing in a finite number of basic games simultaneously. The competition is called a multi-game. For each agent, a specific weight, considered as private information, is allocated to each basic game representing its investment in that game and the utility of each agent for any strategy profile is the weighted sum, i.e., convex combination, of its utilities in the basic games. Multi-games can model decision making in multi-environments in a variety of circumstances, including decision making in multi-markets and decision making when there are both material and social utilities for agents as, we propose, in the Prisoner's Dilemma and the Trust Game. Given a set of pure Nash equilibria, one for each basic game in a multi-game, we construct a pure Bayesian Nash equilibrium for the multi-game. We then focus on the class of so-called uniform multi-games in which each agent is constrained to play in all games the same strategy from an action set consisting of a best response per game. Uniform multi-games are equivalent to multi-dimensional Bayesian games where the type of each agent is a finite dimensional vector with non-negative components. A notion of pure type-regularity for uniform multi-games is developed and it is shown that a multi-game that is pure type-regular on the boundary of its type space has a pure ex post Nash equilibrium which is computed in constant time with respect to the number of the types and is independent of prior probability distributions. We then develop an algorithm, linear in the number of types of the agents, which tests if a multi-game is pure type-regular on the boundary of its type space in which case it returns a pure ex post Nash equilibrium for the multi-game.

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