Dynamic Pricing of Experience Goods in Markets with Demand Uncertainty

2016 ◽  
Author(s):  
Yu-Hung Chen ◽  
Baojun Jiang
Keyword(s):  
Dynamic Pricing ◽  
Demand Uncertainty ◽  
Experience Goods

scholarly journals Dynamic Pricing in a Multi-Period Newsvendor Under Stochastic Price-Dependent Demand

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 520 ◽  
Author(s):  
Mehran Ullah ◽  
Irfanullah Khan ◽  
Biswajit Sarkar
Keyword(s):  
Dynamic Pricing ◽  
Demand Uncertainty ◽  
New Technologies ◽  
Rapid Development ◽  
Life Cycles ◽  
Selling Price ◽  
Market Demand ◽  
Newsvendor Model ◽  
Pricing Policy ◽  
Dependent Demand

The faster growth of technology stipulates the rapid development of new products; with the spread of new technologies old ones are outdated and their market demand declines sharply. The combined impact of demand uncertainty and short life-cycles complicate ordering and pricing decision of retailers that leads to a decrease in the profit. This study deals with the joint inventory and dynamic pricing policy for such products considering stochastic price-dependent demand. The aim is to develop a discount policy that enables the retailer to order more at the start of the selling season thus increase the profit and market share of the retailer. A multi-period newsvendor model is developed under the distribution-free approach and the optimal stocking quantities, unit selling price, and the discount percentage are obtained. The results show that the proposed discount policy increases the expected profit of the system. Additionally, the stocking quantity and the unit selling price also increases in the proposed discount policy. The robustness of the proposed model is illustrated with numerical examples and sensitivity analysis. Managerial insights are given to extract significant insights for the newsvendor model with discount policy.

Dynamic Pricing of New Experience Goods

2006 ◽  
Vol 114 (4) ◽  
pp. 713-743 ◽  
Author(s):  
Dirk Bergemann ◽  
Juuso Välimäki
Keyword(s):  
Dynamic Pricing ◽  
Experience Goods

scholarly journals Dynamic pricing with finite price sets: a non-parametric approach

2021 ◽  
Author(s):  
Athanassios N. Avramidis ◽  
Arnoud V. den Boer
Keyword(s):  
Dynamic Pricing ◽  
Demand Uncertainty ◽  
Numerical Study ◽  
Dynamic Program ◽  
Unknown Parameters ◽  
Perishable Inventory ◽  
Price Optimization ◽  
Time Period ◽  
Dependent Parameter ◽  
Expected Revenue

AbstractWe study price optimization of perishable inventory over multiple, consecutive selling seasons in the presence of demand uncertainty. Each selling season consists of a finite number of discrete time periods, and demand per time period is Bernoulli distributed with price-dependent parameter. The set of feasible prices is finite, and the expected demand corresponding to each price is unknown to the seller, whose objective is to maximize cumulative expected revenue. We propose an algorithm that estimates the unknown parameters in a learning phase, and in each subsequent season applies a policy determined as the solution to a sample dynamic program, which modifies the underlying dynamic program by replacing the unknown parameters by the estimate. Revenue performance is measured by the regret: the expected revenue loss relative to the optimal attainable revenue under full information. For a given number of seasons n, we show that if the number of seasons allocated to learning is asymptotic to $$(n^2\log n)^{1/3}$$ ( n 2 log n ) 1 / 3 , then the regret is of the same order, uniformly over all unknown demand parameters. An extensive numerical study that compares our algorithm to six benchmarks adapted from the literature demonstrates the effectiveness of our approach.

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