Dynamic pricing

About: Dynamic pricing is a research topic. Over the lifetime, 4144 publications have been published within this topic receiving 91390 citations. The topic is also known as: surge pricing & demand pricing.

Prices, Production and Inventories over the Automotive Model Year

Abstract: This paper studies the within-model-year pricing and production of new automobiles. Using new monthly data on U.S. transaction prices, we document that for the typical new vehicle, prices typically fall over the model year at a 9.2 percent annual rate. Concurrently, both sales and inventories are hump shaped. To explain these time series, we formulate a market equilibrium model for new automobiles in which inventory and pricing decisions are made simultaneously. On the demand side, we use micro-level data to estimate time-varying aggregate demand curves for each vehicle. On the supply side, we solve a dynamic programming model of an automaker that, while able to produce only one vintage of a product at a time, may accumulate inventories and consequently sell multiple vintages of the same product simultaneously. The profit maximizing pricing and production strategies under a build-to-stock inventory policy imply declining prices and hump-shaped sales and inventories of the magnitudes observed in the data. Further, roughly half of the price decline is driven by inventory control considerations, as opposed to decreasing demand.

A predictive empirical model for pricing and resource allocation decisions

Abstract: We present a semi-parametric model that describes pricing behaviors in a market environment, and we show how that model can be used to guide resource allocation and pricing decisions in an autonomous trading agent. We validate our model by presenting experimental results obtained in the Trading Agent Competition for Supply Chain Management.

A simulation of the impacts of dynamic price management for perishable foods on retailer performance in the presence of need-driven purchasing consumers

Abstract: Numerous studies have investigated dynamic pricing for perishable products. The models have been designed to determine an optimal pricing structure and improve retailer performance. Previous studies on pricing models for perishable products have considered various assumptions of consumer demand and purchasing behaviour from deterministic and stochastic price-dependent demands to myopic and strategic consumer purchasing behaviour. They have not, however, considered consumer demand in reaction to a situation where the display stock of a particular product has different qualities (such as shelf-life) and prices available at the same time. This is particularly applicable in the analysis of dynamic pricing models for perishable foods. In this paper, we investigate the impact of frequency of discount during a product’s selling period on retailer performance, by considering changes in consumer purchasing behaviour in response to the display stock of a particular food product having different remaining shelf-life and prices. On the basis of a literature review and data obtained from interviews with food retailers, a simulation study is performed to compare the performance of different pricing policies. The results demonstrate the benefits gained by adopting more dynamic price policies.

Dynamic congestion-based pricing of bandwidth and buffer

Abstract: We consider pricing of network resources in a reservation-based quality-of-service architecture. The pricing policy implements a distributed resource allocation to provide guaranteed bounds on packet loss and end-to-end delay for real-time applications. Distributed pricing roles are assigned to each user, each network node, and an arbitrager in between the user and the network. When delay constraints are not binding, we investigate two dynamic pricing algorithms using gradient projection and Newton's method to update prices, and prove their convergence. We analyze the performance of the dynamic pricing policies and show that the gradient algorithm using Newton's method converges more quickly and displays only a few small fluctuations. When delay constraints are binding, we investigate subgradient methods which can provide convergence to some range of the optimal allocation.