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.

Dynamic pricing of airline tickets with competition

Abstract: Competition has a huge influence on customer buying behaviour and will impact on the optimal price that companies should charge for goods or services. To date, many dynamic pricing models have not modelled competition explicitly. In this paper, we introduce pricing strategies that maximize revenue when selling an inventory of identical items by a fixed time and where there is a competing seller. The model used incorporates a probabilistic formulation of customer demand, which is influenced by the prices offered by the company and the competitor, and the time remaining until the end of the selling period. Calculus of variations is used to solve the problem and simple conditions are given that ensure the uniqueness of a solution. Illustrative examples are included. A practical implementation that uses dynamic updating is proposed and tested using simulated data, showing the effectiveness of the method.

Exogenous Learning, Seller-Induced Learning, and Marketing of Durable Goods

Abstract: When learning of product characteristics takes some time, a firm introducing a new durable faces the trade-off between releasing early to an uninformed market and deferring release to a better-informed market. In a two-period monopoly, we examine the strategic interaction between exogenous learning (EL) and seller-induced learning (SIL) and the firm's product release and pricing strategies. The familiar, direct effect of strong learning is to facilitate a higher price for informed customers. We point out its indirect effect of inducing a higher period 1 price for uninformed customers (by lowering their expected utility from learning). These two effects underlie three major results. First, a strong learning intensity does not always imply deferred release. Surprisingly, for medium unit costs, the firm releases late (early) when learning intensity is weak (strong). Second, SIL facilitates different product release strategies, depending on the unit cost level. Potential SIL investment facilitates early release for low or medium unit costs, but may facilitate deferred release for high unit costs. Lastly, when customers have heterogeneous prior valuation, the high-end customers may buy early at a lower price and the low-end customers may buy later at a higher price, contrary to the usual skim pricing with informed customers. This paper was accepted by Preyas Desai, marketing.

Smart Pricing: Linking Pricing Decisions with Operational Insights

Abstract: textThe past decade has seen a virtual explosion of information about customers and their preferences This information potentially allows companies to increase their revenues, in particular since modern technology enables price changes to be effected at minimal cost At the same time, companies have taken major strides in understanding and managing the dynamics of the supply chain, both their internal operations and their relationships with supply chain partners These two developments are narrowly intertwined Pricing decisions have a direct effect on operations and visa versa Yet, the systematic integration of operational and marketing insights is in an emerging stage, both in academia and in business practice This article reviews a number of key linkages between pricing and operations In particular, it highlights different drivers for dynamic pricing strategies Through the discussion of key references and related software developments we aim to provide a snapshot into a rich and evolving field