Estimating Demand for Dynamic Pricing in Electronic Markets

Abstract

Economic theory suggests sellers can increase revenue through
dynamic pricing; selling identical goods or services
at different prices. However, such discrimination requires
knowledge of the maximum price that each consumer is willing
to pay; information that is often unavailable. Fortunately,
electronic markets offer a solution; generating vast
quantities of transaction data that, if used intelligently, enable
consumer behaviour to be modelled and predicted.
Using eBay as an exemplar market, we introduce a model for
dynamic pricing that uses a statistical method for deriving
the structure of demand from temporal bidding data. This
work is a tentative first step of a wider research program
to discover a practical methodology for automatically generating
dynamic pricing models for the provision of cloud
computing services; a pertinent problem with widespread
commercial and theoretical interest.