Estimating Demand for Dynamic Pricing in Electronic Markets

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.