New Revenue Management Model Uses Minimal Demand Information
Airlines want to sell their seats to the right customers at the right time for the right price. The more fare classes or products they have, the more difficult it is to optimize the revenue for each product. That is, airlines have turned to complex mathematical models for revenue management. Hotels, cruise lines and car rental companies all useo forecast demand for their product into the future. Unfortunately, forecasting is notoriously difficult and demand estimates are inaccurate. Side-stepping the problem of demand forecasting can provide a robust solution to these difficulties, according to research at Smith by Michael Ball, Orkand Corporation Professor of Management Science, and Itir Karaesmen, assistant professor of management science, with doctoral students Yingjie Lan and Huina Gao, who have developed models that use minimal demand information for revenue management.