Evaluating extraordinarily large requests in a revenue management network

More and more companies in various industry sectors run automated revenue management (RM) systems to control their sales processes. Customer requests are assumed to be relatively small and a single acceptance or rejection decision has a minimal impact in the total revenue. But how should a company deal with arbitrary large requests, which can have fundamental revenue and capacity impacts? This article proposes evaluation methods to derive the least acceptable prices for the buyer or seller in a network RM environment. Purely resource sale-type requests are extended to contracts, which include return options for unsold resources. We propose deterministic and stochastic models to evaluate both request types. In addition, different business and economical situations require different evaluation approaches. Therefore, we additionally derive risk-averse formulations to enable decision makers to compare expected profit with underlying risks. © 2013 Macmillan Publishers Ltd.