Correspondence: Jon A. Higbie, Revenue Analytics, 3100 Cumberland Blvd., Suite 1000, Atlanta, Georgia 30339, USA

¹is a Doctoral Candidate in Operations Research at the Georgia Institute of Technology and works as an Operations Research Consultant at Revenue Analytics. Before pursuing her doctoral degree, she worked as a Management Science Researcher in Korea Telecom and a Business Analyst in Northwest Airlines. She holds a B.S. degree in Engineering from Seoul National University and an M.S. in Engineering from the Massachusetts Institute of Technology.

²is an Assistant Professor of Civil and Environmental Engineering. Her research interests include travel behaviour modelling and development of advanced discrete choice models. She currently serves as the Chair of the Urban Transportation Special Interest Group of INFORMS and Co-chair of the AGIFORS Scheduling and Strategic Planning Group. Before joining the faculty, she worked for 5 years in the research and development revenue management group for United Airlines and for 1 year in customer science at Mercer Management Consulting.

³serves as Senior Vice President and Chief Scientist of Revenue Analytics. Before joining Revenue Analytics, he served as Chief Scientist for Revenue Management at JDA Software. He is a long-time member of INFORMS and the Revenue Management and Pricing section. He holds a B.A. in Physics from Wittenberg University and a PhD in Management Science from the University of Georgia.

⁴is an Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Before joining the faculty at Georgia Tech, she worked at IBM T.J. Watson Research Center. She received an NSF Career Award in 2001 and the Daniel H. Wagner Prize for Operations Research Practice in 1998.

⁵serves as Manager of Revenue Management Modeling in IHG. Before joining IHG, he served as a Scientist for Revenue Management at PROS Revenue Management. He holds a Bachelors degree in Mechanical Engineering from College of Engineering, Guindy, Madras, and a Masters degree in Industrial and Systems Engineering from the University of Florida.

Received 13 January 2009; Revised 13 January 2009; Published online 27 March 2009.

Abstract

This study uses booking data from 28 US hotels to investigate the validity of two key assumptions in hotel revenue management: (1) customers who book later are willing to pay higher rates than customers who book earlier; and (2) demand is stronger during the week than on the weekend. Empirical results based on an analysis of booking curves, average paid rates and occupancy rates for group, restricted retail, unrestricted retail and negotiated demand segments challenge the validity of these assumptions. Based on these findings, new recommendations for segmenting transient demand and setting weekday versus weekend pricing are provided.