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Sunmee Choi, S. Kimes (2002)
Electronic Distribution Channels’ Effect on Hotel Revenue ManagementCornell Hotel and Restaurant Administration Quarterly, 43
W. Lieberman (2005)
The Theory and Practice of Revenue ManagementJournal of Revenue and Pricing Management, 3
S. Kimes (2005)
Restaurant revenue management: Could it work?Journal of Revenue and Pricing Management, 4
M. Ghalia, Paul Wang (2000)
Intelligent system to support judgmental business forecasting: the case of estimating hotel room demandIEEE Trans. Fuzzy Syst., 8
(2000)
Mid-rate extended-stay provides best return
Zheng Gu (2006)
Product differentiation: Key to Macau's gaming revenue growthJournal of Revenue and Pricing Management, 4
William Cooper, Tito Homem-de-Mello, A. Kleywegt (2006)
Models of the Spiral-Down Effect in Revenue ManagementOper. Res., 54
A. Kuyumcu (2002)
Gaming twist in hotel revenue managementJournal of Revenue and Pricing Management, 1
Tim Baker, D. Collier (2009)
THE BENEFITS OF OPTIMIZING PRICES TO MANAGE DEMAND IN HOTEL REVENUE MANAGEMENT SYSTEMSProduction and Operations Management, 12
Do you really know who your customers are?
L. Garrow, Mark Ferguson, P. Keskinocak, J. Swann (2006)
Expert opinions: Current pricing and revenue management practice across U.S. industriesJournal of Revenue and Pricing Management, 5
W. Lieberman, Tamara Dieck (2002)
Expanding the revenue management frontier: Optimal air planning in the cruise industryJournal of Revenue and Pricing Management, 1
B. Havel, G. Sánchez (2010)
International Air Transport Association
W. Carroll, R. Grimes (1995)
Evolutionary Change in Product Management: Experiences in the Car Rental IndustryInterfaces, 25
A. Heching, G. Gallego, G. Ryzin (2002)
Mark-down pricing: An empirical analysis of policies and revenue potential at one apparel retailerJournal of Revenue and Pricing Management, 1
Sage enters waterpark niche
L. Garrow, Mark Ferguson (2008)
Revenue management and the analytics explosion: Perspectives from industry expertsJournal of Revenue and Pricing Management, 7
P. Belobaba (1989)
OR Practice - Application of a Probabilistic Decision Model to Airline Seat Inventory ControlOper. Res., 37
(2008)
Monthly Traffic Analysis , January 2008
Randell Smith, J. Lesure (1999)
The U.S. lodging industry TodayCornell Hotel and Restaurant Administration Quarterly, 40
D. Jeffrey, R. Barden, P. Buckley, N. Hubbard (2002)
What Makes for a Successful Hotel? Insights on Hotel Management Following 15 Years of Hotel Occupancy Analysis in EnglandThe Service Industries Journal, 22
S. Kimes, L. Schruben (2002)
Golf course revenue management: A study of tee time intervalsJournal of Revenue and Pricing Management, 1
D. Jeffrey, R. Barden (2000)
Monitoring hotel performance using occupancy time-series analysis: the concept of occupancy performance space.International Journal of Tourism Research, 2
Z. Schwartz (2000)
Changes in Hotel Guests’ Willingness to Pay as the Date of Stay Draws CloserJournal of Hospitality & Tourism Research, 24
(2007)
2007 ’ s Hot spots for operations
Mark Hawtin (2003)
The practicalities and benefits of applying revenue management to grocery retailing, and the need for effective business rule managementJournal of Revenue and Pricing Management, 2
HR Varian (1992)
Microeconomic Analysis
Hotels upgrade offerings to boost foodservice sales. Nation's Restaurant News
Brent Lippman (2003)
Retail revenue management — Competitive strategy for grocery retailersJournal of Revenue and Pricing Management, 2
B. Vinod (2004)
Unlocking the value of revenue management in the hotel industryJournal of Revenue and Pricing Management, 3
S. Kimes, Jochen Wirtz, B. Noone (2002)
How long should dinner take? Measuring expected meal duration for restaurant revenue managementJournal of Revenue and Pricing Management, 1
(1992)
Microeconomic Analysis, 3rd edn
PP Belobaba (1989)
Application of a probabilistic decision model to airline seat inventory controlOperations Research, 37
Alberto Abadie (2002)
Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable ModelsJournal of the American Statistical Association, 97
Jens Alstrup, S. Boas, O. Madsen, R. Vidal (1986)
Booking policy for flights with two types of passengersEuropean Journal of Operational Research, 27
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.
Journal of Revenue and Pricing Management – Springer Journals
Published: Mar 27, 2009
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