Forecasting uncertain hotel room demand

被引:71
作者
Rajopadhye, M [1 ]
Ben Ghalia, M
Wang, PP
Baker, T
Eister, CV
机构
[1] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
[2] Bass Hotels & Resorts, Atlanta, GA 30346 USA
关键词
D O I
10.1016/S0020-0255(00)00082-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Economic systems are characterized by uncertainty in their dynamics. This increasing uncertainty is likely to promote bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method, The problem is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of the hotel revenue management system, whose objective is to maximize revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Actual data from a hotel are used to illustrate the forecasting mechanism. (C) 2001 Published by Elsevier Science Inc.
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页码:1 / 11
页数:11
相关论文
共 13 条
[1]  
[Anonymous], 1976, TIME SERIES ANAL
[2]  
[Anonymous], 1976, DECISION SCI
[3]  
[Anonymous], 1976, FORECASTING TIME SER
[4]   Managing hotel reservations with uncertain arrivals [J].
Bitran, GR ;
Gilbert, SM .
OPERATIONS RESEARCH, 1996, 44 (01) :35-49
[5]   AN APPLICATION OF YIELD MANAGEMENT TO THE HOTEL INDUSTRY CONSIDERING MULTIPLE DAY STAYS [J].
BITRAN, GR ;
MONDSCHEIN, SV .
OPERATIONS RESEARCH, 1995, 43 (03) :427-443
[6]  
Chatfield C., 1980, ANAL TIME SERIES INT, V2nd
[7]  
Chatfield C., 1978, Journal of the Royal Statistical Society: Series C (Applied Statistics), V27, P264, DOI [DOI 10.2307/2347162, 10.2307/2347162]
[8]  
Cross R. G., 1997, Revenue Management
[9]  
Harvey A.C., 1989, Forecasting, Structural Time Series Models and the Kalman Filter
[10]  
Harvey AC, 1993, TIME SERIES MODELS