Paper Details: Downloads: 465
Serial Number: P1120806022
Title: A Comparative Study of the Pickup Method and its Variations Using a Simulated Hotel Reservation Data
Authors: Athanasius Zakhary and Neamat El Gayar and Amir F. Atiya
Abstract: Detailed forecasts are major inputs to modern Hotel Revenue Management Systems. Accurate forecasts are crucial to improve rate and availability recommendations for rooms. The data used for hotel demand forecasting are based on current booking activities (Reservations), historical information regarding daily arrivals or rooms sold. Bookings are recent data that if used adequately can make the forecasting process more responsive to demand shifts. Very little work has been done on forecasting techniques using reservation data. In this paper, we examine in more details a popular forecasting model that uses reservation data, referred to in the literature as the ?pickup? method. In particular, we present a new framework for the pickup technique with 8 different variations and compare the results of these variations using a variety of simulated hotel reservations data.
Keywords: Pickup, Reservation-based Forecasting.
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 8
Issue: SI1
Submission Date: 12/1/2007 12:00:00 AM
Review Date: 1/1/2008 12:00:00 AM
Publishing Date: 2/1/2008 12:00:00 AM
Article Downloads: 465
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