Forecasting for Hotel Revenue Management: Testing Aggregation Against Disaggregation

Larry R. Weatherford · Sheryl E. Kimes · Darren A. Scott

106 citations0/0 files storedCornell Hotel and Restaurant Administration Quarterly

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Forecasting Techniques and Applications Supply Chain and Inventory Management Consumer Market Behavior and Pricing

Abstract

[Excerpt] A successful yield-management strategy is predicated on effective control of customer demand. Businesses have two interrelated strategic levers with which to accomplish this, namely, pricing and duration of customer use. Prices can be fixed (one price for the same service for all customers for all times) or variable (different prices for different times or for different customer segments) and duration can be predictable or unpredictable.\nVariable pricing to control demand is conceptually a straightforward process. It can take the form of discount prices at off-peak hours for all customers (such as low weekday rates for movies) or it can be in the form of price discounts for certain classes of customers (such as senior discounts at restaurants).

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2013Forecasting Aggregate Demand: Analytical Comparison of Top-Down and Bottom-Up Approaches in a Multivariate Exponential Smoothing Framework 2019Big Data in Hotel Revenue Management: Exploring Cancellation Drivers to Gain Insights Into Booking Cancellation Behavior 2021Demand forecasting in supply chains: a review of aggregation and hierarchical approaches 2011Relationship or revenue: Potential management conflicts between customer relationship management and hotel revenue management 2007An integrated forecasting approach to hotel demand 2016Hotel daily occupancy forecasting with competitive sets: a recursive algorithm 2006Forecasting demand from heterogeneous customers 2023Application of machine learning to cluster hotel booking curves for hotel demand forecasting

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