Abstract

Revenue management (RM) principles can apply to casino table games just as they do many other service industry operations. Creating a sound and feasible RM model for casinos relies foremost on the ability to create a demand forecast that accounts for the intermittent demand patterns of casino table games. Using a modified Croston’s approach to forecast demand, this article proposes a revenue optimization model to help managers determine how many tables to open and what limits to set. Empirical tests of historical data for hourly demand at blackjack tables in a casino in Ontario, Canada, show that the theoretical win amounts derived using RM applications exceeded the theoretical win actually recorded by the casino. By recording players’ betting patterns and speed of play, the casino industry should be able to use this model to improve on the current practice of opening and closing tables according to intuition and historic demand patterns. With the data in hand, casinos should be able to implement the model without substantial difficulty.

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