Hotel daily occupancy forecasting with competitive sets: a recursive algorithm

Purpose – This paper aims to improve the accuracy of hotel daily occupancy forecasts – an essential element in the revenue management cycle – by proposing and testing a novel approach. The authors add the hotel competitive-set’s predicted occupancy as an input of the individual property forecast and, using a recursive approach, demonstrate that there is a potential for significant reduction in the forecasting error. Design/methodology/approach – The paper outlines the theoretical justification and the mechanism for this new approach. It applies a simulation for exploring the potential to improve the accuracy of the hotel’s daily occupancy forecasts, as well as analysis of data from a field study of two hotel clusters’ daily forecasts to provide empirical support to the procedure’s viability. Findings – The results provide strong support to the notion that the accuracy could be enhanced. Incorporating the competitive set prediction by using either a genetic algorithm or the simple linear regression model i...

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