An accurate forecasting module is a key element of any revenue management system. This
module includes demand forecasting, which involves tasks of forecasting complex seasonal time
series. The challenge of producing accurate demand forecasts requires the application of suitable
forecasting methods to address that complexity. The aim of this paper is to evaluate a new innovation
state space modeling framework, based on innovations approach, developed for forecasting time
series with complex seasonal patterns. This modeling framework provides an alternative to existing
models of exponential smoothing, since it is capable of tackling seasonal complexities such a
multiple seasonal periods and high frequency seasonality.info:eu-repo/semantics/publishedVersio
