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- W2891546960 abstract "Determining price per room to be charged to customers is an important decision to be taken by hotel management. Hotels frequently change their room rates based on the demand of room, occupancy rate, seasonal pattern, and strategies undertaken by other hotels on pricing. We formulated four models to analyse how various influencing variables, such as hotel price, demand, yearly trend and monthly seasonality influence hotel revenue per available room (RevPar). To analyse a case, we used monthly accommodation statistics for Sweden taken for Swedish Agency for Economic and Regional Growth and Statistics from January 2008 to July 2017. We carried out data analysis using both multiple regression and Multivariate Adaptive Regression Splines (MARS) model and found that application of MARS can help establishing a nonlinear relationship of RevPar with other determining variables in a superior way. We also proposed the possibility of developing a better forecasting model using MARS." @default.
- W2891546960 created "2018-09-27" @default.
- W2891546960 creator A5050898158 @default.
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- W2891546960 date "2019-01-01" @default.
- W2891546960 modified "2023-09-27" @default.
- W2891546960 title "Determinants of revenue per available room: Influential roles of average daily rate, demand, seasonality and yearly trend" @default.
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- W2891546960 doi "https://doi.org/10.1016/j.ijhm.2018.09.001" @default.
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