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A new approach to modelling and forecasting monthly guest nights in hotels

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Standard

A new approach to modelling and forecasting monthly guest nights in hotels. / Brannas, Kurt; Hellstrom, Jorgen; Nordstrom, Jonas.

I: International Journal of Forecasting, Bind 18, Nr. 1, 01.2002, s. 19-30.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Brannas, K, Hellstrom, J & Nordstrom, J 2002, 'A new approach to modelling and forecasting monthly guest nights in hotels', International Journal of Forecasting, bind 18, nr. 1, s. 19-30. https://doi.org/10.1016/S0169-2070(01)00104-2

APA

Brannas, K., Hellstrom, J., & Nordstrom, J. (2002). A new approach to modelling and forecasting monthly guest nights in hotels. International Journal of Forecasting, 18(1), 19-30. https://doi.org/10.1016/S0169-2070(01)00104-2

Vancouver

Brannas K, Hellstrom J, Nordstrom J. A new approach to modelling and forecasting monthly guest nights in hotels. International Journal of Forecasting. 2002 jan;18(1):19-30. https://doi.org/10.1016/S0169-2070(01)00104-2

Author

Brannas, Kurt ; Hellstrom, Jorgen ; Nordstrom, Jonas. / A new approach to modelling and forecasting monthly guest nights in hotels. I: International Journal of Forecasting. 2002 ; Bind 18, Nr. 1. s. 19-30.

Bibtex

@article{5d8dc4e183b446dfa92c0da7ccdab8d8,
title = "A new approach to modelling and forecasting monthly guest nights in hotels",
abstract = "Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect mean check-in and the check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables are small.",
author = "Kurt Brannas and Jorgen Hellstrom and Jonas Nordstrom",
year = "2002",
month = "1",
doi = "10.1016/S0169-2070(01)00104-2",
language = "English",
volume = "18",
pages = "19--30",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier",
number = "1",

}

RIS

TY - JOUR

T1 - A new approach to modelling and forecasting monthly guest nights in hotels

AU - Brannas, Kurt

AU - Hellstrom, Jorgen

AU - Nordstrom, Jonas

PY - 2002/1

Y1 - 2002/1

N2 - Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect mean check-in and the check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables are small.

AB - Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect mean check-in and the check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables are small.

U2 - 10.1016/S0169-2070(01)00104-2

DO - 10.1016/S0169-2070(01)00104-2

M3 - Journal article

AN - SCOPUS:0036150482

VL - 18

SP - 19

EP - 30

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 1

ER -

ID: 235072701