Forecasting U.K. Inbound Expenditure by Different Purposes of Visit

Cang, Shuang and Hemmington, Nigel (2010) Forecasting U.K. Inbound Expenditure by Different Purposes of Visit. Journal of Hospitality & Tourism Research, 34 (3). pp. 294-309. ISSN 1096-3480

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1177/1096348009350616

Abstract

Accurately forecasting U.K. inbound expenditure by purpose of visit plays an important role in tourism planning and policy making. Forecasting U.K. inbound expenditure at the disaggregated level is studied in this article. Disaggregating is done on the basis of purpose of visit: holiday, business, study, visit friends or relatives (VFR), and miscellaneous. The most robust two time series forecasting models, seasonal autoregressive integrated moving average (ARIMA) and Winters's multiplicative exponential smoothing (WMES), are applied in this article. The Naïve 2 forecasting model is used as a benchmark to compare with the ARIMA and WMES models. The outcomes of the forecasting results show that the ARIMA model outperforms the WMES model, but it is not statistically superior to the WMES model. The ARIMA and WMES models are both statistically superior to the Naïve 2 model for this U.K. inbound expenditure data set. The ARIMA model forecasts a higher increasing trend for expenditure than the WMES model for the business purpose, whereas the WMES model forecasts a higher increasing trend for expenditure than the ARIMA model for miscellaneous purpose. It is recommended that combining the values from the ARIME and the WMES models is used as forecasting values on these business and miscellaneous purposes.

Item Type: Article
Uncontrolled Keywords: tourism demand, forecasting, autoregressive integrated moving average (ARIMA), Winters’s multiplicative exponential smoothing (WMES)
Subjects: L100 Economics
N800 Tourism, Transport and Travel
Department: Faculties > Business and Law > Newcastle Business School
Depositing User: Becky Skoyles
Date Deposited: 07 Jan 2019 09:16
Last Modified: 19 Nov 2019 09:52
URI: http://nrl.northumbria.ac.uk/id/eprint/37468

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