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Advisor(s)
Abstract(s)
This article appears as an essential contribution for decision-makers in
the Cape Verdean tourism sector given the impact that the number of overnight
stays has on the economy of the country and the Sal Island, which until 2018 had
been increasing every year. Since seasonality is a strong feature of the island's
tourism, decision-makers are interested in knowing the seasonal variation in tourism demand. Thus, this study focused on the application of the Box-Jenkins
method to the time series of the monthly number of nights stays in tourist establishments on the Sal Island, Cape Verde, over the period from January 2000 to
December 2018, to find a model that better describes the series and with good
forecast results for the year 2019. Several SARIMA models were studied using
the Box-Jenkins method, with the SARIMA(1,1,1)(0,1,1)12 and the
SARIMA(2,1,0)(0,1,1)12 demonstrating the best predictive performance in the
test phase. However, in forecasting the series for the year 2019 the
SARIMA(2,1,0)(0,1,1)12 achieved the best results with a MAPE=8.78%. This
model can be used to simulate and analyse the number of overnight stays that be
expected on the Island, if the tourism sector were not affected by the pandemic
caused by COVID-19.
Description
Keywords
Time Series SARIMA models Number of overnight stays Sal Island Cape Verde
Citation
Neves, G.A., Nunes, C.S., Fernandes, P.O. (2022). Seasonal Autoregressive Integrated Moving Average Time Series Model for Tourism Demand: The Case of Sal Island, Cape Verde. In: Carvalho, J.V.d., Liberato, P., Peña, A. (eds) Advances in Tourism, Technology and Systems. Smart Innovation, Systems and Technologies, vol 284 (pp.11-21). Springer, Singapore. https://doi.org/10.1007/978-981-16-9701-2_2
