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Advisor(s)
Abstract(s)
This study is aimed to model and forecast the tourism demand for Mozambique for
the period from January 2004 to December 2013 using artificial neural networks models. The
number of overnight stays in Hotels was used as representative of the tourism demand. A set
of independent variables were experimented in the input of the model, namely: Consumer
Price Index, Gross Domestic Product and Exchange Rates, of the outbound tourism markets,
South Africa, United State of America, Mozambique, Portugal and the United Kingdom. The best
model achieved has 6.5% for Mean Absolute Percentage Error and 0.696 for Pearson correlation
coefficient. A model like this with high accuracy of forecast is important for the economic
agents to know the future growth of this activity sector, as it is important for stakeholders to
provide products, services and infrastructures and for the hotels establishments to adequate
its level of capacity to the tourism demand.
Description
Keywords
Mozambique Artificial neural networks Tourism demand Forecasting Modelling
Citation
Constantino, H.; Fernandes, Paula O.; Teixeira, João Paulo (2016). Tourism demand modelling and forecasting with artificial neural network models: the Mozambique case study. Tékhne Review of Applied Management Studies. ISSN 1645-9911. 51
Publisher
Elsevier