A hybrid approach on tourism demand forecasting
Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is cha...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7007/1/P9903_455b98263296c2429a1b772c751a40db.pdf http://eprints.uthm.edu.my/7007/ https://doi.org/10.1088/1742-6596/995/1/012034 |
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| Summary: | Tourism has become one of the important industries that contributes to the country’s
economy. Tourism demand forecasting gives valuable information to policy makers, decision
makers and organizations related to tourism industry in order to make crucial decision and
planning. However, it is challenging to produce an accurate forecast since economic data such
as the tourism data is affected by social, economic and environmental factors. In this study, an
equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural
Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was
assessed by taking the each individual method as a benchmark. The results showed that this
hybrid approach outperformed the other two models |
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