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...
| 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/ http://eprints.uthm.edu.my/7007/1/P9903_455b98263296c2429a1b772c751a40db.pdf |
| _version_ | 1848888974444068864 |
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| author | Nor, M. E. A. I. M., Nurul Rusiman, M. S. |
| author_facet | Nor, M. E. A. I. M., Nurul Rusiman, M. S. |
| author_sort | Nor, M. E. |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | 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 |
| first_indexed | 2025-11-15T20:18:48Z |
| format | Conference or Workshop Item |
| id | uthm-7007 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:18:48Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-70072022-05-24T01:21:08Z http://eprints.uthm.edu.my/7007/ A hybrid approach on tourism demand forecasting Nor, M. E. A. I. M., Nurul Rusiman, M. S. H Social Sciences (General) 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 2017 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/7007/1/P9903_455b98263296c2429a1b772c751a40db.pdf Nor, M. E. and A. I. M., Nurul and Rusiman, M. S. (2017) A hybrid approach on tourism demand forecasting. In: ISMAp 2107, October 28, 2017, Batu Pahat, Johor. https://doi.org/10.1088/1742-6596/995/1/012034 |
| spellingShingle | H Social Sciences (General) Nor, M. E. A. I. M., Nurul Rusiman, M. S. A hybrid approach on tourism demand forecasting |
| title | A hybrid approach on tourism demand forecasting |
| title_full | A hybrid approach on tourism demand forecasting |
| title_fullStr | A hybrid approach on tourism demand forecasting |
| title_full_unstemmed | A hybrid approach on tourism demand forecasting |
| title_short | A hybrid approach on tourism demand forecasting |
| title_sort | hybrid approach on tourism demand forecasting |
| topic | H Social Sciences (General) |
| url | http://eprints.uthm.edu.my/7007/ http://eprints.uthm.edu.my/7007/ http://eprints.uthm.edu.my/7007/1/P9903_455b98263296c2429a1b772c751a40db.pdf |