Optimal Forecast Combination for Japanese Tourism Demand

Yongmei Fang, Emmanuel Sirimal Silva, Bo Guan, Hossein Hassani and Saeed Heravi ()
Additional contact information
Yongmei Fang: College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
Emmanuel Sirimal Silva: Glasgow School for Business and Society, Glasgow Caledonian University, Glasgow G4 0BA, UK
Bo Guan: Cardiff Business School, University of Cardiff, Cardiff CF10 3EU, UK
Hossein Hassani: International Institute for Applied Systems Analysis (IIASA), A-2361 Laxenburg, Austria
Saeed Heravi: Cardiff Business School, University of Cardiff, Cardiff CF10 3EU, UK

Tourism and Hospitality, 2025, vol. 6, issue 2, 1-19

Abstract: This study introduces a novel forecast combination method for monthly Japanese tourism demand, analyzed at both aggregated and disaggregated levels, including tourist, business, and other travel purposes. The sample period spans from January 1996 to December 2018. Initially, the time series data were decomposed into high and low frequencies using the Ensemble Empirical Mode Decomposition (EEMD) technique. Following this, Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Support Vector Machine (SVM) forecasting models were applied to each decomposed component individually. The forecasts from these models were then combined to produce the final predictions. Our findings indicate that the two-stage forecast combination method significantly enhances forecasting accuracy in most cases. Consequently, the combined forecasts utilizing EEMD outperform those generated by individual models.

Keywords: empirical ensemble mode decomposition; tourism demand; time series analysis; forecast combination; decomposition; Japan (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2673-5768/6/2/79/pdf (application/pdf)
https://www.mdpi.com/2673-5768/6/2/79/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jtourh:v:6:y:2025:i:2:p:79-:d:1650642

Access Statistics for this article

Tourism and Hospitality is currently edited by Mr. Philip Li

More articles in Tourism and Hospitality from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().