To read this content please select one of the options below:

Nonadditive tourism forecast combination using grey relational analysis

Yi-Chung Hu (Department of Business Administration, Chung Yuan Christian University, Taoyuan City, Taiwan)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 2 December 2022

9

Abstract

Purpose

Forecasting tourism demand accurately can help private and public sector formulate strategic planning. Combining forecasting is feasible to improving the forecasting accuracy. This paper aims to apply multiple attribute decision-making (MADM) methods to develop new combination forecasting methods.

Design/methodology/approach

Grey relational analysis (GRA) is applied to assess weights for individual constituents, and the Choquet fuzzy integral is employed to nonlinearly synthesize individual forecasts from single grey models, which are not required to follow any statistical property, into a composite forecast.

Findings

The empirical results indicate that the proposed method shows the superiority in mean accuracy over the other combination methods considered.

Practical implications

For tourism practitioners who have no experience of using grey prediction, the proposed methods can help them avoid the risk of forecasting failure arising from wrong selection of one single grey model. The experimental results demonstrated the high applicability of the proposed nonadditive combination method for tourism demand forecasting.

Originality/value

By treating both weight assessment and forecast combination as MADM problems in the tourism context, this research investigates the incorporation of MADM methods into combination forecasting by developing weighting schemes with GRA and nonadditive forecast combination with the fuzzy integral.

Keywords

Acknowledgements

This research is supported by the Ministry of Science and Technology, Taiwan under grant MOST 110-2410-H-033-013-MY2.

Citation

Hu, Y.-C. (2022), "Nonadditive tourism forecast combination using grey relational analysis", Grey Systems: Theory and Application, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/GS-07-2022-0079

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles