Iman Ghalehkhondabi, Ehsan Ardjmand, William A. Young and Gary R. Weckman
The purpose of this paper is to review the current literature in the field of tourism demand forecasting.
Abstract
Purpose
The purpose of this paper is to review the current literature in the field of tourism demand forecasting.
Design/methodology/approach
Published papers in the high quality journals are studied and categorized based their used forecasting method.
Findings
There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.
Originality/value
This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.
Details
Keywords
Forecasting tourism demand accurately can help private and public sector formulate strategic planning. Combining forecasting is feasible to improving the forecasting accuracy…
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.