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.

中文翻译：

---

基于灰色关联分析的非加性旅游预测组合

目的

准确预测旅游需求可以帮助私营和公共部门制定战略规划。组合预测对于提高预测精度是可行的。本文旨在应用多属性决策（MADM）方法来开发新的组合预测方法。

设计/方法/途径

灰色关联分析 (GRA) 用于评估单个成分的权重，并采用 Choquet 模糊积分将不需要遵循任何统计特性的单个灰色模型的单个预测非线性合成为复合预测。

发现

实证结果表明，所提出的方法在平均精度方面优于所考虑的其他组合方法。

实际影响

对于没有使用灰色预测经验的旅游从业者，所提出的方法可以帮助他们避免因错误选择单一灰色模型而导致预测失败的风险。实验结果证明了所提出的非加性组合方法对旅游需求预测的高度适用性。

原创性/价值

通过将权重评估和预测组合视为旅游环境中的 MADM 问题，本研究通过开发具有 GRA 的加权方案和具有模糊积分的非加性预测组合，研究将 MADM 方法纳入组合预测。