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Cross country relations in European tourist arrivals

机译:欧洲游客入境中的跨国关系

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This paper introduces an optimized Multivariate Singular Spectrum Analysis (MSS) algorithm for identifying leading indicators. Exploiting European tourist arrivals data, we analyse cross country relations for European tourism demand. Cross country relations have the potential to aid in planning and resource allocations for future tourism demand by taking into consideration the variation in tourist arrivals across other countries in Europe. Our findings indicate with statistically significant evidence that there exists cross country relations between European tourist arrivals Which can help in improving the predictive accuracy of tourism demand. We also find that MSSA has the capability of not only identifying leading indicators, but also forecasting tourism demand with far better accuracy in comparison to its univariate counterpart, Singular Spectrum Analysis. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文介绍了一种用于识别领先指标的优化多元奇异谱分析(MSS)算法。利用欧洲游客人数数据,我们分析了欧洲旅游需求的跨国关系。考虑到欧洲其他国家/地区游客人数的变化,跨国关系有可能帮助规划和分配资源,以满足未来的旅游需求。我们的发现以统计显着性证据表明,欧洲游客入境人数之间存在跨国关系,这可以帮助提高旅游需求的预测准确性。我们还发现,与单变量对应的奇异频谱分析相比,MSSA不仅能够识别领先指标,而且能够以更高的准确性预测旅游需求。 (C)2017 Elsevier Ltd.保留所有权利。

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