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A Neural Network model of the impact of political instability on tourism

机译:政治不稳定对旅游业影响的神经网络模型

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This paper presents an empirical integration of the dimensions of political instability with traditional exogenous variables, which are usually employed in econometric tourism demand forecasting, within a tourism demand model in order to investigate causal relationships between political instability and tourism. The work uses the POLINST Database, which contains events of political instability from 1977 to 1997 that took place in the Middle East — Mediterranean region. The model is based on a Focused Tapped Delay Line Neural Network (FTDNN) with a sliding time window of 12 months. The evaluation results show that our model can be used to achieve a good estimation of the effects of political instability on tourism. In an extended set of experiments we were able to show the relative importance of the political instability factors on tourism. Finally, our model also allowed to estimated the time lag between a political instability/terrorist event and the reduction of tourist number to the destination.
机译:本文提出了在旅游需求模型内将政治不稳定因素与传统外生变量(通常用于计量经济旅游需求预测)的经验整合,以研究政治不稳定与旅游之间的因果关系。该工作使用POLINST数据库,该数据库包含了中东-地中海地区从1977年至1997年的政治动荡事件。该模型基于聚焦时间延迟线神经网络(FTDNN),滑动时间窗为12个月。评估结果表明,我们的模型可用于很好地估计政治不稳定因素对旅游业的影响。在一组扩展的实验中,我们能够证明政治不稳定因素对旅游业的相对重要性。最后,我们的模型还可以估算政治不稳定/恐怖事件与减少前往目的地的游客数量之间的时间差。

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