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Modelling Australian domestic and international inbound travel: a spatial-temporal approach

机译:模拟澳大利亚国内和国际入境旅行:时空方法

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In this paper Australian domestic and international inbound travel are modelled by an anisotropic dynamic spatial lag panel Origin-Destination (OD) travel flow model. Spatial OD travel flow models have traditionally been applied in a single cross-sectional context, where the spatial structure is assumed to have reached its long run equilibrium and temporal dynamics are not explicitly considered. On the other hand, spatial effects are rarely accounted for in traditional tourism demand modelling. We attempt to address this dichotomy between spatial modelling and time series modelling in tourism research by using a spatial-temporal model. In particular, tourism behaviour is modelled as travel flows between regions. Temporal dependencies are accounted for via the inclusion of autoregressive components, while spatial autocorrelations are explicitly accounted for at both the origin and the destination. We allow the strength of spatial autocorrelation to exhibit seasonal variations, and we allow for the possibility of asymmetry between capital-city neighbours and non-capital-city neighbours. Significant temporal and spatial dynamics have been uncovered for both domestic and international tourism demand. For example we find strong seasonal temporal autocorrelations, significant trends and significant spatial autocorrelations at both the origin and the destination. Moreover, the spatial patterns are found to be most significant during peak holiday seasons. Understanding these patterns in tourist behaviour has important implications for tourism operators.
机译:本文利用各向异性动态空间滞后面板原点-目的地(OD)旅行流模型对澳大利亚国内和国际入境旅行进行建模。传统上,空间OD流动模型是在单个横截面环境中应用的,其中假定空间结构已达到长期平衡,并且未明确考虑时间动态。另一方面,在传统旅游需求模型中很少考虑空间效应。我们试图通过使用时空模型解决旅游研究中空间建模和时间序列建模之间的这种二分法。特别是,将旅游行为建模为区域之间的旅行流量。时间依赖性通过包含自回归分量来解决,而空间自相关在起点和终点都明确考虑。我们允许空间自相关的强度表现出季节变化,并且允许首都城市邻居和非首都城市邻居之间存在不对称的可能性。对于国内外旅游需求,已经发现了重要的时空动态。例如,我们在始发地和目的地都发现了强烈的季节性时间自相关,明显的趋势和显着的空间自相关。此外,发现空间模式在假日旺季最显着。了解旅游者行为的这些模式对旅游经营者具有重要意义。

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