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A time series analysis of causality between tourist arrivals and climatic effects for nature-based tourism destinations: evidence from Gilgit-Baltistan, Pakistan

机译:基于自然的旅游目的地的旅游抵达与气候效应的因果关系的时间序列分析:来自巴基斯坦吉尔吉特 - 巴尔塔斯坦的证据

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摘要

Do tourist arrivals affect the climate of the destination or is it the climatic conditions that influence tourist decisions to visit a destination? These questions merit special attention for the nature-based and weather-dependent livelihoods in the mountainous regions of South Asia. Communities in these regions, on the one hand, are vulnerable to climatic change and rely on, on the other hand, income from tourism for their livelihoods. This research specifically examines whether a large number of temporary visitors to mountainous regions, which are otherwise isolated from urban settlements, contribute to the change in climate. To capture the changes in climate, we have taken four variables: temperature, rainfall, sunshine and humidity. Tourist arrival is recorded as total annual temporary tourists to the area annually for the years 2000-2017. Using an ARDL bound test method to co-integration and Granger causality test on time series data, this research empirically examines the relationships between tourism and climate change. The findings suggest that indicators like sunshine and temperature have significant long-run and short-run relation with tourist arrival. Likewise, results suggest bidirectional causality between tourists' inflow and temperature, unidirectional causality toward tourist arrivals from sunshine and unidirectional causality from rain to tourist inflow. Humidity and tourist inflow are causality independent.
机译:旅游抵达是否影响了目的地的气候,或者是影响旅游决策访问目的地的气候条件吗?这些问题在于南亚山区的自然和天气依赖生计的特别关注。一方面,这些地区的社区容易受到气候变化,另一方面依赖于旅游业的生计。这项研究特别审查了山区的大量临时游客,距离城市定居点另有孤立,有助于气候变化。为了捕捉气候的变化,我们采取了四个变量:温度,降雨,阳光和湿度。旅游抵达年抵达年度截至2000 - 2017年年度每年临时游客。使用ARDL绑定的测试方法在时间序列数据上共同整合和Granger因果关系测试,本研究经验审查了旅游和气候变化之间的关系。调查结果表明,与阳光和温度等指标与旅游抵达具有重要的长期和短期关系。同样,结果表明游客流入和温度之间的双向因果关系,从雨水到旅游流入的阳光和单向因果关系向旅游者到达的单向因果关系。湿度和旅游流入是因果关系独立的。

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