机构地区:[1]安徽大学商学院,安徽合肥230601 [2]安徽财贸职业学院朱熹文旅学院,安徽合肥230601
出 处:《经济管理》2020年第1期140-154,共15页Business and Management Journal ( BMJ )
基 金:国家自然科学基金项目“区域旅游产业结构演化对旅游效率的时空影响及动力机制研究:以长三角地区为例”(41601142);安徽高校人文社科重点项目“空气污染对区域旅游绩效的时空动态影响及作用机制研究”(SK2019A0014)
摘 要:区域旅游发展与空气质量之间的关系具有复杂性。综合利用脉冲响应模型、双变量空间自相关、地理探测器等分析方法,揭示中国大陆空气污染与旅游经济的时空动态关系及影响机理。主要结论有:首先,2000—2016年中国大陆旅游业发展与空气污染的“库兹涅茨”曲线总体上不显著,空气污染与旅游经济并非简单的负向线性关系。一方面,从脉冲响应的分析结果看,SO2与烟(粉)尘排放量对旅游经济的冲击并非完全负向的;另一方面,空气污染与旅游经济的全局空间自相关指数大部分时段为正值,并且局部空间自相关指数显著性个数较少。其次,空气污染与旅游经济的时空关系具有复杂性,主要原因是中国大陆旅游经济发展不充分、不均衡的客观实际,可能会“消化”空气污染对旅游经济的负向影响。在影响区域旅游经济增长的动力机制中,空气污染不是主导因素。第三,双变量ESDA及地理探测器分析结果为区域旅游高质量发展提供了理论指导,空气污染与旅游经济的时空关系,本质上反映的是旅游经济增长动力机制问题,区域旅游高质量发展需要重视系统中的“合力”因素及单个核心要素。未来中国旅游经济高质量发展需要在提升空气质量的同时,进一步夯实地区经济基础、规范市场化制度、调整产业结构、完善基础设施。There is a complex relationship between regional tourism development and air quality This article comprehensively used the impulse response model,bivariate spatial autocorrelation and geographic detector to reveal the temporal and spatial dynamic relationship between air pollution and tourism economy and its impact mechanism in Chinese mainland.The main conclusions are as follows:the Kuznets curve of tourism development and air pollution is not significant on the whole in China's Mainland from 2000 to 2016,and the curve is not entirely inverted U shaped.There is a certain“inverted U”relationship between tourism development and SO2 emissions,but there is a weak“U”relationship between tourism development and smoke and dust emissions.The relationship between air pollution and tourism economy is not a simple negative linear relationship.On the one hand,from the impulse response analysis results,the impact of SO2 and smoke and dust emissions on tourism economy is not completely negative;on the other hand,the global spatial autocorrelation index of air pollution and tourism economy is positive for most of the time,and the number of significant local of spatial autocorrelation index is less.It found that the spatial relationship between air pollution and tourism economy has certain regularity by the analysis of bivariate spatial autocorrelation.①The high pollution high income(H H)districts are mainly distributed in the eastern area,which facing the external task of improving air pollution.②The low pollution low income(L L)districts are mainly distributed in the western area.The development of tourism economy in the western region is relatively backward,but the air quality is relatively superior.③The low pollution high income(L H)districts are mainly distributed in South China,Beijing,Tianjin and the surrounding areas.The tourism development and air quality in this area have achieved a better optimization combination.④The high pollution low income(H L)districts are mainly distributed in Liaoning,Henan,Sic
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