引用本文:史翔翔.中部地区城市旅游竞争力动态评价研究[J].西南师范大学学报(自然科学版),2019,44(10):40~48
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中部地区城市旅游竞争力动态评价研究
史翔翔
南昌大学 经济管理学院, 南昌 330031
摘要:
针对生态文明建设背景下中部地区旅游业的发展现状,从经济发展、环境支撑和发展潜力三个方面构建融入"生态文明建设"思想的旅游竞争力评价指标体系,以2011-2015年中部地区80个地级市的面板数据为样本,运用BP神经网络动态激励模型、泰尔指数和探索性空间数据分析方法,对中部地区城市旅游竞争力进行动态实证分析.研究表明:一方面,中部地区旅游竞争力持续呈现出一种非均衡发展态势,省域内差异是影响总差异的关键因素,其中湖北省的内部差异尤为突出;另一方面,在空间相关性视角下,中部地区旅游竞争力从整体上看不存在集聚现象,但从局部上看,低高集聚区域主要分布在鄂州、黄石、咸宁、孝感和景德镇,低低集聚区域主要分布在漯河、安阳、周口、商丘、蚌埠、淮北、大同和亳州,高低集聚区域主要分布在武汉.
关键词:  城市旅游竞争力  BP神经网络动态激励模型  泰尔指数  探索性空间数据分析  动态评价
DOI:10.13718/j.cnki.xsxb.2019.10.009
分类号:F59
基金项目:南昌大学研究生创新专项资金资助项目(CX2017090).
On Dynamic Evaluation of Urban Tourism Competitiveness in Central China
SHI Xiang-xiang
School of Economics and Management, Nanchang University, Nanchang 330031, China
Abstract:
According to the status of tourism in central China under the background of ecological civilization construction, evaluation index system integrated has been constructed in this paper with the idea of "ecological civilization construction" on three aspects based from the perspective of economic development, environmental support and development potential. With BP neural network dynamic incentive model, Theil index and exploratory spatial data analysis method, an dynamic empirical study has been constructed on the basis of the data of 80 prefecture-level city in central China. The results show that, on the one hand, tourism competitiveness in central China continues to present an unbalanced situation, and provincial differences is the key factors in the total differences and the differences in Hubei is particularly prominent; on the other hand, there is no agglomeration of tourism competitiveness in central China from the overall perspective, but from the local perspective, low-high areas are mainly distributed in Ezhou, Huangshi, Xianning, Xiaogan and Jingdezhen, low-low areas are mainly distributed in Luohe, Anyang, Zhoukou, Shangqiu, Handan, Huaibei, Datong and Luzhou, high-low ares are mainly distributed in Wuhan.
Key words:  the urban tourism competitiveness  BP neural network dynamic incentive model  Theil index  exploratory spatial data analysis  dynamic evaluation
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