摘要
本文以中国大陆31个省域为研究单元,借鉴和创新世界经济论坛旅游业竞争力评价指标体系(WEF),结合中国实际,从综合竞争力、现实竞争力、潜在竞争力和环境竞争力四个维度来构建中国省域旅游业竞争力评价指标体系,分析比较各省域旅游业发展的竞争态势,并运用ESDA空间分析法,有效揭示指标数据所反映的区域竞争态势之间的空间依赖性与空间异质性,对其空间格局进行描述与可视化呈现。研究内容与结论如下:(1)通过将指标数值归一化为无量纲标量,再对因子层相应指标加和得到各省域旅游业发展四个维度的竞争力分值,研究表明中国省域旅游业竞争力空间分布差异明显,总体呈东强、中柔、西弱的分布格局;(2)通过GeoDA计算出中国省域旅游业发展四个维度竞争力的全局Moran’sI估计值分别为0.1904、0.1972、0.1724和0.1205,均为正值,且正态统计量z值均大于0.05置信水平的临界值(1.96),通过显著性检验,表明中国省域旅游各项竞争力发展水平均存在显著的空间自相关,空间集聚特征较为突出,竞争力强的省域和竞争力弱的省域分别趋于相邻,在空间层面上存在马太效应;(3)以(z,WZ)为坐标点,对变量所有观测值的标准化值=与空间滞后向量耽之间的相关性进行可视化的二维图示,得到中国省域各项旅游业竞争力的Moran散点图及空间关联图,反映出东部沿海省域和长江中下游省域的旅游业各项竞争力水平空间结构上已基本形成了较显著的HH型的连绵区,东北与西部省域则多数处于旅游业竞争力LL集聚区,两极分化的现象明显;(4)运用局部关联指数Getis—Ord Gi*,采取Jenks最佳自然断裂分级法生成中国省域旅游业竞争力的热-冷点区域图,研究表明,中国省域旅游业竞争力热-冷点区呈现由东南向西南、东北、西北推移的阶梯状分布,形成了以长江中下游地区为热点区的典型性核心-边缘结构。
Taking 31 provinces and cities as the basic research units, and referring to the World Economic Forum's (WEF) tourism competitiveness evaluation index system, this article builds the evaluation index system of China' s provincial tourism competitiveness from comprehensive competence, current competence, potential competence, and environmental competitiveness then to use the evaluation index system to analyze the tourism competitive situation of those provinces and cities. Appling Exploratory Spatial Data Analysis ( ESDA), this article further de- tects and visually presents the spatial differences and relevance of China' s provincial tourism competitiveness. This article can be referenced to grasp the current overall spatial patterns of China' s tourism development competitive- ness, and to improve the provincial tourism competitiveness. Research contents and conclusions are as follows: 1 ) The four dimensions of provincial tourism development competitiveness can be obtained by normalizing the index values into a dimensionless scalar, keeping the scores vary between [0, 10] , and summing up the indexes from different factor layers. Research reflects the significant spatial differentiation of China' s provincial tourism competitiveness, which is overall displayed as a pattern of "prosperous east, moderate center and weak west". Generally, some eastern provinces such as Guangdong, Beijing, Shanghai, and Jiangsu, obtained the highest scores in all tourism competitiveness dimensions, especially in comprehensive competitiveness dimension (230. 46) , while some central provinces such as Anhui, Hunan, and Hubei have weakness in environmental com- petitiveness dimension (55.78). Compared with eastern provinces, and central provinces (156. 48), western provinces (139.26) are far more behind in comprehensive competitiveness, but the environmental competitiveness of western provinces (57.82) is slightly higher than that of central provinces, which suggests a promising prospect for the west. 2) Calculated by GeoDA, the overall Moran' s estimator for the four dimensions of China' s provincial compet- itiveness arc 0. 1904, 0. 1972, 0. 1724 and 0. 1205, which are all positive and the normal statistic Z value is grea- ter than 0.05, the Confidence Level Threshold ( 1.96 ) , which suggests a pass of the significant test. Research shows that all the four dimensions of China' s provincial tourism competitiveness display significant Spatial Autocor- relation, and prominent spatial agglomeration. Research also shows neighboring distribution of competitive prov- inces and less competitive provinces, which indicates a Matthew effect in spatial dimensions. 3 ) With (z, Wz) as coordinates, by visualizing the correlation between the standardized value Z of all ob- served variable values and the spatial lag vector Wz into two-dimensional diagrams, we get the Moran scatter plot and spatial correlation graph of China' s provincial tourism competitiveness in all the four dimensions. Research shows that the spatial structure of provincial tourism competitiveness of eastern coastal region, and the middle and lower reaches of the Yangtze River has basically formed a remarkable stretches of the HH type, while the northeast and the western provinces are mainly located in the region of LL type, which suggests a clear polarization phenome- non. 4) By using Partial Correlation Index Getis-Ord Gi * and Jenks best natural fracture classification methods, from high to low, we divided the partially statistics into 4 categories, which generated China' s provincial tourism competitiveness hot-cold area map. Research shows that China' s provincial tourism competitiveness hot-cold area presents a ladder-like distribution stretching from southeast to southwest, northeast, and northwest, and have formed a typical core-periphery structure of the hot zone in the middle and lower reaches of the Yangtze River area. The secondary hot zone is mainly distributed on the north and south sides of the middle and lower reaches of Yangtze River, the secondary cold zone is distributed in north China and southwest China, and the cold zone is mainly concentrated in western region.
出处
《经济管理》
CSSCI
北大核心
2015年第4期126-135,共10页
Business and Management Journal ( BMJ )
基金
教育部哲学社会科学基金项目"中国旅游业发展报告"(11JBGP041)
关键词
旅游业
竞争力
空间格局
空间自相关
tourism
competitiveness
spatial pattern
spatial autocorrelation