中国省际入境旅游集散优势度与旅游经济效率的空间关系

doi:10.11821/dlyj020190280

摘要/Abstract

摘要：

以中国省际入境旅游流为研究对象,在构建集散优势度与旅游经济效率耦合理论框架基础上,运用复杂网络分析方法和空间经济学理论揭示了2005年、2016年各省市“势-效”空间关系演化规律,并据此提出省际入境旅游与当地旅游经济间“势-效”空间关系优化的方式。研究发现：集散优势度存在显著空间分异,且随时间变化发生冷热点迁移。北京、上海、广东、四川最具集散优势。旅游综合效率值整体呈上升趋势,但两极分化现象显著,至2016年基本形成南北高低相间、东西高低分化的“S”型格局。受地区旅游经济增长、资源要素投入等因素影响,“势-效”耦合的空间关系不断调整。针对部分地区“势-效”关系存在失调,研究提出了失衡型、低水平协调型旅游地的协调机制与路径,促进“势-效”关系在空间上良性协同。

关键词: 入境旅游, 集散优势度, 旅游经济效率, 空间关系

Abstract:

The relationship between tourist flow and tourism economic efficiency has been an important topic of research in the fields of tourism economics and tourism geography. Existing studies tend to treat them as independent subjects. In particular, few studies have investigated the spatial relationship between them. This paper aims to fill the research gap through a comprehensive analysis of inter-provincial inbound tourist flows. The paper first constructs a coupling framework between tourist distribution superiority and tourism economic efficiency. It then measures the comparative superiority and economic efficiency for the 31 provincial-level regions to reveal the temporal and spatial patterns. Several conclusions can be dawn as follows. First, inbound tourist distribution superiority shows significant differentiations at the provincial level. During the 11-year period of 2005-2016, relative superiority changed most significantly. Beijing, Shanghai, Guangdong and Sichuan have obvious advantages in attracting inbound tourists. Second, the average economic efficiency increased from 0.485 to 0.520, and the proportion of the 1st- and 5th-level provincial-level regions increased from 29.03% to 48.39%, indicating an obvious rise as well as a polarization trend. By 2016, an 'S'-shaped spatial distribution for high-level efficiency provinces had emerged. Third, the spatial relationship between distribution superiority and efficiency was altered. Specifically, the number of high-level and medium-level coordination (H-H and M-M) areas increased, while that of low-level coordination (L-L) areas decreased. Meanwhile, the number of imbalanced tourist destinations (H-L or L-H) increased. Fourth, tourist distribution superiority and tourism economic efficiency are two key variables that are closely interrelated. An imbalanced relationship between distribution superiority and efficiency affects the overall competitiveness of regional tourism. Thus it is suggested that more resources should be allocated to the weak coupling system to strengthen the relationship between tourist distribution superiority and economic efficiency. More importantly, varying strategies should be implemented for each tourist destination according to their coupling state.

Key words: inbound tourism, distribution superiority, tourism economic efficiency, spatial relationship

王钊, 李涛, 杨山. 中国省际入境旅游集散优势度与旅游经济效率的空间关系[J]. 地理研究, 2020, 39(4): 892-906.

WANG Zhao, LI Tao, YANG Shan. Spatial relationship between inbound tourist distribution superiority and tourism economic efficiency among provinces in China[J]. GEOGRAPHICAL RESEARCH, 2020, 39(4): 892-906.

图/表 12

图1

表1

集散优势度评价指标体系及表征"

指标名称	表达式	解释	拓扑表征
程度中心性（B₁）	$D i = ∑ j = 1 g x ij x ≠ j g - 1$	式中：D_i为省（市）i的程度中心性;i表示与其他节点的关联数;g为节点的可能连接数。	程度中心性直观反映旅游地在网络中的中心地位,程度中心性越高,表明其与其他节点关联数量越多,集散能力越强。
接近中心性（B₂）	$C i = 1 ∑ j = 1 n d ij$	式中：d_ij是省（市）i和省（市）j之间的最短路径距离。	接近中心性反映了该旅游地与其他旅游地之间的距离远近程度,即接近程度。最短路径距离越短,接近中心性越高,可进入性越好。
中间中心性（B₃）	$B i = ∑ j 1 ∑ k 1 g jk (i) / g ik, j ≠ k ≠ i$	式中：g_jk为连接jk最短路径的数目;g_jk(i)为jk之间存在的经过i的最短路径的条数。	中间中心性反映了一个节点处于其他节点间最短路径上的“中介”能力。中间中心性越大,对旅游流的控制力越大,其他旅游地对其依赖程度越高。

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层级	2005年		2016年
层级	省份	比例（%）	省份	比例（%）
第一层级	广东、四川、北京、上海	12.90	北京、上海、广东、四川	12.90
第二层级	江苏、广西、浙江、陕西、山东	16.13	浙江、陕西、湖北、辽宁、江苏、云南、安徽、湖南、山东	29.03
第三层级	福建、云南、湖北、辽宁、山西、湖南、甘肃、天津	25.81	重庆、福建、河南、贵州、山西、河北、黑龙江	22.58
第四层级	吉林、西藏、重庆、黑龙江、河南、河北、海南、安徽、内蒙古、贵州、新疆	35.48	甘肃、西藏、天津、江西、吉林、新疆、青海、广西、内蒙古	29.03
第五层级	江西、青海、宁夏	9.68	海南、宁夏	6.45

层级	2005年		2016年
层级	省份	比例（%）	省份	比例（%）
第一层级	上海、福建、广东、内蒙古、江苏	16.13	天津、内蒙古、浙江、福建、广东、广西、安徽、陕西	25.81
第二层级	天津、北京、辽宁、陕西、浙江、黑龙江	19.35	上海、重庆、吉林、山东、云南、辽宁、湖北	22.58
第三层级	广西、湖南、河北、云南、吉林、山东、安徽	22.58	江西、北京、湖南、新疆	12.90
第四层级	重庆、四川、贵州、海南、河南、西藏、甘肃、山西、湖北	29.03	黑龙江、河南、四川、江苏、西藏	16.13
第五层级	新疆、江西、青海、宁夏	12.90	贵州、河北、海南、宁夏、山西、青海、甘肃	22.58