我国入境旅游流循环空间分布特征及影响因素

doi:10.12054/lydk.bisu.263

摘要/Abstract

摘要：

本研究收集了我国2019年入境旅游流的有关数据，构建入境旅游流循环分析指标，利用自然断点法、社会网络分析法、QAP分析法，揭示我国入境旅游流循环的空间分布特征及影响因素，结果发现：（1）存在117个省际入境旅游流循环、25个经济区间入境旅游流循环以及7个经济区内入境旅游流循环，涉及26个省区市。（2）入境旅游流循环强度的空间分布表现为“东高西低”，流量规模匹配度呈“高分散、低集聚”的空间分布格局，高、中、低3个等级的流向偏好匹配度均集中在中东部地区。（3）省际、区域间、区域内入境旅游流循环类型的数量和空间分布特征存在一定差异。多数入境旅游流循环的强度、流量规模匹配度、流向偏好匹配度不高，反映了我国入境旅游流循环质量不高，有待提升。（4）入境旅游流循环网络呈现出“东密西疏”的空间分布特征，整体网络密度较低。（5）交通便捷程度、对外经济贸易、旅游资源禀赋、经济发展水平和旅游接待能力均是影响入境旅游流循环的重要因素，各因素对入境旅游流循环强度、流量规模匹配度和流向偏好匹配度的影响不同。

关键词: 入境旅游; 旅游流循环; 空间分布特征; 影响因素

Abstract:

Collecting relevant data in 2019 to construct inbound tourism flow circulation analysis indexes, using natural breakpoints, social network analysis, and the quadratic assignment procedure analysis method, while revealing the spatial distribution characteristics of China’s inbound tourism flow circulation and its influencing factors, the results show that, first, there are 117 inter-provincial, 25 inter-economic zone, and 7 intra-economic zone inbound tourism flow circulations, involving 26 provinces and regions; second, the spatial distribution of inbound tourism circulation intensity is “high in the east and low in the west,” and the matching degree of flow scale is “high dispersion and low agglomeration,” while the matching degree of flow preference of high, medium, and low levels are concentrated in the central-eastern region; third, there are some differences in the number and spatial distribution characteristics of inter-provincial, inter-regional, and intra-regional inbound tourism flow circulation types. Most of the inbound tourism flow circulation intensity, flow scale matching, and flow preference matching are not high, indicating that the quality of inbound tourism flow circulation in China is not high and needs to be improved; fourth, the inbound tourism circulation network shows a spatial distribution of “dense in the east and sparse in the west,” and the overall network density is low; fifth, the convenience of transportation, foreign economic trade, tourism resource endowment, economic development level, and tourism reception capacity are all important factors affecting inbound tourism flow circulation, and each factor has different effects on the intensity of inbound tourism flow circulation, flow scale matching degree, and flow preference matching degree.

Keywords: inbound tourism; tourism flow circulation; spatial distribution characteristics; influencing factors

中图分类号:

马丽君, 欧阳旻, 梁逍遥. 我国入境旅游流循环空间分布特征及影响因素[J]. 旅游导刊, 2024, 8(5): 76-109.

MA Lijun, OUYANG Min, LIANG Xiaoyao. Spatial Distribution Characteristics and Influencing Factors of Inbound Tourism Flow Circulation in China[J]. Tourism and Hospitality Prospects, 2024, 8(5): 76-109.

图/表 20

参考文献 39

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位置内部的关系比例Proportion of internal relationship in location	位置接收到的关系比例Proportion of relationships received by location
位置内部的关系比例Proportion of internal relationship in location	≈0	>0
≥(g_k-1)/(g-1)	双向溢出板块	主受益板块
≤(g_k-1)/(g-1)	主溢出板块	经纪人板块

位置内部的关系比例Proportion of internal relationship in location	位置接收到的关系比例Proportion of relationships received by location
位置内部的关系比例Proportion of internal relationship in location	≈0	>0
≥(g_k-1)/(g-1)	双向溢出板块	主受益板块
≤(g_k-1)/(g-1)	主溢出板块	经纪人板块

省区市Provinces	度数中心度Degree centrality	接近中心度Closeness centrality	中间中心度Betweenness centrality	结构洞Structural Holes			网络规模Network size	个体网络密度Individual network density
省区市Provinces	度数中心度Degree centrality	接近中心度Closeness centrality	中间中心度Betweenness centrality	有效规模Effective size	效率Efficiency	限制度Constraint	网络规模Network size	个体网络密度Individual network density
北京	76.000	80.645	9.633	10.200	0.510	0.193	19	0.462 0
天津	4.000	42.373	0.000	1.000	0.500	1.125	1	0.000 0
河北	16.000	51.020	0.074	1.400	0.280	0.638	4	0.833 3
山西	20.000	55.556	0.074	1.333	0.222	0.555	5	0.900 0
辽宁	40.000	62.500	1.160	3.545	0.322	0.327	10	0.688 9
吉林	20.000	54.348	0.000	1.000	0.167	0.560	5	1.000 0
黑龙江	40.000	60.976	1.499	4.273	0.388	0.329	10	0.600 0
上海	60.000	71.429	11.386	7.750	0.484	0.236	15	0.485 7
江苏	52.000	67.568	1.625	4.429	0.316	0.264	13	0.692 3
浙江	52.000	67.568	2.823	4.714	0.337	0.263	13	0.666 7
安徽	32.000	59.524	0.104	1.222	0.136	0.396	8	0.964 3
福建	36.000	58.140	0.316	2.200	0.220	0.358	9	0.833 3
江西	12.000	48.077	0.000	1.000	0.250	0.766	3	1.000 0
山东	36.000	60.976	0.412	2.400	0.240	0.358	9	0.805 6
河南	40.000	60.976	0.735	3.000	0.273	0.329	10	0.755 6
湖北	40.000	60.976	0.485	2.818	0.256	0.328	10	0.777 8
湖南	36.000	60.976	1.625	3.600	0.360	0.358	9	0.638 9
广东	80.000	83.333	12.245	11.000	0.524	0.185	20	0.447 4
海南	24.000	54.348	0.037	1.286	0.184	0.490	6	0.933 3
四川	64.000	73.529	6.817	7.588	0.446	0.220	16	0.533 3
西藏	24.000	55.556	0.429	1.857	0.265	0.485	6	0.800 0
陕西	80.000	83.333	23.859	12.048	0.574	0.183	20	0.389 5
甘肃	24.000	54.348	0.994	2.429	0.347	0.480	6	0.666 7
青海	16.000	51.020	0.000	1.000	0.200	0.648	4	1.000 0
宁夏	4.000	46.296	0.000	1.000	0.500	1.125	1	0.000 0
新疆	8.000	47.170	0.000	1.000	0.333	0.926	2	1.000 0

省区市Provinces	度数中心度Degree centrality	接近中心度Closeness centrality	中间中心度Betweenness centrality	结构洞Structural Holes			网络规模Network size	个体网络密度Individual network density
省区市Provinces	度数中心度Degree centrality	接近中心度Closeness centrality	中间中心度Betweenness centrality	有效规模Effective size	效率Efficiency	限制度Constraint	网络规模Network size	个体网络密度Individual network density
北京	76.000	80.645	9.633	10.200	0.510	0.193	19	0.462 0
天津	4.000	42.373	0.000	1.000	0.500	1.125	1	0.000 0
河北	16.000	51.020	0.074	1.400	0.280	0.638	4	0.833 3
山西	20.000	55.556	0.074	1.333	0.222	0.555	5	0.900 0
辽宁	40.000	62.500	1.160	3.545	0.322	0.327	10	0.688 9
吉林	20.000	54.348	0.000	1.000	0.167	0.560	5	1.000 0
黑龙江	40.000	60.976	1.499	4.273	0.388	0.329	10	0.600 0
上海	60.000	71.429	11.386	7.750	0.484	0.236	15	0.485 7
江苏	52.000	67.568	1.625	4.429	0.316	0.264	13	0.692 3
浙江	52.000	67.568	2.823	4.714	0.337	0.263	13	0.666 7
安徽	32.000	59.524	0.104	1.222	0.136	0.396	8	0.964 3
福建	36.000	58.140	0.316	2.200	0.220	0.358	9	0.833 3
江西	12.000	48.077	0.000	1.000	0.250	0.766	3	1.000 0
山东	36.000	60.976	0.412	2.400	0.240	0.358	9	0.805 6
河南	40.000	60.976	0.735	3.000	0.273	0.329	10	0.755 6
湖北	40.000	60.976	0.485	2.818	0.256	0.328	10	0.777 8
湖南	36.000	60.976	1.625	3.600	0.360	0.358	9	0.638 9
广东	80.000	83.333	12.245	11.000	0.524	0.185	20	0.447 4
海南	24.000	54.348	0.037	1.286	0.184	0.490	6	0.933 3
四川	64.000	73.529	6.817	7.588	0.446	0.220	16	0.533 3
西藏	24.000	55.556	0.429	1.857	0.265	0.485	6	0.800 0
陕西	80.000	83.333	23.859	12.048	0.574	0.183	20	0.389 5
甘肃	24.000	54.348	0.994	2.429	0.347	0.480	6	0.666 7
青海	16.000	51.020	0.000	1.000	0.200	0.648	4	1.000 0
宁夏	4.000	46.296	0.000	1.000	0.500	1.125	1	0.000 0
新疆	8.000	47.170	0.000	1.000	0.333	0.926	2	1.000 0

循环板块Cycle plate	板块一接收关系数Reception count for Plate One	板块二接收关系数Reception count for Plate Two	板块三接收关系数Reception count for Plate Three	板块四接收关系数Reception count for Plate Four	板块成员总数Total plate members	实际内部关系比例Actual internal relation ratio	期望内部关系比例Expected internal relationratio	接受板块外关系数External relation admission count	板块类型Plate type
板块一	40	28	18	11	8	41.24%	28.00%	57	主受益
板块二	28	22	5	14	6	31.88%	20.00%	47	主受益
板块三	18	5	0	6	6	0	20.00%	29	主溢出
板块四	11	14	6	8	6	20.51%	20.00%	31	主受益