广东省市域旅游联系网络结构特征及成因分析

李航飞; 唐承财

doi:10.6054/j.jscnun.2021098

广东省市域旅游联系网络结构特征及成因分析

李航飞^1, ,,
唐承财²

1.
韶关学院旅游与地理学院，韶关 512005
2.
北京第二外国语学院旅游科学学院，北京 100024

基金项目:

教育部人文社会科学研究规划基金项目 18YJA630102

详细信息

通讯作者:
李航飞，Email：lihangfei1980@126.com

中图分类号: F592.7;K921
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- 文章访问数: 385
- HTML全文浏览量: 133
- PDF下载量: 46
出版历程
- 收稿日期: 2021-03-28
- 网络出版日期: 2022-01-09
- 刊出日期: 2021-12-24

An Analysis of the Structural Characteristics of the Tourism Contact Network in Cities of Guangdong Province and Their Causes

LI Hangfei^1, ,,
TANG Chengcai²

1.
School of Tourism and Geography, Shaoguan University, Shaoguan 512005, China
2.
School of Tourism Science, Beijing International Studies University, Beijing 100024, China

摘要

摘要: 为有效促进广东省区域旅游协调发展，以2012—2018年百度指数中的网络关注度为依据，利用社会网络分析方法探讨广东省市域旅游联系的网络结构特征，并分析其形成机制. 研究结果表明：(1)广东省市域旅游联系网络密度不断增大，网络集中度不断下降，网络向均衡化方向发展. (2)广东省四大区域旅游网络联系派系结构不明显，“俱乐部”效应不显著，但在空间上呈现较为明显的“核心—边缘”结构特点；珠三角地市，特别是广州、深圳市，一直处于核心区，点度中心度高，为多维尺度(MDS)图中的第一梯队，东莞、佛山、惠州、珠海市为第二梯队，其余地市为第三梯队. (3)影响广东省市域旅游网络联系强弱的因素主要有时间距离、空间近邻效应、经济发展水平及旅游资源.
- 市域旅游 /
- 网络结构 /
- 形成机制 /
- 社会网络 /
- 广东省
Abstract: To effectively promote the coordinated development of regional tourism in Guangdong Province, the internet attention degree of Baidu index from 2012 to 2018 and the social network analysis method are used to study the structural characteristics of tourism contact network in cities of Guangdong Province and the mechanism for their formation. The following results are obtained. First, the density of the tourism contact network has been increasing, the concentration of the network has been declining and the network develops in the direction of equalization. Second, the factional structure of tourism networks of four regions of Guangdong Province is not obvious. Nor is the "club" effect. But the "core-edge" structure are relatively obvious. The cities in the Pearl River Delta, especially Guangzhou and Shenzhen, have always been in the core area with a high point center degree, belonging to the first echelon in the MDS chart. The cities such as Dongguan, Foshan, Huizhou and Zhuhai are in the second echelon, and the rest of the cities fall into the third echelon. Third, the main factors affecting the strength of the tourism network in Guangdong Province are time, distance, spatial neighbor effect, economic development and tourism resources.
- urban tourism /
- network structure /
- formation mechanism /
- social network /
- Guangdong Province

HTML全文

图 1 广东省各地市2012、2015、2018年的点度中心度

Figure 1. The point center degree of cities of Guangdong Province in 2012, 2015 and 2018

下载: 全尺寸图片幻灯片

图 2 广东省市域旅游网络联系MDS图

Figure 2. The MDS map of urban tourism network contact in Guangdong

下载: 全尺寸图片幻灯片

表 1 2012、2015、2018年广东省旅游网络密度及网络中心势

Table 1 The density and concentration of tourism network of Guangdong Province in 2012, 2015 and 2018 %

年份	网络密度	网络中心势
2012	25.71	78.0
2015	79.05	22.0
2018	87.14	13.5

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表 2 广东省市域旅游网络联系密度矩阵(2012、2015、2018年)

Table 2 The density matrix of urban tourism network links in Guangdong Province in 2012, 2015 and 2018

区域	2012				2015				2018
区域	珠三角	山区	东翼	西翼	珠三角	山区	东翼	西翼	珠三角	山区	东翼	西翼
珠三角	0.694	0.267	0.222	0.259	1.000	0.978	0.889	1.000	1.000	1.000	0.972	1.000
山区	0.267	0.000	0.000	0.000	0.978	0.200	0.350	0.400	1.000	0.400	0.500	0.667
东翼	0.000	0.000	0.333	0.000	0.889	0.350	0.833	0.333	0.972	0.500	1.000	0.583
西翼	0.259	0.000	0.000	0.000	1.000	0.400	0.333	1.000	1.000	0.667	0.583	1.000

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表 3 广东省市域旅游网络联系像矩阵(2012、2015、2018年)

Table 3 The image matrix of urban tourism network links in Guangdong Province in 2012, 2015 and 2018

区域	2012				2015				2018
区域	珠三角	山区	东翼	西翼	珠三角	山区	东翼	西翼	珠三角	山区	东翼	西翼
珠三角	1	1	0	1	1	1	1	1	1	1	1	1
山区	1	0	0	0	1	0	0	0	1	0	0	0
东翼	0	0	1	0	1	0	1	0	1	0	1	0
西翼	1	0	0	0	1	0	0	1	1	0	0	1

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表 4 核心区地市与边缘区地市分布情况(2012、2015、2018年)

Table 4 The distribution of cities in the core district and the fringe district in 2012, 2015 and 2018

分区	2012	2015	2018
核心区	广州、深圳	广州、深圳	广州、深圳
边缘区	东莞、云浮、佛山、湛江、江门、惠州、珠海、茂名、揭阳、中山、肇庆、汕头、云浮、潮州、清远、河源、汕尾	东莞、云浮、佛山、湛江、江门、惠州、珠海、茂名、揭阳、中山、肇庆、汕头、云浮、潮州、清远、河源、汕尾	东莞、云浮、佛山、湛江、江门、惠州、珠海、茂名、揭阳、中山、肇庆、汕头、云浮、潮州、清远、河源、汕尾
模型拟合值	0.895	0.894	0.826

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表 5 QAP回归分析结果

Table 5 The result of QAP regression analysis

变量	2015年标准化回归系数	2018年标准化回归系数
时间距离矩阵X₁	-0.312 585^*	-0.357 486^*
空间距离矩阵X₂	0.158 985	0.144 977
空间近邻效应矩阵X₃	0.286 792^***	0.245 815^***
经济发展水平差异矩阵X₄	0.282 292^**	0.189 893^**
旅游资源丰度差异矩阵X₅	0.348 219^*	0.343 114^*
模型拟合度R²	0.439^*(0.434^*)	0.376^*(0.370^*)
注：、、 * *分别表示通过了0.05、0.01、0.001的显著性检验；括号内为调整后的R².

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