区域经济

新疆旅游经济网络特征的时空演变研究——基于修正的引力模型及社会网络分析

展开
  • 复旦大学工商管理博士后流动站,上海 200433

    山东农业大学经管学院,山东 泰安 271018 ;

    新疆工程学院信息工作学院,新疆 乌鲁木齐 830023; 4 新疆师范大学地理科学与旅游学院,新疆 乌鲁木齐 830054

王松茂(1980-),男,山东潍坊人,教授,主要研究方向为旅游扶贫、旅游经济空间分析. E-mail:1095929778@qq.com

收稿日期: 2019-01-02

  修回日期: 2019-05-28

  网络出版日期: 2020-03-25

基金资助

新疆自治区自然科学基金面上项目(2016D01C047)资助

Spatial and temporal evolution of the tourism economy network in Xinjiang:Based on modified gravity model and social network analysis

Expand
  • Postdoctoral Station of Business Administration Department of Tourism,Fudan University,Shanghai 200433,China;

    College of Economics & Management,Shandong Agriculture University,Taian 271018,ShandongChina;

    School of Information Engineering,Xinjiang Ploytechnical University,Urumq 830023,Xinjiang,China;School of Geography and Tourism,Xinjiang Normal University,Urumqi 830054,Xinjiang,China

Received date: 2019-01-02

  Revised date: 2019-05-28

  Online published: 2020-03-25

摘要

通过构建“旅游综合质量”评价指标,继而将引力模型进行修正以衡量各区域间旅游经济联系度并运用社会网络分析方法探究了20082017年新疆15个地州旅游经济的空间网络特征。结果表明:(1 20082017年间,新疆旅游经济关联网络密度的均值仅为0.356、网络效率均值为0.718、网络等级度均值为0.367。(2 10 a间,乌鲁木齐市、伊犁州直属、喀什地区、昌吉州、吐鲁番市等地属于度数中心度与中间中心度双高区域;阿勒泰地区、巴州等地属于度数中心度较高、中间中心度较低区域;克拉玛依市属于度数中心度较低,中间中心度较高区域;博州、和田地区、哈密地区、塔城地区、克州、阿克苏地区、石河子市等地属于度数中心度、中间中心度双低区域。(3) 乌鲁木齐市、昌吉州、喀什地区、伊犁州直属、阿勒泰地区等地在研究时限内属于“双向溢出板块”;石河子市、克拉玛依市、巴州、吐鲁番市属于“经纪人板块”;博州、哈密地区、塔城地区属于“净受益板块”;阿克苏地区、克州、和田地区属于“主受益板块”。本文旨在丰富旅游经济网络研究视角,同时为新疆各地州旅游经济发展与合作提供量化依据。

本文引用格式

王松茂, 徐宣国, 马江涛, 王艳威 . 新疆旅游经济网络特征的时空演变研究——基于修正的引力模型及社会网络分析[J]. 干旱区地理, 2020 , 43(2) : 458 -465 . DOI: 10.12118/j.issn.1000-6060.2020.02.20

Abstract

In this study,first,an evaluation index of “comprehensive tourism quality was constructed and then the gravity model was modified to measure the degree of tourism economy connection among regions.Finally,the characteristics of the spatial network of the tourism economy were explored in 15 prefectures of Xinjiang,China from 2008 to 2017 by using the social network analysis method.The main conclusions are as follows: (1) From 2008 to 2017,the average density of the Tourism Economic Association Network in Xinjiang was only 0.356,the average network efficiency was 0.718,and the average network hierarchy was 0.367.(2) In the past ten years,Urumqi,Yili,Kashi,Changji,Turpan,and other locations had both high-degree centrality and medium centrality; Altay and Bazhou had high degree centrality and low-medium centrality; Karamay had low-degree centrality and high-medium centrality; Bozhou,Hotan and Hami areas,Tacheng area,Kezhou and Aksu areas,Shihezi city,and other locations had doubly low-degree centrality and medium centrality.(3) Urumqi,Changji,Kashi,Ili,and Altay belonged to the “two-way spillover plate” within the research time limit; Shihezi,Karamay,Bazhou,and Turpan belonged to the broker plate; Bozhou,Hami,and Tacheng belonged to net benefit plate; and Aksu,Kezhou,and Hetian belonged to the main benefit plate.This study aims to enrich the perspective of tourism economy network research and provides a quantitative basis for economic development of tourism and cooperation in Xinjiang.

参考文献

[1]汤放华,汤慧,孙倩.长江中游城市集群经济网络结构分析[J].地理学报,2013,68(10):1357-1366.[TANG Fanghua,TANG Hui,SUN Qian.Analysis of the economic network structure of urban clusters in the middle reaches of the Yangtze River[J].Acta Geographica Sinica,2013,68(10):1357-1366.] [2]王松茂,方良彦,邓峰.新疆旅游经济时空差异演变分析[J].商业研究,2013,55(6):195-199.[WANG Songmao,FANG Liangyan,DENG Feng.Evolution analysis of spatial-temporal differences in tourism economy in Xinjiang[J].Commercial Research,2013,55(6):195-199.] [3]刘佳,李莹莹.国内外基于社会网络理论的旅游研究综述与启示[J].资源开发与市场,2016,32(9):1134-1138.[LIU Jia,LI Yingying.Summary and enlightenment of tourism research based on social network theory at home and abroad[J].Resource Development & Market,2016,32(9):1134-1138.] [4]HWANG Y H,GRETZEL U,FESENMAIER D R.Multicity trip patterns:Tourists to the United States[J].Annals of Tourism Research,2006,33(4):1057-1078. [5]SHIH H Y.Network characteristics of drive tourism destinations: An application of network analysis in tourism[J].Tourism Management,2006,27(5):1029-1039. [6]SCOTT N,COOPER C,BAGGIO R.Destination networks:Four Australian cases[J].Annals of Tourism Research,2008,35(1):169-188. [7]HONG T,MA T,HUAN T C.Network behavior as driving forces for tourism flows[J].Journal of Business Research,2015,68(1):146-156. [8]JUAN C G,JAVER G E,CARMEN M.Identification of tourist hot spots based on social networks:A comparative analysis of European metropolises using photo sharing services and GIS[J].Applied Geography,2015,63(12):408-417. [9]汪德根.京沪高铁对主要站点旅游流时空分布影响[J].旅游学刊,2014,29(1):75-82.[WANG Degen.Impact of Beijing-Shanghai high-speed railway on spatial-temporal distribution of tourism flow at major sites[J].Tourism Tribune,2014,29(1):75-82.] [10]KATHRYN P.The evolution and transformation of a tourism destination network:The waitomo caves,New Zealand[J].Tourism Management,2003,24(2):203-216. [11]HAGEN W.Inter-organizational cooperation in sport tourism:A social network analysis[J].Sport Management Review,2015,18(4):542-554. [12]李敬,陈澍,万广华,等.中国区域经济增长的空间关联及其解释——基于网络分析方法[J].经济研究,2014,(11):4-16.[LI Jing,CHEN Shu,WAN Guanghua,et al.Spatial correlation of regional economic growth in China and its explanation based on network analysis method[J].Economic Research Journal,2014,(11):4-16.] [13]王俊,徐金海,夏杰长.中国区域旅游经济空间关联结构及其效应研究——基于社会网络分析[J].旅游学刊,2017,32(7):15-24.[WANG Jun,XU Jinhai,XIA Jiechang.Spatial relevance structure and its effects of regional tourism economy in China:Based on social network analysis[J].Tourism Tribune,2017,32(7):15-24.] [14]邹永广.“一带一路”中国主要节点城市旅游的经济联系——空间结构与合作格局[J].经济管理,2017,39(5):22-34.[ZOU Yongguang.The economic link between the “one belt and one way” tourism of China’s main node cities:Spatial structure and cooperation pattern[J].Economic Management Journal,2017,39(5):22-34.] [15]李山,王铮,钟章奇.旅游空间相互作用的引力模型及其应用[J].地理学报,2012,67(4):526-544.[LI Shan,WANG Zheng,ZHONG Zhangqi.Gravitational model of tourism spatial interaction and its application[J].Acta Geographica Sinica,2012,67(4):526-544.] [16]刘少湃,田纪鹏,陆林.上海迪士尼在建景区客源市场空间结构预测——旅游引力模型的修正及应用[J].地理学报,2016,71(2):304-321.[LIU Shaopai,TIAN Jipeng,LU Lin.Shanghai Disne[JP8]y’[JP]s spatial structure prediction of tourist market in scenic spots under construction:Revision and application of tourism gravity model[J].Acta Geographica Sinica,2016,71(2):304-321.] [17]刘军.社会网络分析导论[M].北京:社会科学文献出版社,2004.[LIU Jun.Introduction to social network analysis[M].Beijing:Social Science Literature Publishing House,2004.] [18]BAGGIO R,SCOTT N.Network science:A review focused on tourism[J].Annals of Tourism Research,2010,37(3):802-827. [19]WHITE H C ,BOORMAN S A ,BREIGER R L.Social structures from multiple networks:Blockmodels of roles and positions[J].American Journal of Sociology,1976,81(6):1384-1446. [20]王松茂,瓦哈甫·哈力克,邓峰.新疆旅游产业全要素生产率的时空演变[J].经济地理,2016,36(5):202-207.[WANG Songmao,WAHAF Halik,DENG Feng.Spatial and temporal evolution of total factor productivity of tourism industry in Xinjiang[J].Economic Geography,2016,36(5):202-207.] [21]何昭丽,孙慧,张振龙.中国入境旅游发展效率及其影响因素研究[J].干旱区地理,2017,40(6):1282-1289.[HE Zhaoli,SUN Hui,ZHANG Zhenlong.Study on the efficiency of China’s inbound tourism development and its influencing factors[J].Arid Land Geography,2017,40(6):1282-1289.]
文章导航

/