湖南居民省内旅游流网络结构特征分析
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摘要
由于统计数据的限制,国内旅游流网络结构的研究相对较少,且样本量有限,很难全面反映旅游流网络结构特征及其季节变化.采用样本量更大、时间分辨率更高的网络关注度数据,利用社会网络分析等方法,揭示湖南居民省内旅游流网络结构特征及其季节变化,考察各市州在整个网络中的作用.结果发现:①14个市州共有182条旅游流,流量较大的旅游流一般都发生在经济发展水平较高、人口较多、旅游资源丰富的城市之间,旅游流呈东西多、南北少的特点,有明显的区域特征;②湖南居民省内旅游流网络的关联度为0.99,旅游流网络非常稳健,但联系强度相对较弱;经济发达、旅游资源比较丰富的市州往往处于核心区,对其他城市具有控制作用,核心区各市州旅游流密集,边缘区相对独立.利用块模型将14个城市划分为4个板块,发现板块之间都保持着或弱或强的联系,第一板块整体的输出与引入关系较其他板块发展更完整,在整个网络中起着重要作用;③各市州旅游流的输出与引入、网络整体密度、度数中心势、中间中心势,以及各城市中心度均有明显的季节变化.湖南省旅游流网络虽然稳健,但联系强度相对较弱,且季节性变化明显,各市州需在提升自身经济发展水平的同时,进一步加强旅游资源开发与区域旅游合作,从而提高各市州间的旅游流联系,促进区域旅游的发展.
With data restriction,the network structure of domestic tourism flow studies are relatively few,and the sample size is limited,fully reflecting its characteristics and seasonal changes is difficult. We used the network attentiondatawithhighersamplesizeandhighertimeresolution,usingsocialnetworkanalysistorevealthe characteristics and seasonal variations of tourist flow network structure in Hunan Province and examine urban role in it. ①There are 182 tourist flows in 14 cities,greater tourist flows generally occur in cities with higher GDP,larger population and rich tourism resources;the tourist flow with obvious regional characteristics in Hunan Province is east and west more,north and south less. ②The correlation degree of stable tourist flow network is 0.99,but the contact strength is relatively weak;the core area city with higher GDP and abundant tourism resources have control effect to others,its tourist flow is concentrated,marginal zone is relatively independent. Using the block model to divide 14 cities into 4 sections,we find that weak or strong connections exist in the sections. The output and introduction of the whole first section is more complete and important in the whole network than others. ③There is a obvious change with seasons in output and introduction of tourism flow,whole density,degree central potential,central potential and centrality in cities. Although the tourist flow network in Hunan Province is robust,the contact intensity is relatively weak and the seasonal changes are obvious. Cities need to enhance their economic development and strengthen the cooperation between regional tourism resources development so as to improve the tourist flow links,and promote the development of regional tourism.
With data restriction,the network structure of domestic tourism flow studies are relatively few,and the sample size is limited,fully reflecting its characteristics and seasonal changes is difficult. We used the network attentiondatawithhighersamplesizeandhighertimeresolution,usingsocialnetworkanalysistorevealthe characteristics and seasonal variations of tourist flow network structure in Hunan Province and examine urban role in it. ①There are 182 tourist flows in 14 cities,greater tourist flows generally occur in cities with higher GDP,larger population and rich tourism resources;the tourist flow with obvious regional characteristics in Hunan Province is east and west more,north and south less. ②The correlation degree of stable tourist flow network is 0.99,but the contact strength is relatively weak;the core area city with higher GDP and abundant tourism resources have control effect to others,its tourist flow is concentrated,marginal zone is relatively independent. Using the block model to divide 14 cities into 4 sections,we find that weak or strong connections exist in the sections. The output and introduction of the whole first section is more complete and important in the whole network than others. ③There is a obvious change with seasons in output and introduction of tourism flow,whole density,degree central potential,central potential and centrality in cities. Although the tourist flow network in Hunan Province is robust,the contact intensity is relatively weak and the seasonal changes are obvious. Cities need to enhance their economic development and strengthen the cooperation between regional tourism resources development so as to improve the tourist flow links,and promote the development of regional tourism.
引文
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[21]黄泰.长三角城市群旅游流潜力格局演变及其影响因素[J].资源科学,2016,38(2):364-376.
[22]王娟,胡静,贾垚焱,等.城市旅游流的网络结构特征及流动方式--以武汉自助游为例[J].经济地理,2016,36(6):176-184.
[23]周慧玲,许春晓.基于游记行程的湖南旅游流空间网络结构特征[J].经济地理,2016,36(10):201-206.
[24]李山,邱荣旭,陈玲.基于百度指数的旅游景区络空间关注度:时间分布及其前兆效应[J].地理与地理信息科学,2008,24(6):102-107.
[25]黄先开,张丽峰,丁于思.百度指数与旅游景区游客量的关系及预测研究--以北京故宫为例[J].旅游学刊,2013,28(11):93-100.
[26]王硕,曾克峰,童洁,等.黄金周风景名胜区旅游客流量与网络关注度相关性分析--以庐山、华山、八达岭长城风景名胜区为例[J].经济地理,2013,33(11):182-186.
[27]汪秋菊,黄明,刘宇.城市旅游客流量--网络关注度空间分布特征与耦合分析[J].地理与地理信息科学,2015,31(5):102-106.
[28]马丽君,孙根年,黄芸玛,等.城市国内客流量与游客网络关注度时空相关分析[J].经济地理,2011,31(4):680-685.
[29]马丽君,郭留留,吴志才.“爸爸去哪儿”对拍摄地旅游发展的影响--基于游客网络关注度的分析[J].旅游科学,2016,30(3):57-68.
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[34]刘军.整体网分析讲义--UCINET软件实用指南[M].上海:格致出版社,2009.
[35]马丽君,龙云.基于网络关注度的湖南省居民旅游需求时空特征[J].经济地理,2017,37(2):201-208.
[2]WITT S F,MARTIN C A.Econometric models for forecasting international tourism demand[J].Journal of Travel Research,1987,25(3):23-30.
[3]PEARCE D.Japanese tourists in Europe[J].Geographical Review of Japan,1995,68(1):63-74.
[4]MITSUTAKE M.Japanese tourists in transition countries of Central Europe:present behavior and future trends[J].Tourism Management,1998,19(5):433-443.
[5]PRIDEAUX B.Factors affecting bilateral tourist flows[J].Annals of Tourism Research,2005,32(3):780-801.
[6]SANTANA-GALLEGO M,LEDESMA-RODRíGUEZ F J,PéREZ-RODRíGUEZ J V.International trade and tourism flows:An extension of the gravity model[J].Economic Modelling,2016,52(1):1026-1033.
[7]马耀峰,李天顺.中国入境旅游研究[M].北京:科学出版社,1999.
[8]张捷,都金康,周寅康,等.观光旅游地客流时间分布特性的比较研究--以九寨沟、黄山及福建永安桃源洞鳞隐石林国家风景名胜区为例[J].地理科学,1999,19(1):49-54.
[9]马晓龙,吴必虎.西安旅游区旅游流空间结构研究[J].地理与地理信息科学,2004,20(5):95-97.
[10]冯学钢,黄和平,邱建辉.我国入境旅游流季节性特征及其时空演变研究--基于22个热点旅游城市面板数据的实证分析[J].华东经济管理,2015,29(6):1-9.
[11]刘宏盈,马耀峰.入境旅游流空间转移与省域旅游经济联系强度耦合分析--以上海入境旅游流西向扩散为例[J].资源科学,2008,30(8):1162-1168.
[12]陈刚强,李映辉.中国区域旅游规模的空间结构与变化[J].旅游学刊,2011,26(11):84-88.
[13]万绪才,王厚廷,傅朝霞,等.中国城市入境旅游发展差异及其影响因素--以重点旅游城市为例[J].地理研究,2013,32(2):337-346.
[14]陈秀琼,黄福才.基于社会网络理论的旅游系统空间结构优化研究[J].地理与地理信息科学,2006,22(5):75-80.
[15]杨兴柱,吴静.南京市旅游流网络结构特征历时性比较[J].旅游科学,2015,29(4):35-45.
[16]王金莹,吴晋峰,唐澜,等.亚洲入境旅游流地理分布及网络结构特征分析[J].资源科学,2013,35(8):1701-1709.
[17]王永明,马耀峰,王美霞.中国入境游客多城市旅游空间网络结构[J].地理科学进展,2012,31(4):518-526.
[18]吴晋峰.入境外国旅游流网络分布、性质和结构特征研究[J].干旱区资源与环境,2014,28(7):177-182.
[19]彭红松,陆林,路幸福,等.基于社会网络方法的跨界旅游客流网络结构研究--以泸沽湖为例[J].地理科学,2014,34(9):1041-1050.
[20]林文辉,毛峰,何虹,等.杭州市景点旅游流空间网络分析[J].浙江大学学报(理学版),2016,43(4):458-491.
[21]黄泰.长三角城市群旅游流潜力格局演变及其影响因素[J].资源科学,2016,38(2):364-376.
[22]王娟,胡静,贾垚焱,等.城市旅游流的网络结构特征及流动方式--以武汉自助游为例[J].经济地理,2016,36(6):176-184.
[23]周慧玲,许春晓.基于游记行程的湖南旅游流空间网络结构特征[J].经济地理,2016,36(10):201-206.
[24]李山,邱荣旭,陈玲.基于百度指数的旅游景区络空间关注度:时间分布及其前兆效应[J].地理与地理信息科学,2008,24(6):102-107.
[25]黄先开,张丽峰,丁于思.百度指数与旅游景区游客量的关系及预测研究--以北京故宫为例[J].旅游学刊,2013,28(11):93-100.
[26]王硕,曾克峰,童洁,等.黄金周风景名胜区旅游客流量与网络关注度相关性分析--以庐山、华山、八达岭长城风景名胜区为例[J].经济地理,2013,33(11):182-186.
[27]汪秋菊,黄明,刘宇.城市旅游客流量--网络关注度空间分布特征与耦合分析[J].地理与地理信息科学,2015,31(5):102-106.
[28]马丽君,孙根年,黄芸玛,等.城市国内客流量与游客网络关注度时空相关分析[J].经济地理,2011,31(4):680-685.
[29]马丽君,郭留留,吴志才.“爸爸去哪儿”对拍摄地旅游发展的影响--基于游客网络关注度的分析[J].旅游科学,2016,30(3):57-68.
[30]湖南省统计局.统计年鉴[EB/OL].[2017-06-20].http://tjj.hunan.gov.cn/tjsj/tjnj/.
[31]湖南省统计局.各市州统计公报[EB/OL].[2017-06-22].http://tjj.hunan.gov.cn/tjfx/tjgb/szgb/.
[32]湖南旅游监管网.等级旅游景区管理[EB/OL].[2017-06-18].http://jg.hnt.gov.cn/publics/search/search-orgQuery.
[33]百度地图.路线[EB/OL].[2017-06-22].https://map.baidu.com/mobile/webapp/index/index/qt=cur&wd=%E6%B9%98%E6%BD%AD%E5%B8%82&from=maponline&tn=m01&ie=utf-8=utf-8/tab=line.
[34]刘军.整体网分析讲义--UCINET软件实用指南[M].上海:格致出版社,2009.
[35]马丽君,龙云.基于网络关注度的湖南省居民旅游需求时空特征[J].经济地理,2017,37(2):201-208.