流空间的特征分析及其流空间结构的有效揭示与解析,对于厘清和掌握流空间的科学内涵与外延及其内在机制的形成具有极其重要的学术价值。文章基于在线预订数据提取、处理、归纳及分析,结合社会网络分析技术,对长江三角洲地区旅游流的网络结构特征及其影响因素进行分析。结果表明:①旅游流网络结构整体上较为松散且存在不均衡性,具有明显的核心区和边缘区,“核心—边缘”结构特质清晰,“中间重、两头轻”的网络格局已初步形成,核心区的内部联系较之边缘区,密切联系程度显著。②从凝聚子群的分析来看,上海、南京、杭州、苏州、宁波、无锡、常州等城市出现较高的频次,成为支撑整个旅游网络体系重要的派系节点,对于旅游网络体系的形成发挥重要价值。从结构洞指标分析来看,上海、南京、杭州在旅游流网络中占据较多优势,节点的有效规模和效率较高,拥有更多的竞争机会和非替代性区位优势。③针对流空间网络体系的影响因素深度剖析表明,旅游资源禀赋和交通发展水平对于空间流的走向作用更为明显,地区经济发展水平、旅游服务接待水平的作用依然较大,不同因素之间的共同作用和影响促进了流空间在长三角地区网络结构的形成和发展。
Revealing and parsing effectively on the characters and the structure of flow space is of great academic value on clarifying and grasping it's scientific connotation and extension as well as inner mechanism. On the basis of extracting, processing, concluding and analyzing of online reserve data, with Social Network Analysis, this paper studied on the network structure features and influence factors of the Yangtze River Delta Region City's tourism flows. The results showed that:(1) the network structure of city's tourism flow was generally loose and disproportional, it had distinct core areas and marginal areas ,and the feature of ‘core-peripheral' structure was clear, the network format had developed initially into a situation of ‘the middle weighs both ends', besides, the inner relationships in core areas were more frequent than marginal areas.(2)In terms of cohesive subgroups analysis, cities like Shanghai, Nanjing, Suzhou, Ningbo, Wuxi and Changzhou had a high frequency and become important faction nodes of the whole tourism network system, which had great value to the formation of tourism network system. In terms of structure holes index analysis, Shanghai, Nanjing, Hangzhou had more advantages in tourism flows network, the effective scale and efficiency of city nodes were higher, as a result, they had much more competitive opportunities and non-fungible regional advantages.(3)With the depth study of the influence of flow space network system, it manifested that tourism resource endowment and traffic development played an evident role on the direction of space flow, the development of local economy and tourism service quality still had an important effect, besides, the combined effect and influence among different factors drove the formation and development of flow space in the Yangtze River Delta network structure.
[1] 孙九霞,周尚意,王宁,等. 跨学科聚焦的新领域:流动的时间、空间与社会[J]. 地理研究,2016,35(10):1 801-1 818.
[2] 马耀峰,李天顺,刘新平. 中国入境旅游研究[M]. 北京:科学出版社,1999.
[3] Dredge D.Networks,conflict and collaborative communities[J]. Journal of Sustainable Tourism,2006,14(6):562-581.
[4] Shinh H,Network characteristics of drive tourism destinations:An application of network analysis in tourism[J]. Tourism Management,2015,27(5):1 029-1 039.
[5] Albert N.Centralized decentralization of tourism development:a network perspective[J]. Annals of Tourism Reasearch,2012,40(5):235-259.
[6] Dritsakis N.Cointegration analysis of German and British tour-ism demand for Greece[J]. Tourism Management,2014,25:111-119.
[7] Jae H K,Imad A M,Forecasting international tourist flows to Australia:A comparison between the direct and indirect methods[J]. Tourism Management,2005,26(1):69-78.
[8] Haiyan Song,Witt S F.Forecasting international tourist flows to Macau[J]. Tourism Management,2006,27(2):214-224.
[9] 黄震方,袁林旺,俞肇元. 盐城麋鹿生态旅游区游客变化特征及预测[J]. 地理学报,2007,62(12):1 277-1 287.
[10] 陆林,宣国富,章锦河,等. 海滨型与山岳型旅游地客流季节性比较——以三亚、北海、普陀山、黄山、九华山为例[J]. 地理学报,2002,57(6):731-740.
[11] 孙根年,王洁洁. 1987年来台海关系变化对台湾入境大陆客流量的影响[J]. 地理学报,2009,64(12):1 513-1 522.
[12] 牛亚菲,谢丽波,刘春凤,等. 北京市旅游客流时空分布特征与调控对策[J]. 地理研究,2005,24(2):283-292.
[13] 杨霞,刘晓鹰. 旅游流量、旅游构成与西部地区贫困减缓[J]. 旅游学刊,2013,28(6):47-55.
[14] 阎友兵,贺文娟. 国内旅游流流量与流质的时空演化分析[J]. 经济地理,2013,33(4):179-185.
[15] Dredge D.Networks,conflict and collaborative communities[J]. Journal of Sustainable Tourism,2016,14(6):562-581.
[16] Marina N,Birte S,Trisha S.Networks,cluster,and innovation in tourism:A UK experience[J]. Tourism Management,2013,27(4):1 141-1 152.
[17] Lew A,McKercher B. Modeling tourist movement:a local des-tination analysis[J]. Annals of Tourism Research,2006,33(4):403-423.
[18] 钟士恩,任黎秀,欧阳怀龙,等. 世界遗产地庐山“圈层飞地”型旅游客源市场空间结构研究[J]. 地理与地理信息科学,2007,23(4):76-80.
[19] 吴必虎,唐俊雅,黄安民,等. 中国城市居民旅游目的地选择行为研究[J]. 地理学报,1997,52(2):97-103.
[20] 杨国良,钟亚秋,王李清,等. 四川省旅游流空间扩散方向及路径[J]. 地理科学进展,2008,27(1):56-63.
[21] 薛莹. 旅游流在区域内聚:从自组织到组织——区域旅游研究的一个理论框架[J]. 旅游学刊,2006,21(4):47-54.
[22] 杨兴柱,顾朝林,王群,等. 旅游流驱动力系统分析[J]. 地理研究,2011,30(1):23-36.
[23] 刘泽华,李海涛,史春云,等. 短期旅游流时间分布对区域旅游空间结构的响应——以云南省黄金周旅游客流为例[J]. 地理学报,2010,65(12):1 624-1 632.
[24] 吴晋峰,包浩生. 旅游流距离衰减现象演绎研究[J]. 人文地理,2005,20(2):62-65.
[25] Sang H L,Jin Y C,Swung H Y,et al.Evaluating spatial cen-trality for integrated tourism management in rural areas using GIS and network analysis[J]. Tourism Management,2013,34(2):14-24.
[26] 杨国良,张捷,艾南山,等. 旅游流齐夫结构及空间差异化特征:以四川省为例[J]. 地理学报,2006,61(12):1 281-1 289.
[27] 陈超,刘家明,马海涛,等. 中国农民跨省旅游网络空间结构研究[J]. 地理学报,2013,68(4):547-558.
[28] 汪德根,钱佳,牛玉. 高铁网络化下中国城市旅游场强空间格局及演化[J]. 地理学报,2016,71(10):1 784-1 800.
[29] Albert N.Centralized decentralization of tourism development:a network perspective[J]. Annals of Tourism Research,2012,40(5):235-259.
[30] 靳诚,徐菁,黄震方,等. 南京城市内部景点间游客流动特征分析[J]. 地理学报,2014,69(12):1 858-1 870.
[31] 陈浩,陆林,郑嬗婷,等. 基于旅游流的城市群旅游地旅游空间网络结构分析:以珠江三角洲城市群为例[J]. 地理学报,2011,66(2):257-266.
[32] Bhat S,Milne S.Network effects on cooperation in destination website development[J]. Tourism Management,2015,29(6):1 131-1 140.