Journal of Guangxi Normal University(Natural Science Edition) ›› 2021, Vol. 39 ›› Issue (2): 162-173.doi: 10.16088/j.issn.1001-6600.2019050804

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Flow Space Features of Tourism Information Flow Based on Online Platforms:A Case Study of Core Cities in the Pearl River-West River Economic Belt

HUANG Song1*, WANG Mengfei1, LI Yanlin2   

  1. 1. College of History, Culture and Tourism, Guangxi Normal University, Guilin Guangxi 541001, China;
    2. College of Vocation-Technical Teachers, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2019-05-08 Revised:2020-11-08 Online:2021-03-25 Published:2021-04-15

Abstract: Tourism flow, as the foundation of tourism, is the essential areas of tourism geography research. Chinese scholars have made abundant achievements in the field of tourism flow research over the past 30 years. However, most of them focus on the tourist flow. However, the research on the tourism information flow which is the key factor that affects the tourist decision and then affects the tourism flow is rarely involved. Based on a universal scheme for quantitative research on the flow space structure features of tourism information flow, and taking the Pearl River-West River economic belt as the typical research area. 12 739 valid data of tourist information flow of 11 core cities in the Pearl River-West River economic belt (Guangzhou, Foshan, Yunfu, Zhaoqing, Nanning, Liuzhou, Laibin, Wuzhou, Baise, Chongzuo, Guigang) were obtained through 5 major online tourism platforms (Ctrip.com, Qunar.com, fliggy.com, ly.com and tuniu.com) in 2019. Firstly, the correlation matrix of tourism information flow is constructed. Then, this paper describes the flow space structure features of tourism information flow of 11 core cities in this region from 3 aspects: characteristics of direction and its rate, scale and principal-subordinate relationship of tourism information flow. Therefore, it provides a scientific basis for the construction and development of tourism integration of this area and a new perspective and method for the study of tourism flow. The results are obtained as follows: ①The provincial capital cities of Guangzhou and Nanning are not only the main gathering cities of tourism information flow in this region, but also the main export cities, and the aggregation and output of tourism information flow are 1.30, 2.55 and -0.13, 0.76 respectively. The non-provincial capital cities with special tourism resources of Chongzuo and Baise are the main gathering cities in this region, and the aggregation of tourism information flow are 1.74 and 1.55 respectively. The forward and backward flow of tourism information among the provincial capital cities and non-provincial capital cities with distinctive tourism resources is basically the same. Namely, the forward and backward flow of tourism information of Guangzhou$\leftrightarrows$Nanning and Chongzuo$\leftrightarrows$Baise are 0.55, 0.47, -0.25, -0.25. The difference of the forward and backward flow of tourism information between provincial capital cities and non-provincial capital cities with distinctive tourism resources is vast, such as Guangzhou$\leftrightarrows$Chongzuo (6.11, 0.11) and Guangzhou$\leftrightarrows$Baise (5.92, 0.26). ②Among 11 cities of this region, the scale of tourism information flow in Guangzhou (2.39) is far larger than that of other cities. Followed by Chongzuo (0.72) and Baise (0.62), with distinctive tourism resources, and their scales of tourism information flow are basically the same. Nanning (0.40), Foshan (0.22) take the fourth and fifth place. And other cities’ scales of tourism information flow are lower than the average level of this region. ③There is significant polarization of flow space for the tourism information flow in this region, and Guangzhou is the dominant city and the largest flow space node. Nanning, Chongzuo and Baise transformed from the sub-dominant divergent, gathering city and subordinate city of the first tourism information dominant flow to the sub-dominant gathering city, dominant city and sub-dominant gathering city of the second and third dominant flow respectively. It shows that the flow barycenter of tourism information dominant flow gradually shifts to Guangxi. At the same time, Baise and Chongzuo have obvious sub-regional characteristics. Other cities are subordinate cities of tourism information flow.

Key words: tourism information flow, flow space, structure features, online tourism platforms, core cities, Pearl River-West River economic belt

CLC Number: 

  • K902
[1] 吴泽智,陈性元,杨智,等.信息流控制研究进展[J].软件学报,2017,28(1):135-159.
[2] 唐顺铁,郭来喜.旅游流体系研究[J].旅游学刊,1998,13(3):38-41.
[3] 刘法建,张捷,章锦河,等.旅游流空间数据获取的基本方法分析:国内外研究综述及比较[J].旅游学刊,2012,27(6):101-109.
[4] SMALLWOOD C B,BECKLEY L E,MOORE S A.An analysis of visitor movement patterns using travel networks in a large marine park,north-western Australia[J].Tourism Management,2012,33(3):517-528.
[5] DE VITA G.The long-run impact of exchange rate regimes on international tourism flows[J].Tourism Management,2014,45:226-233.
[6] KIM J H,MOOSA I A.Forecasting international tourist flows to Australia:a comparison between the direct and indirect methods[J].Tourism Management,2005,26(1):69-78.
[7] BALLI F,BALLI H O,JEAN LOUIS R.The impacts of immigrants and institutions on bilateral tourism flows[J].Tourism Management,2016,52:221-229.
[8] 秦静,李郎平,唐鸣镝,等.基于地理标记照片的北京市入境旅游流空间特征[J].地理学报,2018,73(8):1556-1570.
[9] 阮文奇,郑向敏,李勇泉,等.中国入境旅游的“胡焕庸线”空间分布特征及驱动机理研究[J].经济地理,2018,38(3):181-189,199.
[10] 王永明,王美霞,吴殿廷,等.基于ZINB模型的中国省域间入境旅游流影响因素[J].经济地理,2018,38(11):234-240.
[11] 冯娜,李君轶.外向在线旅游信息流与入境旅游流的耦合分析:以美加入境旅游流为例[J].旅游学刊,2014,29(4):79-86.
[12] KORNELIUSSEN T,GREENACRE M.Information sources used by european tourists:A cross-national study[J].Journal of Travel Research,2017,57(2):193-205.
[13] CHUA A,SERVILLO L,MARCHEGGIANI E,et al.Mapping cilento:Using geotagged social media data to characterize tourist flows in southern Italy[J].Tourism Management,2016,57:295-310.
[14] TAN W K.The relationship between smartphone usage,tourist experience and trip satisfaction in the context of a nature-based destination[J].Telematics and Informatics,2017,34(2):614-627.
[15] MURNION S,HEALEY R G.Modeling distance decay effects in web server information flows[J].Geographical Analysis,1998,30(4):285-303.
[16] 张秋娈,路紫.旅游网站信息流距离衰减的集中度研究[J].地理科学,2011,31(7):885-890.
[17] KANNAN R,RAY L,SARANGI S.The structure of information networks[J].Economic Theory,2007,30(1):119-134.
[18] 徐敏,黄震方,曹芳东,等.基于在线预订数据分析的旅游流网络结构特征与影响因素:以长三角地区为例[J].经济地理,2018,38(6):193-202.
[19] LOZANO S,GUTIÉRREZ E.A complex network analysis of global tourism flows[J].International Journal of Tourism Research,2018,20(5):588-604.
[20] 闫闪闪,靳诚.基于多源数据的市域旅游流空间网络结构特征:以洛阳市为例[J].经济地理,2019,39(8):231-240.
[21] 路紫,赵亚红,吴士锋,等.旅游网站访问者行为的时间分布及导引分析[J].地理学报,2007,62(6):621-630.
[22] CASTELLES M.The informational city:information technology,economic restructuring and the urban-region progress[M].Oxford:Basil Blackwell,1989:146-147.
[23] 修春亮,魏冶.“流空间”视角的城市与区域结构[M].北京:科学出版社,2015:187-190.
[24] TAYLOR P J.Specification of the world city network[J].Geographical Analysis,2010,33(2):181-194.
[25] TOWNSEND A M.Network city and the global structure of the internet[J].American Behavioral Scientist,2001,44(10):1697-1716.
[26] GRUBESIC T H,O’KELLY M E.Using points of presence to measure accessibility to the commercial internet[J].The Professional Geographer,2002,54(2):259-278.
[27] 董超,修春亮,魏冶.基于通信流的吉林省流空间网络格局[J].地理学报,2014,69(4):510-519.
[28] 宋伟,李秀伟,修春亮.基于航空客流的中国城市层级结构分析[J].地理研究,2008,27(4):917-926.
[29] 冯兴华,修春亮,白立敏,等.基于公路交通流视角的吉林省城镇中心性及影响因素[J].经济地理,2019,39(1):64-72.
[30] 马丽亚,修春亮,冯兴华.多元流视角下东北城市网络特征分析[J].经济地理,2019,39(8):51-58.
[31] 孙中伟,路紫.流空间基本性质的地理学透视[J].地理与地理信息科学,2005,21(1):109-112.
[32] 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):1801-1818.
[33] ALMEIDA-SANTANA A,MORENO-GIL S.New trends in information search and their influence on destination loyalty:Digital destinations and relationship marketing[J].Journal of Destination Marketing &Management,2017,6(2):150-161.
[34] 姜博,修春亮,陈才.辽中南城市群城市流分析与模型阐释[J].经济地理,2008,28(5):853-856,861.
[35] 王聪,曹有挥,陈国伟.基于生产性服务业的长江三角洲城市网络[J].地理研究,2014,33(2):323-335.
[36] 王宁宁,陈锐,赵宇.基于信息流的互联网信息空间网络分析[J].地理研究,2016,35(1):137-147.
[37] BARNETT G A,CHON B,ROSEN D.The structure of the internet flows in cyberspace[J].Netcom,2001,15(1/2):61-80.
[38] HARGITTAI E.Weaving the western web:explaining differences in Internet connectivity among OECD countries[J].Telecommunications Policy,1999,23(10):701-718.
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