The Concentration Analysis on Distance Decay of Information Flow in Tourism Websites

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  • Faculty of Tourism, Hebei Normal University, Shijiazhuang, Hebei 050091, China

Received date: 2010-09-13

  Revised date: 2011-04-07

  Online published: 1997-07-20

Abstract

This paper gets the traffic data of each province in 24 tourism websites by using Baidu, Google, Alexa, Cnzz and other Internet search engines and statistic tool of website traffic.It evaluates the curve model of distance decay of information flow in tourism website, and based on this, further explores the concentration of distance decay of information flow in tourism website.This study includes three stages in which those websites are analyzed by means of going forward by using Zipf law, geographic concentration index and the exponential model.The paper not only describes the concentration of spatial distribution, but also reveals the character of local concentration and economic concentration, and discusses the relationship between local concentration and compliance of exponential model.The research findings are:① rank-size distribution of information flow in tourism website follows Zipf law, mainly shows a single fractal characteristic, and the main scale structure of information flow shows Pareto distribution pattern with significant concentration of spatial distribution.The concentration changed correspondingly with the value of fractal dimension.② The provinces that location quotient value of distance decay of information flow in tourism website bigger than 1 are the tourism website located provinces or economy developed provinces.And the distance decay has obvious local concentration and economic concentration.The spatial Lorenz curve of the distance decay of information flow in tourism websites are concave, and the Gini coefficients of the most tourism websites are more than 0.5.The concentration of distance decay is higher, and imbalance in spatial distribution.③ The local concentration of distance decay of information flow in tourism website is influenced by the nature of the tourism website.The stronger local concentration, the higher of the (goodness-of-fit index), the better match of exponential model with the data points of the website, the closer to standard curve of the various provinces’traffic, the higher match with the fitting curves, the higher traffic proportion of tourism website located province.④ The concentration character of information flow distance decay in tourism websites give a theoretical support to tourist destination defining and tourism websites building and marketing.

Cite this article

ZHANG Qiu-Luan, LU Zi . The Concentration Analysis on Distance Decay of Information Flow in Tourism Websites[J]. SCIENTIA GEOGRAPHICA SINICA, 2011 , 31(7) : 885 -890 . DOI: 10.13249/j.cnki.sgs.2011.07.885

References

[1] Skadberg Y X,Skadberg A N,Kimmel J R.Flow experience and its impact on the effectiveness of a tourism website[J].Information Technology &Tourism,2005,7(3-4):147-156.
[2] Davidson A P,Yu Y M.The internet and the occidental tourist:An analysis of Taiwan’s tourism websites from the perspective of western tourists[J].Information Technology & Tourism,2005,7(2):91-102.
[3] Lexhagen M.The importance of value-added services to support the customer search and purchase process on travel websites[J].Information Technology and Tourism,2005,7(2):119-135.
[4] Gek Woo Tan,Kwok Kee Wei.An empirical study of web browsing behaviour:Towards an effective website design[J].Electronic Commerce Research and Applications,2006,5(4):261-271.
[5] Hyejeong Kim,Linda S Niehm.The impact of website quality on information quality,value,and loyalty intentions in apparel retailing[J].Journal of Interactive Marketing,2009,23(3):221-233.
[6] Murnion S,Healey R G.Modeling distance decay effect in web sever information flows[J].Geographical Analysis,1998,30(4):285-303.
[7] Marc Barthelemy,Bernard Gondran,Eric Guichard.Spatial structure of the internet traffic[J].Physica,2003,A(319):633-642.
[8] Kannan R,Ray L,Sarangi S.The structure of information networks[J].Economic Theory,2007,30(1):119-134.
[9] Antonellis P,Makris C,Tsirakis N.Algorithms for clustering click stream data[J].Information Processing Letters,2009,109(8):381-385.
[10] 吴士锋,路 紫.网站信息流对现实人流替代函数的计算与应用——以中国互联网网络发展状况统计报告为例[J].经济地理,2007,27(1):22~25.
[11] Lu Zi,Han Ruiling,Duan Jie.Analyzing the effect of website information flow on realistic human flow using intelligent decision models[J].Knowledge-based Systems,2010,23(1):40-47.
[12] 杜丽娟,张 欣,路 紫.国内网站信息流对人流导引作用机理研究综述[J].地理与地理信息科学,2008,24(4):84~87.
[13] 李彦丽,路 紫.中美旅游网站对比分析及"虚拟距离衰减"预测模式[J].人文地理,2006,21(6):115~118.
[14] 路 紫,匙 芳,王 然,等.中国现实地理空间与虚拟网络空间的比较[J].地理科学,2008,28(5):601~606.
[15] Ritta Toivonen,Lauri Kovanen,mikko Kivel?,et?a1.A comparative study of social network models:network evolution models and nodal attribute models[J].Social Networks,2009,31(4):240-254.
[16] Galliano D,Roux P.Organizational motives and spatial effects in internet adoption and intensity of use:Evidence from French industrial firms[J].Annals of Regional Science,2008,42(2):425-448.
[17] 陈彦光,刘继生.城市系统的异速生长关系与位序-规模法则——对Steindl模型的修正与发展[J].地理科学,2001,21(5):412~416.
[18] 刘继生,陈彦光.作为CAS的复杂城市地理系统的SOC性质[J].地理科学,2007,27(2):129~135.
[19] 谈明洪,范存会.Zipf维数和城市规模分布的分维值的关系探讨[J].地理研究,2004,23(2):243~248.
[20] 孙才志,张 蕾.基于分形的中国地均农畜产品虚拟水规模分布的时空演变研究[J].地理科学,2009,29(3):402~408.
[21] 黄 泰,保继刚,刘艳艳,等.城市游憩场点系统结构分形及优化——以苏州市区为例[J].地理研究,2010,29(1):79~91.
[22] Paulo G,Octavio F,Douglas W.Dartboard tests for the location quotient[J].Regional Science and Urban Economics,2009,39(3):360-364.
[23] 冒宇晨,王腊春.长三角城市群旅游经济结构的分散化和均质化趋势[J].地理科学,2009,29(5):641~645.
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