通过百度、Google、Alexa、Cnzz等多种网络搜索引擎和网站访问量统计工具获取了24个旅游网站分省访问量资料,运用Origin软件评估了旅游网站信息流距离衰减的曲线模型,在此基础上深入研究了旅游网站信息流距离衰减的集中度问题。研究经过3个阶段,逐级递进分别应用Zipf定律、地理集中度指数和指数模型3种方法,描述了空间分布的集中性,揭示了本地集中性与经济集中性特征,讨论了本地集中性与指数模型符合性的关系。研究发现:①旅游网站信息流的位序—规模分布符合Zipf定律,以单分形特征为主,其信息流的规模结构主体呈Pareto分布模式,具有明显的空间分布集中性,该集中性表现为随分维值大小而相应变化。②各旅游网站信息流距离衰减的区位商值大于1的省份主要为网站所在省或经济发达省份,距离衰减具有明显的本地集中性和经济集中性特征;各旅游网站信息流距离衰减的空间洛伦茨曲线呈内凹型,且多数网站基尼系数大于0.5,距离衰减的集中度较高、空间分布不均衡。③旅游网站信息流距离衰减的本地集中性受旅游网站性质影响,且其本地集中性越强,指数模型拟合优度指数越高,指数模型与网站数据点的匹配效果越好,各省份访问量越接近标准曲线,与拟合曲线的吻合度越高。④旅游网站信息流距离衰减的集中性特征,为旅游目的地确定目标市场和旅游网站的建设与营销提供了理论支持。
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.
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