旅游网站访问者行为时间分布的复杂化与网站功能深度使用分析

THE TIME DISTRIBUTION COMPLICATION OF TOURISM WEBSITE USERS BEHAVIOR AND USABILITY ANALYSIS OF TOURISM WEBSITE FUNCTION IN DEPTH

应用时间日志调查系统,以及Alexa排名、访问量、页面浏览量查询系统,获得了不同类型旅游网站访问者日内、周内、年内行为的近新资料,基此总结了时间分布的复杂化特征及其与网站功能深度使用之间的内在联系。研究发现:旅游网站访问者日内行为不同于一般峰值规律的均匀化分布形态特例增多,其主要存在于网上交流与组织功能较强大的网站类型上;旅游网站访问者周内行为周末较少的状态正在改变,信息功能类网站较其它功能类类网站周末增多现象显著;旅游网站访问者年内行为已出现节后访问高峰的现象,访问行为时间分布不断广泛化。研究认为:访问者行为时间分布的复杂化是基于网站需求的多样化及相应的网站使用时间延长而产生的,由此可构建时间替代、时间效率、活动兼顾的共同作用机制。

To obtain the figures of visitors＇ behavior on tourism websites, this paper uses time daily survey system along with web traffic metrics and rankings from Alexa.com. The inner link between complication characteristics of time distribution and depth use of tourism website function are extracted. The authors find that （1） the mainstream of visitors＇ daily behaviors of tourism website is still double-peak and has further expansion into single-peak, triple-peak and multiple-peak, and more exceptional patterns which are different from average distribution of general peak regular pattern mainly exist in the types of online communication and strongly organized function website; （2） the leading trend in tourism website visiting is still more in the weekdays and less over the weekends, but there are some positive changes in the weekends which is that rising trend in the weekends can be found more in informational functional websites than regular functional ones. Some urban tourism websites which have the intake of population characteristics and technical feature have more diverse online needs; （3） the dominant browsing peak of tourism website visitors＇ annual behavior is still in the early before holidays. Among schedule, self-service and membership, information and outbound types of tourism website, different performances of peak strength and time distribution can be found. Recently, peak phenomenon after holidays has occurred and the time distribution of browsing behavior is increasingly spreading. The study indicated that the reasons for the complication of time distribution of users＇ behaviors are the diversity ofwebsite demands and the incremental to websites＇ using time. Hence, it is possible to build up thefunctioning mechanism by combining time replacement, time efficiency and activities concurrence.