Understanding travellers’ preferences for different types of trip destination based on mobile internet usage data
Understanding travellers’ preferences for different types of trip destination based on mobile internet usage data
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DOI：
10.1016/j.trc.2018.03.009
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发表时间：
2018-05
影响因子：
8.3
通讯作者：
Yihong Wang;G. Correia;B. Arem;H. Timmermans
中科院分区：
文献类型：
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作者：
Yihong Wang;G. Correia;B. Arem;H. Timmermans
新的移动数据源，如移动的电话痕迹，已被证明可以揭示个人在空间和时间上的移动。然而，这些数据中缺少旅行者的社会经济属性。因此，不可能对人口进行划分，也不可能深入了解影响旅行行为的社会人口因素。为了填补这一空白，我们使用移动的互联网使用行为，包括一个人的首选类型的网站和应用程序（应用程序）通过移动的互联网访问以及使用频率的水平，作为不同人群之间的区分元素。我们比较了每个细分市场的旅行行为的偏好类型的旅行目的地。利用兴趣点（POI）数据，根据网格单元的主要功能对城市的网格单元进行聚类，作为确定出行目的地类型的参考。该方法进行了测试，为中国上海市，通过使用一个特殊的移动的电话数据集，不仅包括时空的痕迹，但也移动的互联网使用行为的相同的用户。我们确定了旅客最喜欢的类别的移动的互联网内容和更频繁的类型的旅行目的地，他/她访问之间的统计显着的关系。例如，与其他人相比，最喜欢的应用程序/网站类型属于“旅游”类别的人更喜欢访问旅游区。此外，不同互联网使用强度的用户对目的地类型的偏好也不同。我们发现，更频繁地使用移动的互联网的人更有可能访问更多的商业区，而使用较少的人更喜欢在主要的住宅区进行活动。
New mobility data sources like mobile phone traces have been shown to reveal individuals’ movements in space and time. However, socioeconomic attributes of travellers are missing in those data. Consequently, it is not possible to partition the population and have an in-depth understanding of the socio-demographic factors influencing travel behaviour. Aiming at filling this gap, we use mobile internet usage behaviour, including one’s preferred type of website and application (app) visited through mobile internet as well as the level of usage frequency, as a distinguishing element between different population segments. We compare the travel behaviour of each segment in terms of the preference for types of trip destinations. The point of interest (POI) data are used to cluster grid cells of a city according to the main function of a grid cell, serving as a reference to determine the type of trip destination. The method is tested for the city of Shanghai, China, by using a special mobile phone dataset that includes not only the spatial-temporal traces but also the mobile internet usage behaviour of the same users. We identify statistically significant relationships between a traveller’s favourite category of mobile internet content and more frequent types of trip destinations that he/she visits. For example, compared to others, people whose favourite type of app/website is in the “tourism” category significantly preferred to visit touristy areas. Moreover, users with different levels of internet usage intensity show different preferences for types of destinations as well. We found that people who used mobile internet more intensively were more likely to visit more commercial areas, and people who used it less preferred to have activities in predominantly residential areas.