Abstract
Abstract. The regional disparities of online map user access volume (use ‘user access volume’ in this paper to indicate briefly) is a topic of growing interest with the increment of popularity in public users, which helps to target the construction of geographic information services for different areas. At first place we statistically analysed the online map user access logs and quantified these regional access disparities on different scales. The results show that the volume of user access is decreasing from east to the west in China as a whole, while East China produces the most access volume; these cities are also the crucial economic and transport centres. Then Principal Component Regression (PCR) is applied to explore the regional disparities of user access volume. A determining model for Online Map access volume is proposed afterwards, which indicates that area scale is the primary determining factor for regional disparities, followed by public transport development level and public service development level. Other factors like user quality index and financial index have very limited influence on the user access volume. According to the study of regional disparities in user access volume, map providers can reasonably dispatch and allocate the data resources and service resources in each area and improve the operational efficiency of the Online Map server cluster.
Highlights
China has shown remarkable and unprecedented dynamics
After introducing the current situation on the research of regional disparities in the development of Internet, and the characteristics and access pattern that have been uncovered in online map users, this paper takes Map World as an example, statically analyzes its access log and demonstrate the regional disparities of user access volume
With the method of Principal Component Regression, we established a regression model that explores the relationship between online map users' access volume and its determining factors
Summary
China has shown remarkable and unprecedented dynamics With the method of Principal Component Regression, we established a regression model that explores the relationship between online map users' access volume and its determining factors. The proposed model shows that the regional scale is the most important determining factor for access volume, public transport development level and public service development level are subordinate factors, while the effect of population quality and GDP is inconspicuous. The double-blind peer-review was conducted on the basis of the full paper
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