Clustering Taxi Quantity Regulatory Levels of Chinese Capital Cities

Different purposes of taxi quantity control lead to different performances of quantity regulation in Chinese urban areas. To obtain a clear division of taxi quantity regulation levels of Chinese capital cities, a fuzzy c-means clustering is presented. The paper identifies six important demanding factors such as population, urban built-up area, transit volume, GDP, road area and amount of intercity passenger to get the corresponding indexes of urban taxi quantity regulatory levels. An efficient classification scheme is selected with clustering effectiveness analysis and F-statistics test after running a dedicated the MATLAB 7.0 program. The result indicates that thirty-one capital cities of mainland China are definitely classified into five categories. The categorization of quantity regulatory levels in this paper provide references for formulating the taxi license supply models.