Urban environment effects on private and corporate carsharing: A machine learning analysis
利用法国里昂的汽车共享交易数据，通过机器学习分析城市环境对私人和企业两类会员需求的影响，发现私人需求更依赖人口社会人口特征，企业需求更受邻近特定经济部门影响。
This paper investigates the demand for carsharing of corporate and private members, with a focus on the influence of the urban environment. The results of machine learning on carsharing transaction data from Lyon, France, highlight distinct carsharing profiles between the two market segments. The demand of each segment is found to be driven by various factors related to the urban environment. Private demand is more dependent on the sociodemographic characteristics of the population, while corporate demand is more influenced by proximity to specific economic sectors. Both services are sensitive to proximity to public transport and vehicle size.