论文标题
建模自行车共享站活动：附近的企业和工作的效果
Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations
论文作者
论文摘要
这项研究的目的是确定明尼苏达州尼斯骑行的自行车站活动的相关性，这是明尼阿波利斯的自行车共享系统 - 明尼苏达州的圣保罗大都会地区。我们获得了2011年在Nice Ride Minnesota运营的116个自行车共享站的旅行数量。模型中包含的自变量的数据来自各种来源；包括2010年美国人口普查，大都会议会，区域规划局以及明尼阿波利斯和圣保罗的城市。我们使用对数线性和负二项式回归模型来评估这些因素平均每日旅行的边际影响。我们的模型具有较高的拟合度，并且13个自变量的每个变量在10％或更高的水平上都显着。 NICE乘车站的旅行数量与邻里社会人口统计数据（即年龄和种族），靠近中央商务区，靠近水的距离，通往小路的可及性，与其他自行车股份的距离以及经济活动措施有关。分析师可以使用这些结果来优化自行车共享操作，定位新站，并评估新自行车共享计划的潜力。
The purpose of this research is to identify correlates of bike station activity for Nice Ride Minnesota, a bike share system in Minneapolis - St. Paul Metropolitan Area in Minnesota. We obtained the number of trips to and from each of the 116 bike share stations operating in 2011 from Nice Ride Minnesota. Data for independent variables included in models come from a variety of sources; including the 2010 US Census, the Metropolitan Council, a regional planning agency, and the cities of Minneapolis and St. Paul. We use log-linear and negative binomial regression models to evaluate the marginal effects of these factors on average daily station trips. Our models have high goodness of fit, and each of 13 independent variables is significant at the 10% level or higher. The number of trips at Nice Ride stations is associated with neighborhood socio demographics (i.e., age and race), proximity to the central business district, proximity to water, accessibility to trails, distance to other bike share stations, and measures of economic activity. Analysts can use these results to optimize bike share operations, locate new stations, and evaluate the potential of new bike share programs.
