Abstract Bicycle-sharing systems have experienced strong growth in the last two decades as part of a global trend that started in the 1990s and accelerated after 2005. Early bicycle-sharing systems were provided primarily as a public service by cities. Today, major international bicycle-sharing companies are emerging and seeking to expand their operations to new cities. Two major strategic questions arise: (1) which cities should be considered for expansion and (2) what should be the geographical extent of the service area? An important factor in such decision-making is the expected demand for bicycle-sharing because it relates directly to potential revenue. In this paper, booking data from an electric bicycle-sharing system was used to estimate and assess models for bicycle-sharing demand and to predict expansion to a new city. Employment, population, bars, restaurants and distance to a central location were amongst the most important predictors in terms of variance explained in the same city. Omitting centrality measures improved predictions for the new city.

中文翻译：

---

将 a(n)（电动）自行车共享系统扩展到新城市：使用空间回归和随机森林预测需求

摘要 作为始于 1990 年代并在 2005 年后加速发展的全球趋势的一部分，自行车共享系统在过去二十年经历了强劲增长。早期的自行车共享系统主要由城市提供公共服务。如今，大型国际共享单车公司不断涌现，并寻求将业务扩展到新的城市。出现了两个主要的战略问题：（1）应该考虑扩展哪些城市；（2）服务区的地理范围应该是多少？这种决策的一个重要因素是对共享单车的预期需求，因为它直接关系到潜在收入。在本文中，来自电动自行车共享系统的预订数据用于估计和评估自行车共享需求模型，并预测向新城市的扩张。就业，人口、酒吧、餐馆和到中心位置的距离是在同一城市解释的方差方面最重要的预测因素之一。省略中心性度量改进了对新城市的预测。