In recent years, few transportation modes have gained so much attention so quickly as shared e-scooters. Debates focus on usage patterns over shift effects to environmental impacts. Previous research has mainly been conducted in Asia and North America and in metropolitan areas. Potential interdependencies have been analysed mostly towards public transport (PT). Surprisingly, investigations concerning the usage of shared e-scooters and other shared mobility services have been scarce. However, understanding possible (inter-)dependencies and potentials for inter- and multimodality is crucial for policymakers and transport planners to design efficient and sustainable transportation systems. This is why we draw on an original data set of 118,047 shared e-scooter trips in Karlsruhe, a non-metropolitan city in southwest Germany and add information about carsharing and PT. Apart from station information for both modes, we add departure information for tramways, and weather data. Shared e-scooter data is retrieved via the local providers from November 2020 to April 2021, information about the stations of carsharing and PT is added via OpenStreetMap, and tramway service data is retrieved via the local authority. We find an average trip distance of 1.40 km and substantially less usage on Sundays. The potential of combining shared e-scooters is higher for PT than for carsharing. Shared e-scooter trips show longer distances in times of lower or none PT service. Negative binomial regression models with fixed effects for the PT or carsharing stations show that the number of tram departures positively affects shared e-scooter usage, particularly at off-peak times. Applying mode shift scenarios and focusing on the usage phase, the energy consumption effect of shared e-scooters is found to be between 5 to +0.5 TWh. However, it requires providers to revisit their operations and policy to rethink regulation to get even close to the multimodal or energy consumption potential.

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更快、更环保的踏板车？基于真实驾驶数据的共享电动滑板车使用情况评估

近年来，很少有交通方式能像共享电动滑板车那样如此迅速地受到关注。争论的焦点集中在使用模式对环境影响的转变效应上。先前的研究主要在亚洲和北美以及大都市地区进行。潜在的相互依赖性主要针对公共交通（PT）进行了分析。令人惊讶的是，关于共享电动滑板车和其他共享出行服务的使用情况的调查很少。然而，了解多式联运可能的（相互）依赖性和潜力对于决策者和交通规划者设计高效和可持续的交通系统至关重要。这就是为什么我们利用德国西南部非大都市卡尔斯鲁厄的 118,047 次共享电动滑板车出行的原始数据集，并添加有关汽车共享和 PT 的信息。除了两种模式的车站信息外，我们还添加了电车的发车信息和天气数据。2020年11月至2021年4月期间，通过当地提供商检索共享电动滑板车数据，通过OpenStreetMap添加有关汽车共享和PT站点的信息，并通过地方当局检索有轨电车服务数据。我们发现平均出行距离为 1.40 公里，周日的使用量大幅减少。与汽车共享相比，共享电动滑板车的组合对于 PT 的潜力更大。在 PT 服务较低或没有 PT 服务的情况下，共享电动滑板车的行程显示出更长的距离。公共交通或汽车共享站具有固定效应的负二项式回归模型表明，有轨电车发车数量对共享电动滑板车的使用产生积极影响，特别是在非高峰时段。应用模式转换场景并关注使用阶段，发现共享电动滑板车的能耗效果在5至+0.5 TWh之间。然而，它要求供应商重新审视其运营和政策，重新考虑监管，以接近多式联运或能源消耗潜力。