There is a growing popularity for shared mobility services. With their penetration in a city, a natural phenomenon is the mode shift from conventional modes. Therefore, there is a need for a model, which is capable of capturing this phenomenon. While most existing studies have developed mode choice models consisting of a single shared mobility service, only a few studies of two modes exist. Nevertheless, no study has focused on the development of a joint mode choice model for bike-sharing, car-sharing and ride-hailing services. Hence, the objective of this research is to develop a mode choice model, which is capable of capturing the demand for the aforementioned three services simultaneously. The estimation results show the influence of socio-demographic characteristics (age, gender, education, household car-ownership and possession of public transport pass and license), trip-related variables (trip distance and travel time) and supply parameter (fleet size). For example, bike-sharing systems are more likely to be used for trips with distances up to 5 km, while car-sharing and ride-hailing systems are expected to be used for a longer distance range of 2 to 15 km. However, there is a lower probability to use the three services for travel times beyond 30 min. Discussions are included for the integration of the developed mode choice model into the transport simulation systems. In addition, based on the influential factors, policy measures are suggested under the following categories: (i) Finance (e.g., microsubidies), (ii) Infrastructure (e.g., dedicated cycle lanes), (iii) Campaigns and nudges (e.g., social awareness campaigns), and (iv) Service design (e.g., integration with public transport). Especially, measures that benefit women and attract young and older age groups are proposed. Besides the policy measures, the probable demand segments for the three shared mobility services have been identified and summarized, with a focus to integrate them along with public transport for Mobility as a Service (MaaS). This includes how the three services can be streamlined to target different distance categories and socio-demographic groups. The contributions from this study can allow several cities to estimate more accurately the mode shares for the shared mobility services and also to promote sustainable usage of shared mobility services through MaaS platforms.

共享移动服务越来越受欢迎。随着他们在城市中的渗透，一个自然现象就是传统模式的模式转变。因此，需要一个能够捕捉这种现象的模型。虽然大多数现有研究都开发了由单一共享移动服务组成的模式选择模型，但只有少数研究存在两种模式。尽管如此，还没有研究着眼于开发共享单车、共享汽车和网约车服务的联合模式选择模型。因此，本研究的目的是开发一种模式选择模型，能够同时捕捉对上述三种服务的需求。估计结果显示了社会人口特征（年龄、性别、教育、家庭汽车拥有量和拥有公共交通通行证和执照）、出行相关变量（出行距离和出行时间）和供应参数（车队规模）。例如，共享单车系统更有可能用于 5 公里以内的出行，而汽车共享和网约车系统预计将用于 2 至 15 公里的更长距离范围。但是，旅行时间超过 30 分钟时使用这三种服务的可能性较低。讨论包括将开发的模式选择模型集成到运输模拟系统中。此外，根据影响因素，建议在以下类别下采取政策措施：(i) 金融（例如，小额补贴），(ii) 基础设施（例如，专用自行车道），(iii) 运动和推动（例如，社会宣传活动），(iv) 服务设计（例如，与公共交通的整合）。特别是，提出了有利于妇女和吸引年轻人和老年人的措施。除了政策措施外，还确定并总结了三种共享移动服务的可能需求部分，重点是将它们与公共交通相结合，以实现移动即服务 (MaaS)。这包括如何简化这三种服务以针对不同的距离类别和社会人口群体。这项研究的贡献可以让多个城市更准确地估计共享移动服务的模式份额，并通过 MaaS 平台促进共享移动服务的可持续使用。提出了有利于妇女和吸引年轻人和老年人的措施。除了政策措施外，还确定并总结了三种共享移动服务的可能需求部分，重点是将它们与公共交通相结合，以实现移动即服务 (MaaS)。这包括如何简化这三种服务以针对不同的距离类别和社会人口群体。这项研究的贡献可以让多个城市更准确地估计共享移动服务的模式份额，并通过 MaaS 平台促进共享移动服务的可持续使用。提出了有利于妇女和吸引年轻人和老年人的措施。除了政策措施外，还确定并总结了三种共享移动服务的可能需求部分，重点是将它们与公共交通相结合，以实现移动即服务 (MaaS)。这包括如何简化这三种服务以针对不同的距离类别和社会人口群体。这项研究的贡献可以让多个城市更准确地估计共享移动服务的模式份额，并通过 MaaS 平台促进共享移动服务的可持续使用。重点是将它们与公共交通相结合，以实现移动即服务 (MaaS)。这包括如何简化这三种服务以针对不同的距离类别和社会人口群体。这项研究的贡献可以让多个城市更准确地估计共享移动服务的模式份额，并通过 MaaS 平台促进共享移动服务的可持续使用。重点是将它们与公共交通相结合，以实现移动即服务 (MaaS)。这包括如何简化这三种服务以针对不同的距离类别和社会人口群体。这项研究的贡献可以让多个城市更准确地估计共享移动服务的模式份额，并通过 MaaS 平台促进共享移动服务的可持续使用。