Quasi-Experiment to Assess the Role of Real-Life Tests for the Acceptance of Technology for Mobility as a Service: The Case of Autonomous Vehicles as a Post-COVID Alternative for Tourism in Switzerland

Introduction

In the mobility sector, digitalization and urbanization are mega trends influencing the development of new technologies and services (Bienhaus & Haddud, 2018; Vaz et al., 2015). This digitalization is supported by new information and communication technologies, such as big data, Internet of Things, 5G, and Artificial Intelligence. With digitalization, opportunities like Autonomous Vehicles (AVs) arise (Barreto et al., 2018). For users, AVs enable transit between points of interest without taking care of the logistical elements (traffic or parking). AVs should also bring safety, comfort, or the possibility of enjoying travel without driving; instead, talking with friends, reading, watching a movie, or even admiring a new tourist region (Schwarting et al., 2018). For public transport companies AVs should provide new services like on-demand travel, calling a vehicle when they need it, and first mile/last mile (FMLM) service between stations (bus, train, or airport) and the user’s final destination (home, job, or restaurant) (Chen et al., 2020). Transport companies should also benefit from cost reduction by better energy efficiency and change in job allocation (Lu et al. 2019; Pettigrew et al., 2018).

Urbanization (more people moving into urban centers) will lead to problems such as more congestion, crowded public transport, noise, and confrontations between road users, pedestrians, car drivers, bikers, or scooter users (Han et al., 2018; Fuller et al., 2007). To fight these problems some cities have taken measures like introducing a fee to drive a private car in the city center or the reduction of the speed limit in traffic (Jia et al., 2017). In contrast, fewer people will live in rural areas. Thus, it will become difficult for public transport companies to ensure a public service that is economically viable. AVs could bring an interesting solution in this context.

Digitalization and urbanization support the concept of a Smart City (Ylipulli & Luusua, 2020). A Smart City can be seen as a network where all elements – machines, spaces (like parking), as well as humans – are connected. The elements can communicate and exchange information. For example, an AV can receive information from a traffic light to know when it can cross the road. The traffic light analyzes who wants to cross the road and adapts the time to the ability of the person. The goal is to exploit all these connections to improve life in the city with technology.

AVs enable public transport companies to set up new services, like on-demand or FMLM transport (Chen et al., 2020). These services are grouped under the concept of Mobility as a Service (MaaS) (Becker et al., 2020). These services must be accepted and adopted by users to be considered innovations. Users reusing a service is particularly important (Park, 2019). As example, if inhabitants of a residential quarter do not adopt the AV for FMLM transport between the train station and their home, the service will not be considered a success or an innovation. Furthermore, AVs provide a self-service for mobility. Self-service is the most technology-intensive situation in which the user utilizes a technology without the physical presence of a server (Froehle & Roth, 2004). This situation is totally new for most public transport companies. Indeed, a mobility service traditionally provides transportation with the help of a driver who represents or personifies the company and ensures the co-production of the service with the user. In the absence of a driver, the co-production process of the service between the user and the AV must be totally redesigned. To do this, public transport companies could set up tests in real-life conditions. These living labs enable companies to perform research and development for services.