Barriers to the uptake of shared mobility Shared transport solutions face a series of barriers, such as the establishment of trust relationships between strangers – a key requirement for a platform that brokers sharing transactions. The sign up process for shared solutions can be cumbersome, and not all solutions fit the needs of everybody. Shared modes tend also to be less convenient and flexible than private ones. Mobile apps, aggregating platforms, and the rise of automated mobility can mitigate these issues and create virtuous circles of increased demand and improved offers. Finally, there are cultural barriers to sharing rides with strangers that should also be considered. • The sign-up process for shared solutions can be cumbersome • There are also cultural barriers to sharing rides with strangers • Shared modes tend to be less convenient and flexible than private modes• The establishment of trust relationships between strangers is a key barrier for shared mobility Within a few years, shared mobility services will have escaped from their niche status. Although their net environmental and social benefits remain subject to controversy, they do hold the potential for a positive transformation of our mobility system, at least if policies are set correctly. It is thus important to understand the barriers to their further uptake. What is casually referred to as ‘shared mobility’ is actually a very diverse market, ranging from ‘real’ peer-to-peer services such as personal vehicle sharing (PVS) or acquaintance-based carpooling to ridesourcing companies. An additional challenge in understanding why their use is not more widespread is that studies usually focus on the motivations of current users, and not on those of people who do not (yet) use the services. One common theme, though, appears to be the establishment of a trust relationship. For instance, in PVS, car owners provide short-term access to their private cars to renters who they do not know personally. From an owner’s perspective, the main advantage of renting their car is that this allows the spreading of the acquisition costs. However, it is precisely in the market segment with the highest potential benefits (the upper segment) that the potential costs of sharing the car with strangers (who may damage the car) are the highest as well. Similarly, people may feel reluctant to share rides with strangers or to use their vehicle to pick up more than one stranger (Chan and Shaheen, 2012; ITS America, 2015). Often, the establishment of trust is a key task for a platform company that brokers transactions between strangers. Digital recordkeeping, links with on-line social networks and rating systems could help address some security and liability concerns (ITS America, 2015; Agatz et al., 2012). A second barrier is that, even in our era of mobile apps, the sign-up processes are not always convenient. Moreover, platforms may face trade-offs. For instance, for bicycle sharing, the possibility to sign up on the spot, with a credit card, makes the process much more convenient for most users (Fishman, 2016). However, the requirement to pay with credit card could be a major impediment for the population segments that suffer most from “mobility poverty”. Moving back to cash payments could lower the barriers for those social groups . A third barrier is that, compared to the private car, shared modes are less flexible and convenient. For example, in order to ensure quick access to shared cars and bicycles, carsharing and bicycle sharing require a dense network of supply and drop-off points (see Fishman, 2016 for bicycle sharing). Such a dense network can only be profitable for suppliers if the level of demand is sufficiently high. In other words, there’s a typical chicken-and-egg problem (what economists call ‘network economies’): demand will only materialise if supply is high enough, but this requires a guarantee that demand will be high enough as well. The use of mobile apps has greatly reduced this barrier, at least in dense urban areas. Nevertheless, for the operators, the logistics of re-balancing cars and bicycles across the network can be hugely complex. However, this rebalancing is essential in order to make users confident that they will be able to drive back from a given destination, even if no formal guarantees can be given (Agatz et al., 2012). GPS tracking and big data algorithms become essential for the efficiency of the process. In the case of carpooling, another major source of inconvenience is that people need to adapt to others’ schedules and routes (Chan and Shaheen, 2012). Again, mobile apps and smart algorithms can reduce this inconvenience, but not eliminate it. Technological developments such as improved interoperability among ridesharing databases and standards for sharing open source data among ridematching companies will also help to overcome the critical mass barrier. Other innovations include: “ridematching aggregators” (websites or other interfaces that search all ridesharing databases) and multimodal integration (the seamless connection of ridesharing with other transportation modes, such as public transit and car-sharing) (Chan and Shaheen, 2012). Another development that will help shared mobility is the operational use of automated vehicles (AVs). In the future, AVs that drive themselves to the carsharing users will drastically reduce the time needed to access a carsharing vehicle (Greenblatt and Shaheen, 2015; Kockelman et al., 2016). Last but not least; a problem that is common to carpooling and ridesplitting (i.e. sharing rides with strangers when using a taxi and a ridesourcing service) is that people have a need for personal space and time, and that some people may prefer to avoid social situations (Chan and Shaheen, 2012). There are no obvious technological fixes for this problem, which will require deep cultural changes that may take years to materialize. Agatz, N., Erera, A., Savelsbergh, M., & Wang, X. Optimization for dynamic ride-sharing: A review, European Journal of Operational Research, Volume 223, Issue 2, 1 December 2012, Pages 295-303, ISSN 0377-2217, http://dx.doi.org/10.1016/j.ejor.2012.05.028 Chan, N.D. & Shaheen S. (2012) Ridesharing in North America: Past, Present, and Future, Transport Reviews: A Transnational Transdisciplinary Journal, 32:1, 93-112, DOI: 10.1080/01441647.2011.621557 Fishman, E. (2016), Bikeshare: A Review of Recent Literature, Transport Reviews, 36:1, 92-113, DOI: 10.1080/01441647.2015.1033036 Greenblatt, J. B. and Shaheen, S., Automated Vehicles, On-Demand Mobility, and Environmental Impacts, Current Sustainable/Renewable Energy Reports, 2015, vol 2, n° 3, pp 74—81. ITS America 2015. Rise of the Real-time Traveler: An exploration of trends and innovation in urban mobility, http://www.trb.org/Main/Blurbs/173251.aspx Kockelman, K.M. & Chen D. (2016), Management Of A Shared, Autonomous, Electric Vehicle Fleet: Implications Of Pricing Schemes, Proceedings of the 95th Annual Meeting of the Transportation Research Board (January 2016) and under review for publication in Transportation Research Record