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Introduction:
Urban growth in many countries is characterized by urban sprawl, reaching 18% of surface area in French urban areas from 1975 to 1999. This trend leads to increased travel distances, time, and private car usage, causing external costs like greenhouse gas emissions and congestion. To mitigate these, policies promoting modal shifts have gained popularity, though not without controversy. The rise of digital technologies, smartphones, and connected objects has enabled a reevaluation of sustainable mobility policies. Information and communications technology (ICT) projects impact mobility by influencing travel habits through real-time information access. However, studies show a resistance to change in modal habits, despite efforts to provide alternative information.
Digital technologies, including smartphones, offer opportunities for shared mobility services and real-time information, transforming the transport landscape. Various studies highlight the role of ICT in optimizing travel through applications like Waze or Google Maps. The current study focuses on assessing behavioral changes in transportation habits resulting from a mobile application, SmartMoov, developed for the Montpellier agglomeration. A three-month living lab collected data through surveys, examining mobility behavior before and after SmartMoov implementation. The paper includes a literature review, methodological aspects, descriptive statistics, and logit models explaining behavioral changes. Overall, the study aims to contribute insights into the impact of real-time and multimodal information on users’ transportation choices.
Literature review:
For an extended period, economists have explored the influence of information on user behavior, particularly in the field of transportation. Studies pre-digital era, like Van Berkum and Van Der Mede (1993), addressed the impact of information provision on travel behavior. Theoretical works, such as Arnott et al. (1991) and Ettema and Timmermans (2006), delved into the role of information on motorist route choices and scheduling costs, respectively. Empirical studies, like Emmerink et al. (1996), investigated the impact of radio and Variable Message Signs (VMS) on route choices. Recent studies, exemplified by Kattan et al. (2013) and de Moraes Ramos et al. (2020), explore the effects of real-time information on travel behaviors, indicating modal shifts and route changes.
The emergence of smartphones prompted research on the impact of mobile applications, with Watkins et al. (2011) finding that real-time information reduces perceived and actual waiting times for bus users. Melo et al. (2017) conducted a simulation in Lisbon, revealing that rerouting based on guidance information could reduce travel times. Tseng et al. (2013) observed strong reactions to real-time traffic information, with mobile applications reducing waiting times in public transport and travel time in private cars.
Furthermore, mobile applications have extended to soft travel modes like cycling and walking. Behrendt (2016) studied smart velomobility in Brighton, demonstrating integration between digital and physical mobilities. Nakashima et al. (2017) developed a mobility management system with gamification, inducing behavioral change. Wang et al. (2016) explored smartphone use by tourists, showing that application-based information enhances trip planning and routes.
In summary, studies indicate that information from Advanced Traveler Information Systems (ATIS) can induce behavioral changes. However, mobile applications predominantly focus on specific modes of transportation and lack multimodal integration.
Conclusions:
This research aimed to evaluate the impact of real-time, multimodal information delivered through a mobile application on users’ transportation habits. Conducting a living lab in 3M, the study emphasized the significance of safety margin and average travel time in influencing individuals to change their mobility behavior in response to the app-based information, affecting transportation mode, route, and departure time choices. Additional factors such as possession of a public transport pass and gender also played roles in altering route and departure time behavior. The results indicated that beta-testers were more likely to change departure time (0.97) and route (0.99) choices compared to transportation mode (0.50).
However, potential sample selection bias in the living lab method, with volunteers predominantly aged 18 to 39 and mostly public transport users, was acknowledged. The study suggested the need for a more diverse sample for unbiased results. The research questioned whether the observed changes in behavior led to more sustainable mobility practices.
To assess the long-term impact, longitudinal behavioral data from the application, collected passively, was deemed essential, but technical and ethical challenges, including data privacy and the digital divide, were highlighted. Smartphone ownership discrepancies across age groups and digital illiteracy underscored the importance of considering technology as a complement, not a substitute, for public transport policies.
Technical considerations focused on maintaining a bug-free open data platform for reliable real-time information. However, users exhibited a low willingness to pay for the mobile application (€0.21 on average). The study also raised broader questions about smart city projects, emphasizing the need for policies on user consent, data storage, management, and the economic model of a smart city, especially in the context of efficient Mobility as a Service (MaaS) implementation by public authorities.
Source:
Blayac, T., Reymond, M. & Stéphan, M. (2020). Can digital technologies induce behavioral changes in transportation habits ? Evidence based on User Experience with the SmartMoov Application. Revue d’économie industrielle, 172, 179-215. https://doi.org/10.4000/rei.9639