This paper investigates how the travel behavior relating to Public Transport (PT) changed during the COVID-19 pandemic, and which are the expectations about the extent of PT use post-pandemic. A revealed preferences questionnaire survey was distributed within an academic community in the city of Thessaloniki, Greece. To understand the factors potentially determining the future PT use, hierarchical ordered probit and bivariate ordered probit models were estimated. Results showed that the frequent PT users reduced by almost 75% during the pandemic. More than 29% of the local academic community members are reluctant to resume PT use at pre-pandemic levels. Non-captive users, teleworkers and those being unsatisfied with cleanliness and safety are less willing to travelling by PT post-pandemic. Female and under-stress passengers were found to particularly appreciate the use of facemasks and the increased service frequencies as post-pandemic policy measures. The study findings can inform the recovery strategies of transport authorities in order to retain the PT ridership at levels that will not threat the long-term viability of service provision. Future research may complement these findings by examining other population segments, such as the commuters and the elderly, under more advanced modelling techniques to account for additional unobserved behavioral patterns.

Mobility as a Service (MaaS) is an innovative urban mobility concept that aims to provide a competitive alternative to the use of private cars, by integrating various transportation services. Until today, limited MaaS schemes have been implemented and, in most cases, without succeeding to justify the hype. For achieving the goals of MaaS it is essential to capture holistically the expectations and barriers, as perceived by both the end-users and the various involved stakeholders. This paper aims to bridge this gap, by conducting two surveys in the city of Thessaloniki, Greece; the first survey targeted local authorities, organizations and mobility providers, while the second survey focused on (potential) end-users. The responses of stakeholders were analyzed through the Analytic Hierarchy Process (AHP) method, in order to identify the importance of barriers and expectations. On the other hand, the responses of end-users were analyzed statistically and two ordered logit models were developed for identifying the characteristics of those that are more likely to adopt MaaS. The results of the analyses indicate that there is a loop between MaaS and private car usage; on the one hand, the dominance of private cars hinders the adoption of MaaS, but on the other hand, MaaS can be a “tool” for encountering car domination. The results also enhance the idea that public transport is an essential component of MaaS.

Despite that a lot of research has been carried out for the development of routing algorithms, research for multimodal trip planning is still limited. Even more scarce is the research on incorporating individual preferences in multimodal trip planning; yet, this incorporation is essential since not all users are willing (or they are not equally willing) or capable of using all the different modes of transportation. The main contribution of this paper is the conceptualization of how multimodal trip planners’ results can be customized based on: a) user’s responses in a specific set of questions that aim to capture their preferences, b) the revealed preferences of the users that are automatically collected. The first case is being demonstrated within this paper for the case of Thessaloniki, Greece. The developed multimodal trip planner identifies various alternative combinations of shared modes and walking and for each combination calculates the travel cost, travel duration and number of modes changes. The alternative combinations are being prioritized based on a generalized cost function. The outcomes of this paper can be of interest for researchers, who develop trip planners, and for MaaS operators and authorities that are intending to offer multimodal planning services.