Online exams in higher education: A possible solution to avoid unnecessary car trips

• The research presented in this paper investigates how and to what extent online exams can contribute to a reduction in transport demand and its environmental implications. • This contribution enlarges the concept of “trip avoidance” to include the practice of online exams into the Avoid domain of the ASI approach. • Results show that car is the most used mode (51%), and a total amount of about 40 million vehicle-kilometres travelled per year might be saved. • In case of a 100 % return of in-person exams, about 9 thousand tonnes of CO2eq emissions per year are expected from motorized private transport modes. • Agenda setting suggests to continue improving proctoring technology for remote examination or the implementation of incentives to promote sustainable mobility. Distance learning represents a form of remote participation, resulting in avoidance of commuting trips. After the end of the pandemic emergency, the progressive return to in-person exams is expected to generate a significant volume of car trips, especially for those telematic universities that in the last few years have experienced an impressive growth in students’ enrolment. This research presents the case study from Universitas Mercatorum, the University of the Italian Chambers of Commerce. Through a survey-based methodology, this study aims at estimating the students’ travel demand to take exams in case of full return to traditional in-person format. Following a Well-to-Wheel approach, this study also performs a transport-related greenhouse gas (GHG) emissions assessment. Results show that car is the most used mode (51 %), and a total amount of about 40 million vehicle-kilometres travelled per year is expected. This translates into about 9 thousand tonnes of CO2eq emissions per year. However, the stated preference experiment highlights that 37 % of motorized private transport users (cars and motorbikes) might shift to rail and 37 % of car users are willing to carpool.