Analyzing the individual factors determining the usage duration of an active GPS tracker app using a joint binary-ordered probit model

The complexity of people’s travel behavior, along with the growing need to modify less sustainable behaviors, has made demand analysis methodology increasingly sophisticated, requiring more precise and high-performing data. GPS-tracker applications for smartphones, used for travel surveys, have been highlighted as valid alternatives to traditional methods for data collection, offering a higher level of detail. These applications allow for the detection of travel choices over a broader temporal horizon than single trips, enabling a detailed understanding of user needs. In the context of finding alternative modal solutions to private motorized transport, this type of data proves effective in identifying the modal alternative that best fits the daily/weekly activity and travel schedule, also considering the possibility of better rescheduling the sequence of activities. While the advantages of these surveys are recognized, little is known about the motivations and modalities of participation. Challenges, including high battery consumption and privacy concerns, are acknowledged, but few studies have explored individual factors influencing participation in smartphone travel surveys. This study uses survival analysis to investigate how socio-demographic attributes influence both participation in and the duration of use of an active GPS tracker application called ‘Svoltiamo’. Participants were instructed to utilize the application continuously for two consecutive weeks (three consecutive days within each week) during the third wave of a panel survey conducted in Cagliari, Italy. A censored exponentiated discrete Weibull distribution model highlighted that two of the main factors that influence participation in this type of survey are related to the composition of the household and the distance of regular commuting for work/study.