Profiling post-pandemic activity–travel patterns in Calgary

The transition to the new normal after the pandemic has significantly reshaped travel behavior, work arrangements, and engagement in online activities, underscoring the need to identify the underlying characteristics of emerging traveler types. This study proposes a novel clustering approach to classify new worker profiles in Calgary based on data from the 2024 Canada Travel Activity (CanTRAC) survey, which records recent behavioral trends and work patterns across various Canadian cities. The survey encompasses socio-demographic, household, and work-arrangement data, alongside information on 26 types of in-home (teleworking, online maintenance activities and online discretionary activities) and out-of-home activities. This research employs an unsupervised machine-learning approach, utilizing the K-prototype clustering algorithm to identify three distinct groups: Traditionalists, Hybrid Workers, and Active Professionals. Traditionalists, mainly older adults, are progressively adapting to Information and Communications Technology (ICT). Hybrid Workers, typically middle-aged, navigate a blend of remote and in-office work while maintaining a high level of out-of-home activity, including non-mandatory trips. Active Professionals, the youngest cohort, predominantly work from traditional office settings and exhibit a strong preference for online food ordering, alongside a high engagement in other online activities. The identification and analysis of these groups provide crucial insights into post-pandemic travel and work behavior, informing the development of targeted strategies and policies in urban and transportation planning.