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This paper develops an integrated urban modelling framework (IUMF) to predict how work from home (WFH) decision affects travel behavior. First, it conducts a questionnaire survey among working professionals in Halifax, Canada, to collect data on their socio-demographic characteristics, mode choice, vehicle ownership, and work-arrangement. Bayesian Belief network models are developed using the collected responses to calculate the cumulative probability tables (CPTs) of variables associated with the decision to WFH. Next, the ascertained CPTs are used as input to extend an integrated urban modelling framework (IUMF) that is further utilized to simulate individuals’ work from home choices and travel behavior up to 2025 for Halifax, Canada. Results indicate that around 57% of the workers would like to WFH and 7% wants to relocate closer to workplace. The model forecasts a significant preference for remote work among individuals with offices in the urban core. Results also show that auto mode share is increased to 79% in 2024, whereas transit, walking and biking trips decreased. Average travel distance is higher in the post-pandemic compared to the pre-pandemic, while travel distance of telecommuters is found to be higher than non-telecommuters. Statistically significant differences are observed between telecommuters and non-telecommuters for ‘number of activities’ and ‘distance travelled’ in a day. The outcomes of this study will offer policy makers a better understanding of long-term impacts of WFH on transport and land-use systems and help to develop effective travel demand management strategies.
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Stored only when both papers are in the corpus — 6 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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