Mobility Behaviour of Immigrants in Canada: Analyzing Mode Choice Using GPS Panel Data and Mixed Logit Models

2026-04-16

AI Summary

This study investigates the relationship between travel mode choice and social integration among recent immigrants in Canada, revealing distinct differences from native-born residents in value of travel time and transportation preferences. Leveraging over 80,000 high-precision GPS trips collected via a custom-developed app from 100 participants, the research integrates revealed preference (RP) and stated preference (SP) data within a joint modeling framework. It pioneers the incorporation of a multidimensional social integration index into travel behavior modeling and includes electric mobility options for forward-looking assessment. Using a mixed logit model with five-fold cross-validation, the analysis finds that immigrants exhibit 66% lower sensitivity to in-vehicle travel time than natives, and a one-standard-deviation increase in integration level corresponds to a roughly 5-percentage-point decline in public transit use probability. The model achieves 80–82% prediction accuracy and suggests that improving first/last-mile connectivity is more effective than fare reduction in promoting transit adoption among immigrants.

Technology Category

• Application Domains: Transportation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Knowledge Representation and Reasoning: Preferences

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

We examine these relationships using a panel dataset of more than 80,000 trip observations from 100 participants through a custom-built mobile application. A joint revealed preference (RP) and stated preference (SP) framework is used to estimate multinomial logit (MNL) and mixed logit (MXL) models. The level of integration is represented through a composite index capturing economic, social, civic, and health dimensions of integration. Results indicate two distinct patterns. First, the estimated models suggest that new immigrants in the sample exhibit lower sensitivity to in-vehicle travel time than Canadian-born respondents. The mixed logit specification suggests that the value of travel time for the sampled immigrants is approximately 66% lower than that of Canadian-born residents, with a immigrant-to-Canadian-born ratio of 0.34 that is consistent across both MXL specifications. Second, higher levels of integration are associated with reduced transit use and greater car reliance. A one standard deviation increase in the integration index decreases the probability of choosing public transit by approximately five percentage points. The joint RP-SP specification allows the inclusion of emerging e-mobility alternatives not yet observed in revealed behaviour; these face no inherent preference penalty, competing purely on their level-of-service attributes. Out-of-sample validation using five-fold cross-validation produces a mean prediction accuracy between 80% and 82% across model specifications. The findings suggest that transit policies in immigrant-receiving cities could prioritize service quality improvements, particularly reductions in access time, which are approximately three times more effective than fare reductions in shifting immigrants toward transit use.

Problem

• immigrant mobility
• mode choice
• travel time sensitivity
• integration index
• transportation policy

Innovation

• mixed logit model
• GPS panel data
• revealed and stated preference
• integration index
• e-mobility alternatives