This study examines differences in work trip mode choice behavior under the combined implementation of congestion pricing (a push measure) and metro system introduction (a pull measure) in Mumbai, India. A combined revealed and stated preference (RP–SP) data set is used to estimate a random parameters latent class choice model (RP-LCCM), enabling the identification of distinct behavioral segments within the population. The results reveal two latent classes. Class 1 (43.48%) comprises younger and lower-income individuals who are highly cost-sensitive and less time-sensitive. They are willing to tolerate longer travel and access times and show a higher inclination toward using public transport, particularly metro services. Class 2 (56.62%) represents older, higher-income, and more educated respondents who are more time-sensitive and less cost-sensitive. This class exhibits a stronger preference for private modes such as cars and two-wheelers, valuing convenience and reduced travel time. Satisfaction with travel air quality is also higher in Class 2 (82%) compared to Class 1 (67.4%), reflecting perceptual and lifestyle differences. The estimated scale factor between RP and SP data indicates consistency in behavioral responses across data sets. The findings demonstrate significant heterogeneity in mode choice, showing that the impact of transport demand management (TDM) measures such as congestion pricing and metro expansion varies across income and life-cycle groups. The study emphasizes the importance of incorporating socioeconomic diversity and behavioral segmentation in policy formulation to promote efficient and equitable urban mobility.
Saxena et al. (2026) studied this question.