Exploring Disparities in Mobility: Investigating Activity Patterns and Time-Use Behavior among Low-Income Housing Dwellers in Mumbai, India

This research aims to uncover disparities related to socioeconomic attributes and activity patterns, examining their influence on time-use behaviors within low-income mass housing residents. Through a survey-based approach, respondents are categorized using a two-step clustering technique based on sociodemographic parameters. Subsequently, a multiple discrete continuous extreme value (MDCEV) model analyzes activity time-use patterns in relation to socioeconomic profiles and household characteristics. The cluster analysis reveals three distinct profiles for respondents in each group. Cluster 1 comprises mainly married males aged 30–59 years, who are engaged in formal employment, have a monthly income within the range of 25,000–50,000 INR, and exhibit high smartphone ownership. In contrast, Cluster 2 predominantly consists of married females aged 30–59 years, working as household or domestic workers, with lower smartphone ownership and longer commuting times. Finally, Cluster 3 encompasses mostly unmarried males aged 15–29 years, who are either students or part-time workers, demonstrating relatively high smartphone ownership and lower travel expenses. Additionally, the results from the activity-based model (MDCEV in this case) reveal that respondents in Cluster 2, which majorly includes informal workers and women, show a lower likelihood of owning smartphones compared to Cluster 1 (formal workers) and Cluster 3 (part-time working students). Also, Cluster 2 respondents (household workers, predominantly women) exhibit higher baseline utility and satiation for travel compared to those in other clusters. The findings underscore the need to enhance public transportation for marginalized groups and improve digital literacy among lower-income females.