We propose three tiers of disaggregation to study variation in travel behavior across socio-economic groups. The first tier of disaggregation helps in studying variation in travel choices by gender and SEWS group independently. The second tier of disaggregation helps in studying the variation in travel choices between SEWS group within gender groups. This helps in understanding the issues related to affordability and accessibility related to income while controlling for gender. The third tier of disaggregation is used to study the variation between gender group within each SEWS group. This helps in identifying the differences in access to resources with regard to gender. We have also evaluated the application of interaction term between gender and income levels to model travel choices for the city of Vishakhapatnam. Socio-economic wellbeing score (SEWS) is used as the proxy of income determined using Principal Component Analysis (PCA) on asset ownership data. The study shows the need to understand within group variabilities in travel behaviour based on both income and gender. This highlights affordability and accessibility related issues for income-based disparities and safety, security and empowerment concerns for gender-based inequalities. However, no significant improvement in the variability is explained by the models when the interaction term between gender and income is used as one of the independent variables.
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Jain et al. (2020) studied this question.
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