Segmentation Analysis of Commuters Accessing Transit: Mumbai Study

Abstract

The paper presents the segmentation analysis of commuters accessing suburban rail transit in Mumbai City, India. The emphasis is given to the identification of most influencing variables. The commuters are segmented based on household characteristics like type of accommodation, household income, and dependency level in the household, and personal characteristic like occupation level of the commuter. The data are collected through household survey and logit models are developed under all the four above-mentioned categories. Significant difference in the model specifications is observed across segments. The most significant and highly influencing variables describing the behavior of the commuter are observed to be time of start, relationship to household head, gender, dwelling unit, detour factor and access mode availability distance. The subjective value of travel time is found lower than the average hourly wage rate of the commuters’ in a specified category. This varied logically across segments. Categorization based on occupation level is expected to give the best results, whereas, “type of accommodation” and “household income” categories can substitute for each other.