Commute Mode Choice in a Developing Country
- 1 January 2007
- journal article
- research article
- Published by SAGE Publications in Transportation Research Record: Journal of the Transportation Research Board
- Vol. 2038 (1), 53-61
- https://doi.org/10.3141/2038-07
Abstract
This paper investigates mode choice decisions of workers in Chennai City, a metropolis in India. Mode choice in developing countries such as India may differ significantly from their developed counterparts in several respects. These differences pertain to vehicle types (two-wheelers versus four-wheelers), vehicle ownership levels and growth, wide variation in socioeconomic characteristics, perception of subjective factors, and variability in choice set, among other factors. Toward understanding these differences, this paper investigates the role of the following factors on mode choice: (a) differences between mode choice propensity for two-wheelers and four-wheelers; (b) differences in sensitivity to travel time and cost across different user groups based on captivity effects [captive (no vehicles), semicaptive (fewer vehicles than workers), and choice segments]; (c) alternative means of representing the unavailability or infeasibility of some alternatives to some users; and (d) the influence of subjective factors. To achieve these objectives, a series of disaggregate mode choice models are developed to capture the aforementioned effects, on the basis of data from 550 workers in Chennai City. Six alternatives are considered: two-wheeler, car, bus, train, nonmotorized, and other modes. The empirical results underscore significant variations in two-wheeler and car choice propensities. Furthermore, significant differences in sensitivity to travel time, cost, and vehicle availability are observed across different user segments. The cost sensitivity to various modes reduces as the commute distance increases. Results indicate that disregarding the aforementioned effects can lead to poor model fit, biased coefficients, and erroneous forecasts. These findings have important implications for the evaluation of transit ridership improvement strategies and demand forecasting in developing countries.Keywords
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