Choice Modelling

Choice Modelling

The State of the Art and the State of Practice

Edited by Stephane Hess and Andrew Daly

Choice modelling has been one of the most active fields in economics over recent years. This valuable new book contains leading contributions from academics and practitioners from across the different areas of study where choice modelling is a key analytical technique, drawn from a recent international conference.

Chapter 8: A comprehensive model to capture the preference for mass rapid transit in Dhaka

Annesha Enam and Charisma F. Choudhury

Subjects: economics and finance, valuation, environment, valuation

Extract

Dhaka, the capital of Bangladesh and one of the fastest growing megacities of the world, is already subjected to acute traffic congestion on a regular basis. Increasing the physical capacity to relieve congestion is however not feasible since already more than 70 per cent of the area is built up (Bari and Hasan, 2001). This has recently prompted the Government to prioritize the introduction of mass rapid transit (MRT) options like bus rapid transit (BRT) and Metro Rail in the city. Planning these MRT options however requires rigorous mode choice models that can be used to predict ridership and quantify the willingness-to-pay (WTP) of the travellers. Though Dhaka is an old city (dating back to the 16th century), very few travel demand models have been developed for the city so far. Among the previous studies, four step travel demand models were developed in Dhaka Metropolitan Area Integrated Transport Study (DITS, 1993), Strategic Transport Plan (STP, 2005) and Dhaka Urban Transport Network Development Study (DHUTS, 2010) as well as Habib (2002) and Hasan (2007). However, in each case, the mode choice components were simplified and have grave limitations. In DITS, the mode choice model was simplified to a binomial choice model between private and public modes. In Habib (2002), a multinomial logit (MNL) model structure was adapted for the mode choice but the calibration results were counterintuitive with positive sign of the coefficients for time and cost parameters.

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