Transportation Research Interdisciplinary Perspectives (May 2023)
An integrated estimation approach to incorporate latent variables through SEM into discrete mode choice models to analyze mode choice attitude of a rider
Abstract
Mode Choice preference of each individual commuter depends on a number of factors. The classic models for choice estimation have majorly focused on the quantifiable variables such as travel cost, travel time, socio-economic characteristics of riders, trip characteristics, and mode characteristics. This paper aims at analyzing the hidden impact of latent variables integrated with observed variables on mode choice attitude of a rider for an integrated public transport system with environment-friendly feeder mode. The study is in a tier II type metropolitan city of Vadodara, Gujarat. For the purpose a new class of model, Integrated Choice and Latent Variable (ICLV) model is introduced. It integrates the Structural Equation Modelling (SEM) through Analysis of Moment Structures (AMOS) approach for the analysis of latent variable with the classic type choice model analyzed through Biogeme regression. The study precisely captures the attitude of a rider towards the need for comfort and convenience, safety and security, services and facilities, and riding attraction and quality class of latent variables. 26 of initially considered 41 latent variables clubbed into four latent constructs through Confirmatory Factor Analysis (CFA) and SEM approach were incorporated in the ICLV analysis. The results explain the riders’ attitude driven choice for comfort and convenience and service and facilities over the safety and security and riding quality aspects of the mode. The shift demand governed by these latent variables helps to develop a methodological framework, which sets up a base for transport system design oriented policies’ implications as future scope of the research.
