Empowering revealed preference survey with a supplementary stated preference survey: demonstration of willingness-to-pay estimation within a mode choice case

Abstract

Mode choice models play a pivotal role in transport demand modelling and help transport planners, engineers and researchers with policy and infrastructure investment evaluation. Recent mode choice studies primarily use revealed preference (RP) data to reflect individuals’ true behaviour. However, this may not be the best practice, given the lack of information in RP data. This study uses a nonlinear utility specification for a multinomial logit mode choice model development using high-quality travel data collected by a GPS-based smartphone application complemented by stated preference (SP) data. The model results highlight the impact of sociodemographic variables on mode choice behaviour and individuals’ willingness-to-pay (WTP) when the model is jointly developed compared to stand-alone SP and RP models. The main message of this study is that in addition to collecting RP, which is a reliable and unbiased source of data, collecting complementary SP data is beneficial as it provides information that is not otherwise available in RP data. This may include a proper variation in the public transport cost variable as demonstrated in this study. Moreover, to better understand the travellers' behaviour regarding the trade-off between time and cost a mixed multinomial logit (MMNL) model in the willingness to pay space is developed on the SP data. capturing the unobserved heterogeneity within the estimated WTPs, the MMNL model outputs reveal a higher variation in WTP of car in-vehicle travel time compared to bus in-vehicle travel time.