20 MAY 2019 (MON) | 19:00 - 20:00
ROOM 612B, 6/F HAKING WONG BUILDING, THE UNIVERSITY OF HONG KONG
JUAN DE DIOS ORTÚZAR
Department of Transport Engineering and Logistics, Institute in Complex Engineering Systems, BRT+ Centre of Excellence, Pontificia Universidad Católica de Chile
Institute of Transport Studies, The University of Hong Kong
Department of Geography, The University of Hong Kong
In the last 21 years, bicycle use has experienced an enormous increase in Santiago, Chile. Data from the last three large-scale mobility surveys in the metropolis (1991, 2001-2006 and 2012) has revealed an impressive 13-time increase, from less than 0.3% to 1.87% and 4%, respectively, in this period. Notwithstanding, current figures are estimated to be higher and this research attempted to uncover the triggers for this increase in demand, and to examine in which form latent constructs, such as habit and risk aversion, influence the decision to travel by bike.
Two specially designed surveys were used. In the first, a random sample of 1432 individuals were asked about the main features of their daily trips to work or study, and whether they would be prepared to make that trip by bicycle; this question had the following responses available: No, Maybe/Depends and Yes. Non-bike users who selected one of the last two answers (812 individuals), were asked to participate in the second, a stated choice (SC) survey, with their current mode and bike as alternatives, considering the following level-of-service attributes: travel time, travel cost, walking and waiting time, type of bike infrastructure (cycleways and parking). In addition, respondents were requested to answer a set of specially designed psychometric indicators related with habit (current mode) and user perceptions (pro-environment; aversion to risk) towards bicycle use.
Data from the first survey was used to estimate a combined structural equation-ordinal logit model, where the utility function includes level-of-service attributes, socioeconomic characteristics, built environment attributes and three latent variables: hab