Citation

Piras F, Sottile E, Tuveri G, Meloni I. Res. Transp. Econ. 2022; 95: e101233.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.retrec.2022.101233

PMID

unavailable

Abstract

Over the last few decades, there has been a growing interest in a variety of travel demand management strategies, both hard and soft, aimed at persuading people to reduce their car use. However, only few studies employed predictive models to assess the effectiveness of soft interventions and understand the impact of both objective and socio-psychological variables on changes in travel behavior. Additionally, though a combination of hard and soft measures is recognized as achieving the best results in reducing car use, few studies differentiate between the effects of the two types. The aim of this work is to quantify the effect of a combination of hard (introduction of a new light railway line) and soft measures (Personalized Travel Plan program) among a group of car drivers in the metropolitan area of Cagliari (Sardinia, Italy). We used data collected before and after the implementation of a Personalized Travel Plan program, where a control group was identified to disentangle the effect of the hard from the soft measure. We specified and estimated an Integrated Choice and Laten Variable (ICLV) model to assess the effect of both objective characteristics and some socio-psychological variables on the choice to use a new light railway service or not. Model results point out that people who lived along the light rail corridor and received and read their Personalized Travel Plan were more likely to switch from car to the light rail. Furthermore, we found that the parameters associated with the psycho-social variables Attachment to the car and Dislike of public transport have a negative influence on the probability to use the new travel alternative. At the same time, our findings on the effect of the soft measure need to be interpreted with some caution as its impact on choice probability was mitigated by travel distance and psycho-social variables.

Language: en

Keywords

Control group; Discrete choice model; ICLV model; Light rail; Personalized travel plan; Travel demand management