A pooled RP/SP mode, route and destination choice model to investigate mode and user-type effects in the value of travel time savings

Abstract

Being of great importance for transportation policy appraisals, we investigate mode and user-type effects 1 in the value of travel time savings (VTTS) using a pooled RP/SP Mixed Logit modeling approach for mode, 2 route and destination choice data. For a representative sample of Austrian workers, our analysis reveals 3 population-weighted median VTTS estimates for car (12.3 Euro/h), public transportation (PT; 8.1 Euro/h), 4 bike (11.7 Euro/h) and walk (10.2 Euro/h). 5Considering only those respondents who have used car and PT in the observation period (and thus are 6 familiar with both modes), we find that four user characteristics are able to decompose this substantial 7 difference in median VTTS between car and PT (i.e. the total mode effect) of about 4.9 Euro/h: Posterior 8 means of individual and mode-specific VTTS distributions reveal a reduced mode effect for high income (4.6 9 Euro/h), female (4.5 Euro/h), low educated (4.3 Euro/h) and urban (3.0 Euro/h) user groups. 10Our results indicate that in the case of Austrian workers, characteristics of the mode are more important 11 than characteristics of the users, and that the travel time spent in PT is valued less than in a car for all 12 investigated user groups. 13 changes, providing a powerful transportation planning tool for developing effective travel demand fore-2 casts (e.g. Ben-Akiva and Lerman, 1985; Bhat, 1998; Jara-Diaz, 2007; Ortúzar and Willumsen, 2011). As a 3 key valuation indicator, the value of travel time savings (VTTS) has always been subject to extensive debate 4 in both academia and practice, because savings in travel time account for the biggest share of user benefits 5 in most cost-benefit analyses (e.g. Jara- Diaz, 1990; Wardman and Lyons, 2016; Hensher et al., 2016). 6 Recent research has shown a trend towards a potentially more insightful way to decomposing the VTTS -7 typically derived from mode, route and/or destination choice models -into two separate elements. Following 8 Jara-Diaz and Guevara (2003), Jara-Diaz et al. (2008) and others 1 , the subjective value of travel time savings 9 (VTTS) represents the willingness to pay to reduce travel time by one unit, and is the sum of two components: 10 (1) the value of time as a resource (VoL; also referred to as the value of leisure) representing the monetary 11 equivalent of the willingness to reduce travel time in favor of other activities that generate more utility, 12 and (2) the monetary value of the reduction in direct (dis)-utility derived from the time assigned to travel 13 (VTAT). The VoL is always positive and depends on the time assigned by the individual to all activities 14 including travel, and on their trade-offs. The VTAT depends on the conditions/comfort of travel and can be 15 positive or negative; if negative, it contributes to increase the VTTS above the VoL 2 . If positive, the VTTS 16 is lower than the VoL. A shift of focus from the VTTS to the two components, i.e. the VoL and the VTAT, 17 in cost-benefit analyses would help assessing the options under a bud...

Surveying and analysing mode and route choices in Switzerland 2010–2015

“…that enable public transportation passengers to use in-vehicle time more productively, which may in turn lead to a lower value attached to travel time savings in PT (e.g. Mokhtarian and Salomon, 2001 , Litman, 2008 , Hensher and Wang, 2016 , Wardman and Lyons, 2016 , Weis and Axhausen, 2012 , Schmid et al, 2019 ). In particular, train travel time – especially for longer distances – can be used for engaging in all kinds of activities (Lyons et al, 2013; Schmid, 2019 ).…”

“…According to e.g. Schmid et al, (2019) , this ensures robustness and efficiency in the estimation process and reduces the methodological issues when dealing with pure RP or SP models (i.e. the former providing only limited information on trade-offs, and the latter suffering from a hypothetical bias, anchoring effects and strategic behaviour; Schmid et al, 2019 ).…”

“…Despite the differences that may occur when estimating separate models for RP and SP data, the aim of pooling both data types is that each relieves the problems of the other. If the valuations were identical, there would be no need to collect and pool both data types ( Schmid et al, 2019 ).…”

“…the value of travel time (e.g. Schmid et al, 2019 ). On top, we investigate the dependency of these willingness-to-pay (WTP) values with respect to distance and income, and if this dependency has changed between the two datasets ( ARE, 2017 ).…”

Out of the city – but how and where? A mode-destination choice model for urban–rural tourism trips in Austria

“…The model used for this analysis must facilitate the parameter estimation of a combined choice of tourist destinations and transport modes. As visualized in Table 1, mode choice models are often discrete choice models (MNL model or its derivatives, such as nested logit (NL) or mixed logit, see Bhat, 1998;Schmid et al, 2019;Ortúzar & Willumsen, 2011). Modelling destination choices is less straightforward.…”