Abstract
Recent developments in mobile information and communication technologies (ICT), vehicle automation, and the associated debates on the implications for the operation of transport systems and for the appraisal of investment has heightened the importance of understanding how people spend travel time and how productive they are while travelling. To date, however, no approach has been proposed that incorporates the joint modelling of in-travel activity type, activity duration and productivity behaviour.To address this critical gap, we draw on a recently developed PPS framework (Pawlak et al., 2015) to develop a new joint model of activity type choice, duration and productivity. In our framework, we use copulas to provide a flexible link between a discrete choice model of activity type choice, a hazard-based model for activity duration, and a log-linear model of productivity. Our model is readily amenable to estimation, which we demonstrate using data from the 2008 UK Study of Productive Use of Rail Travel-time. We hence show how journey-, respondent-, attitude-, and ICT-related factors are related to expected in-travel time allocation to work and non-work activities, and the associated productivity.To the best of our knowledge, this is the first framework that both captures the effects of different factors on activity choice, duration and productivity, and models links between these aspects of behaviour. Furthermore, the convenient interpretation of the parameters in the form of semi-elasticities enables the comparison of effects associated with the presence of on-board facilities (e.g., workspace, connectivity) or equipment use, facilitating use of the model outputs in applied contexts.
Highlights
The time that people spend travelling is a pivotal focus of attention in travel behaviour research
We propose a novel and unified way of conceptualising and modelling time allocation jointly with productivity
We show that the PPS framework can be linked to a flexible econometric formulation which can incorporate any number of activity types, spells and productivity indicators
Summary
The time that people spend travelling is a pivotal focus of attention in travel behaviour research. The question of what people do during episodes of travel – the use they make of the time they spend travelling – has received comparatively little attention. The concept of multi-tasking, while recognised in sociology for quite some time (Gershuny and Sullivan, 1998; Harvey, 1993) has only recently seen a more systematic treatment in travel behaviour and time allocation modelling studies (Circella et al, 2012; Pawlak et al, 2016; Pawlak and Polak, 2010). Thomopoulos and Givoni (2015) quote a US Department of Transport analysis putting the productivity gains at $507 billion/year in the United States alone This has all been in spite of growing evidence that there are complex trade-offs between potential improvements in network capacity and ensuring an enjoyable and productive on-board experience (Le Vine et al, 2015). A framework that can suitably model in-travel time use and productivity is essential to understand adoption and use patterns of connected and autonomous vehicles (CAV) as well as their impacts on transport systems
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
