Schmöcker, J-D, Hatori, T and Watling, D (2014) Dynamic process model of mass effects on travel demand. Transportation, 41 (2). 279 - 304. ISSN 0049-4488
Abstract
Whereas transportation planners commonly predict the negative impacts of mass transportation, there is increasing empirical evidence of the existence of positive mass effects, whereby increased use of a mode by the 'mass' will generally increase its attractiveness for future travellers. In this paper we consider the dynamic impact of such an effect on the problem of travel demand forecasting, with particular regards to social network effects. Our proposed modelling approach is inspired by literature from social physics, evolutionary game theory and marketing. For simplicity of exposition, our model is specified for a scenario in which (a) there is a binary choice between two mobility lifestyles, referred to as car-oriented and transit-oriented, and (b) there are two population groups, where one is the "leading" or "innovative" population group and the other the "following" or "imitating" population group. This latter distinction follows the rather well-known Bass model from the marketing literature (1969). We develop the transition probabilities and transition dynamics. We illustrate with a numerical case study that despite lower intrinsic utility for the transit lifestyle, significant changes towards this lifestyle can be achieved by considering congestion, service improvements and mass effects. We further illustrate that mass effects can be positive or negative. In all cases we explore the sensitivity of our conclusions to the assumed parameter values.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013, Springer. This is an author produced version of a paper published in Transportation. Uploaded in accordance with the publisher's self-archiving policy. The original publication is available at www.springerlink.com |
Keywords: | Mass effects; travel demand; long range forecasting; Bass model; social networks; stochastic process model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Mar 2013 14:10 |
Last Modified: | 28 Mar 2018 18:11 |
Published Version: | http://dx.doi.org/10.1007/s11116-013-9460-y |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/s11116-013-9460-y |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75336 |