Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects

This paper presents a universal logit model for P&R patronage. This model was estimated from a Stated Choice experiment, in which 805 car drivers chose among car, P&R and public transport alternatives. In addition to main-effects, attribute cross-effects were estimated denoting the utility c...

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Main Authors: Ilona Bos, Eric Molin
Format: Article
Language:English
Published: TU Delft Open 2006-06-01
Series:European Journal of Transport and Infrastructure Research
Online Access:https://journals.open.tudelft.nl/ejtir/article/view/3449
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spelling doaj-f95db820f07f4709a8ef1fb1580afd112021-07-26T08:49:18ZengTU Delft OpenEuropean Journal of Transport and Infrastructure Research1567-71412006-06-016310.18757/ejtir.2006.6.3.34493044Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-EffectsIlona Bos0Eric Molin1Radboud University NijmegenDelft University of TechnologyThis paper presents a universal logit model for P&R patronage. This model was estimated from a Stated Choice experiment, in which 805 car drivers chose among car, P&R and public transport alternatives. In addition to main-effects, attribute cross-effects were estimated denoting the utility change of an alternative due to changes in the attribute levels of another alternative. The results indicate that improving the levels of the P&R related attributes has a negligible effect on the utility of the car alternative, whereas worsening the levels of the carrelated attributes increases the utility of the P&R facility. Considering the estimated maineffects as well as the estimated cross-effects suggests that ‘stick’ (push) policy measures are more effective to stimulate P&R patronage than ‘carrot’ (pull) policy measures. The paper further reports that the extension of the model by adding cross-effects to the main-effects resulted in a better model fit and that the resulting model could more accurately predict the choices for new observations.https://journals.open.tudelft.nl/ejtir/article/view/3449
collection DOAJ
language English
format Article
sources DOAJ
author Ilona Bos
Eric Molin
spellingShingle Ilona Bos
Eric Molin
Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
European Journal of Transport and Infrastructure Research
author_facet Ilona Bos
Eric Molin
author_sort Ilona Bos
title Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
title_short Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
title_full Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
title_fullStr Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
title_full_unstemmed Is there a ‘Stick’ Bonus? A Stated Choice Model for P&R Patronage incorporating Cross-Effects
title_sort is there a ‘stick’ bonus? a stated choice model for p&r patronage incorporating cross-effects
publisher TU Delft Open
series European Journal of Transport and Infrastructure Research
issn 1567-7141
publishDate 2006-06-01
description This paper presents a universal logit model for P&R patronage. This model was estimated from a Stated Choice experiment, in which 805 car drivers chose among car, P&R and public transport alternatives. In addition to main-effects, attribute cross-effects were estimated denoting the utility change of an alternative due to changes in the attribute levels of another alternative. The results indicate that improving the levels of the P&R related attributes has a negligible effect on the utility of the car alternative, whereas worsening the levels of the carrelated attributes increases the utility of the P&R facility. Considering the estimated maineffects as well as the estimated cross-effects suggests that ‘stick’ (push) policy measures are more effective to stimulate P&R patronage than ‘carrot’ (pull) policy measures. The paper further reports that the extension of the model by adding cross-effects to the main-effects resulted in a better model fit and that the resulting model could more accurately predict the choices for new observations.
url https://journals.open.tudelft.nl/ejtir/article/view/3449
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