TY - DATA
T1 - Supporting Data and Software for the paper: An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability
PY - 2023/03/21
AU - Nejc Geržinič
AU - Oded Cats
AU - Niels van Oort
AU - Sascha Hoogendoorn-Lanser
AU - S.P.(Serge) Hoogendoorn
AU - Michel Bierlaire
UR - 
DO - 10.4121/45cae66c-7eb3-4e04-85a9-59f6e26cfbb9.v1
KW - Instance-based learning
KW - Memory decay
KW - Choice modelling
KW - Ride-hailing
KW - Waiting time
KW - Service reliability
N2 - <p>The files included below are part of the CriticalMaaS research on ride-hailing and on-demand transport services. In this study, passengers' perception of waiting time variability was analysed.</p><p>&nbsp;</p><p>Respondents were presented with 32 hypothetical scenarios with immediate feedback on the performance of their selected alternatives. This feedback information was then incorporated into their decision-making for the following scenario.</p><p><br></p><p>For more information, the pre-print of the paper is available on: <em>https://arxiv.org/abs/2301.04982</em></p><p><br></p><p>Information on the data and model can be found in the README file and the python script below.</p>
ER -