TY - DATA T1 - [Supporting Data and Software] An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability PY - 2023/03/23 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.v2 KW - Instance-based learning KW - Memory decay KW - Choice modelling KW - Ride-hailing KW - Waiting time KW - Service reliability N2 -

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.

 

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.

More information about the research and the data can be found in the files below and the linked pre-print.

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