Supporting Data and Software for the paper: An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability

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.<br>For more information, the pre-print of the paper is available on: <em>https://arxiv.org/abs/2301.04982</em><br>Information on the data and model can be found in the README file and the python script below.