An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability

The files here are asscoiated with the following paper, which is currently in the publication process:
Geržinič, N., Cats, O., van Oort, N., Hoogendoorn-Lanser, S., Bierlaire, M., Hoogendoorn, S. (2022). An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability [Manuscript submitted for publication]. https://arxiv.org/abs/2301.04982

The dataset contains sensitive personal information and could therefore not be included here. A sample dataset with 10 rows of data is included as an example. Note that the values shown are random and do not correspond to any particular respondent.

The original dataset includes the responses of 936 respondents of the Dutch Mobility Panel, each of which answered 32 hypothetical scenarios, with immediate feedback on the performance of their selected alterantive. In addition, the dataset also contains information on the respondents' socio-demographic characteristics and their attitudes towards and familiarity with sharing-economy services.

Here, you will find:
example_dataset.csv     --> Example dataset (10 rows)
choice_model.py         --> Biogeme Pandas code used to estimate the model
model_outcome.html      --> Biogeme output file of the final model
survey_transcript.docx  --> Transcript of the survey in both Dutch and English, with example graphics

