lichtin_2024_road_pricing

32,292 rated or chosen profiles from 3,359 respondents, in up to 5 tasks of 2 profiles varying on 5 attributes.

About this table

DescriptionSwiss Mobility Panel respondents (wave 2, 2021; n=3,359 with a recorded choice) chose between and rated pairs of road-pricing proposals in 5 tasks, varying motorway toll, city-centre entrance fee, motorway and urban peak speeds and the use of the revenue; a randomised information vignette preceded the tasks. Outcomes are the chosen proposal and a 1-5 favour/oppose rating of each.
ReferenceLichtin, F. M., Smith, E. K., Axhausen, K. W., & Bernauer, T. (2024). How to design publicly acceptable road pricing? Experimental insights from Switzerland. Ecological Economics, 218, 108102.
DOI10.1016/j.ecolecon.2023.108102
LicenceCC BY 4.0
Source datahttps://doi.org/10.5281/zenodo.18255559

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents3,359
Rows (one per respondent, task and profile)32,292
Tasks per respondent (most)5
Profiles per task2
Attributes5
Tasks with no profile chosen0

Design

Topicclimate energy environment
A profile representspolicy
CountryCH
Language shownde, fr, it, en
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceSuppose you had to decide between the two proposals in a referendum today. Would you rather support Proposal A or Proposal B? [choice, forced]
ratingHow much would you favor or oppose Proposal A? (B_3_X; Proposal B: B_4_X) [rating, 1 (Strongly favor) to 5 (Strongly oppose)]

Columns

attr_entrance_feeattr_motorway_speedattr_motorway_tollattr_revenue_useattr_urban_speedchoicecov_car_owncov_household_incomecov_languagecov_urban_ruralidprofileratingtasktrial_info_treatment

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("lichtin_2024_road_pricing", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("lichtin_2024_road_pricing", source="conj")

How to cite

@article{Lichtin_2024, title={How to design publicly acceptable road pricing? Experimental insights from Switzerland}, volume={218}, ISSN={0921-8009}, url={http://dx.doi.org/10.1016/j.ecolecon.2023.108102}, DOI={10.1016/j.ecolecon.2023.108102}, journal={Ecological Economics}, publisher={Elsevier BV}, author={Lichtin, Florian and Smith, E. Keith and Axhausen, Kay W. and Bernauer, Thomas}, year={2024}, month=Apr, pages={108102} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0