gonzalezaguilera_2026_interurban_mode

12,480 rated or chosen profiles from 420 respondents, in up to 12 tasks of 3 profiles varying on 9 attributes.

About this table

DescriptionStated-preference experiment on interurban mode choice in the Santiago-Rancagua corridor, Chile: 420 online-panel respondents chose in 12 tasks among a train, a coach bus and (in some designs) a rural bus, described by crowding, last-mile time, frequency, air conditioning, street vendors, cost, travel time and departure variability, or none of them.
ReferenceGonzalez-Aguilera, P., Guevara, C. A., Henriquez-Jara, B., & Daziano, R. A. (2026). Stated preference survey on interurban mode choice: Santiago-Rancagua corridor, Chile [Data set]. Zenodo.
LicenceCC BY 4.0
Source datahttps://doi.org/10.5281/zenodo.21270302

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

Respondents420
Rows (one per respondent, task and profile)12,480
Tasks per respondent (most)12
Profiles per task3
Attributes9
Tasks with no profile chosen164

Design

Topicclimate energy environment
A profile representsproduct service
CountryCL
Language shownes
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceIf these were the only options for your habitual trip, which would you choose? [choice, opt-out allowed]

Columns

attr_air_conditioningattr_costattr_crowdingattr_departure_variabilityattr_frequencyattr_last_mile_timeattr_modeattr_street_vendors_musiciansattr_travel_timechoicecov_agecov_cars_householdcov_destinationcov_driving_licencecov_gendercov_household_sizecov_income_gsecov_last_mile_modecov_reduced_fareidprofiletasktrial_blocktrial_od_design

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("gonzalezaguilera_2026_interurban_mode", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("gonzalezaguilera_2026_interurban_mode", source="conj")

How to cite

@misc{https://doi.org/10.5281/zenodo.21270302,
  doi = {10.5281/ZENODO.21270302},
  url = {https://zenodo.org/doi/10.5281/zenodo.21270302},
  author = {González-Aguilera, Pablo and Guevara, C. Ángelo and Henríquez-Jara, Bastián and Daziano, Ricardo A.},
  keywords = {stated preference, discrete choice, mode choice, interurban transport, public transport, rail, psychometric indicators, Chile},
  language = {en},
  title = {Stated Preference Survey on Interurban Mode Choice: Santiago-Rancagua Corridor, Chile},
  publisher = {Zenodo},
  year = {2026},
  copyright = {Creative Commons Attribution 4.0 International}
}

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