flores_2025_gasoline_brands

3,013 rated or chosen profiles from 270 respondents, in up to 12 tasks of 1 profile varying on 4 attributes.

About this table

DescriptionDrivers in the Monterrey metropolitan area (Mexico) rated 12 hypothetical gas-station visits each, described by brand, waiting time and the prices of 87- and 91-octane gasoline. 270 respondents, 3,013 single-profile ratings on a 1-10 scale.
ReferenceFlores, D., & Arteaga, J. C. (2025). Conjoint gasoline data [Data set]. Mendeley Data.
LicenceCC BY 4.0
Source datahttps://doi.org/10.17632/vdrhxr25m5

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

Respondents270
Rows (one per respondent, task and profile)3,013
Tasks per respondent (most)12
Profiles per task1
Attributes4

Design

Topicconsumer products
A profile representsproduct service
CountryMX
Language shownes
Language of stored levelses
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

ratingRate given to a hypothetical visit, scale of 1 to 10. (Variables description sheet, English) [rating, 1 (unknown) to 10 (unknown)]

Columns

attr_brandattr_price_87attr_price_91attr_wait_minutescov_age_groupcov_fuel_usedcov_gendercov_hybrid_carcov_municipalitycov_weekly_spendidprofileratingtasktrial_version

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("flores_2025_gasoline_brands", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("flores_2025_gasoline_brands", source="conj")

How to cite

@misc{https://doi.org/10.17632/vdrhxr25m5,
  doi = {10.17632/VDRHXR25M5},
  url = {https://data.mendeley.com/datasets/vdrhxr25m5},
  author = {Flores, Daniel and Arteaga, Julio C.},
  keywords = {Energy Economics, Applied Economics, FOS: Economics and business},
  title = {Conjoint gasoline data},
  publisher = {Mendeley Data},
  year = {2025}
}

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