chen_2025_parmigiano_it

4,080 rated or chosen profiles from 340 respondents, in up to 6 tasks of 2 profiles varying on 6 attributes.

One of 6 tables from the same source; this one is the parmigiano_it table. The others are listed under Related tables.

About this table

DescriptionDiscrete choice experiment: Italian consumers (online Qualtrics panel via TGM Research, quota-representative by gender and age, Feb-Mar 2025; n = 340) chose among two options and a 'Neither' alternative on 6 cards; profiles describe Parmigiano Reggiano varying cow feed (alfalfa / fodder mixtures), the 'di Montagna' label, ageing, purchasing place, CO2 compensation and price per kg. Outcome is the chosen option (opt-out allowed).
ReferenceChen, J., Mzek, T., & Piras, S. (2025). Dataset of choice experiment surveys assessing consumers' and farmers' preferences for five underutilised crops in different European countries [Data set]. Zenodo.
LicenceCC BY 4.0
Source datahttps://doi.org/10.5281/zenodo.15420092

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

Respondents340
Rows (one per respondent, task and profile)4,080
Tasks per respondent (most)6
Profiles per task2
Attributes6
Tasks with no profile chosen202

Design

Topicconsumer products
A profile representsproduct service
CountryIT
Language shownunknown
Language of stored levelsen
Randomization restrictionsyes (stated by the source): the codebook (ageing) states that with the 'Parmigiano Reggiano di Montagna' label the quality selection happens at 20 months minimum: label Yes never occurs with 12 months ageing; fixed blocked design of 36 cards in 6 sets; level_weights: label present in 1,586 vs absent in 2,494 profiles, 12-month ageing 907 vs ~1,590 for the others (follows from the label-ageing rule)
Task orderinferred from row order
Profile positionrecorded in the deposit

Because the attribute levels were not randomized independently, an estimator has to account for the restriction; a plain difference in means across levels can mislead. Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choiceWhich option would you buy? (paraphrase) [choice, opt-out allowed]

Columns

attr_ageingattr_cost_per_kgattr_environmental_impactattr_feedattr_label_montagnaattr_purchasing_placechoicecov_age_groupcov_duration_seccov_educationcov_gendercov_income_perccov_income_rangeidprofiletasktrial_choice_cardtrial_choice_settrial_treated

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("chen_2025_parmigiano_it", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("chen_2025_parmigiano_it", source="conj")

How to cite

@misc{https://doi.org/10.5281/zenodo.15420092,
  doi = {10.5281/ZENODO.15420092},
  url = {https://zenodo.org/doi/10.5281/zenodo.15420092},
  author = {CHEN, Jianyu and Mzek, Tareq and Piras, Simone},
  keywords = {underutilised crops, consumer preferences, farmer preferences, discrete choice experiment, public good game, food behaviour, farmer behaviour},
  language = {en},
  title = {Dataset of choice experiment surveys assessing consumers' and farmers' preferences for five underutilised crops in different European countries},
  publisher = {Zenodo},
  year = {2025},
  copyright = {Creative Commons Attribution 4.0 International}
}

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint v4.2
Redivis dataset DOI10.57761/qkye-q530
Manifest pin for this IRW versionv4.2
Metadata sourceirw_meta v44.0