letki_2025_bottle_recycling

21,435 rated or chosen profiles from 21,435 respondents, in up to 1 tasks of 1 profile varying on 3 attributes.

One of 3 tables from the same source; this one is the bottle_recycling table. The others are listed under Related tables.

About this table

Description21,435 respondents in 14 post-communist countries (PGPE survey, 2013-2014) each saw one version of a vignette about a glass-bottle disposal facility (distance, type of machine, and how many others use it) and rated how likely they were to use the facility to dispose of glass bottles (1 very likely to 4 not likely at all).
ReferenceLetki, N. (2025). Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe [Data set]. Dane Badawcze UW.
LicenceCC BY 4.0
Source datahttps://doi.org/10.58132/sbjiw0

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

Respondents21,435
Rows (one per respondent, task and profile)21,435
Tasks per respondent (most)1
Profiles per task1
Attributes3

Design

Topicclimate energy environment, social identity interpersonal
A profile representsscenario
CountryBG, HR, CZ, EE, HU, LV, LT, MD, PL, RO, RS, SK, SI, UA
Language shownunknown
Language of stored levelsen
Task orderinferred from row order
Profile positioninferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

ratingHow likely is it that you will be using these facilities to dispose of your glass bottles? (master English questionnaire, card G04) [rating, 1 (Very likely) to 4 (Not likely at all)]

Columns

attr_distanceattr_machine_typeattr_others_usingcov_age_groupcov_birth_yearcov_countrycov_educationcov_survey_weightidprofileratingtask

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("letki_2025_bottle_recycling", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("letki_2025_bottle_recycling", source="conj")

How to cite

@misc{https://doi.org/10.58132/sbjiw0,
  doi = {10.58132/SBJIW0},
  url = {https://danebadawcze.uw.edu.pl/citation?persistentId=doi:10.58132/SBJIW0},
  author = {Letki, Natalia},
  title = {Public goods through private eyes. Exploring citizens' attitudes to public goods and the state in Central Eastern Europe},
  publisher = {Dane Badawcze UW},
  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