fu_2026_victory_concrete

10,110 rated or chosen profiles from 1,011 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.

One of 2 tables from the same source; this one is the concrete table. The others are listed under Related tables.

About this table

DescriptionTaiwanese adults (wave 2, concrete condition, n=1,011) compared 5 pairs of hypothetical scenarios of Chinese aggression varying international military support (doing nothing/providing weapons/sending troops by the US and Japan), sanctions, economic and military strength, readiness, morale and party unity, choosing one (perceived victory).
ReferenceFu, R. T., Lee, E. I., & Kao, K. Y. (2026). Do you think David can win against Goliath? Evidence on factors affecting popular perceptions of victory in Taiwan against Chinese aggression. Research & Politics.
DOI10.1177/20531680261467197
LicenceCC0 1.0
Source datahttps://doi.org/10.7910/DVN/FUILWY

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

Respondents1,011
Rows (one per respondent, task and profile)10,110
Tasks per respondent (most)5
Profiles per task2
Attributes7
Tasks with no profile chosen0

Design

Topicforeign policy security
A profile representsscenario
CountryTW
Language shownunknown
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choicewhich scenario is more likely to result in Taiwan's victory (paraphrase) [choice, forced]

Columns

attr_economic_strengthattr_military_strengthattr_military_supportattr_moraleattr_party_unityattr_readinessattr_sanctionschoicecov_age_groupcov_birth_yearcov_gendercov_identitycov_regionidprofiletask

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("fu_2026_victory_concrete", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("fu_2026_victory_concrete", source="conj")

How to cite

@article{Fu_2026, title={Do you think David can win against Goliath? Evidence on factors affecting popular perceptions of victory in Taiwan against Chinese aggression}, volume={13}, ISSN={2053-1680}, url={http://dx.doi.org/10.1177/20531680261467197}, DOI={10.1177/20531680261467197}, number={3}, journal={Research &amp; Politics}, publisher={SAGE Publications}, author={Fu, Ronan Tse-min and Lee, Elaine I-lien and Kao, Karyn Y.}, year={2026}, month=July }

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