3,204 rated or chosen profiles from 267 respondents, in up to 6 tasks of 2 profiles varying on 8 attributes.

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

About this table

Description	German municipal front desk officers (March 2023, n = 267) chose between two hypothetical municipal e-government chatbots varying developer, chat-history storage, chat termination, automated decisions, workload reduction, time saving, and communication type and tone, in 6 paired tasks.
Reference	Hemesath, S., & Tepe, M. (2024). Public value positions and design preferences toward AI-based chatbots in e-government. Evidence from a conjoint experiment with citizens and municipal front desk officers. Government Information Quarterly, 41(4), 101985.
DOI	10.1016/j.giq.2024.101985
Licence	CC0 1.0
Source data	https://doi.org/10.7910/DVN/JJYIUD

Notes

Conjoint table (irw_conjoint). Forced choice between two chatbot profiles (paraphrase: which chatbot do you prefer), exactly one chosen per task, no opt-out; 8 attributes with 3 levels each, in German. Sample: municipal front desk officers. The -5..+5 relative-preference slider is dropped because its wording and anchors are undocumented. Randomization restrictions and attribute order undocumented; all level pairs occur.

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents	267
Rows (one per respondent, task and profile)	3,204
Tasks per respondent (most)	6
Profiles per task	2
Attributes	8
Tasks with no profile chosen	0

Design

Topic	public administration, technology ai privacy
A profile represents	product service
Country	DE
Language shown	de
Language of stored levels	de
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	recorded in the deposit

Outcomes:

choice	Which of the two chatbots do you prefer? (paraphrase) [choice, forced]

Columns

attr_chat_historyattr_chat_terminationattr_chatbot_decidesattr_communication_toneattr_communication_typeattr_developerattr_time_savingattr_workload_reductionchoicecov_agecov_duration_seccov_education_codecov_gender_codecov_stateidprofiletask

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 needed Browse on Redivisexplore and query Croissant 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("hemesath_2024_chatbot_officers", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("hemesath_2024_chatbot_officers", source="conj")

How to cite

@article{Hemesath_2024, title={Public value positions and design preferences toward AI-based chatbots in e-government. Evidence from a conjoint experiment with citizens and municipal front desk officers}, volume={41}, ISSN={0740-624X}, url={http://dx.doi.org/10.1016/j.giq.2024.101985}, DOI={10.1016/j.giq.2024.101985}, number={4}, journal={Government Information Quarterly}, publisher={Elsevier BV}, author={Hemesath, Sebastian and Tepe, Markus}, year={2024}, month=Dec, pages={101985} }

Version and provenance

IRW version	v584
Redivis dataset	irw_conjoint v4.2
Redivis dataset DOI	10.57761/qkye-q530
Manifest pin for this IRW version	v4.2
Metadata source	irw_meta v44.0