3,860 responses from 386 respondents to 10 items.
One of 4 tables from the same source; this one is the benefit table. The others are listed under Related tables.
| Description | Perceived AI benefit across 10 sectors (healthcare, insurance, agriculture, finance, military, law enforcement, environment, transport, manufacturing, HR); N=386 adults in Bosnia and Herzegovina; 1-5 Likert |
|---|---|
| Reference | Karajko, A., Slabić, E., & Krivić, S. (2025). Artificial Intelligence in Bosnia and Herzegovina: A Study on Awareness, Attitude, and Trust [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/IREEJJ |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/IREEJJ |
| Responses | 3,860 |
|---|---|
| Respondents | 386 |
| Items | 10 |
| Response categories | 5 |
| Responses per respondent | 10 |
| Responses per item | 386 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Internet-based |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | bos |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Percepcije o vještačkoj inteligenciji (VI) građana BiH -- P7, procjena koliko se VI koristi po sektorima |
|---|---|
| Mean words per item | 8 |
| Mean characters per item | 68 |
| Mean characters per response | 7.200 |
| Flesch-Kincaid grade level | 14.659 |
This codebook is reconstructed by the IRW from the IRW data standard. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | not traced |
item | IRW standard Item identifier. | not traced |
resp | IRW standard Response value. | not traced |
| Respondent covariates | ||
cov_age | Covariate | not traced |
cov_education | Covariate | not traced |
cov_gender | Covariate | not traced |
cov_region | Covariate | not traced |
What item codes and covariate values stand for is in the source’s documentation, ESM_4.pdf.
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("karajko2025_ai_benefit")
# Python
pip install irw
import irw
df = irw.fetch("karajko2025_ai_benefit")
@misc{https://doi.org/10.7910/dvn/ireejj,
doi = {10.7910/DVN/IREEJJ},
url = {https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/IREEJJ},
author = {Karajko, Ajla and Slabić, Elma and Krivić, Senka},
keywords = {Social Sciences, AI Awareness, AI Trust, AI Attitude, AI Governance, Public Perception of AI, Bosnia and Herzegovina},
title = {Artificial Intelligence in Bosnia and Herzegovina: A Study on Awareness, Attitude, and Trust},
publisher = {Harvard Dataverse},
year = {2025}
}
| IRW version | v569 |
|---|---|
| Redivis dataset | item_response_warehouse_2 v33.0 |
| Redivis dataset DOI | 10.57761/6m04-m698 |
| Manifest pin for this IRW version | v33.0 |
| Metadata source | irw_meta v43.0 |