843 responses from 281 respondents to 3 items.
| Description | Usage Intention construct, 3 items, 1-7 scale, N=281 Chinese high-tech SME employees on AI computing leasing adoption |
|---|---|
| Reference | Sun W, Tohirovich Dedahanov A, Li WP, Young Shin H. (2024). Sanctions and opportunities: Factors affecting China's high-tech SMEs adoption of artificial intelligence computing leasing business. Heliyon. |
| DOI | 10.1016/j.heliyon.2024.e36620 |
| Licence | CC BY 4.0 |
| Source data | https://www.sciencedirect.com/science/article/pii/S2405844024126514 |
| Responses | 843 |
|---|---|
| Respondents | 281 |
| Items | 3 |
| Response categories | 7 |
| Responses per respondent | 3 |
| Responses per item | 281 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | Workplace |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Usage |
|---|---|
| Mean words per item | 9.333 |
| Mean characters per item | 51.333 |
| Mean characters per response | 2 |
| Flesch-Kincaid grade level | 8.700 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("sun_2024_usage")
# Python
pip install irw
import irw
df = irw.fetch("sun_2024_usage")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse_4 v7.0 |
| Redivis dataset DOI | 10.57761/cpj5-vm97 |
| Manifest pin for this IRW version | v7.0 |
| Metadata source | irw_meta v23.0 |