Item Response Warehouse / Tables / li_2025_marketing_learningli_2025_marketing_learning
1,760 responses from 352 respondents to 5 items.
About this table
Description Marketing learning scale (5 items 7-pt Likert) rated by managers/employees at Chinese time-honored (heritage) enterprises Reference Li X, et al (2025) Breaking the deadlock: A study on the pathway and effects of reshaping the sustainable marketing capability of Chinese time-honored brands. PLoS ONE 20(6): e0326329 DOI 10.1371/journal.pone.0326329 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0326329
Size and shape
Responses 1,760 Respondents 352 Items 5 Response categories 5 Responses per respondent 5 Responses per item 352 Density 1 Longitudinal FALSE
Classification
sample Workplace measurement tool Survey/questionnaire item format Likert Scale/selected response primary language(s) chi
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
Instrument Marketing Learning (ML) Mean words per item 1 Mean characters per item 2 Mean characters per response 13 Flesch-Kincaid grade level -3.400
Columns
cov_firm_size cov_firm_type cov_gender cov_industry cov_location cov_position id item resp
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("li_2025_marketing_learning")
# Python
pip install irw
import irw
df = irw.fetch("li_2025_marketing_learning")
Version and provenance
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
Part of the Item Response Warehouse , IRW v393. This page describes the table as released in item_response_warehouse_4 v7.0.