419
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Relumining perceived workplace gender discrimination in South Korea: examining determinants and paths through decision trees

ORCID Icon &
Pages 239-256 | Received 23 Jun 2022, Accepted 07 Apr 2023, Published online: 12 Apr 2023
 

ABSTRACT

This study explores how women employees perceive gender discrimination in the workplace and how data can be used to predict perceived workplace gender discrimination (PWGD). The research team modelled the decision tree that predicted PWGD in South Korea using the Classification and Regression Trees (CART) algorithm and the data from the 7th Korean Women Manage Panel (KWMP). Three types of PWGD trees – wage, promotion, and evaluation – and one synthesised PWGD tree were built to predict and classify PWGD by discrimination type. The research findings suggest that the chief executive officer’s (CEO) fairness is the cardinal factor in predicting synthesised PWGD, followed by an employee’s exposure to sexual harassment. Whereas the CEO’s fairness is the principal factor in predicting PWGD in promotion, the direct supervisor’s fairness is the most significant factor in predicting PWGD in evaluation. Perceived disparities in pay between women managers and similarly positioned men colleagues are the critical factor in predicting wage PWGD. Lastly, this paper elaborates on important considerations in PWGD and recommendations for continued inquiry.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 407.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.