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A multilevel analysis of gender gap in human resource development participation: Evidence from South Korean workplaces
Journal of the Korean Data & Information Science Society 2023;34:351-63
Published online March 31, 2023;
© 2023 Korean Data and Information Science Society.

Hyun Woo Kim1

1Department of Sociology, Chungbuk National University
Correspondence to: 1 Assistant professor, Department of Sociology, Chungbuk National University, Chungcheongbuk-do, Korea. E-mail:
Received January 1, 2023; Revised January 26, 2023; Accepted January 30, 2023.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This study examines how employees’ participation rates in human resource development (HRD) programs differ by gender as well as the gender structure of a given workplace. Drawing upon human capital theory and segmented labor market theory, this study discusses how individual employees’ genders and the various unique factors shaping the gender structure of a workplace are associated with employees’ participation in various HRD programs. Utilizing a large-scale, matched employee-workplace data set surveying 48,062 employees in 628 South Korean workplaces, the current study conducted a repeated cross-sectional multilevel regression analysis. The quantitative analysis reveals that individual participation in HRD programs is strongly affected not only by employee-level gender characteristics, but also by workplace-level gender structures, even after controlling for characteristics such as organizational size, perceived HRD climates, or union membership. This study provides practitioners with an applied understanding of the connection between the fair treatment of female employees regarding HRD involvement and the resultant improvement in organizational effectiveness and corporate social responsibility.
Keywords : Evidence-based HRD, gender inequality, human resource development, multilevel analysis, Poisson distribution.