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Korean Academic Society of Business Administration
[ Article ]
korean management review - Vol. 51, No. 6, pp.1649-1672
ISSN: 1226-1874 (Print)
Print publication date 31 Dec 2022
Received 28 Jun 2022 Accepted 08 Aug 2022
DOI: https://doi.org/10.17287/kmr.2022.51.6.1649

국내 기업 근로자들의 고용브랜드 요인 탐색 및 기업 추천/미추천자 간 차이 분석: 구조적 토픽 모델링 적용

Sangsuk Oh ; Owwon Park
(First Author) National Cancer Center blueoss@ncc.re.kr
(Corresponding Author) The Catholic University of Korea owpark@catholic.ac.kr
Exploratory Study on the Analysis of Domestic Firm Workers’ Employer Brand and Differences between Employees Those Who Recommend Their Firm and Those Who Do Not: Application of Structural Topic Modeling


Copyright 2011 THE KOREAN ACADEMIC SOCIETY OF BUSINESS ADMINISTRATION
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study applies Structural Topic Modeling to explore the text data from corporate reviews of the recruitment platform describing employer brands and to investigate whether such data have meaningful differences between the employees who recommend their firms and those who do not. Specifically, we examine the text data on the satisfactory factors of companies as described by incumbent employees who recommend and do not recommend their firms. Topic modeling derives 30 topics, among which 22 are considered appropriate by using a critical review. These topics are labeled considering previous research on employer brands, and the highest percentage are categorized as ‘horizontal corporate culture’. Significant differences are identified between current employees who recommend and do not recommend their firms. Most of the extracted topics are similar to the variables that are previously used in literature. However, new topics are also derived from our studies. Finally, the implications of study findings are discussed.

Keywords:

Employer Brand, Text Mining, Structural Topic Modeling

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∙ The author Sangsuk Oh is a deputy manager of performance management team in National Cancer Center. He received his Ph.D. in management from the Catholic University of Korea. His research interests include strategic human resource management, turnover, and HR analytics.

∙ The author Owwon Park is a professor of management in the Department of Business Administration at the Catholic University of Korea. He received his Ph.D. in management from the Korea University Business School. His research focuses on strategic human resource management, talent management, turnover, and compensation.