Development and Applicability of NCS-based Job Matching Algorithm: Korean Youth Labor Market
Jaehyung Cho1, Yeoungil Lee2, Jungpo Kim3, Seungbum Lee4
1Jaehyung Cho, Associate Professor, Department of Faculty of Global Business, Geumsaem-Ro beon-Gil, Geumjeong-Gu, Busan University of Foreign Studies, Busan, South Korea, East Asian.
2Yeoungil Lee, Associate Professor, Department of Faculty of Global Business, Busan University of Foreign Studies, Busan, South Korea, East Asian.
3Jungpo Kim, Associate Professor, Department of Faculty of Global Business, Busan University of Foreign Studies, Busan, South Korea, East Asian.
4Seungbum Lee, Associate Professor, Department of Faculty of School of Sport Science & Wellness Education, South Broadway Street, The University of Akron, Akron, OH, USA.
Manuscript received on 20 June 2019 | Revised Manuscript received on 27 June 2019 | Manuscript Published on 22 June 2019 | PP: 225-231 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H10410688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Youth unemployment has been such a serious matter in Korea for years and, to respond to this matter, several initiatives have been developed and implemented. Notably, job mismatching as a form of unemployment or underemployment for graduates of colleges and universities is continuously happening. Methods/Statistical analysis: To address job mismatch as a social problem, colleges and universities are asked to focus on competency-based learning; as a result, the National Competency Standards (NCS) was developed so that higher education can strategically strengthen and implement more career-focused curriculum and practical experiences in order to solve the youth unemployment problem. The purpose of this study is to develop a strategic plan that can solve youth unemployment problem in a Korean labor market. Findings: To do so, this study develops an algorithm that presents the most optimal job match between competencies of a job seeker (n) and competencies of an employer (m). In addition, this study will discuss a job matching system based on the algorithm for practical usage. This study standardized NCS-based competencies and proved that this system can be practically utilized to identify multiple job seekers for the company. Improvements/Applications: Calculating and producing weights through the MADM algorithm is particularly helpful in identifying a pool of job seekers for the companies, which will increase the probability of successful hiring/finding a job in the labor market.
Keywords: Youth Unemployment, Job Matching System, Multi-Attribute Decision Making, National Competency Standards.
Scope of the Article: Decision Making