Development and Applicability of NCS-based Job Matching Algorithm: Korean Youth Labor Market

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.