Industrial human resource management optimization based on skills and characteristics

In an increasingly diversified and competitive job market, not only is seeking the right job more challenging but also for companies, finding and holding on to the right persons is becoming the competitive edge necessary to outperform and grow. Skill preference and personality traits are key factors used to find the right candidate and previously many of this process have been conducted manually. The characteristics of job candidate and core-workers in companies are represented by Myers-Briggs Type Indicator (MBTI). The main reason for considering personality trait is to find and hire job candidates having the same trait as the company's core employees' hard working and loyal employees so that adapting to company culture and environment does not become difficult process for new hires. In this paper, the framework named Artificial Intelligence based Design platform (AID) has been applied for career matching based on companies' and candidates' skill preferences and MBTI with constraint of working location. The paper investigates three conceptual matching optimizations including (1) skill preferences, (2) skill preferences under working area constraint, (3) skill and MBTI preference with working area constraint. The numerical results show that the proposed method produces higher quality matching when compared to the conventional methods.