직무 리뷰 분석을 통한 산업군별 직무만족/존속 요인 및 직무불만족/이직 요인에 관한 연구

• 영문명: A Study on Job Satisfaction/Retention Factors and Job Unsatisfaction/Turnover Factors by Industries using Job Reviews
• 발행기관: 한국IT서비스학회
• 저자명: 이종서(Jong seo Lee) 김성근(Sung geun Kim) 강주영(Ju young Kang)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제16권 제1호, 1~26쪽, 전체 26쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2017.03.30

영문 초록

Keeping good, talented people is one of the most significant factors in a company s success. HR analytics is an important area for applying big data analysis techniques to human resources. It provides organizational insight that enables effective management of employees, allowing management to reach their business goals quickly and efficiently. Job satisfaction and employee turnover analysis are the keys to HR analytics. Job review web services have been becoming popular. Because people exchange information about job satisfaction and turnover through these web services, useful information about HR Analytics is accumulated on the job review web sites. In this paper, we identified factors of employee retention by analyzing a Job Satisfaction/Retention group, and the factors of employee turnover by analyzing a Job Unsatisfaction/Turnover group. In order to do this, we first classified employees according to whether their self-reported job satisfaction or turnover was true. We collected and analyzed data from Jobplanet, a popular job review site. Through dominance analysis and LDA topic modeling, we found major factors, topics, and keywords of the classified groups by IT, service, and manufacturing domains. Our approach is a novel model to apply the analysis of reviews and text mining to the HR domain, and it will be practically helpful for setting new strategies that improve job satisfaction.

목차

1. 서 론

2. 관련 연구

3. 연구방법

4. 분석결과

5. 결론 및 시사점

References

키워드

Job Review Data Analysis Job Satisfaction Retention Turnover Dominance Analysis LDA Topic Modeling