Psychometric Factors in Human Capital Research: Identification and Modeling of Employee Groups
Anna Aletdinova, Maxim Bakaev
Available Online December 2017.
- https://doi.org/10.2991/itsmssm-17.2017.57How to use a DOI?
- information society, human capital, freelance, Mincer model, web scraping
- Post-industrial economy is shaped by both digitalization, i.e. network-based co-ordination of relations, advanced development of service industry, increase in the number of open innovations, and by deep changes in the role of human and knowledge. The development of Information society can provide competitive advantages for a country in the world economy, as cyberspace enhances intellectual and emotional human resources, broadens cognitive, creative and communication skills, thus allowing boosting the human capital. Our paper is dedicated to studying the factors of education, work experience and personal features (psychometric factors) with respect to their effect on wages and overall identification of employee groups. In this, we employ labor market statistics (both traditional one and collected from online sources with a dedicated software system) and psychological diagnostics methods, which we modified according to our tasks. In our current work, two groups of employees were identified based on the above factors and enhanced Mincer model's quantitative evaluations: freelancers and full-time employees. We particularly consider the effects of education level and type (including open education), work experience, residence location, and personal features on wages in the Siberian Federal Okrug.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Anna Aletdinova AU - Maxim Bakaev PY - 2017/12 DA - 2017/12 TI - Psychometric Factors in Human Capital Research: Identification and Modeling of Employee Groups BT - IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/itsmssm-17.2017.57 DO - https://doi.org/10.2991/itsmssm-17.2017.57 ID - Aletdinova2017/12 ER -