Managing the Human Potential of Highly Educated Experts in the Field of Technical Sciences

Abstract

Migration of highly educated professionals has intensified worldwide in the last two decades. Attractive working conditions for highly educated specialists are subject to the human resource management policy in companies. The results of the regression analysis identified three variables of preferred working conditions in the workplace that have migration potential in the group of pull migration factors: advancement opportunities, work in the profession, and the possibility of ensuring a good quality of life. The purpose of the research was to analyse whether students in the technical field of science differ from students in other fields of science in the group of migration attraction factors. One-way ANOVA method is used for analysing differences between groups: no statistically significant differences were found in the preferences of students of technical sciences and students of other fields of science. These findings are useful to domestic companies when attracting and creating quality working conditions for technical science experts: employment in jobs in their profession, development of a career plan that includes learning and advancement, financial and nonfinancial benefits that ensure a good quality of life.

Comparative Analysis between Quality of Life and Human Labor in Countries Belonging to G7 and BRICS Blocks: Proposition of Discriminant Analysis Model

“…Both concepts of QoL and labor are linked. QoL has an impact on labor conditions, and such a QoL perception by the population covers either individual subjective aspects or individual and socio-environmental factors that surround a given socio-cultural context, as well as aspects like objectively measuring human life conditions, healthm and labor (Bartolović 2024;Cecere et al 2023;De Oliveira et al 2021;Louzado et al 2021;Randall et al 2023;Razika et al 2023;Sousa et al 2023;Turgut et al 2024). Different statistical methods and questionnaires have been used to investigate and analyze QoL and its relation to labor, such as WHOQOL-bref (Fleck et al 2000), WHOQOL-100 (Fleck et al 1999), cluster analysis (Bird et al 2023), logistic regression (Maryam et al 2023), and, most recently, discriminant analysis (Dunuwila et al 2023).…”