Profiling sustainable career options and its patterns amongst professionals: a longitudinal study
Abstract
Purpose Drawing the rationales from the sustainable career framework, and in the context of social cognitive career theory, the study examines how Science & Technology and Management graduates' career develop over time, illustrating diverse career patterns, their association with the professionals' gender diversity, career success, and self-employment. Design/methodology/approach The present study utilised the LinkedIn database to extract the profiles of professionals working in Information Technology companies. The longitudinal data from 1,161 graduates over a period of 10 years were used for optimal matching analysis (OMA). Findings The results of OMA depicted four distinct career patterns, which are Related, Partly related, Related with career break and Unrelated sustainable career patterns. We find differences in gender among different career patterns. Furthermore, we observed that professionals characterised by Partly related and Unrelated patterns show more career success than Related career pattern, and for self-employment, we find an insignificant relationship. Research limitations/implications The study enriches the literature on career sustainability by investigating occupational career patterns of graduates and highlighting the gender diversity perspective. It also discusses the significance of performance management in enhancing the productivity of professionals to achieve career success. Originality/value The current study provides a novel perspective to sustainable career framework by empirical investigation of career patterns of the Science & Technology and Management graduates over the long term. The findings present practical insights to the organisations and higher education institutions to promote sustainable careers of professionals.
Key Points
Objective
The study aims to explore career development patterns of Science & Technology and Management graduates over time.
Methods
- Utilized LinkedIn database to collect profiles of professionals in Information Technology companies.
- Analyzed longitudinal data from 1,161 graduates over a decade using optimal matching analysis (OMA).
- Investigated associations of career patterns with gender diversity, career success, and self-employment.