An Agentic, Systemic, and Dynamic Perspective on Sustainable Careers

Y Ngoc Nhu Nguyen

Research output: PhD ThesisPhD-Thesis - Research and graduation internal

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Abstract

Crafting a sustainable career—one that allows employees to be happy, healthy, and productive throughout their lifespan—has become a major concern for employees, organizations, and society at large. However, research on sustainable careers is still in its infancy. Thus, we know little about how multiple stakeholders (i.e., supervisors, coworkers, and spouses) contribute to employees’ sustainable careers and how these careers manifest and evolve over time in practice. Across three studies—a meta-analysis of the crossover of happiness, health, and productivity; a three-wave study examining how career competencies and career mentoring may cross over between colleagues; and another three-wave study examining latent profiles and latent changes in career sustainability—this dissertation aims to address these fundamental research gaps and advance the field of sustainable careers. The research findings uncover critical mechanisms (e.g., crossover processes) and contextual conditions (e.g., an emotional culture of joy) under which stakeholders positively shape employees’ sustainable careers. Moreover, this dissertation also reveals several sustainable career patterns that employees may display at work and their change trajectories over time. The new insights in this dissertation contribute to the theorizing on sustainable careers and suggest strategies that employees and organizations can implement to enable more sustainable careers.
Original languageEnglish
QualificationPhD
Awarding Institution
  • Vrije Universiteit Amsterdam
Supervisors/Advisors
  • Khapova, SN, Supervisor
  • Akkermans, Jos, Co-supervisor
Award date25 Sept 2024
Print ISBNs9789036107433
DOIs
Publication statusPublished - 25 Sept 2024

Keywords

  • sustainable careers
  • happiness
  • health, productivity
  • meta-analysis
  • employability
  • career competencies
  • mentoring
  • quantitative research
  • dyadic data

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