Aging populations pose a persistent challenge to the sustainability of public pension systems. To tackle these financial pressures, many countries strengthen the incentives to work by increasing the statutory retirement age and reducing early retirement benefits. These policy reforms make retirement a topic of utmost importance for individuals, organizations, and societies. Although retirement predictors are already a widely studied topic in the literature, there is still much to investigate about why people decide to retire when they do. In particular, the role of work-related variables in the retirement decision-making process is still not fully understood. Thus, the aim of this study was to examine how individual and work factors influence retirement timing (early, on-time, and later retirement). Forty-one interviews were conducted, and data were subjected to content analysis. The inter-relationship between the multiple categories was analyzed by a Multiple Correspondence Analysis (MCA) combined with Cluster Analysis. Results revealed three distinct profiles, which allowed us to group the participants into three clusters. The stay factors profile (e.g., high positive experiences at work, having no dependents, the spouse/partner not being retired) was associated with later retirement. These results can be important for organizations that want and need to retain the best senior talents, by acknowledging that positive experiences at work are associated with older workers’ desire of postponing retirement.

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Retirement,Retirement timing,Retirement transition profiles,Multiple correspondence analysis,Cluster analysis

• Psicologia - Ciências Sociais
• Economia e Gestão - Ciências Sociais