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Educational Gerontology· 2026Q2

Why do silver-age faculty continue teaching after retirement? A study integrating LPA, HMR, and fsQCA

Bingbing Li, Xingman Yu, Xiaoyue Hu, Jing Han et al.

Short summary

Retired faculty teaching in higher education can be categorized into three profiles: comprehensive advantage (56%), stable and balanced (29%), and potential-to-be-unlocked (15%), with organizational identification and intergenerational learning positively driving participation, while age negatively impacts it (adjusted R²=0.492).

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Key points

  • Retired faculty teaching in higher education fall into three profiles: comprehensive advantage (56%), stable and balanced (29%), and potential-to-be-unlocked (15%).
  • Organizational identification (β=0.167) and intergenerational learning (β=0.170) are key positive drivers for continued teaching.
  • Age has a significant negative impact (β=-0.069) on retired faculty participation.
  • The model explaining participation achieved an adjusted R² of 0.492.
  • Five distinct development models for retired faculty were identified, including Integrated Performance Resource Type and Digital Intelligence Communication Type.

AI-generated from the title and abstract; the full text is not read.

Abstract

Against the backdrop of building an education power and an aging population, the development of silver-age faculty in higher education institutions is of great significance for revitalizing the human capital of the elderly and promoting educational equity. However, existing research mostly employs single-factor linear analysis, with insufficient attention paid to group heterogeneity, hierarchical driving mechanisms, and multi-dimensional collaborative paths. This study, based on the theory of social-technical transformation, takes 1,736 silver-age faculty in higher education institutions as the research subjects and comprehensively uses latent profile analysis (LPA), hierarchical multiple regression (HMR), and fsQCA methods for empirical research. The results show that silver-age faculty can be classified into three groups: 56% as the comprehensive advantage type, 29% as the stable and balanced type, and 15% as the potential-to-be-unlocked type; organizational identification (β = 0.167***) and intergenerational learning (β = 0.170***) are significant positive driving factors, while age (β = −0.069**) has a significant negative impact, with the adjusted R2 of the model reaching 0.492; and five development models are identified: Integrated Performance Resource Type, Technical Social Collaboration Type, Social Network Symbiosis Type, Digital Intelligence Communication Type, and Sociotechnical Learning-oriented Type, with an overall consistency of 0.913 and a coverage rate of 0.901. This study effectively enriches the theoretical system of elderly education and human resource development and provides solid empirical support and practical references for higher education institutions to promote silver-age faculty construction.

The authors' abstract, as published at the source. Educational Gerontology, 2026 · DOI ↗

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Field: Demography

DemographySocial Sciences