Investigating the impact of age-differentiated leadership on retention and performance-related outcomes: a moderated dual pathway model

Abstract Although research indicates that age-differentiated leadership (ADL) is positively associated with wellbeing outcomes for both younger and older workers, the ways in which it relates to performance and retention-related outcomes, and the mechanisms through which these effects occur, remain an important focus for further examination. Based on the Categorization-Elaboration Model (CEM), this study proposes and tests a dual pathway model suggesting that ADL is associated with retention-related outcomes via reduction in age bias, while self-rated performance-related outcomes are enhanced via information exchange. It is expected that these pathways will be stronger for older workers, compared to younger workers, based on lifespan developmental theories. Using a sample of 416 workers in Australia, the results showed that ADL predicted retention-related outcomes via age bias, and self-reported performance-related outcomes via information exchange. Age only moderated the strength of the performance pathway and not the retention pathway. This study offers empirical support for the theorized social categorization and information elaboration pathways in the CEM through which ADL positively impacts retention and performance-related outcomes, and expands the range of outcomes considered by previous research.

Authors

Institutions

Publication Details

Journal
Work Aging and Retirement
Published
2025-12-09
DOI
https://doi.org/10.1093/workar/waaf022
Primary Topic
Retirement, Disability, and Employment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the impact of age-differentiated leadership on retention and performance-related outcomes: a moderated dual pathway model

Daniela Andrei, Jane Chong, Sharon K. Parker, Eva Zellman
Work Aging and Retirement
Retirement, Disability, and Employment
article

Investigating the impact of age-differentiated leadership on retention and performance-related outcomes: a moderated dual pathway model

Daniela Andrei, Jane Chong, Sharon K. Parker, Eva Zellman
article en

Abstract

Abstract Although research indicates that age-differentiated leadership (ADL) is positively associated with wellbeing outcomes for both younger and older workers, the ways in which it relates to performance and retention-related outcomes, and the mechanisms through which these effects occur, remain an important focus for further examination. Based on the Categorization-Elaboration Model (CEM), this study proposes and tests a dual pathway model suggesting that ADL is associated with retention-related outcomes via reduction in age bias, while self-rated performance-related outcomes are enhanced via information exchange. It is expected that these pathways will be stronger for older workers, compared to younger workers, based on lifespan developmental theories. Using a sample of 416 workers in Australia, the results showed that ADL predicted retention-related outcomes via age bias, and self-reported performance-related outcomes via information exchange. Age only moderated the strength of the performance pathway and not the retention pathway. This study offers empirical support for the theorized social categorization and information elaboration pathways in the CEM through which ADL positively impacts retention and performance-related outcomes, and expands the range of outcomes considered by previous research.

Work Aging and Retirement
The University of Western Australia (AU), Curtin University (AU)
Openalex Percentile: Top 38%
Retirement, Disability, and Employment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.