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Retirement intentions: what is the role of push factors in predicting retirement intentions?

Published online by Cambridge University Press:  30 April 2012

JODI OAKMAN*
Affiliation:
Centre for Ergonomics and Human Factors, La Trobe University, Bundoora, Australia.
YVONNE WELLS
Affiliation:
Lincoln Centre for Research on Ageing, La Trobe University, Bundoora, Australia.
*
Address for correspondence: Jodi Oakman, Centre for Ergonomics and Human Factors, La Trobe University, Bundoora 3086, Vic, Australia. E-mail: joakman@latrobe.edu.au
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Abstract

Population ageing will significantly impact labour markets in most Organisation for Economic Cooperation and Development countries and as a result individuals will need to remain in paid employment for longer to fund their retirement years. This study examines the retirement intentions of employees of a large public-sector organisation located in Victoria, Australia that was interested in developing policies to assist with retention of their mature-age workforce. Multivariate regression analyses were used to identify the most important predictors of intention to retire. The dependent variable, Intended timing of retirement, was analysed in two forms, as continuous and dichotomised measures. Age and Length of service were strong independent predictors of Intention to retire soon (within five years). Of the work factors that were analysed (Job satisfaction, Job demands, Job control, and Social cohesion), low Job satisfaction and high Social cohesion scores indicated an increased likelihood of retiring soon. The results provide some insight into the development of organisational interventions that might assist with retaining older employees for longer.

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Articles
Copyright
Copyright © Cambridge University Press 2012 
Figure 0

Table 1. Participant demographics

Figure 1

Table 2. Intended timing of retirement by gender

Figure 2

Table 3. Bivariate analysis of Retire soon by independent variables

Figure 3

Table 4. Intention to retire soon by age and job satisfaction

Figure 4

Table 5. Multivariate analysis of Intention to retire soon by work factor variables, age and length of service