Modelling Intention to Stay and Actual Voluntary Exit Using Employee Survey Information: An Investigation of Statistcal and Practical Significance to Human Resources Planning in the Royal New Zealand Navy

This study documents an applied research problem originating from the proposition that the existing employee attitude survey (OAtS) within the Royal New Zealand Navy (RNZN) should assist the RNZN better manage the retention of its uniformed personnel. However, the OAtS was not designed specifically for this purpose. Consequently, this study has two objectives: first, to determine if statistically valid models of Intention to Stay and Actual Voluntary Exit can be produced using survey information collected through the OAtS; and second, to review the practical significance of these statistical models and their potential contribution to RNZN human resource planning. Analyses supporting this study apply a range of statistical techniques. Principal components analysis and reliability analyses assess if the OAtS is a statistically reliable data collection instrument. Multiple linear regressions identify relationships between predictor variables and Intention to Stay. Finally, binary logistic regressions identify relationships between predictor variables and Actual Voluntary Exit. Both regression approaches control for various demographic characteristics. This study found the OAtS is a statistically reliable data collection instrument capable of producing valid models of Intention to Stay and Actual Voluntary Exit. Such analyses and outcomes have not been previously undertaken for the RNZN. Furthermore, this study’s models are consistent with the wealth of empirical research regarding the drivers and predictors of employee retention and voluntary turnover. Models of Intention to Stay explain a notably higher level of variance than many other studies. However, models of Actual Voluntary Exit lack predictive capability. Although the results of modelling are statistically valid and promising, this study highlighted matters affecting their practical significance. These include: dataset representativeness; questionnaire items construction; sampling methodology; self-report data limitations; and whether modelling provides an opportunity to act. These are important considerations when using employee surveys to support human resource planning. Finally, this study provides insights for other organisations. For militaries, the importance of careers, promotion and advancement and work-life balance is highlighted. For all organisations, this study emphasises that opportunities and risks must be carefully balanced when incorporating statistical models of employee attitudes into human resource planning. This balancing act is not documented in research literature.

Name thesis:degree_name

PhD

Level thesis:degree_level

Doctoral

Grantor dc:publisher

ResearchSpace@Auckland

Year dc:date.issued

2012

Author dc:creator

• Latornell, James

Advisors dc:contributor.advisor

• Haworth, N
• Burch, G

Statement dc:rights

• Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.

Licence dc:rights.uri

• https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm

Handle dc:identifier.uri

https://hdl.handle.net/2292/19947

OAI identifier oai:identifier

oai:researchspace.auckland.ac.nz:2292/19947