Understanding the dynamic behaviour of the Australian retirement village industry: A causal loop diagram

Bo Xia*, Qing Chen, Jerry Walliah, Laurie Buys, Martin Skitmore, Connie Susilawati

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)
285 Downloads (Pure)

Abstract

The retirement village industry in Australia has been accommodating an increasing number of residents in recent decades. However, a thorough understanding of the dynamic behaviour of the industry remains largely unknown, which prevents a better prediction of its future growth. This study incorporates system dynamics thinking into residents’ relocation decisions and aims to develop a causal loop diagram to have a full understanding of the complex interactions of variables affecting their relocation, which in turn determines the future growth pattern of the industry. Based on thematic analysis using literature review and interview data, five primary causal loops are identified, including the positive reinforcing loops of word-of-mouth effect and new-supply effect, and three negative balancing loops of the move-out effect, price effect and home-village distance effect. Of these five causal loops, the most dominant ones in determining the system behaviour are the word-of-mouth (reinforcing) and home-village distance (balancing) effects. The causal loop diagram provides a better understanding of the underlying structure of the retirement village industry and will help guide the industry and policy makers in formulating strategies to create a more ageing-friendly living environment for seniors in Australia.

Original languageEnglish
Pages (from-to)346-355
Number of pages10
JournalInternational Journal of Strategic Property Management
Volume25
Issue number5
DOIs
Publication statusPublished - 30 Jun 2021
Externally publishedYes

Fingerprint

Dive into the research topics of 'Understanding the dynamic behaviour of the Australian retirement village industry: A causal loop diagram'. Together they form a unique fingerprint.

Cite this