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Resilience is about addressing vulnerability, not only by surviving a shock to the system, but also thriving in an economic environment of change and uncertainty. A robust conceptual framework is required to navigate through underlining elements of vulnerability. An evolutionary model of regional adaptive cycles around four sequential phases in economic activity – reorganisation, exploitation, conservation and release – is adopted in this study as the framework for recognising such phase patterns. A data mining clustering method which utilises a k-means algorithm evaluates the impact of major shocks, notably economic recessions and drought, on four functional groups of regions (metropolitan, periphery, regional and rural). Applying this clustering method to the adaptive cycle model using census data from 1986, 1991, 1996, 2001, 2006 and 2011, the paper identifies patterns of economic resilience in regions by industry categories. Preliminary results show different resilience patterns and varied stability to this resilience for industry/functional regions ranging from non-resilient to very resilient regions.

This paper won the ANZRSAI 2016 Award for best conference paper.

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