Study of population change via clustering of Australian regional areas: An optimisation approach

Abstract

Grouping regional towns and cities in Australia according to economic functions could improve understanding of the importance of economic factors in determining growth. Several researchers have used clustering techniques to examine the growth and characteristics of regional cities in Australia. The current study extends clustering methodologies by adopting an optimisation approach based on a clustering technique using the k-means algorithm to investigate the impact of socio-economic factors on population growth and decline in regional Australia. The analysis in the paper suggests that industry of employment, individual weekly income, age group and education level have an important impact on population change. These findings have policy implications for economic planning of regional areas in Australia.C