Sustainable Development in Smart and Resilient Local Government Areas: An Empirical Investigation of Victoria, Australia

Abstract

Experts always seek for improving the development and management of multidimensional urban systems, including those of sustainability, smartness, and resiliency. These dimensions are the main keywords in related research to model and predict better development in urban and regional areas; there are overlapped concepts, common attributes, and parallel processes in existing indices designed for each of those keywords, which might not be an ideal option for the status quo. Therefore, there is a need to find a balance between these concepts/indices and identify an integrated development strategy that addresses smart, resilient, and sustainable development demands. For this purpose, first of all, attributes and themes used to develop the development indices are collected from the recent literature. Secondly, a semantic text mining technique is used to discover commonly used attributes among the collected ones. Thirdly, Principal Component Analysis (PCA) is used to investigate the correlation between the selected attributes to reduce or merge similar attributes. Fourthly, after collecting data and normalizing calculated scores for each LGA, a k-means clustering method is used to identify LGAs with similar development behaviour. And finally, the developed index is implemented in Victoria, Australia as a case study that includes 79 regional and urban local government areas. Evaluation of the results (comparing the results with two existing studies) indicated the success of the proposed index in bringing smartness, resiliency and sustainability indices under a united and comprehensive development index.