Building Prosperous Knowledge Cities
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Building Prosperous Knowledge Cities

Policies, Plans and Metrics

Edited by Tan Yigitcanlar, Kostas Metaxiotis and Francisco Javier Carrillo

This unique book reveals the procedural aspects of knowledge-based urban planning, development and assessment. Concentrating on major knowledge city building processes, and providing state-of-the-art experiences and perspectives, this important compendium explores innovative models, approaches and lessons learnt from a number of key case studies across the world.
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Chapter 16: Commuting: The Geography of Melbourne’s Knowledge Economy

Kevin Johnson

Extract

16. Commuting: the geography of Melbourne’s knowledge economy Kevin Johnson INTRODUCTION In our day-to-day work we are often asked which specific policy interventions will improve the local area employment self-containment (ESC) ratio. That is, the proportion of the resident workforce who live and work in the same location. A high ESC ratio is considered an ideal social, economic and environmental goal. Unfortunately the urban economy does not always generate high ESC ratios of its own accord and so policy intervention is necessary. As policy should be informed by evidence, we apply a range of statistical and modeling techniques to analyze demographic, geographical and economic data to answer the question. Fortunately for us, the Australian Bureau of Statistics (ABS) Census data can be used to map a workforce’s employment and residential distribution at the geographical scale of the Statistical Local Area (SLA). These data can be categorized into subsets of the workforce by industry of employment, occupation and any number of demographic variables. Commuter patterns in the subsets can then be examined, albeit with some limits on spatial accuracy.1 Taking the time to investigate these different permutations of the Knowledge Economy (KE) workforce reveals preferences for residential and work locations. In turn, this highlights ways to influence job distribution and transport use. In this analysis we have applied the first (descriptive) step in our analytical and modeling process to explore the KE across the metropolitan area of Melbourne, Australia, using data from the 2006 ABS Census. While the findings are largely...

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