Doctoral Thesis
A Four-Dimensional industrial symbiosis model for the evaluation of industrial precincts
Doctor of Philosophy (PhD), Murdoch University
2024
Abstract
This research takes the traditional definition of industrial ecology into a new multi-dimensional model of industrial symbiosis. As society embraces Circular Economy and advances beyond this toward Regenerative Economy, industry is responding to this by moving beyond a focus on the elimination of waste through the traditional Industrial Symbiosis approach, which is the removal of waste through the re-use of process by-products. For an industrial precinct to regarded as a place that hosts a thriving cluster of enterprises the research suggests there is more than the movement of by-products and waste materials occurring. Some research points to the availability of skilled workers to meet the needs of the enterprises, and to aspects of public sector governance. This research is an emerging field and consequently there is little evidence to identify what critical factors may or may not have an influence on the extent to which a given precinct supports or constrains the activities of the hosted enterprises.
To address this lack of evidence this research has identified four primary characteristics (dimensions) that are observable in certain well-regarded precincts and proceeded to develop a model which can be used to create a four-dimensional profile for any industrial precinct. The model is called the KIC4, or Key Industrial Cluster - Four-dimensional framework for Industrial Symbiosis and it provides a process which delivers a multi-dimensional profile of the symbiotic relationships present in a given industrial precinct; these dimensions being Materials Exchange, Skilled Workforce, Support Industries, and Governance. It does this through an evaluative process where five defined Influencing Factors per Dimension are used to identify constraining and supporting influences, and to present a dimensional profile for the particular industrial precinct.
The model identifies the uncertainties or strengths associated with a precinct, thus enabling the initiation of focused discussion. This process presents a way to optimise the ability of an industrial precinct to present as a more conducive place for an industrial enterprise, and indeed a cluster of enterprises, to operate from. The development and refining of the KIC4 framework involved the identification and testing of the selected Influencing Factors per Dimension, and the application of the model to nine separate industrial precincts. The output of the model is a quartile profile against each Dimension for each precinct selected.
The research confirmed that the more highly regarded precincts as identified in past scholarly papers achieved the highest quartile scores. Those precincts that may be considered as underperforming, present as the lowest or most variable across the dimensions. The research also identified what particular influencing factors require focus of effort if the improvement of the precinct is to be sought as an objective. The results of the research show that there are indeed dimensions of symbiotic relationships that exist beyond the traditional waste material reduction definition, and that these exist in industrial precincts across international borders. In the evaluation of a precinct’s dimensional profile, be it a green or brown-fields site, and through the application of the KIC4 dimensional profiles, precinct managers are better equipped to forward plan to minimise future constraining influencing factors and optimise supporting factors for the betterment of the industrial business environment within which the resident enterprises are or will be operating.
Details
- Title
- A Four-Dimensional industrial symbiosis model for the evaluation of industrial precincts
- Authors/Creators
- Chris Oughton
- Contributors
- Martin Anda (Supervisor) - Murdoch University, Centre for Water, Energy and WasteBiji Kurup (Supervisor)Goen Ho (Supervisor)Jonathan Whale (Supervisor) - Murdoch University, Centre for Water, Energy and Waste
- Awarding Institution
- Murdoch University; Doctor of Philosophy (PhD)
- Identifiers
- 991005674269807891
- Murdoch Affiliation
- Murdoch University
- Resource Type
- Doctoral Thesis
Metrics
83 File views/ downloads
182 Record Views