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ItemThe form and content of internal accounting reports in municipal government in VictoriaHarris, Geoffrey John ( 1971)The purpose of this study is to examine the quality of the internal accounting reports presented to the councillors of fifteen Victorian municipalities. The fifteen municipalities included in the study do not represent a random sample of the 210 Victorian municipalities. There are several different types of municipalities in Victoria. Some municipalities are small in area and are characterized by very high population densities, some municipalities are large in area and are sparsely populated while others are characterized by rapidly growing populations. A classificatory distinction between the different types of municipalities was made because different types of municipalities encounter different problems. It was thought that the form and content of the internal accounting reports could vary in response to the different types of problems encountered by each type of municipality. The following classification was used: 1. Inner-suburban (developed) municipalities. 2. Outer-suburban (developing) municipalities. 3. Country-urban municipalities. 4. Country-rural municipalities.(From Introduction)
ItemEstimation bias in public infrastructure projects and procurement selection and performanceFitzgerald, John Patrick ( 2008)In response to ongoing cost overruns on government construction projects, a number of Australian government jurisdictions have identified the benefit of developing and gathering strategic project data to assist in setting budgets and refining procurement strategies. This is based on the knowledge that there is a proven occurrence of estimation or optimism bias, the need to improve development of business cases and clearer allocation of risk. This thesis establishes that significant cost overruns have occurred over decades, if not centuries, throughout the world, and that optimism bias exists in government infrastructure projects. It also demonstrates that there are substantial information gaps in the data and the studies documented in the referred literature, particularly when comparing the outcomes associated with different procurement processes. The thesis finds that there is a risk category, which includes the commercial risks associated with selecting the delivery model, which is not being fully considered by researchers. It details recent developments in Australia and reflects on the approaches used for risk allocation for Public Private Partnerships (PPPs) compared with those used for traditional procurement. The thesis details the development of an Australian National PPP Forum and how this Forum led to the beginning of a National Benchmarking Study (the Study) of major projects in January 2006. The thesis presents the Study's objectives and approach to capturing project performance, in terms of time, cost and service outcomes. It considers in detail the methodology of project selection, what data is collected to enable robust analysis and the degree of difficulty in collecting data. This thesis is the first written paper to draw on the experience gained from the National Benchmarking Study, establishing that there is an emerging observation that PPPs outperform traditional procurement but that, to date, this is not statistically proven. It does not attempt to provide empirical evidence comparing time, cost and service outcomes between PPPs and traditional procurement processes. Although the Victorian segment of the National Benchmarking Study has now been completed, and the Victorian findings support the observations of earlier researchers, the thesis concludes that it is imperative for the Study to have robust data in the form and detail outlined in order to reach appropriate, scientifically reliable conclusions. The thesis concludes with five recommendations: 1. Further analysis of the causes of cost overruns; 2. Completion of the national benchmarking study; 3. Capture of relevant project data during the execution of the project; 4. A new template for collecting project data; and 5. Further necessary research to develop a predictive model for estimating appropriate financial risk allocation.