The rapid development of economy and society in Shanghai has dramatically spurred the demand of improving city infrastructure. Great concerns have been given to the problems existing in the financing and construction of infrastructure, such as lacking construction funds, low efficiency of construction funds usage, and high financing cost. / The urban infrastructure project financing way must keep unanimity with the attribute of the project. Public good theory (Samuelson, 1954), market ability theory (Kessides, 1993; World Bank, 1994) and project classification model (Xu, 2000) make contribution to classifying projects' attribute, and offer the theoretical foundation for choosing the suitable capital source for urban infrastructure. / The main objective of the dissertation is to build the theoretical basis of classifying infrastructure and identifying investment focus of governmental funds with the help of the classification theory of urban infrastructure, thus to attract more private investment into infrastructure construction in Shanghai which leads to the solution to problems mentioned above. / The evolution of the dissertation is to establish a classification model for urban infrastructure. It is the first time in China to classify infrastructure from the quantitive point of view and to use Monte Carlo simulation to quantitively analyse the risk in the urban infrastructure construction. / Based on the literature, cases, and data collected, the author makes a comprehensive research on the urban infrastructure construction in Shanghai through case analysis and risk simulation. Problems existing in the project investment and financing operation are recognized and the relationship between return and risk in different projects is summarized. Then the evaluation model of urban infrastructure projects classification is established to classify projects quantificationally. / Thesis (DBA(DBusinessAdministration))--University of South Australia, 2005.
| Identifer | oai:union.ndltd.org:ADTP/267405 |
| Creators | Sun, Jian Ping. |
| Source Sets | Australiasian Digital Theses Program |
| Language | Text in Chinese. |
| Detected Language | English |
| Rights | copyright under review |
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