by Ho Ping-kuen Matthew. / Bibliography: leaves 59-60 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1982

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published_or_final_version / Civil and Structural Engineering / Master / Master of Philosophy

The objectives of this thesis are to develop an analytical method for economic risk quantification during feasibility analysis for large engineering projects and to computerize the method to explore its behavior, to validate it and to test its practicality for the measurement of uncertainty of decision variables such as project duration, cost, revenue, net present value and internal rate of return. Based on the probability of project success the method can be utilized to assist on strategic feasibility analysis issues such as contingency provision, "go-no go" decisions and adopting phased or fast track construction. The method is developed by applying a risk measurement framework to the project economic structure. The risk measurement framework is developed for any function Y = g(X), between a derived variable and its correlated primary variables. Using a variable transformation, it transforms the correlated primary variables and the function to the uncorrelated space. Then utilizing the truncated Taylor series expansion of the transformed function and the first four moments of the transformed uncorrelated variables it approximates the first four moments of the derived variable. Using these first four moments and the Pearson family of distributions the uncertainty of the derived variable is quantified as a cumulative distribution function. The first four moments for the primary variables are evaluated from the Pearson family of distributions using accurate, calibrated and coherent subjective percentile estimates elicited from experts. The correlations between the primary variables are elicited as positive definite correlation matrices. The project economic structure describes an engineering project in three hierarchical levels, namely, work package/revenue stream, project performance and project decision. Each of these levels can be described by Y = g(X), with the derived variables of the lower levels as the primary variables for the upper level. Therefore, the input as expert judgements is only at the work package/revenue stream level. Project duration is estimated by combining the generalized PNET algorithm to the project economic structure. This permits the evaluation of the multiple paths in the project network. Also, the limiting values of the PNET transitional correlation (0,1) permits the estimation of bounds on all of the derived variables. Project cost and revenue are evaluated in terms of current, total and discounted dollars, thereby emphasizing the economic effects of time, inflation and interest on net present value and internal rate of return. The internal rate of return is evaluated from a variation of Hillier's method. The analytical method is validated using Monte Carlo simulation. The validations show that the analytical method is a comprehensive and extremely economical alternative to Monte Carlo simulation for economic risk quantification of large engineering projects. In addition, they highlight the ability of the analytical method to go beyond the capabilities of simulation in the treatment of correlation, which are seen to be significant in the application problems. From these applications a technique to provide contingencies based on the probability of project success and to distribute the contingency to individual work packages is developed. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

M.Ing. (Engineering Management) / Capital intensive engineering projects involve the flow of large sums of money over the project life. During the pretender phase of the project, estimates of the forecast cash flow and associate return on investment are made based on certain assumptions which at the time are, at best, only informed guesses. As the project progresses, the uncertainty surrounding the magnitude and the timing of these cash flows and rate of return, diminishes. By recognising the time value of money and the importance of the synthesis of time and cash flow as well as the interdependence of project activities, it is desirable to obtain an estimate of the PROBABLE outcome of the return on investment~ should the bid be accepted. This outcome can only be 'guessed' at by means of a probabilistic analysis of the parameters that go to make up the nett cash flow. This study is an attempt to find a model suitable for use in the construction industry which accurately describes the construction process, and presents an overall analysis of the variation in the rate of return as a result of the probabilistic nature of the original parameters. Various models were investigated. All were found suitable under limited conditions.

Submitted in fulfilment of the academic requirements for the Degree of Magister Technologiae: Civil Engineering, Department of Civil Engineering and Surveying, Faculty of Engineering and the Built Environment, Durban University of Technology, 2009. / Infrastructure project costs are being scrutinised more closely and with greater skill and accuracy as projects have become larger, more complex and more expensive, and clients have become more exacting in their requirements. These and other factors compel engineers to design with greater care and in more detail. However, public planners spend very little time generating alternative project options, often presenting decision-makers with only a few poorly differentiated alternatives borrowed ad hoc from other projects. Even more disturbing is that they often devote the greatest amount of decision making resources to the development of a single decision rather than a variety of options. A systematic and iterative analysis of the cost consequences of different design solutions is commonly suggested for infrastructure projects, but rarely happens. There is a growing need to integrate design and costs. This study concentrates on the issue of cost optimisation of infrastructure projects (particularly at the design stage of the project) and applies construction economics, cost planning, cost optimisation and value engineering techniques to the design of such projects. The methodology proposed in this study for the optimisation of cost and design planning is the Infrastructure Cost Planning Model. This model divides the planning of a project into four stages and utilises twelve Cost Report Forms across these stages. The Cost Report Forms define in a comprehensive, precise and verifiable manner the essential characteristics of a deliverable component. They are used to measure, quantify, verify and audit the different design options. By means of the Cost Report Forms, the Infrastructure Cost Planning Model enables the client to select a combination of alternatives and evaluate a number of possible design options – with their cost implications – at each stage of the design process. This i promotes transparency and accountability, and enables consultants and clients to have greater control over the planning process and overall costs. Two case studies on infrastructure related projects were conducted and confirm that the Infrastructure Cost Planning Model can reduce costs. This study demonstrates that it is possible to overcome the problem of over expenditure by introducing cost effective design decisions prior to the infrastructure design approval process. The Infrastructure Cost Planning Model can improve infrastructure standards and procure design in a cost effective, equitable, competitive and transparent manner. This study contributes to the underdeveloped area of cost planning and forecasting of infrastructure projects. The findings are relevant to the South African government's infrastructure service delivery programme and the general issue of affordable infrastructure services.

Submitted in fulfilment of the academic requirements for the Degree of Magister Technologiae: Civil Engineering, Department of Civil Engineering and Surveying, Faculty of Engineering and the Built Environment, Durban University of Technology, 2009. / Infrastructure project costs are being scrutinised more closely and with greater skill and accuracy as projects have become larger, more complex and more expensive, and clients have become more exacting in their requirements. These and other factors compel engineers to design with greater care and in more detail. However, public planners spend very little time generating alternative project options, often presenting decision-makers with only a few poorly differentiated alternatives borrowed ad hoc from other projects. Even more disturbing is that they often devote the greatest amount of decision making resources to the development of a single decision rather than a variety of options. A systematic and iterative analysis of the cost consequences of different design solutions is commonly suggested for infrastructure projects, but rarely happens. There is a growing need to integrate design and costs. This study concentrates on the issue of cost optimisation of infrastructure projects (particularly at the design stage of the project) and applies construction economics, cost planning, cost optimisation and value engineering techniques to the design of such projects. The methodology proposed in this study for the optimisation of cost and design planning is the Infrastructure Cost Planning Model. This model divides the planning of a project into four stages and utilises twelve Cost Report Forms across these stages. The Cost Report Forms define in a comprehensive, precise and verifiable manner the essential characteristics of a deliverable component. They are used to measure, quantify, verify and audit the different design options. By means of the Cost Report Forms, the Infrastructure Cost Planning Model enables the client to select a combination of alternatives and evaluate a number of possible design options – with their cost implications – at each stage of the design process. This i promotes transparency and accountability, and enables consultants and clients to have greater control over the planning process and overall costs. Two case studies on infrastructure related projects were conducted and confirm that the Infrastructure Cost Planning Model can reduce costs. This study demonstrates that it is possible to overcome the problem of over expenditure by introducing cost effective design decisions prior to the infrastructure design approval process. The Infrastructure Cost Planning Model can improve infrastructure standards and procure design in a cost effective, equitable, competitive and transparent manner. This study contributes to the underdeveloped area of cost planning and forecasting of infrastructure projects. The findings are relevant to the South African government's infrastructure service delivery programme and the general issue of affordable infrastructure services.