Generalized economic model, risk analysis framework and decision support system for the analysis and evaluation of capital investment projects

The goal of this thesis is to contribute to the knowledge base for making high quality decisions about capital investment projects. To achieve this goal, a generalized economic model, risk analysis framework, and decision support system for the evaluation and risk analysis of capital investment projects are developed.; Capital investment projects are a feature of several industries, markets and business sectors. These markets and business sectors have different characteristics and require the use of a variety of methods in preparing estimates and forecasts. An objective of the thesis deals with modeling such diversity. To achieve this objective, a generalized economic model is developed with a multipurpose hierarchical network-based time function structure. The model structure is organized in four components reflecting four classification domains in capital investment projects namely, capital expenditure, revenue, operation and maintenance, and project financing. The basic elements in a component are called constructs. Each construct represents a cash flow that has the same classification type of the component and consequently inherits its properties and methods. With the generalized economic model, a project economic structure can be formulated with any required properties and methods. The generalized model embraces a broad range of periodic and cumulative cash flows and performance measures such as net present value, internal rate of return, total costs life cycle cost, total revenues, debt service coverage ratio, loan life cover ratio, and benefit cost ratios.; To model the uncertainties inherent in the estimates of variables and economic indicators of capital investment projects, a risk analysis framework is introduced. The framework uses an analytical two- and four-moment approach that directly derives the four moments of the performance measures in the generalized model regardless of how complicated their economic structure might be. A rigorous and expanded derivation for the four moments of a system function is introduced for the framework in order to enhance the accuracy over the standard moment approach. Considerable flexibility in terms of several types of methods, e.g. percentile values, moments, and full probability distribution is introduced for modeling the uncertainty of variables in the generalized model. This provides flexibility over the simulation risk analysis approach that works only with full probability distributions.; A practical implementation of the generalized model and the risk analysis framework through a decision support system, called Evaluator, is presented. The system has three components: data, model, and interface/dialogue components and makes use of existing software tools. (Abstract shortened by UMI.)...