Ch10Computational-Economic-Analysis-for-Engineering-and-Industry170-197

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151 chapter ten Multiattribute investment analysis and selection This chapter presents useful techniques for assessing and comparing invest- ments in order to improve the selection process. The techniques presented include utility models, the project value model, polar plots, benchmarking techniques, and the analytic hierarchy process (AHP). 10.1 The problem of investment selection Investment selection is an important aspect of investment planning. The right investment must be undertaken at the right time to satisfy the con- straints of time and resources. A combination of criteria can be used to help in investment selection, including technical merit, management desire, schedule efficiency, benefit/cost ratio, resource availability, criticality of need, availability of sponsors, and user acceptance. Many aspects of investment selection cannot be expressed in quantitative terms. For this reason, investment analysis and selection must be addressed by techniques that permit the incorporation of both quantitative and quali- tative factors. Some techniques for investment analysis and selection are presented in the sections that follow. These techniques facilitate the coupling of quantitative and qualitative considerations in the investment decision process. Such techniques as net present value, profit ratio, and equity break-even point, which have been presented in the preceding chapters, are also useful for investment selection strategies. 10.2 Utility models The term utility refers to the rational behavior of a decision maker faced with making a choice in an uncertain situation. The overall utility of an investment can be measured in terms of both quantitative and qualitative factors. This section presents an approach to investment assessment based on utility models that have been developed within an extensive body of literature. The
152 Computational Economic Analysis for Engineering and Industry approach fits an empirical utility function to each factor that is to be included in a multiattribute selection model. The specific utility values (weights) that are obtained from the utility functions are used as the basis for selecting an investment. Utility theory is a branch of decision analysis that involves the building of mathematical models to describe the behavior of a decision maker faced with making a choice among alternatives in the presence of risk. Several utility models are available in the management science literature. The utility of a composite set of outcomes of n decision factors is expressed in the following general form: where x i = specific outcome of attribute X i , i = 1, 2, …, n and U ( x ) is the utility of the set of outcomes to the decision maker. The basic assumption of utility theory is that people make decisions with the objective of maxi- mizing those decisions’ expected utility. Drawing on an example presented by Park and Sharp-Bette (1990), we may consider a decision maker whose utility function with respect to investment selection is represented by the following expression: where x represents a measure of the benefit derived from an investment.

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