The extension of Data Envelopment Analysis (DEA) developed in this thesis presents a new approach for calculating a common set of weights for use in the scoring and ranking of alternatives in a project selection problem setting. In contrast to the traditional approach where expert opinion is interpreted to derive weights for aggregating individual criterion scores of an alternative, a new development is introduced to derive these weights from empirical data, based on a set of new One-Sided DEA (OSD) models and a new Ranking by Consensus (RC) methodology.; The RC methodology was applied to four relevant problems: (1) Power Plant site selection, (2) Shortlisting Research Grant Proposals for a large Government Granting Agency, (3) Capital City site selection and (4) Two-dimensional simulated data for illustration. The results offer new insights into the possibilities of novel tools which can be helpful in the decision making process by providing a mathematical ranking of alternatives based on a common set of weights.; This set of weights have been shown to represent the consensus opinion of the very candidates being evaluated, with the understanding that the candidates were free to selfishly select weights, with full knowledge of all other candidate's criteria scores, so as to make themselves appear as attractive as possible in the respective selection problem setting. The interpretation and implication of this common set of weights is explored and recommendations for extending the methodology in practice are made.
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