Measuring and incorporating meaningful proportional slacks in radial DEA models, and aspects of non-discretionary DEA models

This thesis is comprised of theoretical contributions in two unique but related DEA fields: non-discretionary DEA models, and slack selection methodologies in radial DEA models and their integration into an overall efficiency score. The theoretical developments are illustrated through the use of intermediation efficiency models using real world data from the retail branch network of one of Canada's five largest banks. The models examine the loan quality and business generation of the bank's branches using data on the branches' business environment, the levels of deposits and loans that they generate, and the resulting levels of bad loans.;The thesis presents a new unit invariant slack selection methodology for radial DEA models that maximizes the relative slack improvements. Relevant background literature is reviewed showing the shortcomings of the current slack selection approaches in radial DEA models, including the CCR and BCC models. In addition, new models are proposed for incorporating the slacks with the radial theta efficiency score into an overall efficiency score that makes the results more usable.;Several theoretical contributions are made in the field of non-discretionary DEA models. It is shown that the NCN non-discretionary DEA model will produce artificially high efficiency scores under certain circumstances. The research also expands on the work of Lovell and Pastor dealing with one-sided DEA models with discretionary variables [LOVE99], by examining how non-discretionary variables can be integrated into one-sided DEA models. A new solution technique for solving one-sided DEA models with semi-negative non-discretionary variables is proposed.