We performed a multiperiod data envelopment analysis (DEA) study of the efficiencies of selected branches of a large US bank (which we will call Big Bank) over six consecutive quarters (second quarter of 1992 to the third quarter of 1993). We developed a number of innovative application tools, including budgeting and target-setting modules, within a DEA framework that we subsequently customized for Big Bank. Within the performance-evaluation framework, we developed the ability to identify different potential groupings of branches that supported the multiple user views of the system. We also developed procedures to evaluate trends over time and differences in performance across user-defined aggregations of branches. We paid attention to the interface with the end users and, in particular, developed presentation tools to make the outcomes of the analysis available to managers at different levels of the bank.

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T h m ha= been many applications of the maximal Covering location problem (MCLP). An underlying assumption of the MCLP is that demand not covered (i.e.. not within a prespecified maximal distana of a facility) is not served. This may be an unrealistic assumption in many location planning scenarios, a p e c i d l y in the public sector. For example. in cascs such as fire protection or ambulance service. calls not technically covcrcd will still be serviced. The MCLP, however, docs not consider the distances or travel times necessary to service such demand.This paper presents a bicriterion locational covering modd which explicitly considers the travel distance or time necessary to service demand not within the maximal covering distance of a facility.The model may be used to generate noninferior (Pareto optimal) siting configurations which demonstrate the inherent trade-offs betwan a siting scheme designed to maximize total coverage and one designed to minimize total t n v d time for uncovmd demand to reach its nearest facility. In addition, it is shown that for MY particular weighting scheme on the two objectives. the problem can be solved as a p-median problem; a problem for which several efficient solution methods exist. Subject A m : Locrrrlon Mod& and Mathematical h#ramrnIn#.