ABSTRACT
Data envelpment analysis, DEA, is a widely used benchmarking tool that is linear programming based which provides an opportunity to formulate and implement a rich model, interpreting results, and building it using R based tools. This demonstrates examples of how to build richer math modeling applications with looping, conditions, and more. Doing a DEA application requires considering choices such as orientation and returns scale so these concepts and other modeling choices are incorporated. Two DEA examples are used. The first is an illustrative application of stores and the second examines university technology transfer.
