The pursuit of organizational efficiency has become something of an obsession for the modern manager. However, managers interested in identifying efficient practice have few tools available, other than the juvenilia hawked by accountants. A notable exception is the technique known as data envelopment analysis (DEA), which was introduced to the world in its modern form in 1978. The deceptively simple DEA model has since become a remarkably fertile field for both research and practice. DEA offers an insight into the relative efficiency of comparabledecision-making units' such as–say–schools. It offers a conservative estimate of comparative efficiency in situations in which multiple inputs and multiple outputs are found. The technique exploits limited data to its full extent, and can be used to examine technical efficiency, allocative efficiency and scale efficiency. It has proved to be immensely useful in a wide range of settings. On the downside, the technique is sensitive to data accuracy, and some DEA practitioners are guilty of stretching their analysis beyond the capacity of the data available to them.

This long awaited book seeks to summarize and codify the state of current scientific knowledge relating to DEA. It comprises three parts: an introduction to the concepts, models and computational aspects of DEA; a set of case studies; and an epilogue and bibliography. Part I first offers an intuitive insight into DEA and then develops a sequence of basic theoretical models, followed by a series of refinements and extensions. The intention is to present a unified treatment of the topic. This part of the book will enable