Sensitivity of efficiency classifications in the additive model of data envelopment analysis

Abstract

In contrast to existing sufficient conditions for preservation of efficiency under special perturbations and matrix structural assumptions, sensitivity of the additive model's classifications in data envelopment analysis (DEA) is investigated by means of new DEA formulations focusing on the stability (sensitivity) of an organization's classification (whether efficient or inefficient). The formulations for the additive model are linear programming problems whose solutions yield a particular region of stability, a ‘cell’, in which an organization's classification remains unchanged. The largest such cell can always be easily computed for each organization and additionally theoretically characterized simply as optimal solutions of particular linear programming problems.