Determining closest targets on the extended facet production possibility set in data envelopment analysis: Modeling and computational aspects

Within the framework of data envelopment analysis (DEA) methodology, the problem of determining the closest targets on the efficient frontier is receiving increased attention from both academics and practi-tioners. In the literature, the number of approaches to this problem are increasing, most of which are based on the computation of closest targets. Some of the existing approaches satisfy the important prop-erty of strong monotonicity. However, they tend to either propose a complex conceptual framework and multi-stage procedure or change the original definition of Holder distance functions. Clearly, these ap-proaches cannot be solved easily when there are many extreme efficient units with multiple inputs and multiple outputs. To solve this problem, we consider the notion of the extended facet production pos-sibility set (EFPPS). In particular, we propose a Mixed Integer Linear Program (MILP) to find the closest efficient targets and that is related to a measure that satisfies the strong monotonicity property. Addition-ally, in this paper, the proposed approach is applied to real data from 38 universities involved in China's 985 university project. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

In the context of data envelopment analysis (DEA) methodology, determining the closest targets on the efficient frontier has become a topic of increasing interest. Various approaches have been proposed in the literature, but many of them either lack strong monotonicity or are too complex for practical use. This paper introduces a Mixed Integer Linear Program (MILP) based on the extended facet production possibility set (EFPPS) to find the closest efficient targets, which addresses these limitations.