A group decision-making method for target setting in data envelopment analysis

Abstract

Data envelopment analysis (DEA) and multiple objective linear programming (MOLP) are tools that can be used in management control and planning. Whilst these two types of model are similar in structure, DEA is directed to assessing past performances as part of management control function and MOLP to planning future performance targets. This article is devoted to investigating equivalent models and interactive tradeoff analysis procedures in MOLP, such that DEA-oriented performance assessment and target setting can be integrated in a way that the decision-makers' preferences can be taken into account in an interactive fashion. In addition, in this article a new target-setting DEA approach is proposed. In this method, the decision-makers are asked to say which inputs and outputs they wish to improve, which ones are allowed to worsen and which ones should stay at their current level for inefficient decision-making units (DMUs). The relative priorities of these inputs and outputs are computed using the group analytic hierarchy process. By solving a proper mathematical model, the amount of increase or decrease for each input or output can be obtained. After doing this amount of increase or decrease, the observed inefficient DMU transforms into an efficient one.