Integrating DEA-oriented performance assessment and target setting using interactive MOLP methods
European Journal of Operational Research
Manchester Business School, The University of Manchester, Manchester, M15 6PB, United Kingdom; Management School, Hefei University of Technology, Hefei, Anhui, China; Department of Statistical Sciences, University of Cape Town, Rondebosch, 7701, South Africa
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 paper is devoted to investigating equivalence 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. Three equivalence models are investigated between the output-oriented dual DEA model and the minimax reference point formulations, namely the super-ideal point model, the ideal point model and the shortest distance model. These models can be used to support efficiency analysis in the same way as the conventional DEA model does and also support tradeoff analysis for setting target values by individuals or groups. A case study is conducted to illustrate how DEA-oriented efficiency analysis can be conducted using the MOLP methods and how such performance assessment can be integrated into an interactive procedure for setting realistic target values. © 2008 Elsevier B.V. All rights reserved.
Communication channels (information theory); Data envelopment analysis; Decision theory; Dynamic programming; Industrial management; Linear programming; Linearization; Particle size analysis; Planning; Targets; Case studies; Dea models; Decision makers; Efficiency analysis; Equivalence models; Future performances; Ideal points; Management controls; MiniMax; Minimax method; Multiple objective linear programming; Multiple objective linear programmings; Performance assessment; Performance assessments; Reference points; Shortest distances; Target settings; Target values; Tradeoff analysis; Two types; Modal analysis