Value-based DEA models: application-driven developments

• Published in: The Journal of the Operational Research Society Vol. 63; no. 1; pp. 16 - 27
• Main Authors: de Almeida, P N, Dias, L C
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.01.2012; Palgrave Macmillan; Palgrave Macmillan UK; Taylor & Francis Ltd
• Series: Journal of the Operational Research Society
• Subjects: additive model; Applied sciences; Business and Management; Chain stores; Cost of sales; Data envelopment analysis; Decision analysis; Decision theory. Utility theory; Efficiency; Efficiency metrics; Exact sciences and technology; General Paper; General Papers; Linear programming; Management; Mathematical programming; Mathematics; Modeling; multi-criteria decision analysis; Multiple criteria decision making; Nonparametric inference; Operational research and scientific management; Operational research. Management science; Operations research; Operations Research/Decision Theory; Probability and statistics; retail chains; Retail stores; Salary; Sciences and techniques of general use; Statistics; Stock sales; Studies; weight restrictions; weight restrictions; additive model; data envelopment analysis; retail chains; multi-criteria decision analysis; Performance evaluation; Decision support system; Multicriteria analysis; Decision making; Retail marketing; Model driven architecture; Non parametric method; Non parametric estimation; Linear programming; Decision analysis; Manager; Relative efficiency; Modeling; Top management; Preference; Data envelopment analysis
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/jors.2011.15

Data envelopment analysis (DEA) is an approach based on linear programming to assess the relative efficiency of peer decision-making units (DMUs). Typically, each DMU is free to choose the weights of the factors used in its evaluation. However, the evaluator's preferences may not warrant so much freedom. Several approaches have been proposed to allow the incorporation of managerial preferences in DEA, but few address the additive DEA model specifically. This paper presents additive DEA models that use multi-criteria decision analysis concepts to incorporate managerial preferences, and presents the corresponding preference elicitation protocols. The models developed allow the incorporation of preferences at different levels: on valuing performance improvements, on introducing weight restrictions, and on finding adequate targets. These were application-driven developments, resulting from discussing modelling options and preliminary results with the top-level management of a retail chain in the context of an assessment of stores' performance, also described in this paper.