A common-weights DEA model for centralized resource reduction and target setting. (January 2015)

• Record Type: Journal Article
• Authors: Hatami-Marbini, Adel; Tavana, Madjid; Agrell, Per J.; Hosseinzadeh Lotfi, Farhad; Ghelej Beigi, Zahra
• Is Part Of: Computers & industrial engineering. Volume 79(2015)
• Page Start: 195
• Page End: 203
• Publication Date: 2015-01
• Subjects: Data Envelopment Analysis -- Centralized resource reduction -- Target setting -- Input and output deterioration -- Common Set of Weights; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2014.10.024
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We propose a DEA model for centrally imposed resource or output reduction. We determine the input and output reduction needed to avoid deteriorating the efficiency scores. We use a Common Set of Weights method for controlling the weight flexibility. We improve the efficiencies of the DMUs and reduce the computational complexities. Abstract: Data Envelopment Analysis (DEA) is a powerful tool for measuring the relative efficiency for a set of Decision Making Units (DMUs) that transform multiple inputs into multiple outputs. In centralized decision-making systems, management normally imposes common resource constraints to maximize operating revenues and minimize operating expenses. In this study, we propose an alternative DEA model for centrally imposed resource or output reduction across the reference set. We determine the amount of input and output reduction needed for each DMU to increase the efficiency score of all the DMUs. The contribution of the proposed model is fourfold: (1) we take into consideration the performance evaluation of the centralized budgeting in hierarchical organizations; (2) we use a Common Set of Weights (CSW) method based on the Goal Programming (GP) concept to control the total weight flexibility in the conventional DEA models; (3) we propose a comprehensive approach for optimizing the inputs and/or outputs contractions and improving the final efficiencies of the DMUs while reducing the computational complexities; (4) we compare the proposed method with an approach in the literature; and (5) we demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example.