Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs
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Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs Mustapha Daruwana Ibrahim1 · Sahand Daneshvar2 · Hüseyin Güden2 · Bela Vizvari2 Accepted: 4 June 2020 © Operational Research Society of India 2020
Abstract In managerial decisions, situations frequently arise when decision makers need to define their capabilities, desires, and limitations when trying to improve efficiency. In this paper, target setting models that accommodate predefined desired output targets or predefined available inputs during efficiency improvement in data envelopment analysis are proposed. The proposed approach guarantees efficient targets when inefficient or weak efficient units’ desire expansion or reduction in outputs/ inputs, and cases of input/output redistribution, or nondiscretionary variables in a production system. The approach is applied to two empirical studies, first, on a poultry chain trying to improve efficiency of some branches, and second on water, energy, land and food nexus trying to attain future sustainability based on preexisting inputs. Results of the empirical studies supports the proposed models. Keywords Data envelopment analysis · Efficiency improvement · Predefined input · Predefined outputs · Target setting
1 Introduction Improving efficiency of operating units after efficiency evaluation is imperative in strategic management of systems. Data envelopment analysis (DEA) is a nonparametric frontier efficiency evaluation method that measures the efficiency of entities known as decision making units (DMUs). Efficient DMUs are located on the frontier, and the inefficient DMUs are enveloped by the frontier. Charnes, Cooper and Rhodes (CCR) proposed efficiency evaluation under constant return to scale * Mustapha Daruwana Ibrahim [email protected] 1
Faculty of Engineering, Industrial Engineering Technology, Higher Colleges of Technology, Sharjah, United Arab Emirates
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Department of Industrial Engineering, Eastern Mediterranean University, N.Cypruss, Via Mersin 10, Famagusta, Turkey
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(CRS) [6]. Subsequently, Banker, Charnes, and Cooper (BCC) introduced the variable return to scale (VRS) efficiency evaluation model [5]. An efficiency score of one signify the DMU as efficient, and less than one as inefficient. For an inefficient DMU to improve its performance and become efficient, a target is proposed on the frontier for the inefficient DMU. Efficiency improvement in DEA is conventionally performed in two forms; first, holding some inputs constant while increasing some outputs, or making some outputs constant while decreasing some inputs, both of which are impractical in most cases. Furthermore, simultaneous improvement of both inputs and outputs is more realistic. Research with efficiency improvement or target setting in DEA literature is scarce [2, 30]. However, there has been some contributions such as combined goal programming and inverse DEA for bank mergers [1], and Environmental performance improvement [35]. Operating
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