Abstract
Data envelopment analysis (DEA) is a useful mathematical tool for evaluating the performance of production units and ranking their relative efficiency. In many real-world applications, production units belong to several separate groups and also consist of several sub-units. In this paper, we introduce a new method of evaluating group efficiency of two-stage production systems. To this end, some new DEA models are introduced for evaluating and ranking groups of production systems based on the average and weakest group performance criteria. Some numerical examples, including an empirical application in the banking industry, are also provided for illustration.
Highlights
The efficiency evaluation of decision-making units (DMUs) is a key task in management science, to better understand the performance of those units and plan to improve them in the future
Some new network Data envelopment analysis (DEA) models are presented for efficiency evaluation of the group of production units in both average and weakest performance criteria
We introduce new network DEA models for group efficiency evaluation
Summary
The efficiency evaluation of decision-making units (DMUs) is a key task in management science, to better understand the performance of those units and plan to improve them in the future. Tone et al [35] proposed a slackbased model (SBM) in network systems that can be used to evaluate sectoral efficiencies along with the overall efficiency of DMUs. Despotis et al [14] suggested network DEA approach for series multi-stage processes. Sotiros et al [33] introduced dominance at the divisional efficiency level in two-stage network DEA They proposed the dominance property as a minimum requirement that the two-stage NDEA methods should satisfy, regardless of the optimality criterion used to evaluate the overall and the divisional efficiencies of a system. Esmaeilzadeh et al [16] employed novel multi-period network DEA models developed for performance evaluation of overall and specific period efficiencies with parallel and series internal structures in the sub-processes for each period. Some new network DEA models are presented for efficiency evaluation of the group of production units in both average and weakest performance criteria.
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