Data envelopment analysis (DEA) - Thirty years on

By Wade D. Cook, L. Seiford. European Journal of Operational Research, 2009

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Review of efficiency ranking methods in data envelopment analysis (2017, methodology): “on applying this analytical technique to situations that require multiple levels such as networking and supply chain assessment [73].”
Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2010, neutral): “For example, Cook and Seiford (2009) review the methodological developments of DEA over the last thirty years.”
Network data envelopment analysis: A review (2014, background): “…that apply multiple inputs to produce multiple outputs, with many theoretical developments and practical applications being reported (see, for example, the review of Cook & Seiford, 2009; Emrouznejad, Parker, & Tavares, 2008; Liu, Lu, Lu, & Lin, 2013a, 2013b; Seiford, 1996; Zhou, Ang, & Poh, 2008).”
Monitoring bank performance in the presence of risk (2014, neutral): “Various DEA applications made way for developing diverse efficiency measures (see Ray 2004; Cooper et al. 2011 or the comprehensive review in Cook and Seiford 2009).”
On how to properly calculate the Euclidean distance-based measure in DEA (2014, background): “Using the additive model3 under constant returns to scale (see Ali and Seiford [1]), we detect that DMUs A, B and C are Pareto–Koopmans efficient (their optimal values are zero), while the last unit, DMU D, is technically inefficient with an optimal value equalling 6 (sþ 1 ¼ 6, s 1 ¼ sþ 2 ¼ sþ 3 ¼ 0”