Open Access
RAIRO-Oper. Res.
Volume 56, Number 2, March-April 2022
Page(s) 795 - 812
Published online 14 April 2022
  • M. Afsharian, Metafrontier efficiency analysis with convex and non-convex metatechnologies by stochastic nonparametric envelopment of data. Econ. Lett. 160 (2017) 1–3. [CrossRef] [Google Scholar]
  • J. Aparicio, M. Kapelko and J.L. Zofo, The measurement of environmental economic inefficiency with pollution-generating technologies. Res. Energy Econ. 62 (2020) 101185. [CrossRef] [Google Scholar]
  • R.D. Banker, Estimating most productive scale size using data envelopment analysis. Eur. J. Oper. Res. 17 (1984) 35–44. [Google Scholar]
  • R.D. Banker, A. Charnes and W.W. Cooper, Some models for estimating technical and scale inefficiences in data envelopment analysis. Manage. Sci. 30 (1984) 1078–1091. [CrossRef] [Google Scholar]
  • A. Charnes, W.W. Cooper and E. Rhodes, Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978) 429–444. [Google Scholar]
  • A. Dellnitz and W. Rödder, Returns to scale as an established scaling indicator: always a good advisor?. Jahrbücher für Nationalökonomie und Statistik 241 (2021) 173–186. [CrossRef] [Google Scholar]
  • A. Dellnitz, A. Kleine and W. Rödder, CCR or BCC: What if we are in the wrong model?. J. Bus. Econ. 88 (2018) 831–850. [Google Scholar]
  • D.K. Despotis, Improving the discriminating power of DEA: focus on globally efficient units. J. Oper. Res. Soc. 53 (2002) 314–323. [CrossRef] [Google Scholar]
  • B. Ebrahimi, M. Tavana, A. Kleine and A. Dellnitz, An epsilon-based data envelopment analysis approach for solving performance measurement problems with interval and ordinal dual-role factors. OR Spect. 43 (2021) 1103–1124. [CrossRef] [Google Scholar]
  • A. Emrouznejad and G. Yang, A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Soc.-Econ. Planning Sci. 61 (2018) 4–8. [CrossRef] [Google Scholar]
  • F.R. Førsund, On the calculation of the scale elasticity in DEA models. J. Prod. Anal. 7 (1996) 283–302. [CrossRef] [Google Scholar]
  • F.R. Førsund and L. Hjalmarsson, Calculating scale elasticity in DEA models. J. Oper. Res. Soc. 55 (2004) 1023–1038. [CrossRef] [Google Scholar]
  • H. Fukuyama, Returns to scale and scale elasticity in data envelopment analysis. Eur. J. Oper. Res. 125 (2000) 93–112. [CrossRef] [Google Scholar]
  • A. Hatami-Marbini, J. Pourmahmoud and E. Babazadeh, A modified super-efficiency in the range directional model. Comput. Ind. Eng. 120 (2018) 442–449. [CrossRef] [Google Scholar]
  • I.C. Henriques, V.A. Sobreiro, H. Kimura and E.B. Mariano, Efficiency in the Brazilian banking system using data envelopment analysis. Future Bus. J. 4 (2018) 157–178. [CrossRef] [Google Scholar]
  • A. Kleine, W. Rödder and A. Dellnitz, Returns to scale revisited – towards Cross-RTS. In: Nachhaltiges Entscheiden: Beiträge zum multiperspektivischen Performancemanagement von Wertschöpfungsprozessen, edited by H. Ahn, M. Clermont and R. Souren. Springer (2016) 85–404. [Google Scholar]
  • T.C. Koopmans, An analysis of production as an efficient combination of activities. In: Activity Analysis of Production and Allocation, edited by T.C. Koopmans. John-Wiley and Sons Inc., New York, London (1951) 33–97. [Google Scholar]
  • H.-S. Lee and J. Zhu, Super-efficiency infeasibility and zero data in DEA. Eur. J. Oper. Res. 216 (2012) 429–433. [CrossRef] [Google Scholar]
  • V. Podinovski, F.R. Førsund and V.E. Krivonozhko, A simple derivation of scale elasticity in data envelopment analysis. Eur. J. Oper. Res. 197 (2009) 149–153. [CrossRef] [Google Scholar]
  • A. Pop, The new banking sector. Towards reforming the too big to fail banks. Proc. Econ. Finance 23 (2015) 1485–1491. [CrossRef] [Google Scholar]
  • W. Rödder, A. Kleine and A. Dellnitz, Scaling production and improving efficiency in DEA: an interactive approach. J. Ind. Eng. Int. 14 (2018) 501–510. [CrossRef] [Google Scholar]

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