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Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data

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Cited by:

  1. Färe, Rolf & Zelenyuk, Valentin, 2020. "Profit efficiency: Generalization, business accounting and the role of convexity," Economics Letters, Elsevier, vol. 196(C).
  2. Yuanxiang Zhou & Shan Wang & Shuqi Xu & Qingyuan Zhu, 2025. "Big data in data envelopment analysis with undesirable outputs based on simulation and environmental-health matching data of Chinese industrial enterprises," Annals of Operations Research, Springer, vol. 348(1), pages 279-298, May.
  3. Kiani Mavi, Reza & Kiani Mavi, Neda, 2021. "National eco-innovation analysis with big data: A common-weights model for dynamic DEA," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
  4. Bao Hoang Nguyen & Valentin Zelenyuk, 2020. "Robust efficiency analysis of public hospitals in Queensland, Australia," CEPA Working Papers Series WP052020, School of Economics, University of Queensland, Australia.
  5. Bao Hoang Nguyen & Valentin Zelenyuk, 2021. "Aggregation of Outputs and Inputs for DEA Analysis of Hospital Efficiency: Economics, Operations Research and Data Science Perspectives," International Series in Operations Research & Management Science, in: Joe Zhu & Vincent Charles (ed.), Data-Enabled Analytics, pages 123-158, Springer.
  6. Nguyen, Bao Hoang & Simar, Léopold & Zelenyuk, Valentin, 2022. "Data sharpening for improving central limit theorem approximations for data envelopment analysis–type efficiency estimators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1469-1480.
  7. Simar, Léopold & Zelenyuk, Valentin, 2020. "Improving finite sample approximation by central limit theorems for estimates from Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1002-1015.
  8. Valentin Zelenyuk, 2024. "Aggregation in efficiency and productivity analysis: a brief review with new insights and justifications for constant returns to scale," Journal of Productivity Analysis, Springer, vol. 62(3), pages 321-334, December.
  9. Natalya Zelenyuk & Valentin Zelenyuk, 2021. "Bank Performance Analysis," CEPA Working Papers Series WP022021, School of Economics, University of Queensland, Australia.
  10. Bao Hoang Nguyen & Valentin Zelenyuk, 2021. "Aggregate efficiency of industry and its groups: the case of Queensland public hospitals," Empirical Economics, Springer, vol. 60(6), pages 2795-2836, June.
  11. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP022020, School of Economics, University of Queensland, Australia.
  12. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
  13. Bao Hoang Nguyen & Valentin Zelenyuk, 2020. "Aggregate Efficiency of Industry and its Groups: The case of Queensland Public Hospitals," CEPA Working Papers Series WP062020, School of Economics, University of Queensland, Australia.
  14. S. C. West & A. W. Mugera & R. S. Kingwell, 2022. "The choice of efficiency benchmarking metric in evaluating firm productivity and viability," Journal of Productivity Analysis, Springer, vol. 57(2), pages 193-211, April.
  15. Mahmood Mehdiloo & Victor V. Podinovski, 2024. "Data envelopment analysis with embedded inputs and outputs," Annals of Operations Research, Springer, vol. 335(1), pages 293-325, April.
  16. Wang, Derek D. & Hu, Peng & Ren, Yaoyao, 2025. "The by-production models for benchmarking," Energy Economics, Elsevier, vol. 143(C).
  17. Emil Heesche & Mette Asmild, 2022. "Implications of Aggregation Uncertainty in DEA," IFRO Working Paper 2022/02, University of Copenhagen, Department of Food and Resource Economics.
  18. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  19. Kenneth Løvold Rødseth & Rasmus Bøgh Holmen & Timo Kuosmanen & Halvor Schøyen, 2024. "Nonparametric estimation of allocative efficiency using indirect production theory: Application to container ports in Norway," Journal of Productivity Analysis, Springer, vol. 62(3), pages 365-377, December.
  20. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2022. "Efficiency Analysis with Stochastic Frontier Models Using Popular Statistical Softwares," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 129-171, Springer.
  21. Valentin Zelenyuk, 2021. "Performance Analysis: Economic Foundations & Trends," CEPA Working Papers Series WP162021, School of Economics, University of Queensland, Australia.
  22. Kok Fong See & Shawna Grosskopf & Vivian Valdmanis & Valentin Zelenyuk, 2021. "What do we know from the vast literature on efficiency and productivity in healthcare? A Systematic Review and Bibliometric Analysis," CEPA Working Papers Series WP072021, School of Economics, University of Queensland, Australia.
  23. Zhichao Wang & Valentin Zelenyuk, 2024. "Data Envelopment Analysis: From Foundations to Modern Advancements," Foundations and Trends(R) in Econometrics, now publishers, vol. 13(3), pages 170-282, November.
  24. Valentin Zelenyuk, 2021. "Performance Analysis: Economic Foundations and Trends," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(3), pages 153-229, September.
  25. Chen Chunhua & Liu Haohua & Tang Lijun & Ren Jianwei, 2021. "A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 378-398, August.
  26. Rolf Färe & Valentin Zelenyuk, 2020. "Profit Efficiency and its Estimation," CEPA Working Papers Series WP072020, School of Economics, University of Queensland, Australia.
  27. Duras, Toni & Javed, Farrukh & Månsson, Kristofer & Sjölander, Pär & Söderberg, Magnus, 2023. "Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data," Energy Economics, Elsevier, vol. 120(C).
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