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Convex Input and Output Projections of Nonconvex Production Possibility Sets

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Cited by:

  1. Kristiaan Kerstens & Ignace Van de Woestyne, 2021. "Cost functions are nonconvex in the outputs when the technology is nonconvex: convexification is not harmless," Annals of Operations Research, Springer, vol. 305(1), pages 81-106, October.
  2. Manh D. Pham & Valentin Zelenyuk, 2017. "Convexity, Disposability and Returns to Scale in Production Analysis," CEPA Working Papers Series WP042017, School of Economics, University of Queensland, Australia.
  3. Mehdiloozad, Mahmood & Podinovski, Victor V., 2018. "Nonparametric production technologies with weakly disposable inputs," European Journal of Operational Research, Elsevier, vol. 266(1), pages 247-258.
  4. Cherchye, L. & Post, G.T., 2001. "Methodological Advances in Dea," ERIM Report Series Research in Management ERS-2001-53-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  5. Bogetoft, Peter & Fare, Rolf & Obel, Borge, 2006. "Allocative efficiency of technically inefficient production units," European Journal of Operational Research, Elsevier, vol. 168(2), pages 450-462, January.
  6. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
  7. Botti, Laurent & Briec, Walter & Cliquet, Gérard, 2009. "Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance," Omega, Elsevier, vol. 37(3), pages 566-578, June.
  8. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
  9. Hougaard, Jens Leth & Tind, Jørgen, 2009. "Cost allocation and convex data envelopment," European Journal of Operational Research, Elsevier, vol. 194(3), pages 939-947, May.
  10. Thierry Post & Laurens Cherchye & Timo Kuosmanen, 2002. "Nonparametric Efficiency Estimation In Stochastic Environments," Operations Research, INFORMS, vol. 50(4), pages 645-655, August.
  11. S Blancard & J-P Boussemart & H Leleu, 2011. "Measuring potential gains from specialization under non-convex technologies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1871-1880, October.
  12. Zambelli, Stefano & Fredholm, Thomas & Venkatachalam, Ragupathy, 2017. "Robust measurement of national technological progress," Structural Change and Economic Dynamics, Elsevier, vol. 42(C), pages 38-55.
  13. Kuosmanen, Timo, 2001. "DEA with efficiency classification preserving conditional convexity," European Journal of Operational Research, Elsevier, vol. 132(2), pages 326-342, July.
  14. Monge, Juan F. & Ruiz, José L., 2023. "Setting closer targets based on non-dominated convex combinations of Pareto-efficient units: A bi-level linear programming approach in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1084-1096.
  15. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
  16. Walter Briec & Kristiaan Kerstens & Philippe Venden Eeckaut, 2004. "Non-convex Technologies and Cost Functions: Definitions, Duality and Nonparametric Tests of Convexity," Journal of Economics, Springer, vol. 81(2), pages 155-192, February.
  17. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
  18. Chavas, Jean-Paul & Kim, Kwansoo, 2013. "Nonparametric Analysis of Technology and Productivity under Non-Convexity," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149684, Agricultural and Applied Economics Association.
  19. Park, K. Sam & Park, Kwangtae, 2009. "Measurement of multiperiod aggregative efficiency," European Journal of Operational Research, Elsevier, vol. 193(2), pages 567-580, March.
  20. Jean-Paul Chavas & Kwansoo Kim, 2015. "Nonparametric analysis of technology and productivity under non-convexity: a neighborhood-based approach," Journal of Productivity Analysis, Springer, vol. 43(1), pages 59-74, February.
  21. Post, Thierry, 2001. "Estimating non-convex production sets - imposing convex input sets and output sets in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 131(1), pages 132-142, May.
  22. Ehrgott, Matthias & Tind, Jørgen, 2009. "Column generation with free replicability in DEA," Omega, Elsevier, vol. 37(5), pages 943-950, October.
  23. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
  24. Brandon Pope & Andrew Johnson, 2013. "Returns to scope: a metric for production synergies demonstrated for hospital production," Journal of Productivity Analysis, Springer, vol. 40(2), pages 239-250, October.
  25. Hervé Leleu & Albane Tarnaud, 2016. "The duality of Shephard’s weakly disposable technology," Working Papers 2016-EQM-06, IESEG School of Management.
  26. Halme, Merja & Korhonen, Pekka & Eskelinen, Juha, 2014. "Non-convex value efficiency analysis and its application to bank branch sales evaluation," Omega, Elsevier, vol. 48(C), pages 10-18.
  27. Victor Podinovski, 2004. "Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only," Journal of Productivity Analysis, Springer, vol. 22(3), pages 227-257, November.
  28. Fukuyama, Hirofumi & Shiraz, Rashed Khanjani, 2015. "Cost-effectiveness measures on convex and nonconvex technologies," European Journal of Operational Research, Elsevier, vol. 246(1), pages 307-319.
  29. Bogetoft, Peter & Hougaard, Jens Leth & Smilgins, Aleksandrs, 2016. "Applied cost allocation: The DEA–Aumann–Shapley approach," European Journal of Operational Research, Elsevier, vol. 254(2), pages 667-678.
  30. Zelenyuk, Valentin, 2020. "Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data," European Journal of Operational Research, Elsevier, vol. 282(1), pages 172-187.
  31. Timo Kuosmanen, 2003. "Duality Theory of Non-convex Technologies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 273-304, November.
  32. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
  33. Anne-Kathrin Last & Heike Wetzel, 2009. "Effizienzmessverfahren – eine Einführung," Working Paper Series in Economics 145, University of Lüneburg, Institute of Economics.
  34. Agrell, Per J. & Bogetoft, Peter & Tind, Jorgen, 2000. "Polarity in DEA Models," Unit of Economics Working Papers 24188, Royal Veterinary and Agricultural University, Food and Resource Economic Institute.
  35. V V Podinovski, 2004. "Local and global returns to scale in performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 170-178, February.
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