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The directional profit efficiency measure: on why profit inefficiency is either technical or allocative

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  1. Tsionas, Mike G., 2023. "Joint production in stochastic non-parametric envelopment of data with firm-specific directions," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1336-1347.
  2. Pedro Macedo & Elvira Silva, 2017. "Sensitivity of directional technical inefficiency measures to the choice of the direction vector: a simulation study," Economics Bulletin, AccessEcon, vol. 37(1), pages 52-62.
  3. Juan Aparicio & José L. Zofío & Jesús T. Pastor, 2023. "Decomposing Economic Efficiency into Technical and Allocative Components: An Essential Property," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 98-129, April.
  4. Kapelko, Magdalena & Oude Lansink, Alfons & Zofío, José L., 2022. "Endogenous dynamic inefficiency and optimal resource allocation: An application to the European Dietetic Food Industry," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1444-1457.
  5. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.
  6. Juan Aparicio & José L. Zofío, 2017. "Revisiting the decomposition of cost efficiency for non-homothetic technologies: a directional distance function approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 133-146, December.
  7. Lee, Chia-Yen & Wang, Ke, 2019. "Nash marginal abatement cost estimation of air pollutant emissions using the stochastic semi-nonparametric frontier," European Journal of Operational Research, Elsevier, vol. 273(1), pages 390-400.
  8. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
  9. Briec, Walter & Dumas, Audrey & Kerstens, Kristiaan & Stenger, Agathe, 2022. "Generalised commensurability properties of efficiency measures: Implications for productivity indicators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1481-1492.
  10. Lee, Chia-Yen, 2016. "Nash-profit efficiency: A measure of changes in market structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 659-663.
  11. Malin Song & Jianlin Wang & Jiajia Zhao & Tomas Baležentis & Zhiyang Shen, 2020. "Production and safety efficiency evaluation in Chinese coal mines: accident deaths as undesirable output," Annals of Operations Research, Springer, vol. 291(1), pages 827-845, August.
  12. Scott E. Atkinson & Mike G. Tsionas, 2018. "Shadow directional distance functions with bads: GMM estimation of optimal directions and efficiencies," Empirical Economics, Springer, vol. 54(1), pages 207-230, February.
  13. Falavigna, G. & Ippoliti, R., 2020. "The socio-economic planning of a community nurses programme in mountain areas: A Directional Distance Function approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
  14. Aparicio, Juan & Pastor, Jesus T. & Zofio, Jose L., 2015. "How to properly decompose economic efficiency using technical and allocative criteria with non-homothetic DEA technologies," European Journal of Operational Research, Elsevier, vol. 240(3), pages 882-891.
  15. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
  16. Mustapha Daruwana Ibrahim & Sahand Daneshvar & Hüseyin Güden & Bela Vizvari, 2020. "Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1319-1336, December.
  17. Aparicio, Juan & Zofío, José L., 2023. "Decomposing profit change: Konüs, Bennet and Luenberger indicators," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
  18. Álvarez, Inmaculada & Barbero, Javier & Zofío, Jose Luis, 2016. "A Data Envelopment Analysis Toolbox for MATLAB," Working Papers in Economic Theory 2016/03, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
  19. Shuguang Lin & Paul Rouse & Ying-Ming Wang & Lin Lin & Zhen-Quan Zheng, 2023. "Performance measurement of nonhomogeneous Hong Kong hospitals using directional distance functions," Health Care Management Science, Springer, vol. 26(2), pages 330-343, June.
  20. Mircea Epure, 2016. "Benchmarking for routines and organizational knowledge: a managerial accounting approach with performance feedback," Journal of Productivity Analysis, Springer, vol. 46(1), pages 87-107, August.
  21. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
  22. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
  23. Deng, Zhongqi & Jiang, Nan & Pang, Ruizhi, 2021. "Factor-analysis-based directional distance function: The case of New Zealand hospitals," Omega, Elsevier, vol. 98(C).
  24. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
  25. Fangqing Wei & Junfei Chu & Jiayun Song & Feng Yang, 2019. "A cross-bargaining game approach for direction selection in the directional distance function," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 787-807, September.
  26. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
  27. Arabmaldar, Aliasghar & Sahoo, Biresh K. & Ghiyasi, Mojtaba, 2023. "A generalized robust data envelopment analysis model based on directional distance function," European Journal of Operational Research, Elsevier, vol. 311(2), pages 617-632.
  28. Engida, Tadesse Getacher & Rao, Xudong & Oude Lansink, Alfons G.J.M., 2020. "A dynamic by-production framework for analyzing inefficiency associated with corporate social responsibility," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1170-1179.
  29. Aparicio, Juan & Garcia-Nove, Eva M. & Kapelko, Magdalena & Pastor, Jesus T., 2017. "Graph productivity change measure using the least distance to the pareto-efficient frontier in data envelopment analysis," Omega, Elsevier, vol. 72(C), pages 1-14.
  30. Sebastián Lozano & Narges Soltani, 2018. "DEA target setting using lexicographic and endogenous directional distance function approaches," Journal of Productivity Analysis, Springer, vol. 50(1), pages 55-70, October.
  31. Chen, Lei & Wang, Ying-Ming, 2023. "Game directional distance function in meta-frontier data envelopment analysis," Omega, Elsevier, vol. 121(C).
  32. Pastor, Jesus T. & Zofio, Jose L., 2017. "Can Farrell's allocative efficiency be generalized by the directional distance function approach?Author-Name: Aparicio, Juan," European Journal of Operational Research, Elsevier, vol. 257(1), pages 345-351.
  33. Bogetoft, Peter & Ramírez-Ayerbe, Jasone & Romero Morales, Dolores, 2024. "Counterfactual analysis and target setting in benchmarking," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1083-1095.
  34. Kuosmanen, Timo & Johnson, Andrew, 2017. "Modeling joint production of multiple outputs in StoNED: Directional distance function approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 792-801.
  35. Lozano, Sebastián & Calzada-Infante, Laura, 2018. "Computing gradient-based stepwise benchmarking paths," Omega, Elsevier, vol. 81(C), pages 195-207.
  36. Aparicio, Juan & Kapelko, Magdalena & Ortiz, Lidia, 2023. "Enhancing the measurement of firm inefficiency accounting for corporate social responsibility: A dynamic data envelopment analysis fuzzy approach," European Journal of Operational Research, Elsevier, vol. 306(2), pages 986-997.
  37. Atkinson, Scott E. & Primont, Daniel & Tsionas, Mike G., 2018. "Statistical inference in efficient production with bad inputs and outputs using latent prices and optimal directions," Journal of Econometrics, Elsevier, vol. 204(2), pages 131-146.
  38. Deng, Zhongqi & Song, Shunfeng & Jiang, Nan & Pang, Ruizhi, 2023. "Sustainable development in China? A nonparametric decomposition of economic growth," China Economic Review, Elsevier, vol. 81(C).
  39. Lee, Chia-Yen, 2018. "Mixed-strategy Nash equilibrium in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1013-1024.
  40. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
  41. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
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