IDEAS home Printed from https://ideas.repec.org/f/c/pjo234.html
   My authors  Follow this author

Andrew L. Johnson

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Yagi, Daisuke & Chen, Yining & Johnson, Andrew L. & Kuosmanen, Timo, 2018. "Shape constrained kernel-weighted least squares: Estimating production functions for Chilean manufacturing industries," LSE Research Online Documents on Economics 86556, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Cristina Polo & Julián Ramajo & Alejandro Ricci‐Risquete, 2021. "A stochastic semi‐non‐parametric analysis of regional efficiency in the European Union," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 7-24, February.
    2. Jose Manuel Cordero & Cristina Polo & Javier Salinas-Jiménez, 2021. "Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods," Journal of Happiness Studies, Springer, vol. 22(2), pages 867-886, February.
    3. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    4. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    5. 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.
    6. Oliver Y. Feng & Yining Chen & Qiyang Han & Raymond J. Carroll & Richard J. Samworth, 2022. "Nonparametric, tuning‐free estimation of S‐shaped functions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1324-1352, September.
    7. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    8. Feng, Oliver Y. & Chen, Yining & Han, Qiyang & Carroll, Raymond J & Samworth, Richard J., 2022. "Nonparametric, tuning-free estimation of S-shaped functions," LSE Research Online Documents on Economics 111889, London School of Economics and Political Science, LSE Library.
    9. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    10. Eunji Lim & Kihwan Kim, 2020. "Estimating Smooth and Convex Functions," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(5), pages 1-40, September.
    11. Ghosal, Rahul & Ghosh, Sujit & Urbanek, Jacek & Schrack, Jennifer A. & Zipunnikov, Vadim, 2023. "Shape-constrained estimation in functional regression with Bernstein polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    12. Mike G. Tsionas & Valentin Zelenyuk, 2022. "Testing for Optimization Behavior in Production when Data is with Measurement Errors: A Bayesian Approach," CEPA Working Papers Series WP012022, School of Economics, University of Queensland, Australia.

  2. Ferrier, Gary D. & Johnson, Andrew L. & Layer, Kevin & Sickles, Robin C., 2018. "Direction Selection in Stochastic Directional Distance Functions," Working Papers 18-010, Rice University, Department of Economics.

    Cited by:

    1. Arabmaldar, A. & Sahoo, B.K. & Ghiyasi, M., 2023. "A generalized robust data envelopment analysis model based on directional distance function," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138962, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. 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).
    3. 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.
    4. Tsionas, Mike G., 2020. "On a model of environmental performance and technology gaps," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1141-1152.
    5. Walter Briec & Audrey Dumas & Kristiaan Kerstens & Agathe Stenger, 2021. "Generalised Commensurability Properties of Efficiency Measures: Implications for Productivity Indicators," Working Papers 2021-EQM-01, IESEG School of Management.
    6. Hongxing Tu & Wei Dai & Xu Xiao, 2022. "Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model," Energies, MDPI, vol. 15(9), pages 1-13, May.
    7. Aparicio, Juan & Zofío, José L., 2023. "Decomposing profit change: Konüs, Bennet and Luenberger indicators," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    8. Chunhua Chen & Jianwei Ren & Lijun Tang & Haohua Liu, 2020. "Additive integer-valued data envelopment analysis with missing data: A multi-criteria evaluation approach," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-20, June.
    9. 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.
    10. Yongseung Han & Arthur Snow & Ronald S. Warren, 2021. "Changes in the productive efficiency of U.S. flour mills in the late nineteenth century: an input-distance-function approach," Journal of Productivity Analysis, Springer, vol. 56(2), pages 115-132, December.

Articles

  1. Daisuke Yagi & Yining Chen & Andrew L. Johnson & Timo Kuosmanen, 2020. "Shape-Constrained Kernel-Weighted Least Squares: Estimating Production Functions for Chilean Manufacturing Industries," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 43-54, January.
    See citations under working paper version above.
  2. Hoon Hwangbo & Andrew L. Johnson & Yu Ding, 2018. "Spline model for wake effect analysis: Characteristics of a single wake and its impacts on wind turbine power generation," IISE Transactions, Taylor & Francis Journals, vol. 50(2), pages 112-125, February.

    Cited by:

    1. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    2. Arslan Salim Dar & Fernando Porté-Agel, 2022. "An Analytical Model for Wind Turbine Wakes under Pressure Gradient," Energies, MDPI, vol. 15(15), pages 1-13, July.

  3. René B. M. De Koster & Andrew L. Johnson & Debjit Roy, 2017. "Warehouse design and management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6327-6330, November.

    Cited by:

    1. Lam, H.Y. & Ho, G.T.S. & Mo, Daniel Y. & Tang, Valerie, 2023. "Responsive pick face replenishment strategy for stock allocation to fulfil e-commerce order," International Journal of Production Economics, Elsevier, vol. 264(C).
    2. Vukašin Pajić & Milorad Kilibarda & Milan Andrejić, 2023. "A Novel Hybrid Approach for Evaluation of Resilient 4PL Provider for E-Commerce," Mathematics, MDPI, vol. 11(3), pages 1-26, January.
    3. Loon, Mark, 2019. "Knowledge management practice system: Theorising from an international meta-standard," Journal of Business Research, Elsevier, vol. 94(C), pages 432-441.
    4. Li, Xiaowei & Hua, Guowei & Huang, Anqiang & Sheu, Jiuh-Biing & Cheng, T.C.E. & Huang, Fengquan, 2020. "Storage assignment policy with awareness of energy consumption in the Kiva mobile fulfilment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    5. de Jesus Pacheco, Diego Augusto & Møller Clausen, Daniel & Bumann, Jendrik, 2023. "A multi-method approach for reducing operational wastes in distribution warehouses," International Journal of Production Economics, Elsevier, vol. 256(C).
    6. Anderson Rogério Faia Pinto & Marcelo Seido Nagano, 2020. "Genetic algorithms applied to integration and optimization of billing and picking processes," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 641-659, March.
    7. Dalia Perkumienė & Kristina Ratautaitė & Rasa Pranskūnienė, 2022. "Innovative Solutions and Challenges for the Improvement of Storage Processes," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    8. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2018. "The influence of e-commerce on the design of warehouses - a literature review," Working Papers 2018013, University of Antwerp, Faculty of Business and Economics.
    9. Ivan Derpich & Juan M. Sepúlveda & Rodrigo Barraza & Fernanda Castro, 2022. "Warehouse Optimization: Energy Efficient Layout and Design," Mathematics, MDPI, vol. 10(10), pages 1-17, May.
    10. Sadia Samar Ali & Rajbir Kaur & Shahbaz Khan, 2023. "Evaluating sustainability initiatives in warehouse for measuring sustainability performance: an emerging economy perspective," Annals of Operations Research, Springer, vol. 324(1), pages 461-500, May.
    11. Baniasadi, Pouya & Foumani, Mehdi & Smith-Miles, Kate & Ejov, Vladimir, 2020. "A transformation technique for the clustered generalized traveling salesman problem with applications to logistics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 444-457.

  4. 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.

    Cited by:

    1. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Agrell, Per Joakim & Teusch, Jonas, 2020. "Predictability and strategic behavior under frontier regulation," LIDAM Reprints CORE 3094, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
    4. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    5. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    6. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    7. Arabmaldar, A. & Sahoo, B.K. & Ghiyasi, M., 2023. "A generalized robust data envelopment analysis model based on directional distance function," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138962, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Josiah Aduda & Stephen Obondy, 2021. "Credit Risk Management and Efficiency of Savings and Credit Cooperative Societies: A Review of Literature," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(1), pages 1-7.
    9. Mike Tsionas & Valentin Zelenyuk, 2021. "Goodness-of-fit in Optimizing Models of Production: A Generalization with a Bayesian Perspective," CEPA Working Papers Series WP182021, School of Economics, University of Queensland, Australia.
    10. Alexander Arévalo S & Víctor Giménez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91, October.
    11. Gbenga I . Olorunsola PhD, ACA, FCIB & Adedoyin Bunmi-Alo & Oyekunbi Olubukola Dele- Oladejo PhD, 2023. "Credit Risk Management and Efficiency of Savings and Credit Cooperative Society in Lagos State," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(3), pages 505-515, March.
    12. Julia Schaefer & Marcel Clermont, 2018. "Stochastic non-smooth envelopment of data for multi-dimensional output," Journal of Productivity Analysis, Springer, vol. 50(3), pages 139-154, December.
    13. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
    14. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
    15. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    16. Nadia M. Guerrero & Juan Aparicio & Daniel Valero-Carreras, 2022. "Combining Data Envelopment Analysis and Machine Learning," Mathematics, MDPI, vol. 10(6), pages 1-22, March.
    17. España, Victor J. & Aparicio, Juan & Barber, Xavier & Esteve, Miriam, 2024. "Estimating production functions through additive models based on regression splines," European Journal of Operational Research, Elsevier, vol. 312(2), pages 684-699.
    18. Zhang, Yue-Jun & Sun, Ya-Fang & Huang, Junling, 2018. "Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment," Energy Policy, Elsevier, vol. 115(C), pages 119-130.
    19. Alexandre Repkine, 2023. "The Estimation of a Polluting By-Production Technology Using Statistical Copulas," Journal of Productivity Analysis, Springer, vol. 60(1), pages 49-62, August.
    20. Sueyoshi, Toshiyuki & Li, Aijun & Liu, Xiaohong, 2019. "Exploring sources of China's CO2 emission: Decomposition analysis under different technology changes," European Journal of Operational Research, Elsevier, vol. 279(3), pages 984-995.
    21. 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.
    22. Simar, Léopold & Wilson, Paul, 2021. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," LIDAM Discussion Papers ISBA 2021003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Tsionas, Mike G., 2020. "On a model of environmental performance and technology gaps," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1141-1152.
    24. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
    25. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
    26. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2021. "Lurking in the Shadows: The Impact of Emissions Target Setting on Carbon Pricing and Environmental Efficiency," QBS Working Paper Series 2021/05, Queen's University Belfast, Queen's Business School.
    27. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    28. Kuosmanen, Timo & Zhou, Xun & Dai, Sheng, 2020. "How much climate policy has cost for OECD countries?," World Development, Elsevier, vol. 125(C).
    29. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
    30. Kalundu Kimanzi & Prof. Mirie Mwangi & Dr. Duncan Elly Ochieng & Prof. Josephat Lishenga, 2020. "Moderating Effect of Board Gender Diversity on the Relationship between Financial Structure and Operating Efficiency," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 9(1), pages 1-1.
    31. Valero-Carreras, Daniel & Aparicio, Juan & Guerrero, Nadia M., 2021. "Support vector frontiers: A new approach for estimating production functions through support vector machines," Omega, Elsevier, vol. 104(C).
    32. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).
    33. Zhang, Tao & Li, Hong-Zhou & Xie, Bai-Chen, 2022. "Have renewables and market-oriented reforms constrained the technical efficiency improvement of China's electric grid utilities?," Energy Economics, Elsevier, vol. 114(C).

  5. Soondo Hong & Andrew L. Johnson & Brett A. Peters, 2016. "Order batching in a bucket brigade order picking system considering picker blocking," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 425-441, September.

    Cited by:

    1. Valle, Cristiano Arbex & Beasley, John E. & da Cunha, Alexandre Salles, 2017. "Optimally solving the joint order batching and picker routing problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 817-834.
    2. Giannikas, Vaggelis & Lu, Wenrong & Robertson, Brian & McFarlane, Duncan, 2017. "An interventionist strategy for warehouse order picking: Evidence from two case studies," International Journal of Production Economics, Elsevier, vol. 189(C), pages 63-76.
    3. Fangyu Chen & Yongchang Wei & Hongwei Wang, 2018. "A heuristic based batching and assigning method for online customer orders," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 640-685, December.
    4. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    5. Soondo Hong, 2018. "The effects of picker-oriented operational factors on hand-off delay in a bucket brigade order picking system," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 781-808, July.

  6. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.

    Cited by:

    1. Ke Wang & Chia-Yen Lee & Jieming Zhang & Yi-Ming Wei, 2016. "Operational performance management of the power industry: A distinguishing analysis between effectiveness and efficiency," CEEP-BIT Working Papers 93, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    2. Liu, Dan & Zhang, Jiahuang & Yu, Ming-Miin, 2023. "Decomposing airline profit inefficiency in NDEA through the non-competitive Nerlovian profit inefficiency model," Journal of Air Transport Management, Elsevier, vol. 107(C).
    3. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    4. Ke Wang & Jieming Zhang & Yi-Ming Wei, 2017. "Operational and environmental performance in China¡¯s thermal power industry: Taking an effectiveness measure as complement to an efficiency measure," CEEP-BIT Working Papers 100, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    5. Yu, Ming-Miin & Chen, Li-Hsueh & Chiang, Hui, 2017. "The effects of alliances and size on airlines’ dynamic operational performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 197-214.

  7. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2015. "Quantifying picker blocking in a bucket brigade order picking system," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 862-873.

    Cited by:

    1. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    2. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2018. "The influence of e-commerce on the design of warehouses - a literature review," Working Papers 2018013, University of Antwerp, Faculty of Business and Economics.
    3. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.

  8. Chia -Yen Lee & Andrew L. Johnson, 2015. "Measuring Efficiency in Imperfectly Competitive Markets: An Example of Rational Inefficiency," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 702-722, February.

    Cited by:

    1. Tsionas, Mike G., 2020. "Bounded rationality and thick frontiers in stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 762-768.
    2. 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.
    3. 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.
    4. Hampf, Benjamin, 2016. "Rational Inefficiency, Adjustment Costs and Sequential Technologies," VfS Annual Conference 2016 (Augsburg): Demographic Change 145796, Verein für Socialpolitik / German Economic Association.
    5. 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.
    6. 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.
    7. 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.
    8. Tseng, Chin-Yi & Lee, Chia-Yen & Wang, Qunwei & Wu, Changsong, 2022. "Data envelopment analysis and stochastic equilibrium analysis for market power investigation in a bi-level market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    9. Levent Kutlu & Ran Wang, 2018. "Estimation of cost efficiency without cost data," Journal of Productivity Analysis, Springer, vol. 49(2), pages 137-151, June.
    10. Chia-Yen Lee & Chin-Yi Tseng, 2023. "Market Power and Efficiency Analysis in Bi-level Energy Transmission Market," Journal of Optimization Theory and Applications, Springer, vol. 196(2), pages 544-569, February.
    11. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    12. Qingxian An & Ping Wang & Honglin Yang & Zongrun Wang, 2021. "Fixed cost allocation in two-stage system using DEA from a noncooperative view," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1077-1102, December.
    13. Hampf, Benjamin, 2017. "Rational inefficiency, adjustment costs and sequential technologies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1095-1108.

  9. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.

    Cited by:

    1. Cristina Polo & Julián Ramajo & Alejandro Ricci‐Risquete, 2021. "A stochastic semi‐non‐parametric analysis of regional efficiency in the European Union," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 7-24, February.
    2. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    3. Tiziano De Angelis & Peter Tankov & Olivier David Zerbib, 2022. "Climate Impact Investing," Carlo Alberto Notebooks 676 JEL Classification: G, Collegio Carlo Alberto.
    4. Bowen Xiao & Dongxiao Niu & Han Wu & Haichao Wang, 2017. "Marginal Abatement Cost of CO 2 in China Based on Directional Distance Function: An Industry Perspective," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    5. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    6. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
    7. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
    8. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    9. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    10. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
    11. Song, Malin & Peng, Jun & Wang, Jianlin & Zhao, Jiajia, 2018. "Environmental efficiency and economic growth of China: A Ray slack-based model analysis," European Journal of Operational Research, Elsevier, vol. 269(1), pages 51-63.

  10. Brandon Pope & Abhijit Deshmukh & Andrew Johnson & James Rohack, 2014. "Multilateral Contracting And Prevention," Health Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 397-409, April.

    Cited by:

    1. Hui Zhang & Christian Wernz & Danny R. Hughes, 2018. "Modeling and designing health care payment innovations for medical imaging," Health Care Management Science, Springer, vol. 21(1), pages 37-51, March.
    2. Hui Zhang & Christian Wernz & Anthony D. Slonim, 2016. "Aligning incentives in health care: a multiscale decision theory approach," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 219-244, November.

  11. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.

    Cited by:

    1. Giménez, Víctor & Thieme, Claudio & Prior, Diego & Tortosa-Ausina, Emili, 2022. "Evaluation and determinants of preschool effectiveness in Chile," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    3. Victor V. Podinovski & Wan Rohaida Wan Husain, 2017. "The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia," Annals of Operations Research, Springer, vol. 250(1), pages 65-84, March.
    4. Mladen Stamenković & Ivan Anić & Marijana Petrović & Nataša Bojković, 2016. "An ELECTRE approach for evaluating secondary education profiles: evidence from PISA survey in Serbia," Annals of Operations Research, Springer, vol. 245(1), pages 337-358, October.
    5. Agasisti, Tommaso & de Oliveira Ribeiro, Celma & Montemor, Daniel Sanches, 2022. "The efficiency of Brazilian elementary public schools," International Journal of Educational Development, Elsevier, vol. 93(C).
    6. Daraio, Cinzia & Simar, Léopold & Wilson, Paul W., 2021. "Quality as a latent heterogeneity factor in the efficiency of universities," Economic Modelling, Elsevier, vol. 99(C).
    7. Paolo Liberati & Raffaele Lagravinese & Giuliano Resce, 2017. "How Does Economic Social And Cultural Status Affect The Efficiency Of Educational Attainments? A Comparative Analysis On Pisa Results," Departmental Working Papers of Economics - University 'Roma Tre' 0217, Department of Economics - University Roma Tre.
    8. Shijie Ding & Jing Zhao & Meng Zhang & Sheng Yang & Hongwei Zhang, 2022. "Measuring the environmental protection efficiency and productivity of the 49 largest iron and steel enterprises in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 454-472, January.
    9. Olesen, Ole Bent & Petersen, Niels Christian & Podinovski, Victor V., 2017. "Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs," European Journal of Operational Research, Elsevier, vol. 261(2), pages 640-655.
    10. Sagarra, Marti & Mar-Molinero, Cecilio & Agasisti, Tommaso, 2017. "Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling," Omega, Elsevier, vol. 67(C), pages 123-133.
    11. Kenan Oğuzhan Oruç & Fatma Gül Altın, 2015. "The Effect of the 2007 Financial Crisis on the Information Technologies Sector: Application of Malmquist Productivity Index Method," International Journal of Business and Social Research, LAR Center Press, vol. 5(6), pages 1-11, June.
    12. Ana B. Ruiz & Mariano Luque & Oscar D. Marcenaro-Gutierrez, 2022. "On the use of Synthetic Indexes Based on Multi-Criteria Decision Making to Study the Efficiency of Teachers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(3), pages 1269-1300, October.
    13. Laura López-Torres & Diego Prior Jiménez, 2014. "Measuring School Demand in the Presence of Spatial Dependence. A Conditional Approach," Working Papers 1403, Departament Empresa, Universitat Autònoma de Barcelona, revised Jun 2014.
    14. D’Inverno, Giovanna & Smet, Mike & De Witte, Kristof, 2021. "Impact evaluation in a multi-input multi-output setting: Evidence on the effect of additional resources for schools," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1111-1124.
    15. Alexander Arévalo S & Víctor Giménez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91, October.
    16. Claudia Curi & Ana Lozano-Vivas, 2015. "Financial center productivity and innovation prior to and during the financial crisis," Journal of Productivity Analysis, Springer, vol. 43(3), pages 351-365, June.
    17. Aparicio, Juan & López-Torres, Laura & Santín, Daniel, 2018. "Economic crisis and public education. A productivity analysis using a Hicks-Moorsteen index," Economic Modelling, Elsevier, vol. 71(C), pages 34-44.
    18. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    19. Luque, Mariano & Marcenaro-Gutierrez, Oscar D. & Ruiz, Ana B., 2020. "Evaluating the global efficiency of teachers through a multi-criteria approach," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    20. Pham, Manh D. & Simar, Léopold & Zelenyuk, Valentin, 2022. "Statistical Inference for Aggregation of Malmquist Productivity Indices," LIDAM Discussion Papers ISBA 2022005, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Aparicio, Juan & Ortiz, Lidia & Santín, Daniel, 2021. "Comparing group performance over time through the Luenberger productivity indicator: An application to school ownership in European countries," European Journal of Operational Research, Elsevier, vol. 294(2), pages 651-672.
    22. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2018. "Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model," Journal of Informetrics, Elsevier, vol. 12(1), pages 10-30.
    23. Lagravinese, Raffaele & Liberati, Paolo & Resce, Giuliano, 2020. "The impact of economic, social and cultural conditions on educational attainments," Journal of Policy Modeling, Elsevier, vol. 42(1), pages 112-132.
    24. Jie Wu & Beibei Xiong & Qingxian An & Jiasen Sun & Huaqing Wu, 2017. "Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs," Annals of Operations Research, Springer, vol. 255(1), pages 257-276, August.
    25. Liao, Hua & Du, Yun-Fei & Huang, Zhimin & Wei, Yi-Ming, 2016. "Measuring energy economic efficiency: A mathematical programming approach," Applied Energy, Elsevier, vol. 179(C), pages 479-487.
    26. Polcyn, Jan, 2017. "Edukacja jako dobro publiczne - próba kwantyfikacji [Education as a public good – an attempt at quantification]," MPRA Paper 76606, University Library of Munich, Germany, revised 2017.
    27. Kenan Oğuzhan Oruç & Fatma Gül Altın, 2015. "The Effect of the 2007 Financial Crisis on the Information Technologies Sector: Application of Malmquist Productivity Index Method," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 5(6), pages 1-11, June.
    28. López-Torres, Laura & Prior, Diego, 2013. "Do Parents Perceive The Technical Quality Of Public Schools? An Activity Analysis Approach," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 13(3), pages 39-60.
    29. Manuel Salas‐Velasco, 2020. "Assessing the performance of Spanish secondary education institutions: Distinguishing between transient and persistent inefficiency, separated from heterogeneity," Manchester School, University of Manchester, vol. 88(4), pages 531-555, July.

  12. Lee, Jongsung & Kim, Byung-In & Johnson, Andrew L. & Lee, Kiho, 2014. "The nuclear medicine production and delivery problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 461-472.

    Cited by:

    1. Devapriya, Priyantha & Ferrell, William & Geismar, Neil, 2017. "Integrated production and distribution scheduling with a perishable product," European Journal of Operational Research, Elsevier, vol. 259(3), pages 906-916.
    2. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2018. "Vehicle routing problems with multiple trips," Annals of Operations Research, Springer, vol. 271(1), pages 127-159, December.
    3. Ling Liu & Wenli Li & Kunpeng Li & Xuxia Zou, 2020. "A coordinated production and transportation scheduling problem with minimum sum of order delivery times," Journal of Heuristics, Springer, vol. 26(1), pages 33-58, February.
    4. Chen, Wanying (Amanda) & De Koster, René B.M. & Gong, Yeming, 2021. "Performance evaluation of automated medicine delivery systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    5. Alexis Robbes & Yannick Kergosien & Virginie André & Jean-Charles Billaut, 2022. "Efficient heuristics to minimize the total tardiness of chemotherapy drug production and delivery," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 785-820, September.
    6. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "Vehicle routing problems with multiple trips," 4OR, Springer, vol. 14(3), pages 223-259, September.
    7. Chevroton, Hugo & Kergosien, Yannick & Berghman, Lotte & Billaut, Jean-Charles, 2021. "Solving an integrated scheduling and routing problem with inventory, routing and penalty costs," European Journal of Operational Research, Elsevier, vol. 294(2), pages 571-589.
    8. Véronique François & Yasemin Arda & Yves Crama, 2019. "Adaptive Large Neighborhood Search for Multitrip Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 53(6), pages 1706-1730, November.
    9. Ling Liu & Sen Liu, 2020. "Integrated Production and Distribution Problem of Perishable Products with a Minimum Total Order Weighted Delivery Time," Mathematics, MDPI, vol. 8(2), pages 1-18, January.
    10. Kergosien, Y. & Gendreau, M. & Billaut, J.-C., 2017. "A Benders decomposition-based heuristic for a production and outbound distribution scheduling problem with strict delivery constraints," European Journal of Operational Research, Elsevier, vol. 262(1), pages 287-298.
    11. Yang, Weibo & Ke, Liangjun & Wang, David Z.W. & Lam, Jasmine Siu Lee, 2021. "A branch-price-and-cut algorithm for the vehicle routing problem with release and due dates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    12. Berghman, Lotte & Kergosien, Yannick & Billaut, Jean-Charles, 2023. "A review on integrated scheduling and outbound vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 1-23.

  13. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.

    Cited by:

    1. Costa Melo, Isotilia & Alves Junior, Paulo Nocera & Callefi, Jéssica Syrio & da Silva, Karoline Arguelho & Nagano, Marcelo Seido & Rebelatto, Daisy Aparecida do Nascimento & Rentizelas, Athanasios, 2023. "Measuring the performance of retailers during the COVID-19 pandemic: Embedding optimal control theory principles in a dynamic data envelopment analysis approach," Operations Research Perspectives, Elsevier, vol. 10(C).
    2. Hampf, Benjamin, 2016. "Rational Inefficiency, Adjustment Costs and Sequential Technologies," VfS Annual Conference 2016 (Augsburg): Demographic Change 145796, Verein für Socialpolitik / German Economic Association.
    3. Petra Zýková, 2022. "The overall efficiency of the dynamic DEA models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 495-506, June.
    4. Cherchye, Laurens & De Rock, Bram & Kerstens, Pieter Jan, 2018. "Production with storable and durable inputs: Nonparametric analysis of intertemporal efficiency," European Journal of Operational Research, Elsevier, vol. 270(2), pages 498-513.
    5. Hirofumi Fukuyama & William L. Weber, 2017. "Japanese Bank Productivity, 2007–2012: A Dynamic Network Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 649-676, October.
    6. Calogero Guccio & Marco Martorana & Isidoro Mazza & Ilde Rizzo, 2021. "Back to the Future: Does the use of information and communication technology enhance the performance of public historical archives?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(1), pages 13-43, March.
    7. Magdalena Kapelko & Alfons Oude Lansink & Spiro E. Stefanou, 2017. "Input-Specific Dynamic Productivity Change: Measurement and Application to European Dairy Manufacturing Firms," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 579-599, June.
    8. Arnaud Abad & Paola Ravelojaona, 2017. "Exponential environmental productivity index and indicators," Post-Print hal-03025344, HAL.
    9. Silva, Elvira & Magalhães, Manuela, 2023. "Environmental efficiency, irreversibility and the shadow price of emissions," European Journal of Operational Research, Elsevier, vol. 306(2), pages 955-967.
    10. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.
    11. Li, Linda & Miller, David & Schmidt, Charles P., 2016. "Optimizing inventory׳s contribution to profitability in a regulated utility: The Averch–Johnson effect," International Journal of Production Economics, Elsevier, vol. 175(C), pages 132-141.
    12. Queiroz, Marcelo Victor Alves Bila & Sampaio, Raquel Menezes Bezerra & Sampaio, Luciano Menezes Bezerra, 2020. "Dynamic efficiency of primary education in Brazil: Socioeconomic and infrastructure influence on school performance," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    13. Fukuyama, Hirofumi & Matousek, Roman, 2018. "Nerlovian revenue inefficiency in a bank production context: Evidence from Shinkin banks," European Journal of Operational Research, Elsevier, vol. 271(1), pages 317-330.
    14. Kapelko, Magdalena, 2015. "Dynamic versus Static Inefficiency Assessment of the Polish Meat-Processing Industry in the Aftermath of the European Union Integration and Financial Crisis," 2015 Conference, August 9-14, 2015, Milan, Italy 211830, International Association of Agricultural Economists.
    15. F. Ang & K. H. Dakpo, 2021. "Comment: Performance measurement and joint production of intended and unintended outputs," Journal of Productivity Analysis, Springer, vol. 55(3), pages 185-188, June.
    16. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    17. Encarna Guillamon-Saorin & Magdalena Kapelko & Spiro E. Stefanou, 2018. "Corporate Social Responsibility and Operational Inefficiency: A Dynamic Approach," Sustainability, MDPI, vol. 10(7), pages 1-26, July.
    18. Antonio Peyrache & Maria C. A. Silva, 2019. "The Inefficiency of Production Systems and its decomposition," CEPA Working Papers Series WP052019, School of Economics, University of Queensland, Australia.
    19. Ioannis Skevas & Grigorios Emvalomatis & Bernhard Brümmer, 2018. "The effect of farm characteristics on the persistence of technical inefficiency: a case study in German dairy farming," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 45(1), pages 3-25.
    20. Laurens Cherchye & Bram De Rock & Antonio Estache & Marijn Verschelde, 2015. "Efficiency Measures in Regulated Industries: History, Outstanding Challenges and Emerging Solutions," Working Papers ECARES ECARES 2015-09, ULB -- Universite Libre de Bruxelles.
    21. Fukuyama, Hirofumi & Weber, William L. & Xia, Yin, 2016. "Time substitution and network effects with an application to nanobiotechnology policy for US universities," Omega, Elsevier, vol. 60(C), pages 34-44.
    22. Magdalena Kapelko & Alfons Oude Lansink, 2018. "Managerial and program inefficiency for European meat manufacturing firms: A dynamic multidirectional inefficiency analysis approach," Journal of Productivity Analysis, Springer, vol. 49(1), pages 25-36, February.
    23. Hampf, Benjamin, 2017. "Rational inefficiency, adjustment costs and sequential technologies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1095-1108.
    24. Magdalena Kapelko & Alfons Oude Lansink, 2020. "Dynamic Cost Inefficiency of the European Union Meat Processing Firms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 760-777, September.
    25. Del Barrio-Tellado, María José & Gómez-Vega, Mafalda & Gómez-Zapata, Jonathan Daniel & Herrero-Prieto, Luis César, 2021. "Urban public libraries: Performance analysis using dynamic-network-DEA," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    26. S. Ghobadi & G. R. Jahanshahloo & F. Hosseinzadeh Lotfi & M. Rostamy-Malkhalifeh, 2018. "Efficiency Measure Under Inter-Temporal Dependence," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 657-675, March.

  14. Lee, Chia-Yen & Johnson, Andrew L., 2014. "Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments," European Journal of Operational Research, Elsevier, vol. 232(3), pages 537-548.

    Cited by:

    1. Ke Wang & Chia-Yen Lee & Jieming Zhang & Yi-Ming Wei, 2016. "Operational performance management of the power industry: A distinguishing analysis between effectiveness and efficiency," CEEP-BIT Working Papers 93, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    2. Lee, Chia-Yen & Charles, Vincent, 2022. "A robust capacity expansion integrating the perspectives of marginal productivity and capacity regret," European Journal of Operational Research, Elsevier, vol. 296(2), pages 557-569.
    3. 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.
    4. Liangpeng Wu & Qingyuan Zhu, 2021. "Impacts of the carbon emission trading system on China’s carbon emission peak: a new data-driven approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2487-2515, July.
    5. Chia -Yen Lee & Andrew L. Johnson, 2015. "Measuring Efficiency in Imperfectly Competitive Markets: An Example of Rational Inefficiency," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 702-722, February.
    6. 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.
    7. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    8. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    9. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    10. Ke Wang & Jieming Zhang & Yi-Ming Wei, 2017. "Operational and environmental performance in China¡¯s thermal power industry: Taking an effectiveness measure as complement to an efficiency measure," CEEP-BIT Working Papers 100, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    11. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
    12. 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.
    13. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    14. Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    15. Yu, Ming-Miin & Chen, Li-Hsueh & Chiang, Hui, 2017. "The effects of alliances and size on airlines’ dynamic operational performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 197-214.

  15. 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.

    Cited by:

    1. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    2. Eder, Andreas, 2017. "Cost efficiency and economies of diversification of biogas-fuelled cogeneration plants in Austria: a nonparametric approach," MPRA Paper 80369, University Library of Munich, Germany.
    3. Eder, Andreas, 2018. "Measuring and decomposing economies of diversification: An application to biogas-fuelled cogeneration plants in Austria," International Journal of Production Economics, Elsevier, vol. 204(C), pages 421-432.
    4. Frederic Ang & Simon M. Mortimer & Francisco J. Areal & Richard Tiffin, 2018. "On the Opportunity Cost of Crop Diversification," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 794-814, September.

  16. Soondo Hong & Andrew Johnson & Brett Peters, 2013. "A note on picker blocking models in a parallel-aisle order picking system," IISE Transactions, Taylor & Francis Journals, vol. 45(12), pages 1345-1355.

    Cited by:

    1. Mowrey, Corinne H. & Parikh, Pratik J., 2014. "Mixed-width aisle configurations for order picking in distribution centers," European Journal of Operational Research, Elsevier, vol. 232(1), pages 87-97.
    2. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2015. "Quantifying picker blocking in a bucket brigade order picking system," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 862-873.
    3. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2018. "The influence of e-commerce on the design of warehouses - a literature review," Working Papers 2018013, University of Antwerp, Faculty of Business and Economics.
    4. Hong, Soondo, 2014. "Two-worker blocking congestion model with walk speed m in a no-passing circular passage system," European Journal of Operational Research, Elsevier, vol. 235(3), pages 687-696.

  17. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.

    Cited by:

    1. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    2. 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.
    3. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2017. "Specification of merger gains in the Norwegian electricity distribution industry," Energy Policy, Elsevier, vol. 102(C), pages 96-107.
    4. José Luis Preciado Arreola & Daisuke Yagi & Andrew L. Johnson, 2020. "Insights from machine learning for evaluating production function estimators on manufacturing survey data," Journal of Productivity Analysis, Springer, vol. 53(2), pages 181-225, April.
    5. Pang Du & Christopher F. Parmeter & Jeffrey S. Racine, 2012. "Nonparametric Kernel Regression with Multiple Predictors and Multiple Shape Constraints," Department of Economics Working Papers 2012-08, McMaster University.
    6. K. Hervé Dakpo & Yann Desjeux & Laure Latruffe, 2023. "Cost of abating excess nitrogen on wheat plots in France: An assessment with multi‐technology modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 800-815, September.
    7. Wang, Yongqiao & Wang, Shouyang & Dang, Chuangyin & Ge, Wenxiu, 2014. "Nonparametric quantile frontier estimation under shape restriction," European Journal of Operational Research, Elsevier, vol. 232(3), pages 671-678.
    8. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    9. Hishinuma, Kazuhiro & Iiduka, Hideaki, 2020. "Fixed point quasiconvex subgradient method," European Journal of Operational Research, Elsevier, vol. 282(2), pages 428-437.
    10. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
    11. Seifert, Stefan, 2015. "Productivity Growth and its Sources - A StoNED Metafrontier Analyis of the German Electricity Generating Sector," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112975, Verein für Socialpolitik / German Economic Association.
    12. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    13. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    14. Tsionas, Mike G., 2023. "Performance estimation when the distribution of inefficiency is unknown," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1212-1222.
    15. Stefan Seifert, 2015. "Measuring Productivity When Technologies Are Heterogeneous: A Semi-Parametric Approach for Electricity Generation," Discussion Papers of DIW Berlin 1526, DIW Berlin, German Institute for Economic Research.
    16. 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.
    17. Tsionas, Mike G. & Izzeldin, Marwan, 2018. "Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares," European Journal of Operational Research, Elsevier, vol. 271(3), pages 797-807.
    18. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
    19. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    20. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    21. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    22. Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    23. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
    24. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    25. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2016. "Specification of merger gains in the Norwegian electricity distribution industry," Discussion Papers 2016/7, Norwegian School of Economics, Department of Business and Management Science.
    26. Keshvari, Abolfazl, 2017. "A penalized method for multivariate concave least squares with application to productivity analysis," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1016-1029.

  18. Lee, Chia-Yen & Johnson, Andrew L., 2012. "Two-dimensional efficiency decomposition to measure the demand effect in productivity analysis," European Journal of Operational Research, Elsevier, vol. 216(3), pages 584-593.

    Cited by:

    1. Charles-Henri Dimaria & Chiara Peroni, 2012. "Unit labor cost and productivity recovery under non neutral technical change," Working Papers halshs-00826351, HAL.
    2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    3. Meryem Duygun & Diego Prior & Mohamed Shaban & Emili Tortosa-Ausina, 2015. "Disentangling the European Airlines efficiency puzzle:A network data envelopment analysis approach," Working Papers 2015/04, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    5. Charles-Henri DI MARIA & Chiara PERONI, 2012. "A new unit labour cost changes decomposition Four pillars of cost competitiveness recovery," LEO Working Papers / DR LEO 179, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    6. Liu, Dan & Zhang, Jiahuang & Yu, Ming-Miin, 2023. "Decomposing airline profit inefficiency in NDEA through the non-competitive Nerlovian profit inefficiency model," Journal of Air Transport Management, Elsevier, vol. 107(C).
    7. Reza Feizabadi & Mehri Bagherian, 2023. "Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming," SN Operations Research Forum, Springer, vol. 4(4), pages 1-14, December.
    8. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    9. Lee, Chia-Yen & Johnson, Andrew L., 2014. "Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments," European Journal of Operational Research, Elsevier, vol. 232(3), pages 537-548.
    10. Ang, Sheng & Chen, Chien-Ming, 2016. "Pitfalls of decomposition weights in the additive multi-stage DEA model," Omega, Elsevier, vol. 58(C), pages 139-153.
    11. Tavassoli, Mohammad & Faramarzi, Gholam Reza & Farzipoor Saen, Reza, 2014. "Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 146-153.
    12. Appelbaum, Elie & Berechman, Joseph, 1991. "Demand conditions, regulation, and the measurement of productivity," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 379-400, February.
    13. Georges Assaf, A. & Gillen, David, 2012. "Measuring the joint impact of governance form and economic regulation on airport efficiency," European Journal of Operational Research, Elsevier, vol. 220(1), pages 187-198.
    14. 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.
    15. Charles-Henri DI MARIA, 2012. "Cannon was right but Incomplete: Frankel was a Neglected Early Contribution to Growth Theory," LEO Working Papers / DR LEO 291, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    16. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    17. Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    18. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    19. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    20. Zhao, Yu & Morita, Hiroshi & Maruyama, Yukihiro, 2019. "The measurement of productive performance with consideration for allocative efficiency," Omega, Elsevier, vol. 89(C), pages 21-39.
    21. Heshmati, Almas & C. Kumbhakar, Subal & Kim, Jungsuk, 2016. "Persistent and Transient Efficiency of International Airlines," Working Paper Series in Economics and Institutions of Innovation 444, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.

  19. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2012. "Batch picking in narrow-aisle order picking systems with consideration for picker blocking," European Journal of Operational Research, Elsevier, vol. 221(3), pages 557-570.

    Cited by:

    1. Matusiak, Marek & de Koster, René & Kroon, Leo & Saarinen, Jari, 2014. "A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse," European Journal of Operational Research, Elsevier, vol. 236(3), pages 968-977.
    2. Arbex Valle, Cristiano & Beasley, John E, 2020. "Order batching using an approximation for the distance travelled by pickers," European Journal of Operational Research, Elsevier, vol. 284(2), pages 460-484.
    3. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    4. Sören Koch & Gerhard Wäscher, 2016. "A grouping genetic algorithm for the Order Batching Problem in distribution warehouses," Journal of Business Economics, Springer, vol. 86(1), pages 131-153, January.
    5. Mowrey, Corinne H. & Parikh, Pratik J., 2014. "Mixed-width aisle configurations for order picking in distribution centers," European Journal of Operational Research, Elsevier, vol. 232(1), pages 87-97.
    6. Fangyu Chen & Gangyan Xu & Yongchang Wei, 2019. "An Integrated Metaheuristic Routing Method for Multiple-Block Warehouses with Ultranarrow Aisles and Access Restriction," Complexity, Hindawi, vol. 2019, pages 1-14, June.
    7. Žulj, Ivan & Salewski, Hagen & Goeke, Dominik & Schneider, Michael, 2022. "Order batching and batch sequencing in an AMR-assisted picker-to-parts system," European Journal of Operational Research, Elsevier, vol. 298(1), pages 182-201.
    8. De Santis, Roberta & Montanari, Roberto & Vignali, Giuseppe & Bottani, Eleonora, 2018. "An adapted ant colony optimization algorithm for the minimization of the travel distance of pickers in manual warehouses," European Journal of Operational Research, Elsevier, vol. 267(1), pages 120-137.
    9. David Füßler & Stefan Fedtke & Nils Boysen, 2019. "The cafeteria problem: order sequencing and picker routing in on-the-line picking systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 727-756, September.
    10. Matusiak, M. & de Koster, M.B.M. & Saarinen, J., 2015. "Data-driven warehouse optimization," ERIM Report Series Research in Management ERS-2015-008-LIS, 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.
    11. Žulj, Ivan & Kramer, Sergej & Schneider, Michael, 2018. "A hybrid of adaptive large neighborhood search and tabu search for the order-batching problem," European Journal of Operational Research, Elsevier, vol. 264(2), pages 653-664.
    12. Boysen, Nils & de Koster, René & Füßler, David, 2021. "The forgotten sons: Warehousing systems for brick-and-mortar retail chains," European Journal of Operational Research, Elsevier, vol. 288(2), pages 361-381.
    13. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris & de Koster, René B.M., 2019. "Designing efficient order picking systems: The effect of real-life features on the relationship among planning problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 47-73.
    14. Polten, Lukas & Emde, Simon, 2021. "Scheduling automated guided vehicles in very narrow aisle warehouses," Omega, Elsevier, vol. 99(C).
    15. Maximilian Löffler & Michael Schneider & Ivan Žulj, 2023. "Cost-neutral reduction of infection risk in picker-to-parts warehousing systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 151-179, March.
    16. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2015. "Quantifying picker blocking in a bucket brigade order picking system," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 862-873.
    17. Glock, Christoph H. & Grosse, Eric H. & Abedinnia, Hamid & Emde, Simon, 2019. "An integrated model to improve ergonomic and economic performance in order picking by rotating pallets," European Journal of Operational Research, Elsevier, vol. 273(2), pages 516-534.
    18. Valle, Cristiano Arbex & Beasley, John E. & da Cunha, Alexandre Salles, 2017. "Optimally solving the joint order batching and picker routing problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 817-834.
    19. Maximilian Löffler & Nils Boysen & Michael Schneider, 2022. "Picker Routing in AGV-Assisted Order Picking Systems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 440-462, January.
    20. Claeys, Dieter & Adan, Ivo & Boxma, Onno, 2016. "Stochastic bounds for order flow times in parts-to-picker warehouses with remotely located order-picking workstations," European Journal of Operational Research, Elsevier, vol. 254(3), pages 895-906.
    21. Scholz, André & Henn, Sebastian & Stuhlmann, Meike & Wäscher, Gerhard, 2016. "A new mathematical programming formulation for the Single-Picker Routing Problem," European Journal of Operational Research, Elsevier, vol. 253(1), pages 68-84.
    22. AERTS, Babiche & CORNELISSENS, Trijntje & SÖRENSEN, Kenneth, 2018. "The influence of e-commerce on the design of warehouses - a literature review," Working Papers 2018013, University of Antwerp, Faculty of Business and Economics.
    23. André Scholz & Daniel Schubert & Gerhard Wäscher, 2016. "Order picking with multiple pickers and due dates – Simultaneous solution of order batching, batch assignment and sequencing, and picker routing problems," FEMM Working Papers 160005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    24. Matusiak, Marek & de Koster, René & Saarinen, Jari, 2017. "Utilizing individual picker skills to improve order batching in a warehouse," European Journal of Operational Research, Elsevier, vol. 263(3), pages 888-899.
    25. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    26. Hong, Soondo & Kim, Youngjoo, 2017. "A route-selecting order batching model with the S-shape routes in a parallel-aisle order picking system," European Journal of Operational Research, Elsevier, vol. 257(1), pages 185-196.
    27. Fangyu Chen & Hongwei Wang & Yong Xie & Chao Qi, 2016. "An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 389-408, April.
    28. Weidinger, Felix & Boysen, Nils & Schneider, Michael, 2019. "Picker routing in the mixed-shelves warehouses of e-commerce retailers," European Journal of Operational Research, Elsevier, vol. 274(2), pages 501-515.
    29. Vidal Vieira, José Geraldo & Ramos Toso, Milton & da Silva, João Eduardo Azevedo Ramos & Cabral Ribeiro, Priscilla Cristina, 2017. "An AHP-based framework for logistics operations in distribution centres," International Journal of Production Economics, Elsevier, vol. 187(C), pages 246-259.
    30. Sebastian Henn & André Scholz & Meike Stuhlmann & Gerhard Wäscher, 2015. "A New Mathematical Programming Formulation for the Single-Picker Routing Problem in a Single-Block Layout," FEMM Working Papers 150005, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.

  20. Soondo Hong & Andrew Johnson & Brett Peters, 2012. "Large-scale order batching in parallel-aisle picking systems," IISE Transactions, Taylor & Francis Journals, vol. 44(2), pages 88-106.

    Cited by:

    1. Pan, Jason Chao-Hsien & Shih, Po-Hsun & Wu, Ming-Hung, 2015. "Order batching in a pick-and-pass warehousing system with group genetic algorithm," Omega, Elsevier, vol. 57(PB), pages 238-248.
    2. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    3. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    4. Matusiak, Marek & de Koster, René & Kroon, Leo & Saarinen, Jari, 2014. "A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse," European Journal of Operational Research, Elsevier, vol. 236(3), pages 968-977.
    5. Arbex Valle, Cristiano & Beasley, John E, 2020. "Order batching using an approximation for the distance travelled by pickers," European Journal of Operational Research, Elsevier, vol. 284(2), pages 460-484.
    6. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    7. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2012. "Batch picking in narrow-aisle order picking systems with consideration for picker blocking," European Journal of Operational Research, Elsevier, vol. 221(3), pages 557-570.
    8. Mowrey, Corinne H. & Parikh, Pratik J., 2014. "Mixed-width aisle configurations for order picking in distribution centers," European Journal of Operational Research, Elsevier, vol. 232(1), pages 87-97.
    9. Heiko Diefenbach & Simon Emde & Christoph H. Glock & Eric H. Grosse, 2022. "New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 535-573, June.
    10. Hong, Soondo & Johnson, Andrew L. & Peters, Brett A., 2015. "Quantifying picker blocking in a bucket brigade order picking system," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 862-873.
    11. Valle, Cristiano Arbex & Beasley, John E. & da Cunha, Alexandre Salles, 2017. "Optimally solving the joint order batching and picker routing problem," European Journal of Operational Research, Elsevier, vol. 262(3), pages 817-834.
    12. Ardjmand, Ehsan & Shakeri, Heman & Singh, Manjeet & Sanei Bajgiran, Omid, 2018. "Minimizing order picking makespan with multiple pickers in a wave picking warehouse," International Journal of Production Economics, Elsevier, vol. 206(C), pages 169-183.
    13. Hong, Soondo, 2014. "Two-worker blocking congestion model with walk speed m in a no-passing circular passage system," European Journal of Operational Research, Elsevier, vol. 235(3), pages 687-696.
    14. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    15. Hong, Soondo & Kim, Youngjoo, 2017. "A route-selecting order batching model with the S-shape routes in a parallel-aisle order picking system," European Journal of Operational Research, Elsevier, vol. 257(1), pages 185-196.

  21. Mekaroonreung, Maethee & Johnson, Andrew L., 2012. "Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach," Energy Economics, Elsevier, vol. 34(3), pages 723-732.

    Cited by:

    1. Keshvari, Abolfazl & Kuosmanen, Timo, 2013. "Stochastic non-convex envelopment of data: Applying isotonic regression to frontier estimation," European Journal of Operational Research, Elsevier, vol. 231(2), pages 481-491.
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Yan, Ming-Zhe & Wang, Jian-Lin & Xie, Bai-Chen, 2019. "Which provincial administrative regions in China should reduce their coal consumption? An environmental energy input requirement function based analysis," Energy Policy, Elsevier, vol. 127(C), pages 51-63.
    4. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    5. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    6. Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
    7. Elisa Fusco & Bernardo Maggi, 2022. "Computing nonperforming loan prices in banking efficiency analysis," Computational Management Science, Springer, vol. 19(1), pages 1-23, January.
    8. 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.
    9. Benjamin Hampf & Kenneth Løvold Rødseth, 2017. "Optimal profits under environmental regulation: the benefits from emission intensity averaging," Annals of Operations Research, Springer, vol. 255(1), pages 367-390, August.
    10. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    11. Ling-Yun He & Jia-Jia Ou, 2017. "Pollution Emissions, Environmental Policy, and Marginal Abatement Costs," IJERPH, MDPI, vol. 14(12), pages 1-16, December.
    12. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal Profits under Environmental Regulation: The Benefits from Emission Intensity Averaging," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 68011, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    14. Zeng, Shihong & Jiang, Xue & Su, Bin & Nan, Xin, 2018. "China's SO2 shadow prices and environmental technical efficiency at the province level," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 86-102.
    15. Lee, Chia-Yen & Zhou, Peng, 2015. "Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990–2010," Energy Economics, Elsevier, vol. 51(C), pages 493-502.
    16. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    17. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    18. Karanfil, Fatih & Pierru, Axel, 2021. "The opportunity cost of domestic oil consumption for an oil exporter: Illustration for Saudi Arabia," Energy Economics, Elsevier, vol. 96(C).
    19. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.
    20. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    21. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Environmental assessment on coal-fired power plants in U.S. north-east region by DEA non-radial measurement," Energy Economics, Elsevier, vol. 50(C), pages 125-139.
    22. Bei Gao & Zuoren Sun, 2023. "Marginal CO 2 and SO 2 Abatement Costs and Determinants of Coal-Fired Power Plants in China: Considering a Two-Stage Production System with Different Emission Reduction Approaches," Energies, MDPI, vol. 16(8), pages 1-26, April.
    23. Shen, Xiaobo & Lin, Boqiang, 2017. "The shadow prices and demand elasticities of agricultural water in China: A StoNED-based analysis," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 21-28.
    24. Hampf, Benjamin, 2018. "Cost and environmental efficiency of U.S. electricity generation: Accounting for heterogeneous inputs and transportation costs," Energy, Elsevier, vol. 163(C), pages 932-941.
    25. Alexander Arévalo S & Víctor Giménez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91, October.
    26. Prasad, Sanjeev K. & Mangaraj, B.K., 2022. "A multi-objective competitive-design framework for fuel procurement planning in coal-fired power plants for sustainable operations," Energy Economics, Elsevier, vol. 108(C).
    27. Podinovski, Victor V., 2019. "Direct estimation of marginal characteristics of nonparametric production frontiers in the presence of undesirable outputs," European Journal of Operational Research, Elsevier, vol. 279(1), pages 258-276.
    28. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Carbon dioxide emission standards for US power plants: An efficiency analysis perspective," Darmstadt Discussion Papers in Economics 219, Darmstadt University of Technology, Department of Law and Economics.
    29. Liang Chun Lu & Yung-ho Chiu & Shih-Yung Chiu & Tzu-Han Chang, 2022. "Do Forests help environmental development of Cities in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6602-6629, May.
    30. Kenneth Løvold Rødseth, 2017. "Axioms of a Polluting Technology: A Materials Balance Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(1), pages 1-22, May.
    31. Chung, William & Yeung, Iris M.H., 2017. "Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings," Applied Energy, Elsevier, vol. 203(C), pages 454-462.
    32. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal profits under environmental regulation: The benefits from emission intensity averaging," Darmstadt Discussion Papers in Economics 220, Darmstadt University of Technology, Department of Law and Economics.
    33. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    34. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    35. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
    36. Lee, Sang-choon & Oh, Dong-hyun & Lee, Jeong-dong, 2014. "A new approach to measuring shadow price: Reconciling engineering and economic perspectives," Energy Economics, Elsevier, vol. 46(C), pages 66-77.
    37. Irz, Xavier & Leroy, Pascal & Réquillart, Vincent & Soler, Louis-Georges, 2016. "Welfare and sustainability effects of dietary recommendations," Ecological Economics, Elsevier, vol. 130(C), pages 139-155.
    38. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2015. "Carbon dioxide emission standards for U.S. power plants: An efficiency analysis perspective," Energy Economics, Elsevier, vol. 50(C), pages 140-153.
    39. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.
    40. Tamaki, Tetsuya & Shin, Kong Joo & Nakamura, Hiroki & Fujii, Hidemichi & Managi, Shunsuke, 2018. "Shadow prices and production inefficiency of mineral resources," Economic Analysis and Policy, Elsevier, vol. 57(C), pages 111-121.
    41. Xiaoliang Guan & Junbiao Zhang & Xianrong Wu & Linlin Cheng, 2018. "The Shadow Prices of Carbon Emissions in China’s Planting Industry," Sustainability, MDPI, vol. 10(3), pages 1-12, March.
    42. Kenneth Rødseth & Eirik Romstad, 2014. "Environmental Regulations, Producer Responses, and Secondary Benefits: Carbon Dioxide Reductions Under the Acid Rain Program," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 111-135, September.
    43. Dimitris Bertsimas & Nishanth Mundru, 2021. "Sparse Convex Regression," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 262-279, January.
    44. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    45. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
    46. Jorge Bonilla & Jessica Coria & Thomas Sterner, 2018. "Technical Synergies and Trade-Offs Between Abatement of Global and Local Air Pollution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(1), pages 191-221, May.
    47. Zhou, P. & Zhou, X. & Fan, L.W., 2014. "On estimating shadow prices of undesirable outputs with efficiency models: A literature review," Applied Energy, Elsevier, vol. 130(C), pages 799-806.
    48. Kenneth Løvold Rødseth, 2017. "Environmental regulations and allocative efficiency: application to coal-to-gas substitution in the U.S. electricity sector," Journal of Productivity Analysis, Springer, vol. 47(2), pages 129-142, April.
    49. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
    50. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    51. Hampf, Benjamin, 2015. "Estimating the materials balance condition: A stochastic frontier approach," Darmstadt Discussion Papers in Economics 226, Darmstadt University of Technology, Department of Law and Economics.
    52. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    53. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.

  22. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.

    Cited by:

    1. Gong, Yeming & Liu, Jiawen & Zhu, Joe, 2019. "When to increase firms’ sustainable operations for efficiency? A data envelopment analysis in the retailing industry," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1010-1026.
    2. Anastasiou Athanasios & Kalligosfyris Charalampos & Kalamara Eleni, 2022. "Assessing the effectiveness of tax administration in macroeconomic stability: evidence from 26 European Countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2237-2261, November.
    3. Banker, Rajiv & Natarajan, Ram & Zhang, Daqun, 2019. "Two-stage estimation of the impact of contextual variables in stochastic frontier production function models using Data Envelopment Analysis: Second stage OLS versus bootstrap approaches," European Journal of Operational Research, Elsevier, vol. 278(2), pages 368-384.
    4. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
    5. Jamasb, Tooraj & Llorca, Manuel & Khetrapal, Pavan & Thakur, Tripta, 2021. "Institutions and performance of regulated firms: Evidence from electricity distribution in India," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 68-82.
    6. Irene Wei Kiong Ting & Imen Tebourbi & Wen-Min Lu & Qian Long Kweh, 2021. "The effects of managerial ability on firm performance and the mediating role of capital structure: evidence from Taiwan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    7. Chien-Ming Chen & Magali A. Delmas & Marvin B. Lieberman, 2015. "Production frontier methodologies and efficiency as a performance measure in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 36(1), pages 19-36, January.
    8. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    9. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    10. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.
    11. Vijesh Krishna & Prakashan Veettil, 2015. "Productivity and Efficiency Impacts of Zero Tillage Wheat in Northwest Indo-Gangetic Plains," Working Papers id:7716, eSocialSciences.
    12. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    13. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    14. Tsolas, Ioannis E., 2014. "Precious metal mutual fund performance appraisal using DEA modeling," Resources Policy, Elsevier, vol. 39(C), pages 54-60.
    15. Mutz, Rüdiger & Bornmann, Lutz & Daniel, Hans-Dieter, 2017. "Are there any frontiers of research performance? Efficiency measurement of funded research projects with the Bayesian stochastic frontier analysis for count data," Journal of Informetrics, Elsevier, vol. 11(3), pages 613-628.
    16. Orea, Luis & Jamasb, Tooraj, 2014. "Identifying efficient regulated firms with unobserved technological heterogeneity: A nested latent class approach to Norwegian electricity distribution networks," Efficiency Series Papers 2014/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    17. Wanke, Peter & Azad, Abul Kalam & Emrouznejad, Ali, 2018. "Efficiency in BRICS banking under data vagueness: A two-stage fuzzy approach," Global Finance Journal, Elsevier, vol. 35(C), pages 58-71.
    18. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    19. Mariarosaria Agostino & Sabrina Ruberto & Francesco Trivieri, 2018. "Lasting lending relationships and technical efficiency. Evidence on European SMEs," Journal of Productivity Analysis, Springer, vol. 50(1), pages 25-40, October.
    20. Thiago Christiano Silva & Solange Maria Guerra & Marcus Vinicius B. Santos, 2022. "The role of externalities in fiscal efficiency," Empirical Economics, Springer, vol. 62(6), pages 2827-2864, June.
    21. Saastamoinen, Antti & Kuosmanen, Timo, 2016. "Quality frontier of electricity distribution: Supply security, best practices, and underground cabling in Finland," Energy Economics, Elsevier, vol. 53(C), pages 281-292.
    22. Wei-han Liu & Qian Long Kweh, 2022. "Reexamining nonlinear effects of intellectual capital on firm efficiency," Annals of Operations Research, Springer, vol. 315(2), pages 1319-1344, August.
    23. Rødseth, Kenneth Løvold, 2023. "Shadow pricing of electricity generation using stochastic and deterministic materials balance models," Applied Energy, Elsevier, vol. 341(C).
    24. Eugénia de Matos Pedro & João Leitão & Helena Alves, 2021. "HEI Efficiency and Quality of Life: Seeding the Pro-Sustainability Efficiency," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
    25. Tsionas, Mike G., 2023. "Performance estimation when the distribution of inefficiency is unknown," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1212-1222.
    26. Agostino, Mariarosaria & Nifo, Annamaria & Trivieri, Francesco & Vecchione, Gaetano, 2016. "Total factor productivity heterogeneity: channelling the impact of institutions," MPRA Paper 72759, University Library of Munich, Germany.
    27. Ayodotun Stephen Ibidunni & Uchechukwu Emena Okorie & Busola Kehinde & Obindah Gershon & Joachim Abolaji Abiodun, 2023. "Productivity in Sub-Saharan Africa’s Agricultural Sector: An Application of Data Envelopment Analysis and Regression Analysis," SN Operations Research Forum, Springer, vol. 4(2), pages 1-29, June.
    28. Martin Ardanaz & Stanislao Maldonado, 2016. "Natural Resource Windfalls and Efficiency of Local Government Expenditures: Evidence from Peru," Documentos de Trabajo 14578, Universidad del Rosario.
    29. Amer Ait Sidhoum, 2023. "Assessing the contribution of farmers’ working conditions to productive efficiency in the presence of uncertainty, a nonparametric approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8601-8622, August.
    30. George Halkos & Nickolaos Tzeremes, 2013. "National culture and eco-efficiency: an application of conditional partial nonparametric frontiers," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 15(4), pages 423-441, October.
    31. Cambini, Carlo & Croce, Annalisa & Fumagalli, Elena, 2014. "Output-based incentive regulation in electricity distribution: Evidence from Italy," Energy Economics, Elsevier, vol. 45(C), pages 205-216.
    32. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    33. Kao, Ta-Wei (Daniel) & Simpson, N.C. & Shao, Benjamin B.M. & Lin, Winston T., 2017. "Relating supply network structure to productive efficiency: A multi-stage empirical investigation," European Journal of Operational Research, Elsevier, vol. 259(2), pages 469-485.
    34. Chongfeng Ren & Ruihuan Li & Ping Guo, 2016. "Two-Stage DEA Analysis of Water Resource Use Efficiency," Sustainability, MDPI, vol. 9(1), pages 1-17, December.
    35. Sueyoshi, Toshiyuki & Ryu, Youngbok, 2022. "Performance assessment on technology transition from small businesses to the U.S. Department of Defense," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    36. Kenneth Løvold Rødseth & Rasmus Bøgh Holmen & Timo Kuosmanen & Halvor Schøyen, 2023. "Market access and seaport efficiency: the case of container handling in Norway," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-25, December.
    37. Luis Orea & Tooraj Jamasb, 2017. "Regulating Heterogeneous Utilities: A New Latent Class Approach with Application to the Norwegian Electricity Distribution Networks," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    38. da Silva e Souza, Geraldo & Gomes, Eliane Gonçalves, 2015. "Management of agricultural research centers in Brazil: A DEA application using a dynamic GMM approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 819-824.
    39. Orea, Luis & Wall, Alan, 2015. "A parametric frontier model for measuring eco-efficiency," Efficiency Series Papers 2015/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    40. Liu, Jiawen & Gong, Yeming (Yale) & Zhu, Joe & Zhang, Jinlong, 2018. "A DEA-based approach for competitive environment analysis in global operations strategies," International Journal of Production Economics, Elsevier, vol. 203(C), pages 110-123.
    41. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
    42. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
    43. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
    44. Ana M. Reyna & Hugo J. Fuentes & José A. Núñez, 2022. "Response of Mexican life and non-life insurers to the low interest rate environment," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 409-433, April.
    45. Ayoola Tajudeen John & Obokoh Lawrence Ogechukwu, 2018. "Corporate Governance and Financial Distress in the Banking Industry: Nigerian Experience," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 182-193.
    46. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    47. Alessandro Fiorini, 2016. "Technical efficiency in a technological innovation system perspective: The case of bioenergy technologies R&D resources mobilisation in a sample from EU-28," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2016(2), pages 107-127.
    48. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.
    49. Molinos-Senante, Maria & Maziotis, Alexandros, 2022. "Evaluation of energy efficiency of wastewater treatment plants: The influence of the technology and aging factors," Applied Energy, Elsevier, vol. 310(C).
    50. Panayiotis Tzeremes, 2020. "Productivity, efficiency and firm’s market value: Microeconomic evidence from multinational corporations," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 95-105.
    51. Kosycarz, Ewa & Dędys, Monika & Ekes, Maria & Wranik, Wiesława Dominika, 2023. "The effects of provider contract types and fiscal decentralization on the efficiency of the Polish hospital sector: A data envelopment analysis across 16 health regions," Health Policy, Elsevier, vol. 129(C).
    52. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    53. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    54. Timo Kuosmanen & Yong Tan & Sheng Dai, 2023. "Performance analysis of English hospitals during the first and second waves of the coronavirus pandemic," Health Care Management Science, Springer, vol. 26(3), pages 447-460, September.

  23. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.

    Cited by:

    1. Toloo, Mehdi & Babaee, Seddigheh, 2015. "On variable reductions in data envelopment analysis with an illustrative application to a gas company," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 527-533.
    2. Pavala Malar Kannan & Govindan Marthandan & Rathimala Kannan, 2021. "Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method," Energies, MDPI, vol. 14(12), pages 1-21, June.
    3. Maria Elisabete Neves & Carla Henriques & João Vilas, 2021. "Financial performance assessment of electricity companies: evidence from Portugal," Operational Research, Springer, vol. 21(4), pages 2809-2857, December.
    4. Camelia BURJA & Vasile BURJA, 2013. "Dimensions Of Sustainable Development In Romania - A Data Envelopment Analysis," Romanian Journal of Economics, Institute of National Economy, vol. 37(2(46)), pages 153-163, December.
    5. Patricija Bajec & Danijela Tuljak-Suban, 2019. "An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    6. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    7. Muchen Luo & Yimin Wu, 2022. "Data-Driven Evaluation and Optimisation of Livelihood Improvement Efficiency," Sustainability, MDPI, vol. 14(13), pages 1-24, July.
    8. Charles Henri DiMaria & Chiara Peroni & Francesco Sarracino, 2020. "Happiness Matters: Productivity Gains from Subjective Well-Being," Journal of Happiness Studies, Springer, vol. 21(1), pages 139-160, January.
    9. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    10. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2015. "Testing the accuracy of DEA estimates under endogeneity through a Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 244(2), pages 511-518.
    11. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.
    12. Imad Bou-Hamad & Abdel Latef Anouze & Ibrahim H. Osman, 2022. "A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information," Annals of Operations Research, Springer, vol. 308(1), pages 63-92, January.
    13. lo Storto, Corrado, 2020. "Performance evaluation of social service provision in Italian major municipalities using Network Data Envelopment Analysis," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    14. Santos, Sérgio P. & Amado, Carla A.F., 2014. "On the need for reform of the Portuguese judicial system – Does Data Envelopment Analysis assessment support it?," Omega, Elsevier, vol. 47(C), pages 1-16.
    15. Adler, Nicole & Liebert, Vanessa & Yazhemsky, Ekaterina, 2013. "Benchmarking airports from a managerial perspective," Omega, Elsevier, vol. 41(2), pages 442-458.
    16. Viera Mendelová, 2022. "Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis," Journal of Productivity Analysis, Springer, vol. 57(1), pages 1-22, February.
    17. Piran, Fabio Antonio Sartori & Lacerda, Daniel Pacheco & Camargo, Luis Felipe Riehs & Viero, Carlos Frederico & Dresch, Aline & Cauchick-Miguel, Paulo Augusto, 2016. "Product modularization and effects on efficiency: An analysis of a bus manufacturer using data envelopment analysis (DEA)," International Journal of Production Economics, Elsevier, vol. 182(C), pages 1-13.
    18. He Jiang, 2022. "A novel robust structural quadratic forecasting model and applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1156-1180, September.
    19. Bojiang Yang & Youliang Zhang & Hongjun Zhang & Rui Zhang & Baoyu Xu, 2016. "Factor-specific Malmquist productivity index based on common weights DEA," Operational Research, Springer, vol. 16(1), pages 51-70, April.
    20. Aydın, Umut & Karadayi, Melis Almula & Ülengin, Füsun, 2020. "How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis," Journal of Air Transport Management, Elsevier, vol. 82(C).
    21. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.
    22. Jahangoshai Rezaee, Mustafa & Moini, Alireza & Makui, Ahmad, 2012. "Operational and non-operational performance evaluation of thermal power plants in Iran: A game theory approach," Energy, Elsevier, vol. 38(1), pages 96-103.
    23. Veiga, Gabriela Lobo & Pinheiro de Lima, Edson & Frega, José Roberto & Gouvea da Costa, Sérgio Eduardo, 2021. "A DEA-based approach to assess manufacturing performance through operations strategy lenses," International Journal of Production Economics, Elsevier, vol. 235(C).
    24. Toloo, Mehdi & Keshavarz, Esmaeil & Hatami-Marbini, Adel, 2021. "Selecting data envelopment analysis models: A data-driven application to EU countries," Omega, Elsevier, vol. 101(C).
    25. DiMaria, Charles Henri & Peroni, Chiara & Sarracino, Francesco, 2014. "Happiness matters: the role of well-being in productivity," MPRA Paper 56983, University Library of Munich, Germany.
    26. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    27. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    28. Jamal Ouenniche & Skarleth Carrales, 2018. "Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback," Annals of Operations Research, Springer, vol. 266(1), pages 551-587, July.
    29. François Charles Wolff, 2014. "Lift ticket prices and quality in French ski resorts: Insights from a non-parametric analysis," Working Papers hal-00957842, HAL.
    30. Hainan Guo & Yang Zhao & Tie Niu & Kwok-Leung Tsui, 2017. "Hong Kong Hospital Authority resource efficiency evaluation: Via a novel DEA-Malmquist model and Tobit regression model," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-24, September.
    31. Benítez-Peña, Sandra & Bogetoft, Peter & Romero Morales, Dolores, 2020. "Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach," Omega, Elsevier, vol. 96(C).
    32. Kaya, Gizem & Aydın, Umut & Karadayı, Melis Almula & Ülengin, Füsun & Ülengin, Burç & İçken, Ayhan, 2022. "Integrated methodology for evaluating the efficiency of airports: A case study in Turkey," Transport Policy, Elsevier, vol. 127(C), pages 31-47.
    33. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
    34. Esteban Lafuente & László Szerb & Zoltan J. Acs, 2016. "Country level efficiency and national systems of entrepreneurship: a data envelopment analysis approach," The Journal of Technology Transfer, Springer, vol. 41(6), pages 1260-1283, December.
    35. Toloo, Mehdi & Hančlová, Jana, 2020. "Multi-valued measures in DEA in the presence of undesirable outputs," Omega, Elsevier, vol. 94(C).
    36. Huang, Yuti & Coelho, Vânia R., 2017. "Sustainability performance assessment focusing on coral reef protection by the tourism industry in the Coral Triangle region," Tourism Management, Elsevier, vol. 59(C), pages 510-527.
    37. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    38. Gao, Qiuming & Wang, Derek, 2021. "Hospital efficiency and equity in health care delivery: A study based in China," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    39. Mohammad Nourani & Qian Long Kweh & Wen-Min Lu & Ikhlaas Gurrib, 2022. "Operational and investment efficiency of investment trust companies: Do foreign firms outperform domestic firms?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    40. Mohamed Mehdi Jelassi & Ezzeddine Delhoumi, 2021. "What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    41. Villanueva-Cantillo, Jeyms & Munoz-Marquez, Manuel, 2021. "Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 290(2), pages 657-670.
    42. Martín-Gamboa, Mario & Iribarren, Diego & García-Gusano, Diego & Dufour, Javier, 2019. "Enhanced prioritisation of prospective scenarios for power generation in Spain: How and which one?," Energy, Elsevier, vol. 169(C), pages 369-379.
    43. Congcong Yang & Alfred Taudes & Guozhi Dong, 2017. "Efficiency analysis of European Freight Villages: three peers for benchmarking," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 91-122, March.
    44. Tenente, Marcos & Henriques, Carla & da Silva, Patrícia Pereira, 2020. "Eco-efficiency assessment of the electricity sector: Evidence from 28 European Union countries," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 293-314.
    45. Pendharkar, Parag C., 2015. "Cost minimizing target setting heuristics for making inefficient decision-making units efficient," International Journal of Production Economics, Elsevier, vol. 162(C), pages 1-12.
    46. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2013. "Dealing with the Endogeneity Problem in Data Envelopment Analysis," MPRA Paper 47475, University Library of Munich, Germany.
    47. Anna Łozowicka & Bartłomiej Lach, 2022. "CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    48. 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).

  24. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.

    Cited by:

    1. Cristina Polo & Julián Ramajo & Alejandro Ricci‐Risquete, 2021. "A stochastic semi‐non‐parametric analysis of regional efficiency in the European Union," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 7-24, February.
    2. Anastasiou Athanasios & Kalligosfyris Charalampos & Kalamara Eleni, 2022. "Assessing the effectiveness of tax administration in macroeconomic stability: evidence from 26 European Countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2237-2261, November.
    3. Jose Manuel Cordero & Cristina Polo & Javier Salinas-Jiménez, 2021. "Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods," Journal of Happiness Studies, Springer, vol. 22(2), pages 867-886, February.
    4. Banker, Rajiv & Natarajan, Ram & Zhang, Daqun, 2019. "Two-stage estimation of the impact of contextual variables in stochastic frontier production function models using Data Envelopment Analysis: Second stage OLS versus bootstrap approaches," European Journal of Operational Research, Elsevier, vol. 278(2), pages 368-384.
    5. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
    6. Jamasb, Tooraj & Llorca, Manuel & Khetrapal, Pavan & Thakur, Tripta, 2021. "Institutions and performance of regulated firms: Evidence from electricity distribution in India," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 68-82.
    7. Irene Wei Kiong Ting & Imen Tebourbi & Wen-Min Lu & Qian Long Kweh, 2021. "The effects of managerial ability on firm performance and the mediating role of capital structure: evidence from Taiwan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    8. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    9. Cheng, Xiaomei & Andersson, Jonas & Bjørndal, Endre, 2015. "On the Distributional Assumptions in the StoNED model," Discussion Papers 2015/24, Norwegian School of Economics, Department of Business and Management Science.
    10. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    11. Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
    12. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
    13. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Monica Auteri & Guido Borà, 2017. "La spesa sanitaria delle Regioni in Italia - Saniregio2017," Working Papers CERM 01-2017, Competitività, Regole, Mercati (CERM).
    14. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    15. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2017. "Specification of merger gains in the Norwegian electricity distribution industry," Energy Policy, Elsevier, vol. 102(C), pages 96-107.
    16. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    17. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    18. Lee, Chia-Yen & Johnson, Andrew L., 2012. "Two-dimensional efficiency decomposition to measure the demand effect in productivity analysis," European Journal of Operational Research, Elsevier, vol. 216(3), pages 584-593.
    19. Vijesh Krishna & Prakashan Veettil, 2015. "Productivity and Efficiency Impacts of Zero Tillage Wheat in Northwest Indo-Gangetic Plains," Working Papers id:7716, eSocialSciences.
    20. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    21. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2015. "Optimal Scale in Different Environments – The Case of Norwegian Electricity Distribution Companies," Discussion Papers 2015/22, Norwegian School of Economics, Department of Business and Management Science.
    22. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
    23. Núñez, F. & Arcos-Vargas, A. & Villa, G., 2020. "Efficiency benchmarking and remuneration of Spanish electricity distribution companies," Utilities Policy, Elsevier, vol. 67(C).
    24. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.
    25. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    26. Bjørndal, Endre & Bjørndal, Mette & Cullmann, Astrid & Nieswand, Maria, 2018. "Finding the right yardstick: Regulation of electricity networks under heterogeneous environments," European Journal of Operational Research, Elsevier, vol. 265(2), pages 710-722.
    27. Vidoli, Francesco & Canello, Jacopo, 2016. "Controlling for spatial heterogeneity in nonparametric efficiency models: An empirical proposal," European Journal of Operational Research, Elsevier, vol. 249(2), pages 771-783.
    28. Topcu, Taylan G. & Triantis, Konstantinos & Roets, Bart, 2019. "Estimation of the workload boundary in socio-technical infrastructure management systems: The case of Belgian railroads," European Journal of Operational Research, Elsevier, vol. 278(1), pages 314-329.
    29. Alexander Arévalo S & Víctor Giménez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91, October.
    30. Saastamoinen, Antti & Kuosmanen, Timo, 2016. "Quality frontier of electricity distribution: Supply security, best practices, and underground cabling in Finland," Energy Economics, Elsevier, vol. 53(C), pages 281-292.
    31. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
    32. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2015. "Malmquist Productivity Analysis based on StoNED," Discussion Papers 2015/25, Norwegian School of Economics, Department of Business and Management Science.
    33. Rødseth, Kenneth Løvold, 2023. "Shadow pricing of electricity generation using stochastic and deterministic materials balance models," Applied Energy, Elsevier, vol. 341(C).
    34. George Halkos & Nickolaos Tzeremes, 2013. "National culture and eco-efficiency: an application of conditional partial nonparametric frontiers," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 15(4), pages 423-441, October.
    35. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    36. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2014. "Cost Efficiency Analysis based on The DEA and StoNED Models: Case of Norwegian Electricity Distribution Companies," Discussion Papers 2014/28, Norwegian School of Economics, Department of Business and Management Science.
    37. Maria Nieswand & Stefan Seifert, 2016. "Operational Conditions in Regulatory Benchmarking Models: A Monte Carlo Analysis," Discussion Papers of DIW Berlin 1585, DIW Berlin, German Institute for Economic Research.
    38. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    39. Francesco Vidoli & Giancarlo Ferrara, 2015. "Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models," Empirical Economics, Springer, vol. 49(2), pages 641-658, September.
    40. Orea, Luis & Wall, Alan, 2015. "A parametric frontier model for measuring eco-efficiency," Efficiency Series Papers 2015/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    41. Stefan Seifert, 2014. "Effizienzanalysemethoden in der Regulierung deutscher Elektrizitäts- und Gasversorgungsunternehmen," DIW Roundup: Politik im Fokus 40, DIW Berlin, German Institute for Economic Research.
    42. Nieswand, Maria & Seifert, Stefan, 2018. "Environmental factors in frontier estimation – A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 265(1), pages 133-148.
    43. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
    44. Surender Kumar & Sudesh Kumar, 2015. "Does modernization improve performance: evidence from Indian police," European Journal of Law and Economics, Springer, vol. 39(1), pages 57-77, February.
    45. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
    46. Romano, Teresa & Cambini, Carlo & Fumagalli, Elena & Rondi, Laura, 2022. "Setting network tariffs with heterogeneous firms: The case of natural gas distribution," European Journal of Operational Research, Elsevier, vol. 297(1), pages 280-290.
    47. E. Fusco & R. Benedetti & F. Vidoli, 2023. "Stochastic frontier estimation through parametric modelling of quantile regression coefficients," Empirical Economics, Springer, vol. 64(2), pages 869-896, February.
    48. Mekaroonreung, Maethee & Johnson, Andrew L., 2012. "Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach," Energy Economics, Elsevier, vol. 34(3), pages 723-732.
    49. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
    50. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    51. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    52. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.
    53. Paolo Postiglione, 2021. "New directions for regional analysis: Methods and applications," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 3-5, February.
    54. Panayiotis Tzeremes, 2020. "Productivity, efficiency and firm’s market value: Microeconomic evidence from multinational corporations," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 95-105.
    55. Saastamoinen, Antti & Bjørndal, Endre & Bjørndal, Mette, 2016. "Specification of merger gains in the Norwegian electricity distribution industry," Discussion Papers 2016/7, Norwegian School of Economics, Department of Business and Management Science.
    56. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    57. Timo Kuosmanen & Yong Tan & Sheng Dai, 2023. "Performance analysis of English hospitals during the first and second waves of the coronavirus pandemic," Health Care Management Science, Springer, vol. 26(3), pages 447-460, September.
    58. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
    59. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.

  25. Trevor Collier & Andrew L. Johnson & John Ruggiero, 2011. "Measuring Technical Efficiency in Sports," Journal of Sports Economics, , vol. 12(6), pages 579-598, December.

    Cited by:

    1. Fiona Carmichael & Dennis Thomas, 2014. "Team performance: production and efficiency in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 10, pages 143-165, Edward Elgar Publishing.
    2. R. Todd Jewell, 2020. "NCAA Expenditure and Efficiency: Analyzing Generated and Allocated Revenue in the Football Bowl Subdivision," Journal of Sports Economics, , vol. 21(4), pages 363-390, May.
    3. Thanasis Bouzidis, 2019. "On-field Performance Evaluation in Soccer based on Network Data Envelopment Analysis," Discussion Paper Series 2019_05, Department of Economics, University of Macedonia, revised Nov 2019.
    4. Russell D. Kashian & Jeff Pagel, 2016. "Measuring X-Efficiency in NCAA Division III Athletics," Journal of Sports Economics, , vol. 17(6), pages 558-577, August.
    5. Lozano, Sebastián, 2023. "Bargaining approach for efficiency assessment and target setting with fixed-sum variables," Omega, Elsevier, vol. 114(C).
    6. Thanasis Bouzidis & Giannis Karagiannis, 2022. "Extending the zero-sum gains data envelopment analysis model," Journal of Productivity Analysis, Springer, vol. 58(2), pages 171-184, December.
    7. Todd Jewell, 2014. "Major league soccer in the USA," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 21, pages 351-367, Edward Elgar Publishing.
    8. Thanasis Bouzidis & Giannis Karagiannis, 2022. "A note on the zero-sum gains data envelopment analysis model," Operational Research, Springer, vol. 22(3), pages 1737-1758, July.
    9. Ira Horowitz, 2017. "An Efficiency Evaluation of Men’s College Basketball Coaches," The American Economist, Sage Publications, vol. 62(1), pages 77-98, March.
    10. Carlos Pestana Barros & Eduardo Couto & Antonio Samagaio, 2014. "Management ability, strategy, tactics and team performance," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 11, pages 166-188, Edward Elgar Publishing.
    11. Sebastián Lozano & Gabriel Villa, 2023. "Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games," Annals of Operations Research, Springer, vol. 322(2), pages 879-919, March.
    12. Bouzidis, Thanasis & Karagiannis, Giannis, 2022. "An alternative ranking of DMUs performance for the ZSG-DEA model," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    13. Emilio Gómez-Déniz & Nancy Dávila-Cárdenes & Alejandro Leiva-Arcas & María J. Martínez-Patiño, 2021. "Measuring Efficiency in the Summer Olympic Games Disciplines: The Case of the Spanish Athletes," Mathematics, MDPI, vol. 9(21), pages 1-15, October.
    14. Laura Beaudin, 2018. "Examining the Relationship Between Athletic Program Expenditure and Athletic Program Success Among NCAA Division I Institutions," Journal of Sports Economics, , vol. 19(7), pages 1016-1045, October.
    15. Fiona Carmichael & Giambattista Rossi & Denis Thomas, 2017. "Production, Efficiency, and Corruption in Italian Serie A Football," Journal of Sports Economics, , vol. 18(1), pages 34-57, January.
    16. Thanasis Bouzidis, 2018. "On-field Performance Assessment in Football: Applying the Connected Network Data Envelopment Analysis Model," Discussion Paper Series 2018_12, Department of Economics, University of Macedonia, revised Dec 2018.
    17. Thanasis Bouzidis & Giannis Karagiannis, 2021. "An Alternative Ranking of DMUs Performance for the ZGS-DEA Model," Discussion Paper Series 2021_12, Department of Economics, University of Macedonia, revised Oct 2021.
    18. Thanasis Bouzidis & Giannis Karagiannis, 2022. "Extending the Zero-Sum Gains Data Envelopment Analysis Model," Discussion Paper Series 2022_06, Department of Economics, University of Macedonia, revised Aug 2022.

  26. Collier, Trevor & Johnson, Andrew L. & Ruggiero, John, 2011. "Technical efficiency estimation with multiple inputs and multiple outputs using regression analysis," European Journal of Operational Research, Elsevier, vol. 208(2), pages 153-160, January.

    Cited by:

    1. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    2. Färe, Rolf & Mizobuchi, Hideyuki & Zelenyuk, Valentin, 2021. "Hicks neutrality and homotheticity in technologies with multiple inputs and multiple outputs," Omega, Elsevier, vol. 101(C).
    3. Laura Di Giorgio & Abraham D Flaxman & Mark W Moses & Nancy Fullman & Michael Hanlon & Ruben O Conner & Alexandra Wollum & Christopher J L Murray, 2016. "Efficiency of Health Care Production in Low-Resource Settings: A Monte-Carlo Simulation to Compare the Performance of Data Envelopment Analysis, Stochastic Distance Functions, and an Ensemble Model," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-20, January.
    4. Tsionas, Mike G., 2016. "Notes on technical efficiency estimation with multiple inputs and outputs," European Journal of Operational Research, Elsevier, vol. 249(2), pages 784-788.
    5. Lin, Winston T. & Chen, Yueh H. & Shao, Benjamin B.M., 2015. "Assessing the business values of information technology and e-commerce independently and jointly," European Journal of Operational Research, Elsevier, vol. 245(3), pages 815-827.
    6. Lin, Winston T. & Chuang, Chia-Hung, 2013. "Investigating and comparing the dynamic patterns of the business value of information technology over time," European Journal of Operational Research, Elsevier, vol. 228(1), pages 249-261.
    7. Lin, Winston T. & Kao, Ta-Wei (Daniel), 2014. "The partial adjustment valuation approach with dynamic and variable speeds of adjustment to evaluating and measuring the business value of information technology," European Journal of Operational Research, Elsevier, vol. 238(1), pages 208-220.

  27. Johnson, Andrew L. & Ruggiero, John, 2011. "Allocative efficiency measurement with endogenous prices," Economics Letters, Elsevier, vol. 111(1), pages 81-83, April.

    Cited by:

    1. Sotiros, Dimitrios & Rodrigues, Vasco & Silva, Maria Conceição, 2022. "Analysing the export potentials of the Portuguese footwear industry by data envelopment analysis," Omega, Elsevier, vol. 108(C).
    2. David J. Mayston, 2017. "Data envelopment analysis, endogeneity and the quality frontier for public services," Annals of Operations Research, Springer, vol. 250(1), pages 185-203, March.
    3. Ayouba, Kassoum & Boussemart, Jean-Philippe & Lefer, Henri-Bertrand & Leleu, Hervé & Parvulescu, Raluca, 2019. "A measure of price advantage and its decomposition into output- and input-specific effects," European Journal of Operational Research, Elsevier, vol. 276(2), pages 688-698.
    4. Benjamin Hampf & Kenneth Løvold Rødseth, 2017. "Optimal profits under environmental regulation: the benefits from emission intensity averaging," Annals of Operations Research, Springer, vol. 255(1), pages 367-390, August.
    5. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal Profits under Environmental Regulation: The Benefits from Emission Intensity Averaging," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 68011, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Saeideh Fallah-Fini & Konstantinos Triantis & Andrew Johnson, 2014. "Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art," Journal of Productivity Analysis, Springer, vol. 41(1), pages 51-67, February.
    7. David J. Mayston, 2015. "Data envelopment analysis, endogeneity and the quality frontier for public services," Discussion Papers 15/05, Department of Economics, University of York.
    8. Portela, Maria Conceição A. Silva & Thanassoulis, Emmanuel, 2014. "Economic efficiency when prices are not fixed: disentangling quantity and price efficiency," Omega, Elsevier, vol. 47(C), pages 36-44.
    9. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal profits under environmental regulation: The benefits from emission intensity averaging," Darmstadt Discussion Papers in Economics 220, Darmstadt University of Technology, Department of Law and Economics.
    10. Farvaque, Etienne & Foucault, Martial & Vigeant, Stéphane, 2020. "The politician and the vote factory: Candidates’ resource management skills and electoral returns," Journal of Policy Modeling, Elsevier, vol. 42(1), pages 38-55.

  28. Andrew Johnson & Leon McGinnis, 2011. "Performance measurement in the warehousing industry," IISE Transactions, Taylor & Francis Journals, vol. 43(3), pages 220-230.

    Cited by:

    1. Aparicio, J. & Zofío, J.L., 2019. "Economic Cross-Efficiency," ERIM Report Series Research in Management ERS-2019-001-LIS, 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.
    2. Balk, Bert M. & (René) De Koster, M.B.M. & Kaps, Christian & Zofío, José L., 2021. "An evaluation of cross-efficiency methods: With an application to warehouse performance," Applied Mathematics and Computation, Elsevier, vol. 406(C).

  29. Timo Kuosmanen & Andrew L. Johnson, 2010. "Data Envelopment Analysis as Nonparametric Least-Squares Regression," Operations Research, INFORMS, vol. 58(1), pages 149-160, February.

    Cited by:

    1. Keshvari, Abolfazl & Kuosmanen, Timo, 2013. "Stochastic non-convex envelopment of data: Applying isotonic regression to frontier estimation," European Journal of Operational Research, Elsevier, vol. 231(2), pages 481-491.
    2. Cristina Polo & Julián Ramajo & Alejandro Ricci‐Risquete, 2021. "A stochastic semi‐non‐parametric analysis of regional efficiency in the European Union," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 7-24, February.
    3. Jose Manuel Cordero & Cristina Polo & Javier Salinas-Jiménez, 2021. "Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods," Journal of Happiness Studies, Springer, vol. 22(2), pages 867-886, February.
    4. Lamb, John D. & Tee, Kai-Hong, 2012. "Resampling DEA estimates of investment fund performance," European Journal of Operational Research, Elsevier, vol. 223(3), pages 834-841.
    5. Elvira Silva & Pedro Macedo & Isabel Soares, 2019. "Maximum entropy: a stochastic frontier approach for electricity distribution regulation," Journal of Regulatory Economics, Springer, vol. 55(3), pages 237-257, June.
    6. Elahi, Ehsan & Khalid, Zainab & Weijun, Cui & Zhang, Huiming, 2020. "The public policy of agricultural land allotment to agrarians and its impact on crop productivity in Punjab province of Pakistan," Land Use Policy, Elsevier, vol. 90(C).
    7. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    8. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Vouldis, Angelos T. & Konstantakis, Konstantinos N., 2015. "Global approximation to arbitrary cost functions: A Bayesian approach with application to US banking," European Journal of Operational Research, Elsevier, vol. 241(1), pages 148-160.
    9. 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.
    10. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    11. Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
    12. 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.
    13. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    14. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    15. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
    16. Zhou, Xun & Kuosmanen, Timo, 2020. "What drives decarbonization of new passenger cars?," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1043-1057.
    17. Prakashan Veettil & Stijn Speelman & Guido Huylenbroeck, 2013. "Estimating the Impact of Water Pricing on Water Use Efficiency in Semi-arid Cropping System: An Application of Probabilistically Constrained Nonparametric Efficiency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 55-73, January.
    18. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2015. "Testing the accuracy of DEA estimates under endogeneity through a Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 244(2), pages 511-518.
    19. Afsharian, Mohsen, 2017. "Metafrontier efficiency analysis with convex and non-convex metatechnologies by stochastic nonparametric envelopment of data," Economics Letters, Elsevier, vol. 160(C), pages 1-3.
    20. Sun, Qinghe & Chen, Li & Meng, Qiang, 2022. "Evaluating port efficiency dynamics: A risk-based approach," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 333-347.
    21. Olesen, O.B. & Ruggiero, J., 2022. "The hinging hyperplanes: An alternative nonparametric representation of a production function," European Journal of Operational Research, Elsevier, vol. 296(1), pages 254-266.
    22. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
    23. K. Hervé Dakpo & Yann Desjeux & Laure Latruffe, 2023. "Cost of abating excess nitrogen on wheat plots in France: An assessment with multi‐technology modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 800-815, September.
    24. Schmidt, Rouven & Kneib, Thomas, 2023. "Multivariate distributional stochastic frontier models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    25. Agrell, Per J. & Brea-Solís, Humberto, 2017. "Capturing heterogeneity in electricity distribution operations: A critical review of latent class modelling," Energy Policy, Elsevier, vol. 104(C), pages 361-372.
    26. Aparicio, Juan & Pastor, Jesús T. & Vidal, Fernando & Zofío, José L., 2017. "Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis," Omega, Elsevier, vol. 67(C), pages 134-144.
    27. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    28. Wang, Yongqiao & Wang, Shouyang & Dang, Chuangyin & Ge, Wenxiu, 2014. "Nonparametric quantile frontier estimation under shape restriction," European Journal of Operational Research, Elsevier, vol. 232(3), pages 671-678.
    29. Kuo‐Cheng Kuo & Wen‐Min Lu & Dinh Tam Nguyen & Hsiu Fei Wang, 2020. "The effect of special economic zones on governance performance and their spillover effects in Chinese provinces," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 446-460, April.
    30. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    31. Elahi, Ehsan & Khalid, Zainab, 2022. "Estimating smart energy inputs packages using hybrid optimisation technique to mitigate environmental emissions of commercial fish farms," Applied Energy, Elsevier, vol. 326(C).
    32. Delnava, Haleh & Khosravi, Ali & El Haj Assad, Mamdouh, 2023. "Metafrontier frameworks for estimating solar power efficiency in the United States using stochastic nonparametric envelopment of data (StoNED)," Renewable Energy, Elsevier, vol. 213(C), pages 195-204.
    33. Sipilainen, Timo & Huhtala, Anni, 2012. "Opportunity Costs of Providing Crop Diversity in Organic and Conventional Farming," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126652, International Association of Agricultural Economists.
    34. Mike Tsionas & Valentin Zelenyuk, 2021. "Goodness-of-fit in Optimizing Models of Production: A Generalization with a Bayesian Perspective," CEPA Working Papers Series WP182021, School of Economics, University of Queensland, Australia.
    35. Bellini, Tiziano, 2012. "Forward search outlier detection in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 216(1), pages 200-207.
    36. Shen, Xiaobo & Lin, Boqiang, 2017. "The shadow prices and demand elasticities of agricultural water in China: A StoNED-based analysis," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 21-28.
    37. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    38. Stefan Seifert, 2016. "Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation," Discussion Papers of DIW Berlin 1571, DIW Berlin, German Institute for Economic Research.
    39. Jradi, Samah & Ruggiero, John, 2019. "Stochastic data envelopment analysis: A quantile regression approach to estimate the production frontier," European Journal of Operational Research, Elsevier, vol. 278(2), pages 385-393.
    40. Alexander Arévalo S & Víctor Giménez G & Diego Prior J, 2022. "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 92(2), pages 45-91, October.
    41. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.
    42. Olesen, O.B. & Ruggiero, J., 2018. "An improved Afriat–Diewert–Parkan nonparametric production function estimator," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1172-1188.
    43. Tsionas, Mike G., 2023. "Clustering and meta-envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 304(2), pages 763-778.
    44. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    45. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study," Operational Research, Springer, vol. 23(3), pages 1-33, September.
    46. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
    47. Rødseth, Kenneth Løvold, 2023. "Shadow pricing of electricity generation using stochastic and deterministic materials balance models," Applied Energy, Elsevier, vol. 341(C).
    48. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    49. Nadia M. Guerrero & Juan Aparicio & Daniel Valero-Carreras, 2022. "Combining Data Envelopment Analysis and Machine Learning," Mathematics, MDPI, vol. 10(6), pages 1-22, March.
    50. España, Victor J. & Aparicio, Juan & Barber, Xavier & Esteve, Miriam, 2024. "Estimating production functions through additive models based on regression splines," European Journal of Operational Research, Elsevier, vol. 312(2), pages 684-699.
    51. Chung, William & Yeung, Iris M.H., 2017. "Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings," Applied Energy, Elsevier, vol. 203(C), pages 454-462.
    52. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    53. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    54. Lee, Chia-Yen & Johnson, Andrew L., 2014. "Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments," European Journal of Operational Research, Elsevier, vol. 232(3), pages 537-548.
    55. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    56. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    57. Trevor Collier & Andrew L. Johnson & John Ruggiero, 2011. "Measuring Technical Efficiency in Sports," Journal of Sports Economics, , vol. 12(6), pages 579-598, December.
    58. 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.
    59. Gianpaolo Iazzolino & Rossella Gabriele, 2016. "Energy Efficiency and Sustainable Development: An Analysis of Financial Reliability in Energy Service Companies Industry," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 222-233.
    60. Manuel Salas-Velasco, 2020. "Measuring and explaining the production efficiency of Spanish universities using a non-parametric approach and a bootstrapped-truncated regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 825-846, February.
    61. Lin, Winston T. & Chen, Yueh H. & Hung, TingShu, 2019. "A partial adjustment valuation approach with stochastic and dynamic speeds of partial adjustment to measuring and evaluating the business value of information technology," European Journal of Operational Research, Elsevier, vol. 272(2), pages 766-779.
    62. Lee, Chia-Yen & Cai, Jia-Ying, 2020. "LASSO variable selection in data envelopment analysis with small datasets," Omega, Elsevier, vol. 91(C).
    63. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    64. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
    65. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    66. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    67. Sekitani, Kazuyuki & Zhao, Yu, 2021. "Performance benchmarking of achievements in the Olympics: An application of Data Envelopment Analysis with restricted multipliers," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1202-1212.
    68. Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
    69. Chen, Sheng-Syan & Lin, Chih-Yen, 2018. "Managerial ability and acquirer returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 171-182.
    70. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    71. Kounetas, Konstantinos E. & Polemis, Michael L. & Tzeremes, Nickolaos G., 2021. "Measurement of eco-efficiency and convergence: Evidence from a non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 291(1), pages 365-378.
    72. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    73. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
    74. Antonio Angelo Romano & Giuseppe Scandurra & Alfonso Carfora, 2016. "Estimating the Impact of Feed-in Tariff Adoption: Similarities and Divergences among Countries through a Propensity-score Matching Method," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 144-151.
    75. Lee, Chia-Yen, 2016. "Most productive scale size versus demand fulfillment: A solution to the capacity dilemma," European Journal of Operational Research, Elsevier, vol. 248(3), pages 954-962.
    76. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
    77. Anaya, Karim L. & Pollitt, Michael G., 2017. "Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1078-1094.
    78. Hideyuki Mizobuchi, 2017. "Incorporating Sustainability Concerns in the Better Life Index: Application of Corrected Convex Non-parametric Least Squares Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 947-971, April.
    79. Kuosmanen, Timo & Saastamoinen, Antti & Sipiläinen, Timo, 2013. "What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods," Energy Policy, Elsevier, vol. 61(C), pages 740-750.
    80. Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
    81. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    82. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    83. Rødseth, Kenneth Løvold, 2023. "Noise pollution of container handling: External and abatement costs and environmental efficiency," Transport Policy, Elsevier, vol. 134(C), pages 82-93.
    84. Yantuan Yu & Jianhuan Huang & Yanmin Shao, 2019. "The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression," Sustainability, MDPI, vol. 11(6), pages 1-25, March.
    85. Valero-Carreras, Daniel & Aparicio, Juan & Guerrero, Nadia M., 2021. "Support vector frontiers: A new approach for estimating production functions through support vector machines," Omega, Elsevier, vol. 104(C).
    86. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    87. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    88. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).
    89. 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).

  30. Wen-Chih Chen & Andrew Johnson, 2010. "The dynamics of performance space of Major League Baseball pitchers 1871–2006," Annals of Operations Research, Springer, vol. 181(1), pages 287-302, December.

    Cited by:

    1. Amar Oukil & Srikrishna Madhumohan Govindaluri, 2017. "A systematic approach for ranking football players within an integrated DEA‐OWA framework," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 38(8), pages 1125-1136, December.
    2. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.
    3. Yutaka Ueda & Yoko Ohzono, 2013. "A New Measure of Distributive Justice by Data Envelopment Analysis," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(3), pages 49-59, June.
    4. Qing Zhu & Renxian Zuo & Yuze Li & Shan Liu, 2021. "A system evaluation of NBA rookie contract execution efficiency with stacked Autoencoder and hybrid DEA," Operational Research, Springer, vol. 21(4), pages 2771-2807, December.
    5. Aydın, Umut & Karadayi, Melis Almula & Ülengin, Füsun, 2020. "How efficient airways act as role models and in what dimensions? A superefficiency DEA model enhanced by social network analysis," Journal of Air Transport Management, Elsevier, vol. 82(C).
    6. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    7. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.
    8. Isidoro Guzmán-Raja & Manuela Guzmán-Raja, 2021. "Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football," SAGE Open, , vol. 11(1), pages 21582440219, February.
    9. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    10. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
    11. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.
    12. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    13. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.

  31. A L Johnson & L F McGinnis, 2009. "The hyperbolic-oriented efficiency measure as a remedy to infeasibility of super efficiency models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1511-1517, November.

    Cited by:

    1. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    2. Simar, Léopold & W. Wilson, Paul, 2019. "Central limit theorems and inference for sources of productivity change measured by nonparametric Malmquist indices," European Journal of Operational Research, Elsevier, vol. 277(2), pages 756-769.
    3. 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.
    4. Halická, Margaréta & Trnovská, Mária & Černý, Aleš, 2024. "A unified approach to radial, hyperbolic, and directional efficiency measurement in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 312(1), pages 298-314.
    5. Simar, Léopold & Wilson, Paul, 2022. "Another Look at Productivity Growth in Industrialized Countries," LIDAM Discussion Papers ISBA 2022028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Mustapha D. Ibrahim & Sahand Daneshvar & Mevhibe B. Hocaoğlu & Olasehinde-Williams G. Oluseye, 2019. "An Estimation of the Efficiency and Productivity of Healthcare Systems in Sub-Saharan Africa: Health-Centred Millennium Development Goal-Based Evidence," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 371-389, May.
    7. Halická, Margaréta & Trnovská, Mária, 2019. "Duality and profit efficiency for the hyperbolic measure model," European Journal of Operational Research, Elsevier, vol. 278(2), pages 410-421.
    8. Zhang, Zibin & Ye, Jianliang, 2015. "Decomposition of environmental total factor productivity growth using hyperbolic distance functions: A panel data analysis for China," Energy Economics, Elsevier, vol. 47(C), pages 87-97.
    9. Rezaeiani, M.J. & Foroughi, A.A., 2018. "Ranking efficient decision making units in data envelopment analysis based on reference frontier share," European Journal of Operational Research, Elsevier, vol. 264(2), pages 665-674.
    10. Li, Yongjun & Xie, Jianhui & Wang, Meiqiang & Liang, Liang, 2016. "Super efficiency evaluation using a common platform on a cooperative game," European Journal of Operational Research, Elsevier, vol. 255(3), pages 884-892.

  32. Johnson, Andrew L. & McGinnis, Leon F., 2008. "Outlier detection in two-stage semiparametric DEA models," European Journal of Operational Research, Elsevier, vol. 187(2), pages 629-635, June.

    Cited by:

    1. Carlucci, Fabio & Corcione, Carlo & Mazzocchi, Paolo & Trincone, Barbara, 2021. "The role of logistics in promoting Italian agribusiness: The Belt and Road Initiative case study," Land Use Policy, Elsevier, vol. 108(C).
    2. Helmut Herwartz & Christoph Strumann, 2014. "Hospital efficiency under prospective reimbursement schemes: an empirical assessment for the case of Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(2), pages 175-186, March.
    3. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    4. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "Data envelopment analysis 1978–2010: A citation-based literature survey," Omega, Elsevier, vol. 41(1), pages 3-15.
    5. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    6. Ali Bahari & Ali Emrouznejad, 2014. "Influential DMUs and outlier detection in data envelopment analysis with an application to health care," Annals of Operations Research, Springer, vol. 223(1), pages 95-108, December.
    7. Horta, Isabel M. & Camanho, Ana S., 2015. "A nonparametric methodology for evaluating convergence in a multi-input multi-output setting," European Journal of Operational Research, Elsevier, vol. 246(2), pages 554-561.
    8. Farnè, Matteo & Vouldis, Angelos T., 2018. "A methodology for automised outlier detection in high-dimensional datasets: an application to euro area banks' supervisory data," Working Paper Series 2171, European Central Bank.
    9. A L Johnson & L F McGinnis, 2009. "The hyperbolic-oriented efficiency measure as a remedy to infeasibility of super efficiency models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1511-1517, November.
    10. 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.
    11. José Cordero Ferrera & Eva Cebada & Luis Murillo Zamorano, 2014. "The effect of quality and socio-demographic variables on efficiency measures in primary health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(3), pages 289-302, April.
    12. Khezrimotlagh, Dariush & Cook, Wade D. & Zhu, Joe, 2020. "A nonparametric framework to detect outliers in estimating production frontiers," European Journal of Operational Research, Elsevier, vol. 286(1), pages 375-388.
    13. Helmut Herwartz & Christoph Strumann, 2012. "On the effect of prospective payment on local hospital competition in Germany," Health Care Management Science, Springer, vol. 15(1), pages 48-62, March.
    14. Zhu, Ning & Wu, Yanrui & Wang, Bing & Yu, Zhiqian, 2019. "Risk preference and efficiency in Chinese banking," China Economic Review, Elsevier, vol. 53(C), pages 324-341.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.