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Using DEA to improve the management of congestion in Chinese industries (1981-1997)

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Cited by:

  1. Wei, Quanling & Yan, Hong, 2009. "Weak congestion in output additive data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 40-54, March.
  2. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "Methodological comparison between two unified (operational and environmental) efficiency measurements for environmental assessment," European Journal of Operational Research, Elsevier, vol. 210(3), pages 684-693, May.
  3. Feihua Huang & Yue Du & Debao Hu & Bin Zhang, 2021. "Sustainable Performance Analysis of Power Supply Chain System from the Perspective of Technology and Management," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
  4. Yang, Zhuofan & Shi, Yong & Yan, Hong, 2017. "Analysis on pure e-commerce congestion effect, productivity effect and profitability in China," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 35-49.
  5. Patrick Brockett & William Cooper & Honghui Deng & Linda Golden & T. Ruefli, 2004. "Using DEA to Identify and Manage Congestion," Journal of Productivity Analysis, Springer, vol. 22(3), pages 207-226, November.
  6. Wu, Desheng(Dash) & Liang, Liang & Yang, Zijiang, 2008. "Analyzing the financial distress of Chinese public companies using probabilistic neural networks and multivariate discriminate analysis," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 206-220, September.
  7. Pang, Qinghua & Qiu, Man & Zhang, Lina & Chiu, Yung-ho, 2023. "Congestion effects of energy and capital in China's carbon emission reduction: Evidence from provincial levels," Energy, Elsevier, vol. 274(C).
  8. F. Wu & P. Zhou & D. Zhou, 2015. "Measuring Energy Congestion in Chinese Industrial Sectors: A Slacks-Based DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 479-494, October.
  9. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
  10. Khodabakhshi, M., 2009. "Estimating most productive scale size with stochastic data in data envelopment analysis," Economic Modelling, Elsevier, vol. 26(5), pages 968-973, September.
  11. W. Cooper & Shanling Li & L. Seiford & Kaoru Tone & R. Thrall & J. Zhu, 2001. "Sensitivity and Stability Analysis in DEA: Some Recent Developments," Journal of Productivity Analysis, Springer, vol. 15(3), pages 217-246, May.
  12. Ren, Xian-tong & Fukuyama, Hirofumi & Yang, Guo-liang, 2022. "Eliminating congestion by increasing inputs in R&D activities of Chinese universities," Omega, Elsevier, vol. 110(C).
  13. Alfonso Mendoza-Velázquez & Francisco Benita, 2019. "Efficiency, Productivity, and Congestion Performance: Analysis of the Automotive Cluster in Mexico," Journal of Industry, Competition and Trade, Springer, vol. 19(4), pages 661-678, December.
  14. Chen, Zhenling & Li, Jinkai & Zhao, Weigang & Yuan, Xiao-Chen & Yang, Guo-liang, 2019. "Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China," Energy Policy, Elsevier, vol. 125(C), pages 122-134.
  15. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
  16. Cooper, William W. & Deng, H. & Huang, Zhimin & Li, Susan X., 2004. "Chance constrained programming approaches to congestion in stochastic data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 155(2), pages 487-501, June.
  17. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
  18. Wu, F. & Zhou, P. & Zhou, D.Q., 2020. "Modeling carbon emission performance under a new joint production technology with energy input," Energy Economics, Elsevier, vol. 92(C).
  19. Cooper, William W. & Ruiz, Jose L. & Sirvent, Inmaculada, 2007. "Choosing weights from alternative optimal solutions of dual multiplier models in DEA," European Journal of Operational Research, Elsevier, vol. 180(1), pages 443-458, July.
  20. Noura, A.A. & Hosseinzadeh Lotfi, F. & Jahanshahloo, G.R. & Rashidi, S. Fanati & Parker, Barnett R., 2010. "A new method for measuring congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 44(4), pages 240-246, December.
  21. Flegg, A.T. & Allen, D.O., 2009. "Congestion in the Chinese automobile and textile industries revisited," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 177-191, September.
  22. Sang-Lyul Ryu & Jayoun Won, 2022. "The Value Relevance of Operational Innovation: Insights from the Perspective of Firm Life Cycle," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
  23. P. Zhou & F. Wu & D. Q. Zhou, 2017. "Total-factor energy efficiency with congestion," Annals of Operations Research, Springer, vol. 255(1), pages 241-256, August.
  24. Cooper, W. W. & Deng, Honghui & Huang, Zhimin M. & Li, Susan X., 2002. "A one-model approach to congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 36(4), pages 231-238, December.
  25. Wei, Quanling & Yan, Hong, 2004. "Congestion and returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 153(3), pages 641-660, March.
  26. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
  27. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "DEA congestion and returns to scale under an occurrence of multiple optimal projections," European Journal of Operational Research, Elsevier, vol. 194(2), pages 592-607, April.
  28. Kao, Chiang, 2010. "Congestion measurement and elimination under the framework of data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 123(2), pages 257-265, February.
  29. Jun Wang & Yong Zha, 2014. "Distinguishing Technical Inefficiency from Desirable and Undesirable Congestion with an Application to Regional Industries in China," Sustainability, MDPI, vol. 6(12), pages 1-19, December.
  30. Gattoufi, Said & Oral, Muhittin & Reisman, Arnold, 2004. "A taxonomy for data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 38(2-3), pages 141-158.
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