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Measurement of Congestion in the Simultaneous Presence of Desirable and Undesirable Outputs

Author

Listed:
  • H. Zare-Haghighi
  • M. Rostamy-Malkhalifeh
  • G. R. Jahanshahloo

Abstract

The concept of congestion, which is mainly applied in economics, refers to a situation where inputs are overinvested. Many studies have focused on congestion measurement by means of data envelopment analysis (DEA). However, most of the previous investigations only considered the framework of desirable outputs. In fact, firms in the real world unavoidably generate undesirable outputs (such as pollutants or wastes) along with desirable outputs. Therefore, a new scheme is required for measuring congestion in the simultaneous presence of both desirable and undesirable outputs. This paper develops a nonradial efficiency measure for including undesirable outputs into the environmental performance. Based on the proposed model, a new definition and a new approach are presented to deal with congestion in the simultaneous presence of desirable and undesirable outputs. Then, this paper uses the presented method to study the pollutants (waste gas emission and waste discharge) of 31 administrative regions of China. The finding indicates that 7 industries pay attention to the reduction of their pollutants accompanying improvement of their commercial targets. Consequently, they do not show congestion in any input.

Suggested Citation

  • H. Zare-Haghighi & M. Rostamy-Malkhalifeh & G. R. Jahanshahloo, 2014. "Measurement of Congestion in the Simultaneous Presence of Desirable and Undesirable Outputs," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:512157
    DOI: 10.1155/2014/512157
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    References listed on IDEAS

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    1. F. Hosseinzadeh Lotfi & G. R. Jahanshahloo & M. Khodabakhshi & M. Rostamy-Malkhlifeh & Z. Moghaddas & M. Vaez-Ghasemi, 2013. "A Review of Ranking Models in Data Envelopment Analysis," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-20, July.
    2. 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.
    3. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.
    4. H. Jahanshahloo & F. Hosseinzadeh Lotfi & M. Khodabakhshi, 2014. "Modified Nonradial Supper Efficiency Models," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    5. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    6. Brockett, Patrick L. & Cooper, William W. & Wang, Yuying & Shin, Hong-Chul, 1998. "Inefficiency and congestion in Chinese production before and after the 1978 economic reforms," Socio-Economic Planning Sciences, Elsevier, vol. 32(1), pages 1-20, March.
    7. Fare, Rolf, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    8. Cooper, William W. & Seiford, Lawrence M. & Zhu, Joe, 2000. "A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 1-25, March.
    9. F. Hosseinzadeh Lotfi & G. R. Jahanshahloo & M. Khodabakhshi & M. Rostamy-Malkhlifeh & Z. Moghaddas & M. Vaez-Ghasemi, 2013. "A Review of Ranking Models in Data Envelopment Analysis," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    10. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    11. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    12. H. Jahanshahloo & F. Hosseinzadeh Lotfi & M. Khodabakhshi, 2014. "Modified Nonradial Supper Efficiency Models," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-5, February.
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