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Congestion in the Chinese automobile and textile industries revisited

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  • Flegg, A.T.
  • Allen, D.O.

Abstract

This paper re-examines a problem of congested inputs in the Chinese automobile and textile industries, which was identified by Cooper et al. [Cooper WW, Deng H, Gu B, Li S, Thrall RM. Using DEA to improve the management of congestion in Chinese industries (1981-1997). Socio-Economic Planning Sciences 2001;35:227-242]. Since these authors employed a single approach in measuring congestion, it is worth exploring whether alternative procedures would yield very different outcomes. Indeed, the measurement of congestion is an area where there has been much theoretical debate but relatively little empirical work. After examining the theoretical properties of the two main approaches currently available, those of Färe et al. [Färe R, Grosskopf S, Lovell CAK. The measurement of efficiency of production. Boston: Kluwer-Nijhoff; 1985] and Cooper et al., we use the data set assembled by Cooper et al. for the period 1981-1997 to compare and contrast the measurements of congestion generated by these alternative approaches. We find that the results are strikingly different, especially in terms of the amount of congestion identified. Finally, we discuss the new approach to measuring congestion proposed by Tone and Sahoo [Tone K, Sahoo BK. Degree of scale economies and congestion: a unified DEA approach. European Journal of Operational Research 2004;158:755-772].

Suggested Citation

  • 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.
    • Handle: RePEc:eee:soceps:v:43:y:2009:i:3:p:177-191
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. A. T. Flegg & D. O. Allen, 2007. "Does Expansion Cause Congestion? The Case of the Older British Universities, 1994-2004," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 75-102.
    4. Cooper, W. W. & Deng, Honghui & Gu, Bisheng & Li, Shanling & Thrall, R. M., 2001. "Using DEA to improve the management of congestion in Chinese industries (1981-1997)," Socio-Economic Planning Sciences, Elsevier, vol. 35(4), pages 227-242, December.
    5. Cooper, W. W. & Seiford, L. M. & Zhu, J., 2001. "Slacks and congestion: response to a comment by R. Fare and S. Grosskopf," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 205-215, September.
    6. Cherchye, Laurens & Kuosmanen, Timo & Post, Thierry, 2001. "Alternative treatments of congestion in DEA: A rejoinder to Cooper, Gu, and Li," European Journal of Operational Research, Elsevier, vol. 132(1), pages 75-80, July.
    7. Fare, Rolf & Grosskopf, Shawna, 1998. "Congestion: a note," Socio-Economic Planning Sciences, Elsevier, vol. 32(1), pages 21-23, March.
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    15. A. T. Flegg & D. O. Allen & K. Field & T. W. Thurlow, 2004. "Measuring the efficiency of British universities: a multi-period data envelopment analysis," Education Economics, Taylor & Francis Journals, vol. 12(3), pages 231-249.
    16. Cooper, W. W. & Gu, Bisheng & Li, Shanling, 2001. "Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA," European Journal of Operational Research, Elsevier, vol. 132(1), pages 62-74, July.
    17. A T Flegg & D O Allen, 2007. "Using Coopers Approach to Explore the Extent of Congestion in the New British Universities," Economic Issues Journal Articles, Economic Issues, vol. 12(2), pages 47-82, September.
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    Cited by:

    1. Yaisawarng, Suthathip & Ng, Ying Chu, 2014. "The impact of higher education reform on research performance of Chinese universities," China Economic Review, Elsevier, vol. 31(C), pages 94-105.
    2. 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.
    3. Agostino, M. & Nifo, A. & Ruberto, S. & Scalera, D. & Trivieri, F., 2022. "Productivity changes in the automotive industry of three European countries. An application of the Malmquist index decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 216-226.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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.

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