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Analysis on pure e-commerce congestion effect, productivity effect and profitability in China

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  • Yang, Zhuofan
  • Shi, Yong
  • Yan, Hong

Abstract

This paper examines the relationship of e-commerce congestion effect, productivity effect and profit generation in China. The technique of Data Envelopment Analysis (DEA) is used to measure returns to scale and total factor productivity in e-commerce. The results show that e-commerce firms achieve productivity growth but suffer from input congestion. Congestion weakens profitability and leads to negative returns of inputs to outputs. This finding offers a new insight to explain the determinants of profit change. This research enriches production theory of internet companies, and helps managers strengthen their profitability by measuring the existence of congestion and eliminating input congestion resources.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:soceps:v:57:y:2017:i:c:p:35-49
    DOI: 10.1016/j.seps.2016.08.002
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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. Irene Bertschek & Helmut Fryges & Ulrich Kaiser, 2006. "B2B or Not to Be: Does B2B E-Commerce Increase Labour Productivity?," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 13(3), pages 387-405.
    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. Garrigosa, E Genescá & Tatjé, E Grifell, 1992. "Profits and total factor productivity: A comparative analysis," Omega, Elsevier, vol. 20(5-6), pages 553-568.
    5. 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.
    6. 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.
    7. 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.
    8. Marques, Rui Cunha & Simões, Pedro, 2010. "Measuring the influence of congestion on efficiency in worldwide airports," Journal of Air Transport Management, Elsevier, vol. 16(6), pages 334-336.
    9. 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.
    10. 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.
    11. 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.
    12. William Greene & Dan Segal, 2004. "Profitability and Efficiency in the U.S. Life Insurance Industry," Journal of Productivity Analysis, Springer, vol. 21(3), pages 229-247, May.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. 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.
    15. Anandhi S. Bharadwaj & Sundar G. Bharadwaj & Benn R. Konsynski, 1999. "Information Technology Effects on Firm Performance as Measured by Tobin's q," Management Science, INFORMS, vol. 45(7), pages 1008-1024, July.
    16. Odeck, James, 2006. "Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway," Socio-Economic Planning Sciences, Elsevier, vol. 40(1), pages 52-69, March.
    17. An, Qingxian & Yan, Hong & Wu, Jie & Liang, Liang, 2016. "Internal resource waste and centralization degree in two-stage systems: An efficiency analysis," Omega, Elsevier, vol. 61(C), pages 89-99.
    18. 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.
    19. Kurosawa, Kazukiyo, 1975. "An aggregate index for the analysis of productivity and profitability," Omega, Elsevier, vol. 3(2), pages 157-168, April.
    20. 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.
    21. Oral, Muhittin & Yolalan, Reha, 1990. "An empirical study on measuring operating efficiency and profitability of bank branches," European Journal of Operational Research, Elsevier, vol. 46(3), pages 282-294, June.
    22. Liu, Ting-Kun & Chen, Jong-Rong & Huang, Cliff C.J. & Yang, Chih-Hai, 2013. "E-commerce, R&D, and productivity: Firm-level evidence from Taiwan," Information Economics and Policy, Elsevier, vol. 25(4), pages 272-283.
    23. E. Grifell-Tatjé & C. A. K. Lovell, 1999. "Profits and Productivity," Management Science, INFORMS, vol. 45(9), pages 1177-1193, September.
    24. Mohamed M. Mostafa, 2010. "Does efficiency matter?," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 59(3), pages 255-273, March.
    25. Gold, Bela, 1973. "Technology, productivity and economic analysis," Omega, Elsevier, vol. 1(1), pages 5-24, February.
    26. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    27. 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.
    28. 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.
    29. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
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