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Assessing container operator efficiency with heterogeneous and time-varying production frontiers

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  • Yan, Jia
  • Sun, Xinyu
  • Liu, John J.

Abstract

We build an empirical model under the stochastic frontier framework to assess production efficiencies of container operators from the world's major container ports in the years between 1997 and 2004. The empirical model measures efficiencies, efficiency changes, and time-persistence of efficiencies after controlling for the individual heterogeneity in technology and technical change. The model is estimated using a Bayesian approach via the Markov Chain Monte-Carlo simulation. We find that the mean efficiency level of the container operators is in the range of 70-90% of their full efficiencies, and the mean efficiency changed with time slightly. However, the percentage of highly efficient operators has increased since 1997. Common model misspecifications without controlling for the individual heterogeneity and technical change can alter the results dramatically.

Suggested Citation

  • Yan, Jia & Sun, Xinyu & Liu, John J., 2009. "Assessing container operator efficiency with heterogeneous and time-varying production frontiers," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 172-185, January.
    • Handle: RePEc:eee:transb:v:43:y:2009:i:1:p:172-185
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    Cited by:

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    2. Assaf, A. George & Gillen, David & Tsionas, Efthymios G., 2014. "Understanding relative efficiency among airports: A general dynamic model for distinguishing technical and allocative efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 18-34.
    3. Talley, Wayne K. & Ng, ManWo, 2013. "Maritime transport chain choice by carriers, ports and shippers," International Journal of Production Economics, Elsevier, vol. 142(2), pages 311-316.
    4. Suárez-Alemán, Ancor & Morales Sarriera, Javier & Serebrisky, Tomás & Trujillo, Lourdes, 2016. "When it comes to container port efficiency, are all developing regions equal?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 56-77.
    5. Tsionas, Efthymios & Assaf, A. George & Gillen, David & Mattila, Anna S., 2017. "Modeling technical and service efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 113-125.
    6. César Ducruet & Hidekazu Itoh, 2022. "Spatial network analysis of container port operations: the case of ship turnaround times," EconomiX Working Papers 2022-15, University of Paris Nanterre, EconomiX.
    7. 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.
    8. Barros, Carlos P. & Bin Liang, Qi & Peypoch, Nicolas, 2013. "The efficiency of French regional airports: An inverse B-convex analysis," International Journal of Production Economics, Elsevier, vol. 141(2), pages 668-674.
    9. Wang, Sun Ling & Newton, Doris J., 2015. "Productivity and Efficiency of U.S. Field Crop Farms: A Look at Farm Size and Operator’s Gender," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205344, Agricultural and Applied Economics Association.
    10. Yip, Tsz Leung & Sun, Xin Yu & Liu, John J., 2011. "Group and individual heterogeneity in a stochastic frontier model: Container terminal operators," European Journal of Operational Research, Elsevier, vol. 213(3), pages 517-525, September.
    11. Suárez-Alemán, Ancor & Morales Sarriera, Javier & Serebrisky, Tomás & Trujillo, Lourdes, 2016. "When it comes to container port efficiency, are all developing regions equal?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 56-77.
    12. César Ducruet & Hidekazu Itoh, 2022. "Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times," Networks and Spatial Economics, Springer, vol. 22(4), pages 883-902, December.
    13. Sanderson Abel & Alex Bara & Pierre Le Roux, 2019. "Evaluating Bank Cost Efficiency Using Stochastic Frontier Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 11(3), pages 48-57.
    14. Chen, Xiaodong & Guo, Anda & Miao, Zhuang & Zhu, Pengyu, 2024. "Assessing the performance of the transport sector within the global supply chain context: Decomposition of energy and environmental productivity," Applied Energy, Elsevier, vol. 358(C).
    15. 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.

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