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Port Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case

Author

Listed:
  • Renata Machado de Andrade

    (Graduate School of Logistics, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

  • Suhyung Lee

    (Graduate School of Logistics, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

  • Paul Tae-Woo Lee

    (Ocean College, Zhejiang University, No.1, Haida Zheda Road, Zhoushan 316021, China)

  • Oh Kyoung Kwon

    (Asia Pacific School of Logistics, Graduate School of Logistics, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

  • Hye Min Chung

    (Graduate School of Logistics, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

Abstract

Data envelopment analysis (DEA) has many advantages for analyzing the efficiency of decision-making units, as well as drawbacks, such as a lack of discrimination power. This study applied bi-objective multiple-criteria data envelopment analysis (BiO-MCDEA), a programming approach used to overcome the limitations of traditional DEA models, to analyze the efficiency of 20 Brazilian ports with a consideration of six input and one output variables from 2010 to 2016. Two time-related variables were included to reflect current problems faced by Brazilian ports experiencing long wait times. The results reveal a significant disparity in port efficiency among Brazilian ports. The top five most efficient ports are those with the highest cargo throughput. A clustering analysis also confirmed a strong correlation between cargo throughput and port efficiency scores. Total time of stay, pier length, and courtyard also had strong correlations with the efficiency scores. The clustering method divided Brazilian ports into three groups: efficient ports, medium efficient ports, and inefficient ports.

Suggested Citation

  • Renata Machado de Andrade & Suhyung Lee & Paul Tae-Woo Lee & Oh Kyoung Kwon & Hye Min Chung, 2019. "Port Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:16:p:4340-:d:256733
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    References listed on IDEAS

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    1. Lee, Hsuan-Shih & Chu, Ching-Wu & Zhu, Joe, 2011. "Super-efficiency DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 212(1), pages 141-147, July.
    2. Wang, Ying-Ming & Chin, Kwai-Sang, 2011. "The use of OWA operator weights for cross-efficiency aggregation," Omega, Elsevier, vol. 39(5), pages 493-503, October.
    3. Tovar, Beatriz & Hernández, Rubén & Rodríguez-Déniz, Héctor, 2015. "Container port competitiveness and connectivity: The Canary Islands main ports case," Transport Policy, Elsevier, vol. 38(C), pages 40-51.
    4. Li, Xiao-Bai & Reeves, Gary R., 1999. "A multiple criteria approach to data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 507-517, June.
    5. Cabral, Alexandra Maria Rios & Ramos, Francisco de Sousa, 2014. "Cluster analysis of the competitiveness of container ports in Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 423-431.
    6. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    7. Yuen, Andrew Chi-lok & Zhang, Anming & Cheung, Waiman, 2013. "Foreign participation and competition: A way to improve the container port efficiency in China?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 220-231.
    8. Leonardo Ramos Rios & Antonio Carlos Gastaud Maçada, 2006. "Analysing the Relative Efficiency of Container Terminals of Mercosur using DEA," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(4), pages 331-346, December.
    9. Cullinane, Kevin & Wang, Teng-Fei & Song, Dong-Wook & Ji, Ping, 2006. "The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(4), pages 354-374, May.
    10. Carlos Pestana Barros & J. Augusto Felício & Renato Leite Fernandes, 2012. "Productivity analysis of Brazilian seaports," Maritime Policy & Management, Taylor & Francis Journals, vol. 39(5), pages 503-523, September.
    11. Wanke, Peter F., 2013. "Physical infrastructure and flight consolidation efficiency drivers in Brazilian airports: A two-stage network-DEA approach," Journal of Air Transport Management, Elsevier, vol. 31(C), pages 1-5.
    12. Timothy Anderson & Keith Hollingsworth & Lane Inman, 2002. "The Fixed Weighting Nature of A Cross-Evaluation Model," Journal of Productivity Analysis, Springer, vol. 17(3), pages 249-255, May.
    13. Wanke, Peter F., 2013. "Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach," Transport Policy, Elsevier, vol. 29(C), pages 145-153.
    14. Gabriel Figueiredo de Oliveira & Pierre Cariou, 2011. "A DEA study of the efficiency of 122 iron ore and coal ports and of 15/17 countries in 2005," Maritime Policy & Management, Taylor & Francis Journals, vol. 38(7), pages 727-743, May.
    15. Halvor Schøyen & James Odeck, 2013. "The technical efficiency of Norwegian container ports: A comparison to some Nordic and UK container ports using Data Envelopment Analysis (DEA)," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 15(2), pages 197-221, June.
    16. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    17. Carlos Pestana Barros, 2006. "A Benchmark Analysis of Italian Seaports Using Data Envelopment Analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(4), pages 347-365, December.
    18. Tongzon, Jose, 2001. "Efficiency measurement of selected Australian and other international ports using data envelopment analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 107-122, February.
    19. Peter Wanke & Rafael Garcia Barbastefano & Maria Fernanda Hijjar, 2011. "Determinants of Efficiency at Major Brazilian Port Terminals," Transport Reviews, Taylor & Francis Journals, vol. 31(5), pages 653-677.
    20. Ghasemi, M.-R. & Ignatius, Joshua & Emrouznejad, Ali, 2014. "A bi-objective weighted model for improving the discrimination power in MCDEA," European Journal of Operational Research, Elsevier, vol. 233(3), pages 640-650.
    21. Lee, Hsuan-Shih & Zhu, Joe, 2012. "Super-efficiency infeasibility and zero data in DEA," European Journal of Operational Research, Elsevier, vol. 216(2), pages 429-433.
    22. Teng-Fei Wang & Kevin Cullinane & Dong-Wook Song, 2005. "Container Port Production and Economic Efficiency," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-50597-1.
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