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DEA models for identifying sensitive performance measures in container port evaluation

Author

Listed:
  • Jie Wu

    (School of Management, University of Science and Technology of China, Hefei, Anhui Province, People's Republic of China)

  • Hong Yan

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China)

  • John Liu

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China)

Abstract

In the container port performance evaluation, the heterogeneity of input or output measures often exist owing to non-controllable external factors such as geographical location, regional economy, political systems and so on. Therefore, it becomes imperative to investigate the individual input or output measures so as to identify their specific impact on the efficiency of a port. In addition, the purpose of performance evaluation cannot be a mere exercise of candidate ranking. The purpose of this article is to study ways of retaining efficiency and improving on inefficiency. The article utilizes the conventional Data Envelopment Analysis model to test the sensitivity of the individual input and output of a decision-making unit (DMU). For an efficient DMU, we measure how much an input can be increased, or an output decreased, without changing its efficiency status. For an inefficient DMU, we measure how much an input should be decreased, or an output increased, to make it achieve the best practice frontier. The new approaches are applied to the efficiency analysis of 77 global container ports. The results indicate that the number of berths and the capital deployed are the most sensitive measures impacting performance of most container ports. The analysis also reveals that container ports located in different continents behave differently.

Suggested Citation

  • Jie Wu & Hong Yan & John Liu, 2010. "DEA models for identifying sensitive performance measures in container port evaluation," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(3), pages 215-236, September.
  • Handle: RePEc:pal:marecl:v:12:y:2010:i:3:p:215-236
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    Citations

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    Cited by:

    1. Odeck, James & Schøyen, Halvor, 2020. "Productivity and convergence in Norwegian container seaports: An SFA-based Malmquist productivity index approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 222-239.
    2. Odeck, James & Bråthen, Svein, 2012. "A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: A comparison of fixed and random-effects regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1574-1585.
    3. Gong, Xiaoxing & Wu, Xiaofan & Luo, Meifeng, 2019. "Company performance and environmental efficiency: A case study for shipping enterprises," Transport Policy, Elsevier, vol. 82(C), pages 96-106.
    4. Stephen Hynes & Ingrid Mateo-Mantecón & Eamonn O’Connor & Andreas Tsakiridis, 2020. "Relative size and technical efficiency in peripheral port markets: evidence from Irish and North Atlantic Spanish ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(3), pages 383-402, September.
    5. Marcelo Müller Beuren & Rafael Andriotti & Guilherme Bergmann Borges Vieira & José Luis Duarte Ribeiro & Francisco José Kliemann Neto, 2018. "On measuring the efficiency of Brazilian ports and their management models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(1), pages 149-168, March.
    6. Evelin Krmac & Mozhgan Mansouri Kaleibar, 2023. "A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(4), pages 817-881, December.
    7. Leonardo Ensslin & Vinicius Dezem & Ademar Dutra & Sandra Rolim Ensslin & Karine Somensi, 2018. "Seaport-performance tools: an analysis of the international literature," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(4), pages 587-602, December.
    8. Deepankar Sinha & Shuvo Roy Chowdhury, 2017. "Optimizing Private and Public Mode of Operation in Major Ports of India for Better Customer Service," Working Papers 1732, Indian Institute of Foreign Trade.
    9. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    10. Deepankar Sinha & Shuvo Roy Chowdhury, 2017. "Optimizing Private and Public Mode of Operation in Major Ports of India for Better Customer Service," Working Papers LD-17-32, Indian Institute of Foreign Trade.
    11. B. Adenso-Díaz & N. García Álvarez & J. A. Lago Alba, 2020. "A fuzzy AHP classification of container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(2), pages 218-238, June.
    12. Hynes, S. & Mateo-Mantecón, I. & O’Connor, E. & Tsakiridis, A., 2019. "Examining the relationship between relative size and technical efficiency in peripheral port markets: Evidence from Irish and North Atlantic Spanish ports," Working Papers 309603, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    13. Mrinal Kumar Dasgupta & Deepankar Sinha, 2016. "Impact of Privatization of Ports on Relative Efficiency of Major Ports of India," Foreign Trade Review, , vol. 51(3), pages 225-247, August.

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