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Groups in DEA based cross-evaluation: An application to Asian container ports

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  • Jie Wu
  • Hong Yan
  • John Liu

Abstract

In container port performance evaluation, a group of ports in one country is always significantly different from a group of ports in another country. This is noticed as the heterogeneity of port performance. It is therefore necessary to further investigate the impact of the different groups on efficiency evaluation of ports. The cross-evaluation method is a DEA extension tool to identify best performing DMUs and to rank DMUs using cross efficiency scores linked to all DMUs. A factor that possibly reduces the usefulness of the cross efficiency evaluation method is that cross efficiency scores may not be unique due to the presence of alternative optima. Doyle and Green 1 propose the use of secondary goals to deal with the non-uniqueness issue by the aggressive / benevolent model formulations. This article extends the model of Doyle and Green by considering the groups of DMUs in the determination of final cross efficiency. A new approach based on cross efficiency evaluation method is developed and applied to efficiency analysis of 28 container ports from 12 countries in Asia. A comparative study between traditional and newly proposed methods is conducted.

Suggested Citation

  • Jie Wu & Hong Yan & John Liu, 2009. "Groups in DEA based cross-evaluation: An application to Asian container ports," Maritime Policy & Management, Taylor & Francis Journals, vol. 36(6), pages 545-558, December.
  • Handle: RePEc:taf:marpmg:v:36:y:2009:i:6:p:545-558
    DOI: 10.1080/03088830903346095
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    Cited by:

    1. 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.
    2. Ganji, Seyedreza Seyedalizadeh & Rassafi, Amir Abbas & Bandari, Samaneh Jamshidi, 2020. "Application of evidential reasoning approach and OWA operator weights in road safety evaluation considering the best and worst practice frontiers," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).

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