Evaluating efficiency of international container shipping lines: A bootstrap DEA approach
In this article, a non-parametric analysis of the efficiency of major international container shipping lines (CSLs) is conducted in order to evaluate the effects of the recent profound global economic crisis on such a crucial sector in seaborne trade. Data Envelopment Analysis (DEA) is applied to highlight the efficiency status of top CSLs using a bias-corrected efficiency estimator. In the first stage, hypotheses regarding the underlying production frontier of major international CSLs are tested. In the second stage, an output-oriented, non-increasing returns to scale DEA model is used to compute efficiency scores estimates of the different CSLs. The model considers labour, number of ships and fleet capacity as inputs, and container throughput handled and turnover as outputs. Confidence interval estimates of efficiency and returns to scale for each CSL are reported. The results of the analysis indicate that none of the CSLs assessed operates under constant returns to scale and that average efficiency is 0.74, finding considerable waste in the production of CSLs for the year 2009. In addition, the major international CSLs in 2009 have oversized operations that exceed the most productive scale size. The evidence suggests that strategic alliance membership is not a guarantee for efficient practices in operations. There must be other reasons, purportedly of a strategic nature, for CSLs to join such alliances.
Year of publication: |
2014
|
---|---|
Authors: | Gutiérrez, Ester ; Lozano, Sebastián ; Furió, Salvador |
Published in: |
Maritime Economics and Logistics. - Palgrave Macmillan, ISSN 1479-2931. - Vol. 16.2014, 1, p. 55-71
|
Publisher: |
Palgrave Macmillan |
Saved in:
Saved in favorites
Similar items by person
-
Evaluating efficiency of international container shipping lines : a bootstrap DEA approach
Gutiérrez Moya, Ester, (2014)
-
Palacio, Antonio, (2016)
-
A complex network analysis of global tourism flows
Lozano, Sebastián, (2018)
- More ...