Performance Based Clustering for Benchmarking of Container Ports: an Application of Dea and Cluster Analysis Technique

DOI

10.2991/ijcis.2010.3.6.2How to use a DOI?

Keywords

Decision support systems; Data envelopment analysis; Performance measurement; Machine learning; Benchmarking; Container ports

Abstract

The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA), an effective tool for relative efficiency assessment, is utilized for measuring the performances and benchmarking of the 77 world container ports in 2007. The used approaches in the current study consider four inputs (Capacity of Cargo Handling Machines, Number of Berths, Terminal Area and Storage Capacity) and a single output (Container Throughput). The results for the efficiency scores are analyzed, and a unique ordering of the ports based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing ports to use as benchmarks.

Copyright

© 2010, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Jie Wu
AU  - Liang Liang
AU  - Malin Song
PY  - 2010
DA  - 2010/12/01
TI  - Performance Based Clustering for Benchmarking of Container Ports: an Application of Dea and Cluster Analysis Technique
JO  - International Journal of Computational Intelligence Systems
SP  - 709
EP  - 722
VL  - 3
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.6.2
DO  - 10.2991/ijcis.2010.3.6.2
ID  - Wu2010
ER  -