Environmental efficiency assessment of Dublin Port using two-stage non-radial DEA model

Boban Djordjević, Raja Maitra, Bidisha Ghosh

Research output: Contribution to journalArticlepeer-review

Abstract

The operation of a port is of critical economic importance because of its role in international trade. However, increased operations increase the port's environmental impact and contribute to climate change and global warming. Dublin Port is one of the busiest ports in Ireland, and throughput is expected to increase as the economy continues to grow. Achieving a balance between growing economic activity and reducing environmental impacts is critical to a sustainable future. The efficiency of the port considering operation, economic, and environmental factors can be evaluated using the well-known nonparametric model of Data Envelopment Analysis (DEA). In this study, a novel two-stage non-radial DEA model is used to evaluate the environmental efficiency of Dublin Port considering landward and seaward operations. The proposed two-stage model DEA isolates the efficiency of the two port sides and calculates the overall efficiency. The model minimizes Dublin Port's annual CO2 emissions by reducing a combination of variables that can be realistically controlled by engineering and policy measures. The analysis was extended to account for possible variations in a number of key environmental output factors to compensate for the lack of real-world data availability. The study found that the number of terminals and capital expenditures have significant impacts on the port's environmental efficiency. Small adjustments or reductions in key indicators can improve Dublin Port's efficiency. This methodology can be applied to other ports in growing economies that use similar indicators to assess their environmental efficiency.

Original languageEnglish
Article number100078
JournalMaritime Transport Research
Volume4
DOIs
Publication statusPublished - Jun 2023

Keywords

  • Dublin Port
  • Environmental efficiency
  • Non-radial DEA
  • Optimization
  • Two-stage DEA

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