Container terminals' efficiency with the unexpected output: a revised SBM approach

Area of Science:

• Environmental Science
• Operations Research
• Maritime Logistics

Background:

• Port operations significantly contribute to greenhouse gas (GHG) emissions, exacerbating climate change.
• International Maritime Organization (IMO) and national governments have implemented regulations to reduce port-related pollution.
• Assessing container terminal efficiency must account for environmental impacts like CO2 emissions.

Purpose of the Study:

• To develop a revised Slack-Based Model Data Envelopment Analysis (SBM-DEA) to evaluate container terminal efficiency.
• To incorporate carbon dioxide (CO2) emissions as an undesirable output in efficiency assessments.
• To provide a comprehensive methodology for reducing air pollution in port areas.

Main Methods:

• Utilized cluster analysis to ensure homogeneity among decision-making units (DMUs).
• Proposed a power utilization approach to estimate CO2 emissions from container terminal operators (CTOs).
• Developed a revised SBM-DEA model integrating CO2 emissions for a complete efficiency ranking.

Main Results:

• The revised SBM-DEA model successfully ranked the efficiency of 12 CTOs in Vietnam.
• Identified strategies for CTOs to reduce CO2 emissions using slack variables.
• Demonstrated that efficiency can be maintained while reducing environmental impact.

Conclusions:

• The proposed methodology offers a robust framework for evaluating and improving container terminal operational and environmental efficiency.
• CTOs can leverage the model's insights to mitigate CO2 emissions effectively.
• This research contributes to sustainable port operations and climate change mitigation efforts.