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

Emissions of greenhouse gases (GHGs) from port operations are a major environmental factor contributing to the problem of climate change. To cope with this challenge, International Maritime Organization (IMO) and port governments in nations have developed stringent regulations to curb the release of GHGs and other pollutants. To contribute a methodology towards the reduction in air pollution at port areas, the paper aims to assess container terminals' (CTs) efficiency by considering the unexpected output (i.e., CO₂ emissions) in their operations by a revised SBM-DEA model. The main originality of this paper includes (1) using cluster analysis to determine the homogeneity of decision-making units (DMUs), (2) proposing the power utilization approach to estimate the amount of CO₂ emissions released by container terminal operators (CTOs), (3) incorporating CO₂ emissions into the assessment model to provide a complete efficiency ranking for CTs, and (4) developing the revised SBM to estimate efficiency scores for CT operations. Finally, 12 CTOs affiliated with the SNP corporation of Vietnam were empirically employed to validate the research model. Based on the result from the proposed research model, CTOs might reduce the amount of CO₂ emissions by adopting the slack variables while guaranteeing their operating efficiency.