Measuring the operational efficiency of dry ports using DEA approach

Abstract Dry ports facilitate the containerization trade by connecting seaports with their hinterlands, yet their operational efficiency remains scarcely examined in the existing literature. This study addresses the gap by developing an input–output model to measure the operational efficiency of dry ports which includes 18 private dry ports in Bangladesh for the study. An output-oriented Data Envelopment Analysis (DEA) model with constant returns to scale was applied, incorporating nine input variables and three output variables identified through a systematic literature review. Cross-efficiency and super-efficiency analyses were further employed to enable robust benchmarking beyond self-evaluation. The results reveal that 11 out of 18 dry ports (61%) achieved full efficiency in all three years studied (2019 to 2021), while four dry ports remained persistently inefficient. Infrastructural and operational factors, including equipment capacity, total area, manpower and distance from the seaport, were found to be the key determinants of dry port performance. Five dry ports emerged as consistently strong benchmarks and four were identified as persistently inefficient which require targeted intervention. Unlike most prior DEA studies that focus on seaports, this study contributes a replicable benchmarking framework specifically designed for dry ports. It offers actionable insights for port operators, logistics planners and policymakers in Bangladesh and other developing economies seeking to improve hinterland logistics performance.