Sea transport is the backbone of international trade and economy. According to the UNCTAD, maritime transport accounts for about 80 percent of world trade volume, an enormous amount handled daily by ports worldwide. The relationship between port infrastructure and international trade is linked inextricably since ports remain the main gateway for international trade. Therefore, all international ports have as their goal the effective and efficient management of ever increasing cargo. Although some previous research had attempted to investigate the impact of the port efficiency on international trade, we found that some biases remain in their measurement model. In order to correct such biases, this study developed a new port efficiency measurement model using the bootstrapping SBM-DEA. The study then built the linkage model with the international trade by applying the gravity model in consideration with the PPML and MR term. We used and analysed data from 2002–2012 on 23 major container ports in China and the trade data. The result of our robust model shows a more significant and positive impact of port efficiency on international trade than in other models. Thus, this research is expected to fill the research gap in the literature by providing a more robust model for investigating the relationship between port efficiency and international trade and to expand the literature in trade research area.

Data envelopment analysis (DEA) has many advantages for analyzing the efficiency of decision-making units, as well as drawbacks, such as a lack of discrimination power. This study applied bi-objective multiple-criteria data envelopment analysis (BiO-MCDEA), a programming approach used to overcome the limitations of traditional DEA models, to analyze the efficiency of 20 Brazilian ports with a consideration of six input and one output variables from 2010 to 2016. Two time-related variables were included to reflect current problems faced by Brazilian ports experiencing long wait times. The results reveal a significant disparity in port efficiency among Brazilian ports. The top five most efficient ports are those with the highest cargo throughput. A clustering analysis also confirmed a strong correlation between cargo throughput and port efficiency scores. Total time of stay, pier length, and courtyard also had strong correlations with the efficiency scores. The clustering method divided Brazilian ports into three groups: efficient ports, medium efficient ports, and inefficient ports.