Probabilistic analysis of the sustainable performance of container terminals

Since port activity is essential for countless supply chains, its operational efficiency is a relevant research topic for logistics and transport management. In order to be able to analyze, measure and improve its performance, it is necessary to establish evaluation criteria that take into account not only economic aspects, but also society and the environment. However, this type of evaluation generally uses deterministic data for the performance indicators, distorting the real result of its values and hindering adequate decision-making. Thus, this research aims to propose a probabilistic analysis of container terminals' sustainable performance, taking into account uncertainties that the indicators' values can assume. Methodologically, the study was supported by secondary data collection in nine container terminals, followed by a Gray Relational Analysis and Monte Carlo Simulation. With respect to the case study, it is observed that the indicator “number of jobs generated” is the one that most penalized the sustainable performance of the analyzed terminals, whereas, antagonistically, the “net revenue” had little influence on the sustainability indexes. Also noteworthy is that the generation of performance probability curves for each terminal promoted a more appropriate analysis for decision-making at the corporate and governmental levels.