Metrics for assessing overall performance of inland waterway ports : a Bayesian Network based approach

Abstract

Because ports are considered to be the heart of the maritime transportation system, thereby assessing port performance is necessary for a nation’s development and economic success. This study proposes a novel metric, namely, “port performance index (PPI)”, to determine the overall performance and utilization of inland waterway ports based on six criteria, port facility, port availability, port economics, port service, port connectivity, and port environment. Unlike existing literature, which mainly ranks ports based on quantitative factors, this study utilizes a Bayesian Network (BN) model that focuses on both quantitative and qualitative factors to rank a port. The assessment of inland waterway port performance is further analyzed based on different advanced techniques such as sensitivity analysis and belief propagation. Insights drawn from the study show that all the six criteria are necessary to predict PPI. The study also showed that port service has the highest impact while port economics has the lowest impact among the six criteria on PPI for inland waterway ports.

Performance Analysis in Production Systems with Uncertain Data: A Stochastic Data Envelopment Analysis Approach

“…is model is formulated under variable returns to scale and its efficiency score is obtained from the following formula. 4 Complexity…”

“…In the last two decades, performance analysis in an uncertain environment has been studied frequently. See for instances Hossain et al [4], Mo et al [5], Rong et al [6], Amirteimoori et al [7], and Ghasemi et al [8]. Some of the differences between DEA and stochastic DEA (SDEA) models have been presented in Table 1.…”