Mutual information analysis of the factors influencing port throughput

Journal Article (2020)
Author(s)

Majid Eskafi (University of Iceland)

Milad Kowsari (University of Iceland)

Ali Dastgheib (IHE Delft Institute for Water Education)

Gudmundur F. Ulfarsson (University of Iceland)

P Taneja (TU Delft - Rivers, Ports, Waterways and Dredging Engineering)

Ragnheidur I. Thorarinsdottir (University of Iceland)

Research Group
Rivers, Ports, Waterways and Dredging Engineering
DOI related publication
https://doi.org/10.1108/MABR-05-2020-0030
More Info
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Publication Year
2020
Language
English
Research Group
Rivers, Ports, Waterways and Dredging Engineering
Issue number
2
Volume number
6 (2021)
Pages (from-to)
129-146

Abstract

Purpose
Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables.

Design/methodology/approach
Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable.

Findings
This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput.

Originality/value
Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.

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