Author:
Eskafi Majid,Kowsari Milad,Dastgheib Ali,Ulfarsson Gudmundur F.,Taneja Poonam,Thorarinsdottir Ragnheidur I.
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.
Subject
Management of Technology and Innovation,Strategy and Management,Transportation,Business and International Management
Reference52 articles.
1. Exploratory modeling for policy analysis;Operations Research,1993
2. Port cargo throughput forecasting based on combination model,2016
3. A modified regression model for forecasting the volumes of Taiwan’s import containers;Mathematical and Computer Modelling,2008
4. Combining models and commodity chain research for making long-term projections of port throughput: an application to the Hamburg-Le Havre range;European Journal of Transport and Infrastructure Research,2012
5. Throughput forecasting of different types of cargo in the Adriatic seaport Koper;Maritime Policy and Management,2020
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献