Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach

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 ut...

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Main Authors: Niamat Ullah Ibne Hossain, Farjana Nur, Raed Jaradat, Seyedmohsen Hosseini, Mohammad Marufuzzaman, Stephen M. Puryear, Randy K. Buchanan
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/3518705
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author Niamat Ullah Ibne Hossain
Farjana Nur
Raed Jaradat
Seyedmohsen Hosseini
Mohammad Marufuzzaman
Stephen M. Puryear
Randy K. Buchanan
author_facet Niamat Ullah Ibne Hossain
Farjana Nur
Raed Jaradat
Seyedmohsen Hosseini
Mohammad Marufuzzaman
Stephen M. Puryear
Randy K. Buchanan
author_sort Niamat Ullah Ibne Hossain
collection DOAJ
description 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.
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issn 1076-2787
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language English
publishDate 2019-01-01
publisher Wiley
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series Complexity
spelling doaj-art-6fa9a37db83644b19db80b3121c671ad2025-08-20T02:06:13ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/35187053518705Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based ApproachNiamat Ullah Ibne Hossain0Farjana Nur1Raed Jaradat2Seyedmohsen Hosseini3Mohammad Marufuzzaman4Stephen M. Puryear5Randy K. Buchanan6Department of Industrial and Systems Engineering, Mississippi State University, P.O. Box 9542, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Mississippi State University, P.O. Box 9542, Mississippi State, MS 39762, USADepartment of Industrial and Systems Engineering, Mississippi State University, P.O. Box 9542, Mississippi State, MS 39762, USAIndustrial Engineering Technology, University of Southern Mississippi, Long Beach, MS 39560, USADepartment of Industrial and Systems Engineering, Mississippi State University, P.O. Box 9542, Mississippi State, MS 39762, USACenter for Advanced Vehicular Systems Extension (CAVSE), Mississippi State University, 153 Mississippi Parkway, Canton, MS 39046, USAInstitute of Systems Engineering Research (ISER), U.S. Army Engineer Research Development Center (ERDC), 3909 Halls Ferry Rd, Vicksburg, MS 39180, USABecause 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.http://dx.doi.org/10.1155/2019/3518705
spellingShingle Niamat Ullah Ibne Hossain
Farjana Nur
Raed Jaradat
Seyedmohsen Hosseini
Mohammad Marufuzzaman
Stephen M. Puryear
Randy K. Buchanan
Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
Complexity
title Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
title_full Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
title_fullStr Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
title_full_unstemmed Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
title_short Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach
title_sort metrics for assessing overall performance of inland waterway ports a bayesian network based approach
url http://dx.doi.org/10.1155/2019/3518705
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