Container handling operations using data envelopment analysis: A systematic review

This paper gives a systematic review of container handling operations analysis efficiency utilizing Data Envelopment Analysis (DEA). The goal of this research is to examine several studies on DEA models used to estimate efficiency. It was also intended to signify which decision-making unit (DMU), as...

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Bibliographic Details
Published in:AIP Conference Proceedings
Main Author: Aznam N.H.Z.; Khurizan N.S.N.
Format: Conference paper
Language:English
Published: American Institute of Physics 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188462249&doi=10.1063%2f5.0192201&partnerID=40&md5=56e6410fd6e8b8e744408522ac881db4
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Summary:This paper gives a systematic review of container handling operations analysis efficiency utilizing Data Envelopment Analysis (DEA). The goal of this research is to examine several studies on DEA models used to estimate efficiency. It was also intended to signify which decision-making unit (DMU), as well as input and output variables, were frequently utilized in this study. This paper examines 28 papers published on Scopus and Web of Science databases from 2011 to 2021. The chosen papers in this review were identified using a multi-stage selection procedure. Some eliminations were made to select research conducted employing DEA in container operations depending on the author's criteria. According to the findings, DEA in container operations was widely utilized in 2018 and 2021. Port was chosen as a decision-making unit in eleven studies (46%). The most commonly used input variable was "berth length"or "quay length". The most frequently used output variable was "container throughput."This study will enable financial institutions, corporations, academics, and researchers to analyse the port's efficiency by employing DEA for input and output variable selection, an essential stage in DEA applications. This research also aimed to create awareness among lawmakers and port managers to enhance the efficiency of operations. © 2024 Author(s).
ISSN:0094243X
DOI:10.1063/5.0192201