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Benchmarking Sustainability Performance of Ports

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Benchmarking Sustainability Performance of Ports

Adegoke, Akolade (2018) Benchmarking Sustainability Performance of Ports. Masters thesis, Concordia University.

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Abstract

Sustainable development agendas are challenging the world and ports, in particular, to find ways to become more efficient while meeting economic, social and environmental objectives. Although there has been a considerable body of documentation on green port practices and performance in Europe and America, there is limited synthesis about evaluation of sustainable practices in the Canadian ports context. This research aims to provide a modeling framework for benchmarking the sustainability performance of ports and to identify targets for improvement.

A two-step approach is proposed. First, a review of literature and initiatives employed by global port authorities is conducted to identify major sustainability performance indicators. Second, data envelopment analysis (DEA) is applied to evaluate port performance while taking into account the dimensions of sustainable development. The DEA models evaluate both undesirable and desirable outputs for ports. Three categories of models are proposed namely; ignoring undesirable output, treating undesirable output as input, and directional distance function under variable and constant returns to scale. A case study for 13 North American ports is conducted. The results indicate that performance evaluations vary with economic and social criteria. The indicators and methodology undertaken can be used by ports and other industrial service sectors for improving green performance.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (Masters)
Authors:Adegoke, Akolade
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Industrial Engineering
Date:13 June 2018
Thesis Supervisor(s):Awasthi, Anjali
Keywords:Ports; Sustainability Measurement; Performance Analysis; Benchmarking; Data Envelopment Analysis
ID Code:984075
Deposited By: Akolade Adegoke
Deposited On:16 Nov 2018 16:19
Last Modified:16 Nov 2018 16:19
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