Moammer, M (2025) Developing a Readiness Assessment Model for Transforming Traditional Ports into Smart Ports. Doctoral thesis, Liverpool John Moores University.
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2025Maisem MoammerPhD.pdf - Published Version Restricted to Repository staff only until 17 March 2027. Available under License Creative Commons Attribution Non-commercial. Download (6MB) |
Abstract
Shipping goods by sea has been fundamental to human civilization for millennia. In recent centuries the volume of international trade has accelerated greatly, and ports have become of greater importance to humanity than ever before, including for basic economic survival and food security. Governments consider developing high-quality ports to be a basic requirement for long-term economic growth, as well as national political and food security and stability. As a result, the maritime industry is witnessing a major and pivotal shift towards developing traditional ports based on modern technological breakthroughs in many fields, involving smart information technologies and engineering advancements fuelling the emergence of smart ports and logistics services. Smart ports have emerged to meet the demands of ships transporting large quantities of goods, which necessitate swift and efficient handling operations, all while minimising environmental impacts, particularly in terms of energy and carbon efficiency. Traditional ports around the world are under great pressure to develop their facilities and operations to keep pace with developments in modern ports around the world, as well as the ability to receive these giant ships carrying thousands of containers. Implementing smart port projects has become essential for all traditional ports around the world, and ensuring successful implementation requires a comprehensive understanding of the multifaceted factors that affect their effectiveness. This doctoral thesis seeks to provide a comprehensive approach through which the most important factors influencing smart port projects can be identified. It achieves this through a rigorous and careful review of the literature, and then consideration of the opinions and judgements of experts to build a hierarchical model that identifies the complex interrelationship between the factors. This thesis uses a mixed approach, leveraging quantitative and qualitative data to determine the relative importance of important factors affecting smart port projects. It develops a framework using the Hierarchical Decision Model methodology to evaluate traditional ports’ preparedness for implementing smart port projects. The results prove the importance of all points of view, but to varying degrees. The research relied on experimental evidence from case studies to gain practical insights into the effectiveness of the proposed model in reality. The model has proven its ability to provide important and effective recommendations for each case study based on precise foundations while clarifying its strengths and weaknesses. In addition, the thesis presented implementable recommendations for port authorities to overcome the complexities surrounding port development and enhance maritime transport systems in a manner consistent with reducing environmental impact. The research identifies 19 factors as the most important factors influencing the smart port project, among which those pertaining to the infrastructure perspective is the most important in implementing smart port projects, followed by the technology perspective. The energy and environment perspectives came third and fourth in order of importance in the model. The thesis worked to provide a strong framework to support practical decisions in the field of modern logistics services (smart ports).
Item Type: | Thesis (Doctoral) |
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Uncontrolled Keywords: | Smart port; Port operation; Energy efficiency; Environmental impacts |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Engineering |
SWORD Depositor: | A Symplectic |
Date Deposited: | 18 Mar 2025 11:07 |
Last Modified: | 18 Mar 2025 11:08 |
DOI or ID number: | 10.24377/LJMU.t.00025842 |
Supervisors: | Bashir, M, Pyne, R and Wang, J |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/25842 |
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