The abatement of greenhouse gas emissions represents a major global challenge and an important topic for transportation research. Several studies have argued that energy efficiency measures for virtual arrival and associated reduced anchorage time can significantly reduce emissions from ships by allowing for speed reduction on passage. However, virtual arrival is uncommon in shipping. In this paper, we examine the causes for waiting time for ships at anchor and the limited uptake of virtual arrival. We show the difficulties associated with the implementation of virtual arrival and explain why shipping is unlikely to achieve the related abatement potential as assumed by previous studies. Combining onboard observations with seafarers and interviews with both sea-staff and shore-based operational personnel we show how charterers’ commercial priorities outweigh the fuel saving benefits associated with virtual arrival. Moreover, we demonstrate how virtual arrival systems have unintended, negative consequences for seafarers in the form of fatigue. Our findings have implications for the IMO’s greenhouse gas abatement goals.
The DNV Nordic Maritime Universities Workshop is organized as a collaboration between DNV and universities in the Nordic region with a maritime related education or research line. The workshop covers all research topics related to naval architecture, maritime engineering and maritime transport, including safety, energy efficiency and environmental performance, environmental pressures, new technologies and digitalization. The 25th Nordic Maritime Universities Workshop was held on 30-31 January 2025 at the Technical University of Denmark (DTU), Lyngby Campus. The workshop has been organized and hosted by the Maritime Group at the Department of Civil and Mechanical Engineering (DTU Construct). In total we received 77 abstracts from 7 countries. This includes 23 abstracts from Denmark, 23 from Sweden, 16 from Norway, 10 from Germany, 3 from Finland, 1 from The Netherlands, and 1 from Poland. The presentation of the abstracts and the talks is carried out over two days of the workshop and in 10 sessions, distributed over 7 topics:
• Maritime Safety & Risk Reduction (17 talks)
• Structures & Ship Design (8 talks)
• Numerical Methods & Marine Hydrodynamics (14 talks)
• Ship Operations & Navigation (14 talks)
• Autonomous Shipping & Digitalization (8 talks)
• Alternative Marine Fuels (8 talks)
• Wind Assisted & Alternative Propulsion (8 talks)
This year a special issue has been initiated in International Shipbuilding Progress to commemorate the 25th Nordic Maritime Universities Workshop. All abstract presenters have been invited to submit a full paper, to be considered for publication in this journal after a peer-review process. This compendium includes the workshop program, the session details and the 77 abstracts arranged in alphabetical order.
This paper studies the Quay Crane Scheduling Problem (QCSP). The QCSP determines how a number of quay cranes should be scheduled in order to service a vessel with minimum makespan. Previous work considers the QCSP to be a combinatorially hard problem. For that reason, the focus has been on developing efficient heuristics. Our study shows, however, that the QCSP is tractable in the realistic setting, where quay cranes can share the workload of bays. We introduce a novel linear time algorithm that solves the QCSP and prove its correctness.
Even though that there has been increasing focus on the energy-efficient operation of vessels and that the knowledge of cost-effective improvements is widespread in the industry, energy-efficient operation is only a minor topic on board many working vessels. A significant reduction in fuel can be achieved through changes in the operational practices, but to establish a successful system for best practices within energy-management the installation of a decision support system is essential. This article presents a decision support system for working vessels to determine best practice for the reduction of fuel consumption. Requirements for the system are defined through interviews with crew and observations on board vessels. Case studies are used for illustrating the usefulness. The use of generators onboard is analyzed using the software. It is found that the generators are not running optimally, but the crew can use the software to re-organize and find the most fuel-efficient loading range for the generators on board.
Due to limited access to domain knowledge and domain-relevant benchmark data, the Container Stowage Planning Problem (CSPP) is notably under-researched. In particular, previous models of the CSPP have lacked two key aspects of the problem: lashing forces and paired block stowage. The former may reduce vessel capacity by up to 10%, and the latter is NP-hard. The Representative CSPP (RCSPP), which captures all critical aspects of the problem is formulated. The presented RCSPP incorporates overlooked constraints such as paired block stowage and lashing, along with an innovative method for estimating lashing forces, all while maintaining simplicity. A heuristic method, STOW, has been developed to identify solutions for the RCSPP using a specially designed benchmark suite based on real-world scenarios. STOW algorithm is an advanced search heuristic employing a diverse range of solution modification strategies, each tailored to address specific aspects of stowage optimization. Feasible solutions were successfully identified for all instances within the benchmark suite. Our initial findings emphasize the importance of accurately modeling lashing forces and employing paired block stowage. Results show that removing the lashing constraint can increase the number of containers stowed by over 7% on average, while disabling paired block stowage can result in nearly a 5% increase.
Our research highlights the current state and trends of artificial intelligence (AI) adoption in Denmark’s chartering, particularly in the dry bulk and tanker segments. Companies in the dry bulk sector are leading AI adoption, with the tanker segment closely following and adoption rates in our sample appear higher than national averages reported by consultancies. Most firms are in either the experimental phase or transitioning toward more integrated AI systems, often opting for hybrid models that allow them to maintain internal control over key processes. Factors such as company size and maturity also influence the pace and approach to AI adoption.AI is seen as a tool to enhance rather than replace jobs in the early stages of shipping operations, especially in pre-fixture activities. However, there is greater potential for automation and job substitution in the post-fixture phase, particularly in tasks such as contract (CP) management.
On the supply side, the market for maritime AI and software solutions is highly competitive and fragmented, with many providers offering diverse products. Recent consolidation trends reflect different strategies: some companies, like are specializing in core offerings, while others, like are diversifying into both SaaS and pure software models. These consolidations are not only intensifying competition but also fostering partnerships between rivals—a dynamic known as coopetition. Interestingly, some shipping firms are entering the software market themselves, signaling innovation in business models. Machine learning (ML) technologies are primarily used in pre-fixture tools (like email management and tracking), while generative AI is increasingly applied in post-fixture functions, particularly contract management.
The oceans, covering approximately 70% of Earth's surface, play a pivotal role in climate regulation, biodiversity, and biogeochemical processes. The large and growing volume and complexity of ocean data, spanning diverse disciplines and formats, and dispersed across a wide range of sources, presents opportunities and challenges for advancing scientific research, informing policy, and addressing societal needs.
In this review paper we aim to create an easy-to-navigate map of the field of ocean data, enabling the reader to establish a broad understanding of the ocean data sector, and bridging gaps between different disciplines and levels of familiarity with ocean data. This is done through the concept of the "data ecosystem", which is used to describe the actors, organisations, and infrastructures involved in all aspects of the data value chain. We propose a structured ocean data ecosystem model as a method for comprehensive mapping of the ocean data market landscape. The proposed model consists of five key elements: stakeholders, societal elements, data sources and product offering, standards and best practices, and emerging technologies. We provide an up-to-date analysis of ocean data sources and emerging solutions and a summary of relevant data standardization efforts such as marine standards, vocabularies, and ontologies. All this will promote the development of needs-based solutions, components, products, services, and technologies, thus contributing to the evolution of the ocean data ecosystem and promoting data-based ocean research.
This white paper shows how small and medium sized companies (SME) involved in supply chains affiliated to the maritime industry and port industrial areas are challenged by the diffusion of technologies and managerial principles associated with Industry 4.0 with a special focus on blockchain technology. Blockchain technology creates potential for added value through transparency and auditability of data flows that arise through system decentralization, where intermediary parties such as a central authority will not store data or verify transactions. Instead of conventional workflows, the technology brings new approaches to collaboration by combining multiple parties with equality of data ownership. In doing so, blockchain technology challenges conventional rules of data ownership.
While attention on blockchain technology has been increasing, most blockchain projects are still under development. However, the technology gained ground in areas such as healthcare, governance, and supply chain management. This white paper focuses on the potentials and challenges of blockchain technology in maritime related supply chains.
Based on a discussion of industry preparedness for Industry 4.0, a taxonomy of blockchain adoption is presented. The taxonomy is based on two dimensions including: (1) the digital complexity of internal activities and (2) the degree of value chain integration between actors in the supply chain. The dimensions encompass four archetypes of behavior on blockchain adoption that are applied in the following analysis.
The potential for blockchain technology is increasingly evident in supply chain logistics and manufacturing that is often located in industrial areas such as ports. By studying blockchain potentials in Danish maritime SMEs, the findings reflect the currently limited insight into blockchain technology from the point of view of business actors. As shown in the study of three Danish supply chains, containers, seafood and recirculated plastics, there are low-hanging potentials to be realized through changes to the current technologies and systems in application.
This chapter presents the latest development in digital platforms for data sharing in Maritime Informatics as discussed in chapter 1—Responding to humanitarian and global concerns with digitally enabled supply chain visibility. Specifically, we use the TradeLens digital data sharing platform as a case study to illustrate the key actors in containerised global transport and the technical set-up (including the utilisation of a hybrid cloud, permissioned blockchain, and data exchange standards), the benefits and challenges for the individual types of actors, and the overall potential and future challenges of the TradeLens platform.
The potential of data sharing platforms is dependent on the wide adoption of the ecosystem. Today, there is a high interest for the TradeLens ecosystem, and many actors have already adopted the platform, due to the vast variety of benefits it provides to all actors in global trade. Regardless, some actors seem to face internal obstacles to adopting the platform, which are either low or high technical advancement. For these actors, a paradigm shift is necessary to move from a reactive to a proactive scheme enabled by a near real-time supply and logistics data network. Finally, we discuss the challenges of network collaboration.
The Ghana National Single Window has become the focus of attention over its potential to move goods swiftly. However, since its inception in 2002, the controversies surrounding the implementation suggest issues beyond trade facilitation. The Information Systems literature primarily ascribes the controversies to resistance to technology. By adopting the Soft Systems Methodology (SSM) as a learning process for understanding port stakeholders' relations and attitudes, we explore the controversies to determine the meanings port stakeholders attribute to them. We combined SSM with interviews, media content analysis and focus groups made possible by snowballing. The responses were analyzed using rich pictures and validated through a conceptual model. The results reveal a fragmented government where ministries, agencies, and personalities assert power in single window implementation through I.T. vendor contracts. The situation results in a high cost of doing business at the port for shippers due to non-transparent and questionable contracts. The public's attitude towards the controversies reflects fears, hopes and expectations and legitimate concerns about important political and social goals. Using SSMs focus on relations and attitudes, we can document how controversies attributed to new technology is not a question of technology but of perceived political interference.