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.
This chapter argues that state-owned Chinese integrated maritime logistics enterprises are about to change the power balance vis-à-vis the hitherto dominant, privately owned enterprises based in Europe. This shift, which has been actively supported as part of China’s ambitious Belt and Road Initiative, will directly affect the European Union’s common transport and competition policy. Within the larger Belt and Road Initiative, the Maritime Silk Road project can be seen as the umbrella concept for the comprehensive management of the entire supply chain between China and Europe. We discuss possible policy implications for both China and the European Union when it comes to managing the subtle balance between geopolitical considerations and efficient operations of trade and transport controlled by a few dominant actors. As part of our theoretical framework, we use two extensions of the classical obsolescing bargaining model: the one-tier bargaining model and a bargaining model of reciprocation. By combining the two models, we aspire to explain the changing nature of bargaining relations between, on the one hand, the Chinese government and its state-owned enterprises and, on the other, the private-owned European companies as a function of the goals, resources and constraints of the involved parties.
The accelerated melting of the Arctic ice leads to the navigation of the Northern Sea Route (NSR) linking Asia and Europe, shortening transport channel between China and the European Union (EU). This has a significant impact on the China-EU bilateral trade which is analyzed in the present study. We present a framework based on a general equilibrium model for analyzing the impact of the NSR on the trade and the economies of China and the EU. Different fuel cost scenarios, consisting of fuel prices and sailing speeds on ice, are also considered. Specifically, we measure the changes in shipping costs between China and the EU, brought about by NSR navigation. These are used as a basis to quantify changes in transport technology. The Global Trade Analysis Project (GTAP) model is used to predict the trade and economic impacts. The results show that the NSR can save 0.98% in shipping costs and generate an increase in the exports of China and the EU in the order of 14,986 and 8,228 million US dollars, respectively. Among these exports, the mining industry shows the fastest growth, while the electronics industry experiences the largest increase in trade volume. Our findings reveal the potential of the NSR as an alternative route and its positive impact on bilateral trade between China and the EU. The results can provide a basis for shipping companies and governments to make decisions regarding the use of Arctic routes.
This study presents a novel approach to forecast freight rates in container shipping by integrating soft facts in the form of measures originating from surveys among practitioners asked about their sentiment, confidence or perception about present and future market development. As a base case, an autoregressive integrated moving average (ARIMA) model was used and compared the results with multivariate modelling frameworks that could integrate exogenous variables, that is, ARIMAX and Vector Autoregressive (VAR). We find that incorporating the Logistics Confidence Index (LCI) provided by Transport Intelligence into the ARIMAX model improves forecast performance greatly. Hence, a sampling of sentiments, perceptions and/or confidence from a panel of practitioners active in the maritime shipping market contributes to an improved predictive power, even when compared to models that integrate hard facts in the sense of factual data collected by official statistical sources. While investigating the Far East to Northern Europe trade route only, we believe that the proposed approach of integrating such judgements by practitioners can improve forecast performance for other trade routes and shipping markets, too, and probably allows detection of market changes and/or economic development notably earlier than factual data available at that time.
Just as containerized goods appear to flow seamlessly across the planet's oceans, internationalized and standardized certificates present seafaring labor as uniform and seamless. But underneath these certificates are the intimate and unequal entanglements of local masculinity norms, age, and kinship ties that sustain the maritime labor supply chain. In this article, we follow how three young, male seafarers from eastern India find ways to contain piracy risks at work and poverty risks at home, and their sense of obligation as men, sons, husbands, and fathers. By delving into the unequal conditions for industrial male workers from the Global South, this article demonstrates how containerized maritime labor commodities are not uniform but are dependent upon economic inequality and intimate kinship ties to be productive.
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 report is organized as follows. The introduction will lay out the current state-of-play of eco-efficiency and the zeitgeist of the current situation on maritime that we find ourselves in, in 2020. The next section will provide some historical context looking back to 2010 and 2000 to trace the trajectory and developmental course on which we are. The core contribution of this report is the Maritime Operations Roadmap that can be found in Figure 1 on page 9. This illustration plots the expectations for technological capabilities and policy from 2020 to 2030.
To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.
This chapter is a historical case study of Maersk Line, the world’s leading container carrier. Maersk Line’s global leadership was achieved within a relatively short time period and was the result of Mærsk Mc-Kinney Møllers decision in 1973 to enter container shipping—the biggest investment in the history of the AP Moller companies. When Maersk Line managed to achieve global leadership in a period of just about 25 years, the company’s own country offices were particularly important. They allowed the interconnection of three types of networks: The physical network of ships and routes, the digital network of information and communication systems and the human network of Maersk employees. The interaction between the vessels, the systems and the people is still at the core of the company today and central to its continued development.
Considering 91 countries with seaports, this study conducted an empirical inquiry into the broader economic contribution of seaborne trade, from a port infrastructure quality and logistics performance perspective. Investment in quality improvement of port infrastructure and its contribution to economy are often questioned by politicians, investors and general public. A structural equation model (SEM) is used to provide empirical evidence of significant economic impacts of port infrastructure quality and logistics performance. Furthermore, analysis of a multi-group SEM is performed by dividing countries into developed and developing economy groups. The results reveal that it is vital for developing countries to continuously improve the quality of port infrastructure as it contributes to better logistics performance, leading to higher seaborne trade, yielding higher economic growth. However, this association weakens as the developing countries become richer.