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 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.
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 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.
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.
This article analyzes the competitive strategies of Odense Steel Shipyard between 1918 and 2012 and challenges existing scholarship on competition in global industries. Until the 1980s, the yard adopted typical strategies in shipbuilding, starting with cost leadership and subsequently adopting global segmentation and differentiation strategies. From the mid-1980s, however, it successfully followed a unique national responsiveness strategy, which scholars including Dong Sung Cho and Michael E. Porter had ruled out in shipbuilding. The article shows how shipyard owners shaped strategies and influenced competitiveness.
Infrastructure-led development is driving geopolitical agendas in the Global South, and Djibouti is a case in point. Strategically situated in the Horn of Africa, Djibouti's seaports and related infrastructure have been modernized through foreign investments to serve international trade and growing African hinterlands. Scholarship often posits foreign logistics investors as hegemons driven by geopolitical interests, and host states as passive recipients. This paper questions such claims. It examines the relationship between "hegemon" and "host state" from the perspective of the latter, in this case the Djibouti government's interactions with Emirati and Chinese infrastructure companies. Methodologically, the analysis is based on interviews, secondary data and document analysis. It applies a conflict-sensitive controversies approach from critical logistics studies to trace contestation over authority in Djibouti's logistics sector. It shows how Djibouti's government applies various strategies (discursive, legal and political) to exercise agency in its logistics sector. The paper concludes that the geopolitics of infrastructure-led development is a reciprocal effort that goes beyond conventional logics of hegemons imposing on host states.
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 introduces a state-of-the-art volatility forecasting method for container shipping freight rates. Over the last decade, the container shipping industry has become very unpredictable. The demolition of the shipping conferences system in 2008 for all trades calling a port in the European Union (EU) and the global financial crisis in 2009 have affected the container shipping freight market adversely towards a depressive and non-stable market environment with heavily fluctuating freight rate movements. At the same time, the approaches of forecasting container freight rates using econometric and time series modelling have been rather limited. Therefore, in this paper, we discuss contemporary container freight rate dynamics in an attempt to forecast for the Far East to Northern Europe trade lane. Methodology-wise, we employ autoregressive integrated moving average (ARIMA) as well as the combination of ARIMA and autoregressive conditional heteroscedasticity (ARCH) model, which we call ARIMARCH. We observe that ARIMARCH model provides comparatively better results than the existing freight rate forecasting models while performing short-term forecasts on a weekly as well as monthly level. We also observe remarkable influence of recurrent general rate increases on the container freight rate volatility.
This article aims to present the most relevant practices of offshore oil contracting at an international level, in order to better understand the legal dynamics of the sector. The problem investigated deals with the terms of the legal relationship between the State and national and foreign public companies, as well as the relationship between States, with a view to the exploitation of shared offshore oil resources. This problem is current, taking into account both the fact that oil is a scarce resource, as well as the fact that its offshore exploration is particularly complex and risky. This article presents, in a non-exhaustive way, some examples of practices that illustrate contractual trends that have already crystallized. The approach to its content is made from an international law perspective, focused on the transnational challenges posed to States and operators. It is concluded that the sector is characterized by a huge variety of practices, which reveals an ability of operators to adapt to the characteristics of the concrete challenges of an offshore exploration project. It also shows the political and economic particularities of the States involved in the process.