Teleoperated driving complements automated driving and acts as transitional technology towards full automation. An economic advantage of teleoperated driving in logistics operations lies in managing fleets with fewer teleoperators compared to vehicles with in-vehicle drivers. This alleviates growing truck driver shortage problems in the logistics industry and save costs. However, a trade-off exists between the teleoperator-to-vehicle (TO/V) ratio and the service level of teleoperation. This study designs a simulation framework to explore this trade-off generating multiple performance indicators as proxies for teleoperation service level. By applying the framework, we identify factors influencing the trade-off and optimal TO/V ratios under different scenarios. Our case study on road freight tours in the Netherlands reveals that for any operational settings, a TO/V ratio below one can manage all freight truck tours without delay, while one represents the current situation. The minimum TO/V ratio for zero-delay operations is never above 0.6, implying a minimum of 40% teleoperation labor cost saving. For operations where a small delay is allowed, TO/V ratios as low as 0.4 are shown to be feasible, which indicates potential savings of up to 60%. This confirms great promise for a positive business case for the teleoperated driving as a service.

Alignment of core supply chain functions with corporate supply chain strategy is a key success factor for firms. Misalignments can lead to inefficiencies, higher costs, risks, and weaker performance. In particular, misalignment between transportation strategy and supply chain strategy can reduce responsiveness and flexibility, increase risks, and amplify environmental impacts. Although classic supply chain frameworks established the theoretical foundations of supply chain strategy, they treated transportation as a secondary issue and overlooked contextual decision factors such as product density, perishability, product life cycle, resilience, and sustainability. Consequently, a conceptual model that systematically integrates the complexity of the transportation and supply chain strategy alignment is not yet present in the literature. To address this gap, we develop a conceptual framework that introduces four transportation strategies, i.e. Cost-Oriented, Flexibility-Reliant, Modal-Control-Intensive, and Value-Enhanced, mapped against supply chain strategies across thirteen contextual criteria. Using the Best-Worst Method, we supplement the framework with an illustrative survey study of Global Fortune 500 companies. The results indicate that no single transportation strategy is right across all supply chains, but tailor-made service bundles can lead to alignment. Our study extends alignment theory to transportation and offers practical insights for managers of shipper firms and logistics service providers.

To support a modal shift toward sustainable freight solutions, such as inland waterway transport (IWT), researchers and practitioners require long-term historical data on IWT freight flows. However, such comprehensive time series have been unavailable until now. This study addresses this gap by presenting a harmonized dataset encompassing 50 years (1970–2023) of IWT freight data across Europe, with a focus on the Rhine-Alpine Corridor. The dataset includes transport volumes (in tonnes) and transport performance (in ton-kilometers), classified according to NST-R, NST2007, and CCR nomenclatures. To ensure data continuity and completeness, processing techniques—including imputation and optical character recognition—were applied. The dataset offers valuable insights for researchers, policymakers, and transport planners aiming to comprehend and enhance the role of IWT in Europe’s freight transport landscape.

The existence of time-bound targets for decarbonization of freight transport raises the need for knowledge of the dynamic behavior of the system. However, little is known about the factors that determine these dynamics, conceptually and empirically. We argue that research is needed to allow substantiated claims about the feasibility of decarbonization policies. We propose a transition theory-inspired framing of the problem, which considers the dynamics of new technologies as alternatives to the established markets, institutions and regulations. We review the relevant freight modeling research literature and develop recommendations for research. While the literature does contain a small set of studies that address the dynamic behavior of the freight system, the relevant phenomena are only partially considered and empirical evidence is scant. We recommend the use of a multi-level dynamic perspective, which includes a long-term view beyond the time horizons considered today. Most importantly, new empirical modeling work is needed to develop valid dynamic models of the relevant decisions taken by all freight transport system stakeholders.

Nowadays, e-commerce is gaining popularity worldwide. End consumers are shifting from in-store shopping to online due to the numerous advantages. The e-deliveries are associated with smaller and more frequent deliveries, failed and geographically sprawled ones. It causes the increase of the number of vehicles as well as of the kilometres travelled, and then the raise of the negative impacts, e.g., pollutant emissions, congestions. Therefore, new delivery channels have been developed to optimise the delivery system and new procedures are necessary for their assessment. A key role in these assessment procedures is played by the analysis of how each of the new delivery omni-channels are really chosen by end consumers. Then, this study points out end consumers’ choices through a structured survey. The data collected are then analysed through a clustering approach. The aim is to find out the decision processes by comparing various delivery channels based on service attributes (e.g., delivery time and price, the place where the item is received), respondents’ characteristics and choices made. The results show that such an analysis could be a powerful tool for forecasting end consumers’ decisions, which should be taken into consideration when designing new city logistics scenarios.

Purpose – This study aims to examine how coercive, legitimate, expert, referent and reward power shape compliance, satisfaction and collaboration in innovation-intensive semiconductor B2B dyads. The authors map bilateral power-pairings and develop a dyadic power-pairing viability (DPPV) framework explaining which pairings persist without sustained satisfaction loss and why others do not.

Design/methodology/approach – This study used qualitative multiple-case study of 22 Dutch customer–supplier dyads. The authors code each side’s use of the five power bases, derive pairings, link them to outcomes and use cross-case pattern matching and negative-case analysis to elaborate DPPV and derive testable propositions. 

Findings – Only 9/25 theoretical pairings appear; the dominant configuration is {Customer-Legitimate, Supplier-Expert}. Coercive buys short-term compliance but depresses satisfaction. Expert and referent underpin durable collaboration when aligned to partner needs. Legitimate coordinates under clear roles. Reward works when value and fairness are credible. Viability is shaped by IP risk, time-to-market pressure and capability asymmetries.

Research limitations/implications – Single sector, The Netherlands; qualitative design limits generalizability. Future work should test DPPV quantitatively/longitudinally, probe boundary conditions across sectors/cultures and model dynamic switching between pairings under shocks.

Practical implications – This study avoids prolonged coercive use, aligns expert/referent to the locus of capability, uses legitimate with explicit roles/decision rights, applies reward with transparent value sharing, combines bases across the dyad (e.g. {Customer-Legitimate, Supplier-Expert}) and mitigates IP exposure, speed pressures and asymmetries.

Originality/value – This study introduces a dyadic, configuration-level view of power (DPPV) that explains observed vs absent power-pairings, links them to compliance-satisfaction trade-offs and tailors power use to semiconductor contexts, extending power-base theory to high-tech B2B governance.

Improving connectivity between ports and the hinterlands they serve is critical for reliable and cost-efficient freight transport. However, overreliance on a single port, or small subset of ports, can cause economic losses when those ports fail, given limited redundancies of port-hinterland systems. However, planners often lack critical insights into port-hinterland redundancy. Here, we analyse the port-hinterland redundancies across Africa, a continent with a small number of gateway ports serving large hinterlands and large investment need in the coming decades, providing a window of opportunity to embed redundancy in strategic transport investments. We find that regions with high accessibility, in particular coastal cities close to a major seaport (e.g., Namibia, Senegal, Kenya) have low redundancy. In contrast, some landlocked hinterlands (e.g., Zambia, Zimbabwe, Niger, and Chad) have low accessibility, yet high redundancies given their reliance on different port ranges. We further show that new transport investments aimed at improving accessibility can create both synergies and trade-offs with system redundancy. Port terminal expansions, in particular, can reduce the redundancy of the core hinterland while improving the redundancy of the hinterland periphery. Rail connections can improve access to a wider set of ports at a comparable cost but can also reinforce the dependency on a single cost-efficient rail connection. Analysing redundancies of port hinterlands can support strategic planning of regional investments and help improve the resilience of the regional and continental transport system against disruptions.

Digitalisation is transforming logistics operations worldwide. However, low-income countries continue to face significant barriers to adoption, including limited infrastructure and resources. In Ethiopia, supply chains remain inefficient due to inadequate technological integration. The technology acceptance model (TAM) has been used by several researchers to explain the usage and adoption of technologies. However, this framework has rarely been applied to digital logistics in the context of low-income countries. This study empirically investigated the intention of stakeholders in Ethiopian supply chains to adopt digital technologies using a modified version of TAM. Data were collected through an extensive survey of logistics professionals. The results indicated that, beyond perceived usefulness and ease of use, external factors such as infrastructure availability, human resource capacity, technological accessibility and supportive policies, significantly influence stakeholders' intention to adopt digital technologies. The study emphasises the importance of awareness-raising initiatives and the development of digital strategies to support successful digital transformation in low-income countries. These findings offer valuable insights for policymakers and practitioners seeking to better understand the relationship between technology adoption, user perceptions and enabling conditions.

The demand for new offshore wind farms is increasing at a rapid pace, and the installation rate must be quadrupled by 2030 to meet the ambitions of European countries. The installation of the superstructures involves several components and is highly weather-dependent, making this an important bottleneck. In this paper, we evaluate the two main strategies for the installation of superstructures: feedering and shuttling. With feedering, the installation vessel is fed with components by feeder vessels directly from manufacturing ports. With shuttling, the installation vessel retrieves the components itself from a marshalling port. In contrast to existing studies, we include manufacturing ports and their production rate to have a better understanding of their influence on the installation rate and develop a rolling horizon optimization-simulation framework composed of a mixed integer linear programming model and a Markov simulation model for weather forecasting. A heuristic is proposed to solve the model to overcome the limitation of commercial solvers. Results indicate that accurate initial buffer calculations, depending on the production rate at the manufacturing ports and project-dependent characteristics, can increase the installation rate significantly for both strategies. Finally, feedering outperforms shuttling in most scenarios and is less weather dependent.

The continuous growth of international container trade calls for logistics networks that seamlessly connect cross-border, domestic, and local transport services. In the design of these networks with various hubs and modes of transport, the consideration of both economies of scale for multimodal transport and congestion is essential since they can significantly impact the location of the hubs and their size. Thereby, in this paper, we study these features within a multimodal hub location problem for international trade that considers a hierarchy in the network structure. We develop a mixed-integer linear programming formulation, minimizing infrastructural, operational, and congestion costs. A hybrid adaptive variable neighborhood search algorithm with tailored operators and speed-up strategies is proposed to solve large-scale instances. Numerical experiments are conducted for China's New Western Land-Sea Corridor case and provide new managerial insights for designing hierarchical, multi-modal, cross-border logistics networks.

Large-scale social digital twinning projects are complex with multiple objectives. For example, a social digital twinning platform for innovative last-mile delivery solutions may aim to assess consumer delivery method choices within their social environment. However, no single tool can achieve all objectives. Different simulators exist for consumer behavior and freight transport. Therefore, we propose a high-level architecture and present a blueprint for a generic modelling framework. This includes defining modules, input/output data, and interconnections, while addressing data suitability and compatibility risks. We demonstrate the framework’s effectiveness with two real-world case studies.

Dry port construction facilitates intermodal freight transport in the import and export corridors, especially for landlocked countries. Selecting the optimal locations for dry ports is a crucial component of national planning. In this study, multi-criteria decision-making (MCDM) combined with GIS was used to map suitable sites for dry ports. Essential criteria for selecting optimum dry port locations were identified from the literature and a Simple Multi-Attribute Ranking Technique (SMART) was used for expert weighting these criteria. The results revealed that distance from road and distance from railway are the two most important criteria, while distance from a seaport is the least important. Application of the method to identify optimal dry port locations in Ethiopia showed that most of its territory is moderately suitable for dry port location. However, most of the existing dry ports in the region are found to lie within the highly suitable areas. Overall, the suitability map developed in this study provides a rich basis of information for future sustainable dry port investments.