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.

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.

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.

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.

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 transport sector is the second highest emitting sector in the Netherlands, with 19 % of the total energy consumption. Where other sectors are becoming more sustainable, the transport sector remains one of the most difficult to decarbonize, despite the many studies in this field. This research aims to gather a list of potential measures and combine them to reach an 80% reduction of CO2 emissions in 2040 for the hinterland freight corridor of Rotterdam – Venlo which has a high rail freight intensity. Literature study and expert interviews established a list of potential measures. Using an iterative normative scenario design approach, a list of 8 potential measures with corresponding targets was drafted. After computation, a reduction of 80% is estimated for the corridor. The results show that for this particular corridor, the reduction depends greatly on the availability and adaptability of biodiesels and the electrification of vehicles and vessels. In contrast, measures aiming to improve the logistical
efficiency do reduce the total energy required and could therefore alleviate challenges related to biodiesel availability and electrification, but have a smaller potential in reducing CO2 emissions.

Very few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight solutions or policies. Especially the behavioral responses of logistic agents are difficult to include systematically in impact assessments. This is mainly due to limitations on urban freight data and absence of validated and proven simulation tools. We present an urban freight simulator: Multi-Agent Simulation System for Goods Transport (MASS-GT). MASS-GT is an agent-based model consisting of a framework of discrete choice and optimization models to describe the logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model was first implemented for a study area in the Netherlands and calibrated and validated using a variety of data sources.

The e-commerce growth trend has great potential to influence both the nature and the dimension of the challenges policymakers will face in the near future. In this sense, the purchasing habits of the end consumer have undergone a significant change with the development of the emerging information and communication technologies that impact on the purchase behaviour and the way of receiving the item bought. The goal of the paper is thus to analyse cutting-edge last mile delivery alternatives while looking at the characteristics that determine the preferred alternative for receiving e-purchases. The identified new alternatives besides traditional mail are: crowdshipping, delivery to the car trunk, delivery by autonomous delivery robots, unattended parcel locker, attended pick up point and click-and-collect service. The paper presents the methodology for designing and delivering, as well as the findings of a survey carried out for investigating users' behaviour, after reviewing the key attributes and levels that influence end consumers in choosing how to receive their e-purchases.

In practice, speed limits on road networks are often determined pragmatically, which can give suboptimal solutions for traffic performance and unfair results for the underlying user classes. This study presents an elegant approach to determine optimal speed limits on a traffic network with asymmetric user classes under congested conditions, that minimizes individual user travel time and does justice to differences in economic importance. Existing prescriptive approaches typically lack one or more of these features, cannot guarantee optimality or are difficult to solve. We formulate a new prescriptive method using mixed-integer quadratic programming. The model can be solved with well-established operation research approaches and commercial solvers such as Cplex or Gurobi. To demonstrate the approach, we apply it to a regional network in the Netherlands. The result shows a reduction of travel time of passenger cars by 6% and of trucks by 13%, with mild changes in speed limits compared to the base situation, of between −20% and +10%. The speed limit changes and impacts are in line with the relatively high economic importance of freight traffic. Also we find in this case that the speed limit changes are ordered by major routes through the network, which makes implementation relatively straightforward.

The energy transition is reshaping global trade flows, introducing uncertainty into energy-related liquid bulk logistics, particularly within ports. Despite the significance of liquid bulk in global supply chains, existing port choice models are primarily developed for containerized cargo. This study investigates the key determinants of decision-making in liquid bulk logistics within the context of sustainability transitions. Using a multi-case study approach, including stakeholder interviews and qualitative analysis, we identify factors shaping infrastructure planning, port selection, storage, and transportation modes.

The findings reveal that logistical choices in liquid bulk are highly interdependent, shaped by supply chain structures, stakeholder dynamics, and regulatory frameworks. As ports might evolve into multienergy hubs, new actors and uncertainties emerge, particularly regarding the role of hydrogen and biofuels. Understanding these evolving dynamics is crucial for optimizing logistics strategies and ensuring efficient, sustainable energy supply chains.

Despite the importance of urban freight transportation for the accessibility and livability of cities, few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight transportation solutions or policies. There is a lack of transparent literature on the full specification and estimation of these models, which not only hampers continued research, but also the development of evidence-based urban freight transport policies. We present the urban freight simulator Multi-Agent Simulation System for Goods Transport (MASS-GT) with its full specification and empirical implementation for a study area in The Netherlands. It concerns an agent-based model based on a framework of discrete choice and optimization models, which describes logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model is estimated and validated using a variety of data sources: truck trip diaries, supply/use statistics, an e-commerce demand survey, traffic counts and other relevant statistics. The article presents the full specifications of the model and their empirical estimation, including the data sources used. Also, the validity of the model is evaluated using road freight traffic counts. Finally, examples of applications of the model to case studies are provided.

Game-theoretic models are frequently used to analyse the effects of information availability and quality on supply chain decision-making. Although information asymmetry plays a vital role in shaping sustainable supply chains, a comprehensive review of these models within this context remains lacking. This study conducts a systematic literature review and performs an in-depth content-based analysis of 73 peer-reviewed journal articles, categorising them based on their assumptions regarding supply chain structure, information structure, and interaction among supply chain members. We find that researchers are extending traditional supply chain models to address emerging challenges and opportunities driven by sustainable practices under asymmetric information. However, the research remains in a preliminary phase, with most models relying on simplified settings – typically dyadic, single-product, and single-period frameworks – and focusing primarily on demand and cost information asymmetries. Multilateral information structures and non-contractual coordination mechanisms remain largely unexplored. Theoretical advancements have considerably outpaced empirical validation, revealing a critical gap in the integration of real-world practices. Our findings highlight the importance of information sharing and coordination mechanisms in achieving sustainability outcomes and improving supply chain performance. These insights enrich the theoretical discourse on information asymmetry in sustainable supply chains.

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.

De transitie naar een circulaire economie vraagt om intensieve samenwerking binnen waardeketens. Dit artikel bouwt op concepten voor de analyse van logistieke systemen zoals ge¨ıntroduceerd door prof. Kees Ruijgrok, en verbindt deze aan recent onderzoek naar Value Chain Collaboration en circulaire prestaties. Met behulp van kwalitatieve data, verzameld via semi-gestructureerde interviews, en kwantitatieve data, verkregen uit twee opeenvolgende vragenlijsten, is de relatie tussen samenwerking en prestaties op de Rladder van de circulaire economie nader onderzocht. Samenwerking blijkt sterk te correleren met circulaire prestaties, met name in technologie-intensieve sectoren die profiteren van gedeelde platforms en infrastructuur. Traditionele sectoren lijken te worden belemmerd door een gebrek aan vertrouwen en beperkte middelen. Deze resultaten benadrukken de noodzaak van maatwerkoplossingen om unieke uitdagingen en kansen binnen sectoren te benutten. Het artikel beoogt bij te dragen aan de literatuur over circulaire economie en samenwerking in de logistiek, als basis voor toekomstig onderzoek en praktijktoepassingen

This paper investigates the potential improvements in multimodal freight systems through the use of modular vehicles (MVs), aiming to enhance operational adaptability and integrate these vehicles within the mobility-as-a-service (MaaS) concept. The research examines a specialized form of the Pickup and Delivery Problem (PDP) adapted for rail and road logistics, presenting a new mathematical model for the Pickup and Delivery Modular Vehicle Routing Problem (PDMVRP) that includes road and rail. This model tackles significant operational issues such as routing of MVs on road, platooning and the scheduling of MVs on railways and transfers between road and rail MVs. A practical example in a regional road and railway network demonstrates the effectiveness of the proposed model, indicating their ability to decrease costs(energy and emissions), shorten travel times, and boost the efficiency of rail capacity, thereby promoting the advancement of MV usage in future transport systems.

Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration. The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).

This paper presents the first results of a Delphi survey aimed at eliciting experts' opinions on possible scenarios of integration between passenger and freight transport enabled by a Mobility as a Service (MaaS) platform. Combining freight shipments with passenger trips is a promising addition to the MaaS business model that could help to reduce the number of freight vehicles and contribute to a more efficient use of passenger transport services and modes. The research objective of this paper is therefore to explore the feasibility of an extended version of MaaS including freight, called “MaaS for Passenger and Freight” (MaaS4PaF). Passenger and freight transport experts were asked to express their opinions with respect to the potential market penetration, business ecosystem, and implementation of this concept. Results allow to elaborate on opportunities and barriers, especially related to uncertain business models and the multitude of actors involved, and propose a research agenda to further investigate the feasibility and potential of MaaS for passenger and freight transport integration.

As ports are experiencing heavier traffic, the pressure to improve port call processes is increasing. Port call optimization (PCO) is one of these improvement initiatives, enabling the arrival of vessels to the port just-in-time when the vessel services, like pilotage, towage, and mooring, are all readily available. Otherwise, vessels that sailed at full speed to arrive at the port may have to wait, idling at anchorage, occupying space, burning fuel, and leading to increased congestion. One of the main challenges in the implementation of PCO is determining the time at which availability of these services can be guaranteed. The paper addresses this challenge by presenting a model that jointly schedules vessels and service providers. It extends the current approaches to allow application to larger and busier ports, where repositioning times for pilots and tugboats is highly variable and vessels experience waiting times between services. The problem is formulated as a mixed-integer linear programming one and is modelled in continuous time. We test alternative scheduling strategies using three different objective functions, based on the current ‘first-come-first-serve’ approach, a minimal level of service, and the best capacity utilization. The model is applied on data made available by the Port of Rotterdam, and it provides a full-service schedule for vessels and service providers.

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.

As the rapid growth of urban e-commerce increases the volume of last-mile deliveries, logistics service providers have difficulty in meeting the demand of on-demand consumer requests. This increase in demand challenges traditional delivery, with some parcels becoming disproportionately costly to deliver to their destinations. To address this, we introduce a cost-based outlier parcel selection mechanism that identifies parcels with a high negative impact on the marginal delivery costs. These outlier parcels are then eliminated from their tours and outsourced to a crowdshipping market, where individuals combine the delivery task with their already planned trips. We use unique data on delivery tours of six service providers for the province of South Holland in the Netherlands. The cost-based decision rule for identifying outlier parcels results in a low proportion of outsourcing to the crowdshipping market compared to earlier literature. We identify only about 1 % of the total parcel demand as outliers across all carriers combined. Of these outlier parcels, the proportion selected for crowdshipping based on their cost efficiency ranges from 42.78 % to 3 %, depending on the scenario. While crowdshipping provides a viable solution for handling a small portion of last-mile deliveries, its environmental and economic sustainability is restricted by factors such as compensation rates and the delivery mode used. This study demonstrates that outsourcing high-cost outlier parcels to crowdshipping can be cost-efficient and reduce emissions of last-mile logistics companies; however, the proportion of these parcels is very small, limiting the overall impact on sustainability.