This study investigates the decarbonization of truck-based container transport in the Port of Rotterdam's hinterland, focusing on the adoption of three key low-carbon technologies: Battery Electric Trucks (BETs), Fuel-Cell Electric Trucks (FCETs), and e-diesel. As the largest logistics hub in Europe, the Port of Rotterdam faces increasing pressure to reduce CO₂ emissions, especially from road transport. Using a system dynamics model developed in Vensim and informed by expert interviews, the research explores technology adoption dynamics, including infrastructure availability, technology maturity, awareness, energy source supply, and lifecycle costs. The study identifies interdependent feedback loops among these factors and evaluates policy interventions that can accelerate adoption. Two key policies—stimulation of lower-emission truck adoption and collaborative BET implementation—are found to be particularly effective in initiating exponential adoption growth. Scenario analyses also highlight the importance of early and coordinated policy action. BETs emerge as the most viable near-term solution due to their faster cost reductions and existing infrastructure advantages, while FCETs remain a longer-term option for specific use cases. The findings offer actionable insights for the Port of Rotterdam Authority and policymakers, emphasizing early intervention, national coordination, and a strategic focus on BETs to achieve carbon neutrality in hinterland transport by 2050.

This thesis compares two pathways for decarbonising long-haul freight: Battery Electric Heavy-Duty Vehicles (BEHDVs) using static charging and BEHDVs supported by Electric Road Systems (ERS) enabling dynamic charging. Using the Multi-Actor Multi-Criteria Analysis (MAMCA) and Best-Worst Method (BWM), the study evaluates both options from the perspectives of six stakeholder groups: carriers, shippers, vehicle manufacturers, grid operators, road operators, and freight forwarders.

Stakeholder criteria were identified through eleven expert interviews and weighted via BWM surveys, then linked to measurable, normalised indicators. Results show BEHDV-only is preferred by manufacturers and freight forwarders, while ERS is favoured by grid and road operators for its grid load balancing and land use efficiency. Shippers and carriers show moderate ERS preference, citing reliability and driver well-being benefits.

A phased strategy, static charging for near-term deployment and targeted ERS rollout on high-utilisation corridors, is recommended to balance operational, economic, and long-term sustainability goals.

Background.
Global Food Supply Chains (FSC) have been posing risks due to contamination, adulteration, and fraudulent behavior. These issues compromise consumer safety and damage customers' trust. These have led to a substantial rise in the demand for transparency, with traceability serves as a key enabler. Despite its importance, the reality is that complete traceability is more the exception than the rule.

A significant barrier lies in the internal traceability (within company or factory) system, which is often non-transparent and asymmetric, posing a serious threat to the security and reliability of the information. While digitalization offers promising solutions, many organizations continue to rely on conventional systems, or face interoperability or integration issues when digital systems are implemented. There is a high urgency to address these current issues to make traceability more efficient and effective.

Problem.
This research focuses on the category of infant nutrition (baby formula). In this area, transparency is much more important due to the high-risk nature of the consumer group and the relatively small number of companies, which makes the supply chain more susceptible to disruptions. From an academic perspective, there is limited research on frameworks for adopting digital traceability, particularly for internal traceability. To the author’s knowledge, empirical evidence is limited, with no studies specifically addressing traceability in infant formula manufacturing.

From a business standpoint (case study), traceability practices vary widely across factories. Some factories in the studied company use standardized digital systems ("core tools"), while others rely on legacy or manual methods. These differences reflect varying levels of digital maturity and hinder the company’s transparency goals. Inconsistent data management adds pressure on factories to meet traceability standards efficiently. Therefore, this study aims to address the need for a unified approach by answering the question: “What conceptual framework can be developed for the factories in infant formula manufacturing to adopt Digital Traceability tools to achieve Transparency?”.

Research Approach.
We utilized the information system's Design Science Research (DSR) framework of \textcite{hevner_three_2007}. The framework consists of three contexts: Knowledge, Environment, and Design. The formulation of the framework follows Process Pattern Models.

Conceptual Framework of Digital Traceability Adoption.
The conceptual framework for the adoption of digital traceability, as the output of this research, emphasizes the adoption process. It is used as the 'way of thinking' to understand the current situation and what steps to take ahead. The framework consists of three main parts: i) Factors affecting digital traceability adoption (drivers and challenges), ii) Maturity Level Assessment, and iii) Adoption Stages.

Future Research.
This research has contributed to the first steps of digital adoption for internal traceability in FSC. There are several areas recommended. First, to further investigate the relationship between traceability and transparency across different levels of traceability maturity level. Second, the relationship between drivers and adoption outcomes remains underexplored, though this study hints that initial motivations can influence current traceability levels. Third, future research should investigate integrating internal factory traceability with external supply chain traceability, as current literature treats them separately. Finally, the study has identified the components, but solution and more practical use of the frameworks are much more to be explored. For government: Access to emerging technologies enhances digital traceability, this emphasizes the importance for industry and academia collaboration.

Novelty.
The novelty of this thesis is in its integration of Design Science Research (DSR) and the Process Pattern Model (PPM) to develop a practical, systematic framework for adopting digital traceability tools. Unlike prior studies that emphasize external traceability or emerging technologies such as blockchain, this research focuses on the underexplored domain of 'internal traceability' using widely deployed manufacturing systems (MES, PMS, WMS, LIMS, ERP). It further contributes to academic inquiry into infant formula traceability, a niche but high-risk segment that is scarce in the existing literature. By combining theoretical insights with empirical evidence, the framework emphasizes the adoption process, incorporates post-adoption considerations, and delivers guidance for factory-level implementation.

Abstract─ Indonesia’s container port sector is economically vital but contributes significantly to national greenhouse gas (GHG) emissions. Emissions reduction planning remains fragmented, especially for small and medium-sized terminals. This study develops a standardized, scalable framework for quantifying emissions, forecasting trends, and assessing the cost-effectiveness of decarbonization measures across Indonesian container terminals. Using operational data from five terminals, large (TPS, BJTI, TTL), medium (Palembang), and small (Jambi), an activity-based inventory was built for Scope 1, 2, and 3 emissions. Future emissions were projected under business-as-usual (BAU) and mitigation scenarios, and five decarbonization strategies were evaluated using Marginal Abatement Cost Curve (MACC) analysis. In 2024, carbon intensity ranged from 20.1 to 34.2 kgCO₂e/TEU, with higher values driven by vessel hoteling and carbon-intensive grids rather than terminal size. Without intervention, emission intensity is projected to decrease by 20% and increasing up to 11% by 2050. Operational measures like layout optimization (as low as €0.1/tCO₂) and operator training (€7.3/tCO₂) offer immediate, low-cost reductions. Structural options such as onshore power supply (OPS) and equipment electrification yield larger abatement but are only cost-effective with a cleaner electricity grid. Solar PV offers moderate reductions and energy resilience, becoming viable at carbon prices above €40/t. Most structural measures are economically attractive between €0–50/t. The findings support a phased strategy: prioritize operational efficiency first, implement OPS and solar PV as the grid decarbonizes, and phase in electrification during asset renewal cycles to support sustainable port development.
Index Terms─ Container Port Decarbonization, CO2 Emissions, Marginal Abatement Cost Curve (MACC)

Megaprojects frequently face cost overruns and schedule delays, a pattern known as the iron law of megaprojects, which persists partly because traditional determinis tic or probabilistic planning methods are inadequate for managing deep uncertainty. This form of uncertainty arises when the probability, timing, or impact of key events cannot be reliably estimated, often leading to unrealistic schedules and ineffective risk responses. This study investigates the question: How can Exploratory Modelling and Analysis and Dynamic Adaptive Policy Pathways be applied to improve schedule robustness in infrastructure construction projects? The research focuses on the Schiphol bridge reconstruction, which is part of the Veenix A9 BaHo project and is conducted in collaboration with Count & Cooper. A Discrete Event Simulation (DES) model is built in SimPy and structured using a task dependency graph de rived from the project’s original schedule via NetworkX. The model is sampled 10,000 times under baseline conditions using Latin Hypercube Sampling. In scenario discovery, Patient Rule Induction Method (PRIM) is used in combination with a scaling function identifying six high-impact scenarios, which serve both as inputs for robust policy search and as Adaptation Tipping Points (ATP) for the Dynamic Adaptive Policy Pathways (DAPP) schedule. Robust mitigation strategies are derived using a Multi-Objective Evolutionary Algorithm under the Multi-Objective Robust Decision Making framework, with a second PRIM experiment selecting four final robust policies. These policies correspond to at least one of the high-impact scenarios and form the backbone of a conditional DAPP schedule. The DAPP schedule is evaluated against a static baseline using 5,000 DES simulations with identical uncertainty sampling. In 20 comparative runs, it reduced project duration by an average of 67 days and cost by approximately e97.5 million on the entire project schedule. All three robust policies include the measures new design, overtime labour, and electric machinery, suggesting that a focused subset of actions can improve resilience even when the future is highly uncertain. Unlike prior Decision Making under Deep Uncertainty (DMDU) applications, which often focus on long-term or high-level strategic planning, this study embeds adaptive logic within a highly granular, task-level construction schedule based on real project data. This approach raises methodological challenges in how adaptation tipping points are defined, triggered, and monitored within network-based simulation. The findings demonstrate not only the feasibility of combining Exploratory Modelling and Analysis (EMA) and DAPP in operational construction settings but also the need for further research into real-time scenario recognition and policy switching mechanisms under uncertainty.

The road freight transport market accounts for 40 \% of the carbon dioxide emissions of the transport sector globally. To reduce these emissions, battery electric trucks (BETs) have the greatest potential as they are zero-emission vehicles. However, compared to the private electric vehicle market, this market faces significant implementation barriers, as seen from the low BET sales. This is mainly due to the optimized market and low profit margins limiting freight carriers from investing in BETs. Furthermore, BETs face serious operational challenges due to long charging times and low operational flexibility. The way to charge the BET plays a big role in finding solutions to these challenges. In recent years, new technologies such as Electric Road Systems (ERS) and battery swapping have been developed next to depot charging and on-road charging. This study gains insight into the preferences of different freight carriers for charging alternatives, using a scenario-based multi-criteria decision analysis(MCDA). Four charging alternatives: depot charging, on-road charging, ERS, and battery swapping, are compared from a freight carrier's perspective on ten criteria identified through literature review, expert interviews, and a survey. The criteria are: Investment costs, operational costs, lifetime of the battery, charging time, operational flexibility, payload capacity, emission reduction, pioneering, complexity of implementation, and strategic policy alignment. To compare the charging alternatives, the criteria weights were obtained through the best-worst method and the analytic hierarchy process, and the performance of the alternatives on the criteria was calculated for daily distance use cases. These performances and weights were combined to arrive at a final ranking of alternatives. This was done for different freight carrier groups based on daily distance, sectors, company sizes, and countries of operation. The results show that financial and operational criteria were considered most important by all the segments of freight carriers. Furthermore, depot charging appeared to be the preferred alternative in most cases, and battery swapping scored best for larger daily distances. However, in almost all freight carrier groups, depot charging, ERS, and battery swapping had similar scores. This result advocates for stakeholders to consider investing in the charging alternatives to give the freight carrier the possibility to choose the charging alternative that is best for them. On-road charging had the lowest score for all the freight carrier groups. This result mismatches with the current investments in the charging alternative and showcases the need to reconsider these investments. Due to the number of criteria and the difficulties in obtaining many responses from freight carriers, the criteria performance and weights can be studied in more detail in future research. Also, using better weighing and evaluation methods and improved research on the four alternatives in a similar scenario can improve the quality of the results in future studies. Also, looking at the problem from different perspectives in future studies can provide great insight into which charging alternatives will shape the future of BETs.

Hyperconnectivity (HC) is an emerging concept in logistics that allows for large-scale collaboration of logistics services through shared assets, information exchange, standardised protocols, and flow alignment. A hyperconnected last mile delivery (LMD) system could lead to more optimised routing decisions through processes such as consolidation with fewer vehicle kilometres and more sustainable operations as a result. However, little is known about the combination of connected services that are deemed promising among stakeholders. The Q-methodology was applied to reveal the dominant perspectives among stakeholders on the implementation of HC characteristics in LMD services. Subsequently, the results were fed back to participants to validate whether the analysis was performed accurately. This paper concludes that there is a consensus among stakeholders that the current LMD system is too segmented and that services such as shared parcel lockers and white label concepts could help consolidate delivery operations. Important barriers identified were the fear of losing a competitive market position by sharing information, as well as economic concerns.

The European Union’s (EU’s) Critical Raw Materials Act (CRMA) aims to strengthen the EU’s resource resilience by increasing the autonomy of Critical Raw Material (CRM) supply through EU-based extraction, processing, and recycling, thereby reducing external dependencies and promoting a circular economy. The CRMA mandates, among others, that at least 25% of CRMs come from EU-based recycling. Copper, a key CRM, faces growing demand, and with mining alone, future supply will not fulfill demand. This research analyzed the copper supply chain before and after the CRMA. It was found that recycling is the most promising solution for adherence to the CRMA and a sustainable and resilient future. The study develops a Mixed Integer Linear Programming (MILP) model to optimize the European copper recycling network under the CRMA recycling requirement. The model minimizes total costs while determining the optimal number, locations, and capacities of recycling facilities. The model is tested through a case study of a natural resource company and is usable to similar firms. Results identify four optimal facility locations: Stuttgart, Geithain, Bologna, and Barcelona, which were selected based on, among others, geographic centrality and supply and demand quantities. Sensitivity and scenario analyses reveal the network is vulnerable to facility outages, supply shortages, and significant demand increases. Decentralizing the network by adding a fifth facility improves resilience with limited additional cost.

This study focuses on optimizing last-mile delivery in e-commerce by balancing cost efficiency and customer preferences, particularly for mixed perishable and non-perishable goods networks. As online grocery shopping grows, ensuring the timely and efficient delivery of perishable products while maintaining quality remains a critical challenge. The model evaluates home delivery, attended pickup points, and lockers, revealing that cost-driven strategies shift deliveries toward self-pickup, with perishable items primarily assigned to attended pickup points due to temperature control. The findings provide insights for improving delivery network design, enhancing service quality, and optimizing the distribution of both perishable and non-perishable products.

The aviation industry is poised for substantial expansion, with forecasts predicting that passenger demand will double by the mid-2030s. This increase in demand presents both opportunities and challenges for various stakeholders within the industry. One sector anticipated to encounter difficulties is Maintenance, Repair, and Overhaul (MRO), particularly regarding data sharing within the supply chain for part tracking. Effective part tracking is essential as it entails crucial data that confirms the 'airworthiness' of parts, demonstrating their safety for operation. Currently, the absence of comprehensive inter-organizational maintenance record software impedes accurate tracking of aircraft parts. This lack leads to increased maintenance and communication costs for all stakeholders involved, as each party must independently verify parts history, often resulting in redundant work and additional pressure on profit margins.

With profit margins already under strain, aviation companies must innovate. One promising solution is blockchain technology, which has the potential to serve as an inter-organizational maintenance record system, facilitating the tracking and tracing of part histories and offering significant cost reductions. However, effective lifecycle tracking of parts requires a collective effort since multiple entities are involved at different stages of the lifecycle, making the formation of a data-sharing consortium necessary. The creation of such a consortium is further incentivized by the implementation of the Corporate Sustainability Reporting Directive (CSRD), which requires companies to disclose all activities related to both downstream and upstream value chains and assess their sustainability impacts. Despite the potential for cost reduction, increased efficiency in inventory management, and legal mandates, companies remain hesitant to join a data-sharing blockchain consortium. Research into similar industry data-sharing consortia indicates that one persistent barrier to success is the design of governance mechanisms within the consortium. Although extensive research on governance mechanisms exists, stakeholder participation in these data-sharing blockchain consortia remains low.

The objective of this research is to develop governance mechanisms that enhance stakeholder participation by taking into account stakeholder values. To achieve this, a value-focused thinking methodology is utilized, ensuring that stakeholder values are integral to the governance design process rather than relying on arbitrary arrangements. In addition to conducting a literature review to discover values, contact was established with the Independent Data Consortium for Aviation (IDCA). IDCA is a global consortium of leading aviation companies at all levels of the industry coming together to develop the foundation for allowing data to be shared in a non-competitive manner. Its objective is to create a more efficient marketplace where both waste and the time required to get to a common solution are minimized. A combination of participatory observations within the part-tracking work group of IDCA and interviews with high-level executives from the aviation industry is conducted to discover stakeholder values. Three contexts, 21 values and 11 sub-values, were identified for joining a data-sharing blockchain consortium. The three contexts are the data that will be shared and received, the stakeholders that will join the consortium, and the blockchain platform that will be used.

Adopting such a broad perspective on values has necessitated the prioritization of these values to create a clear roadmap for the governance design process. This approach ensures that the final governance designs are not only comprehensive but also practical, enabling effective and sustainable blockchain implementation for part tracking in the aviation industry. To obtain this ranking, a survey employing the Bayesian Best-Worst Method (BWM) was used to systematically analyse stakeholder values where 12 aviation stakeholders pertaining to the eight different stakeholder groups encompassing the full life-cycle of a part were received.

Survey takers ranked the data context as the most important, underscoring the value companies place on data as their primary resource, which was followed by stakeholder context. On the other hand, the blockchain platform was ranked the lowest in importance, which was also justified by the credal ranking calculations indicating it is seen merely as a tool for data sharing. Within the data context, the values of integrity, access control, confidentiality, and ownership emerged not only as the highest priorities but also as the most important values overall. This underscores the critical importance stakeholders place on data. These were followed by the values of trust, legitimacy, neutrality, compliance, and benefit equality within the stakeholder context. Completing the top ten, security within the blockchain context was followed by adaptability and tangibility.

Once these stakeholder values are identified, governance designs can be proposed to ensure their fulfilment. A benchmarking study was conducted on existing governance research to understand its definition, scope, and blockchain data-sharing initiatives in other industries. The literature review revealed that no unified definition or established mechanisms for blockchain governance currently exist. Therefore, the researcher established the following definition: "Consortium blockchain governance refers to the process and mechanisms that ensure the direction, control, and coordination of a blockchain platform to which stakeholders jointly contribute."

Given that consortium blockchain governance is a broad term, it is essential to keep its definition straightforward while supplementing it with specific mechanisms. To supplement this definition, a comprehensive table was developed that combines all previously identified mechanisms.Finally, five real-world blockchain consortia were investigated to understand how these mechanisms are designed and implemented in projects that have undergone piloting or advanced further.

The research was finalized by linking the eight most important stakeholders' values to governance mechanisms and, subsequently, governance designs. One example is Executive neutrality, which concerns the impartiality of the entity controlling a platform's direction. Stakeholders also, during interviews, have stated from past experiences that the executive body might not remain unbiased, leading to decisions that favour specific parties. Several governance mechanisms can ensure executive neutrality, including legal compliance, where decisions are based on industry laws and standards. However, due to the underdevelopment of data-sharing policies, industry standards, policies cannot yet serve as reliable benchmarks. Another approach is relying on ethical responsibilities, assuming all participants will adhere to principles of the greater good, though this might be overly optimistic in a profit-driven ecosystem. Since this value primarily revolves around the decisions made by the governing body, decision rights are identified as the most suitable governance mechanism and governance designs can be established.

Based on similar projects like VeChainThor and PharmaLedger, four governance designs were considered: Ecosystem members-led, Service Provider-led, Foundation-led, Independently Governed, and Foundation-led Ecosystem Governed. It was decided, based on the stakeholder value, that the foundation-led ecosystem-governed model was the most suitable, where a non-profit foundation directs the network's operations while being accountable to a board comprising ecosystem stakeholders. This model ensures stakeholder involvement and collective decision-making, maintaining executive neutrality. Finally, it is acknowledged that design inherently involves trade-offs. Therefore, selecting a particular design to address one stakeholder’s value can have ramifications on other values. Because of that, the design decision on other values is investigated. One potential downside is its impact on growth, as involving more stakeholders in decision-making can be challenging and may lead to resistance to adding new entities, potentially hindering growth. This method was employed for the other seven most important values that were identified through the BWM. However, it is important to note that this recommendation is based on the values identified through stakeholder interviews. If stakeholders prefer not to participate actively in the execution of governance duties, then a foundation-led, independently governed model would be more suitable. In this model, an independent non-profit entity would take on the responsibility of directing and managing the network, creating technology roadmaps, and providing necessary services, with limited direct involvement from the stakeholders.


In conclusion, to address the primary research objective of designing governance mechanisms that enhance participation in blockchain-based aviation part-tracking consortia, it can be stated that \textbf{there is no universally optimal governance mechanism design that enhances stakeholder participation; rather, this varies according to the values held by stakeholders within their specific context. As these values change depending on the context, it is recommended that decision-makers begin by investigating stakeholder values.} A value-focused thinking approach constitutes the primary contribution of this research, as it introduces a novel method of blockchain governance that prioritizes stakeholder values. By integrating these values into governance designs, a mutual understanding among consortium members is established, promoting more effective collaboration and decision-making. Furthermore, this research addresses a literature gap within the aviation industry, where blockchain consortiums have not been extensively examined.


For the initial phase of implementation, it is advisable to engage regulators to establish credibility, thereby fostering increased participation. Once a stable level of participation is achieved, the focus can then shift to examining the values of the stakeholders involved. Future research could assess the applicability of identified values and governance mechanisms in contexts beyond the aviation industry. Similar studies across various industries are important to ensure external validity. Additionally, further research could be conducted into how different mechanisms besides the one suggested in this research could fulfil stakeholder values and investigate the interaction among those mechanisms.

The increasing volume of global freight trade, coupled with economic growth, necessitates ongoing innovation in optimizing freight operations. Over the past decade, the concept of synchromodality has been explored to encourage a modal shift from unimodal to multimodal transport. Synchromodality, with its flexibility feature, can create more resilient freight transport systems. Various models employing different techniques have been proposed to establish a resilient synchromodal framework capable of reacting to disruptions. However, there are only few studies addressing the unknown duration of disruptions. This research proposes a learning-based modular framework comprising to capture the dynamics of disruptions in multimodal transport and learn to make more effective decisions, thus addressing the challenge of limited prior knowledge about disruptions and enabling fast responses to disruptions.

Dry ports have emerged as a promising solution to hinterland transport challenges. Existing literature implies an area of study on the topic of dry port that considers dry port stakeholders’ perspectives to construct a maturity model that could help dry port develop. This study has tried to contribute to this subject, starting with considering arguably two of the most relevant dry port stakeholders: the customer and the dry port operator. A series of performance logistic attributes has been identified to represent dry port customers’ perspectives, while a series of innovation factors is used to represent the dry port operator’s perspective. Utilizing the creative approach of MAMCA-Swing to analyze the services offered by a dry port using each of the stakeholders’ perspectives as criteria, the study has established a link between this analysis result and the creation of a dry port maturity model. A case study based on Indonesian dry ports has also been conducted to illustrate the use of such a framework, resulting in a dry port maturity model for Indonesia that is arguably relevant and useful in helping Indonesian dry ports develop.

This research presents a mathematical model for routing that incorporates multiple depots, occasional drivers, and multiple depot visits, a problem faced by many companies in reality. An Adaptive Large Neighborhood Search (ALNS) algorithm was employed, using Random and Worst removal operators, Basic Greedy and Regret-2 insertion strategies, a roulette wheel for operator selection, and simulated annealing for acceptance criteria. Computational experiments validated the effectiveness of the ALNS algorithm and model.Sensitivity analysis revealed that adding depots (ODs) can reduce routing costs by up to 15.21%, with various OD capacities offering additional savings (7.86% for 60% capacity and 9.97% for 70% capacity). A case study with the Dutch e-commerce company Ochama, scaled to 150 requests, confirmed practical applicabil- ity, achieving cost reductions of 11.37% for small vehicles and 6.85% for medium-sized vehicles. The results highlight that integrating ODs into routing strategies can significantly lower costs, with optimal outcomes dependent on market research to balance savings, service quality, and OD capacity.

The transport sector is the Netherlands’ second highest emitting sector, with 19% of the total energy demand. Where other sectors are becoming more sustainable, the transport sector is one of the most difficult to decarbonise 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 emissions in 2040 for the hinterland freight corridor of Rotterdam - Venlo with a high rail freight intensity. A list of potential measures was established with literature studies and expert interviews. With a normative scenario design approach, an iterative process resulted in a list of 8 potential measures with a set of targets for these measures. After computation with the DeCaMod model a reduction of 80% is achieved on the corridor. The results showed that for this corridor, the reduction depends on the availability and adaptability of biodiesels and the electrification of vehicles and vessels. In contrast, measures aiming to improve logistics efficiency do reduce the total energy required but are less effective in reducing carbon dioxide emissions.

Port systems face numerous challenges, including limited storage capacity at terminal yards, congestion in road port access due to overwhelmed infrastructure, and inefficient inter-terminal transportation. Close dry ports, situated between 10-40 km from the port, offer a potential solution, but lack flexible and reliable transport connections that efficiently handle transportation without adding extra handling moves. Recent technological advances in rail systems, particularly fully automated magnetic levitation (maglev) cargo shuttles, provide promising solutions for connecting dry ports with seaport terminals.

This research explores the integration of maglev technology into port logistics, focusing on connecting a dry port terminal to seaport terminals, with a direct connection to the berth. Using the Transport System Bögl (TSB) Cargo system as a reference, five different designs were developed for integration. These designs required a redesign of the dry port and terminal yard, as well as the design of the system’s berth connection and connections between all terminals.

Simulation modeling using Siemens Tecnomatix Plant Simulation software evaluated the performance of these designs under various scenarios based on Port of Hamburg demand input data. Results showed that all designs improved median berth times compared to the German benchmark of 18.96 hours, with Design 5 demonstrating the best performance together with Design 2.

Recommendations include continued collaboration with port authorities through simulation case studies, serving as proof of performance for potential integration projects, and exploration of collaboration opportunities with smaller scale ports facing space availability and road access issues. Further research should expand the model to accommodate new export container loading requirements and include all terminals, while studying new algorithms to balance the volumes and requests of all three terminals. This research demonstrates the feasibility of integrating maglev systems into port logistics, challenging the ’status quo’ and opening up new possibilities for improving port operations. Through a systematic approach, this study offers valuable insights for the integration of maglev technology into port logistics, paving the way for future advancements in the field.

Local governments hardly have a clear overview of their current progress in reducing emissions. This could be explained by the inadequacy of available tools. To address this issue, this research used a design cycle to explore the development of a feasible and useful method for allocating emissions in the road freight transport subsector. Four methods, two existing and two proposed, were evaluated against criteria derived from a literature review. A synthetic case study of Delft was conducted to evaluate these four methods and an indirect approach for relative accuracy, adaptability and feasibility. One of the proposed methods showed promise, but further research is needed to evaluate its absolute uncertainty. This proposed method is recommended to pursue, up until the moment the international standard only includes one method per subsector. Additionally, the proposed indirect allocation approach may offer greater flexibility when standards change and data is not fully accessible.

Long truck queues and congestion around terminals is a common sight, however they come with many negative externalities for all the stakeholders involved. Truck Appointment System (TAS) is the most commonly used system to face these problems, but it still has some drawbacks and limitations. Consequently, in this research an extension of the typical TAS is proposed in order to improve its performance. The main components of this system are the use of truck dependent time-windows, the utilization of real-time information and the adaptive trucks rescheduling model. The duration of the arrival time-windows is longer than the actual service times, allowing overlap between time-windows. Thus, the actual service sequence might be different from the reserved one. To determine the actual loading sequence an Optimization model is developed, which is run periodically while utilizing real-time truck information. A chemical plant is used as a case study in this research. The performance of the proposed TAS is assessed with the use of a Simulation model. The outcomes of this research suggest that the a less strict TAS can significantly improve the system’s performance, especially trucks’ waiting times. Also, the system’s resilience against disruptions and the plant’s environmental footprint are improved, while queues are reduced.