The ongoing electrification of the Dutch energy system, driven by ambitious 2050 climate targets, is causing increasing congestion in medium- and low-voltage electricity networks. A key challenge lies in the mismatch between rapidly increasing renewable electricity generation and the limited capacity of the grid infrastructure. This imbalance not only delays the energy transition but also obstructs economic growth, as businesses and consumers struggle to connect new renewable projects to the grid. Residential Battery Energy Storage Systems (R-BESS) are considered a key flexibility solution to mitigate this problem. However, if operated purely for market profit, especially through arbitrage and participation in the imbalance market, R-BESS can unintentionally exacerbate grid congestion. This thesis investigates how congestion-neutral operation of R-BESS can be implemented to ensure their contribution to a stable and resilient grid. This thesis investigates how the concept of congestion-neutral operation, a relatively new design approach that aims to prevent residential batteries from contributing to peak grid load, can be applied to the integration of R-BESS. While R-BESS are often deployed to maximize economic returns through market participation, this research focuses on the impact of this implementation and investigates operational strategies that explicitly avoid increasing grid congestion. The central research question addressed is: How can congestion-neutral R-BESS be integrated into Dutch electricity networks to mitigate net congestion while balancing techno-economic trade-offs? A mixed-method approach was applied. The qualitative phase involved literature review and interviews with involved actors (distribution system operators, aggregators, and policy advisors) to identify key technical and institutional design elements for congestion-neutral R-BESS. The quantitative phase implemented a Mixed-Integer Linear Programming model in PyPSA to simulate R-BESS behavior at aggregator level under various market scenarios. The model was applied to a real Dutch medium-voltage substation (MSR), with scenario analyses for 2024 and 2030, supported by sensitivity and robustness testing on weather variability and system parameters. Results show that uncoordinated R-BESS operation substantially increases congestion, particularly in the imbalance market. The outcomes are summarized in Table 1. Congestion-neutral strategies, in particular time constraints, significantly reduced negative grid impacts. For example, applying time constraints reduced new congestion events by half for day-ahead and imbalance 2024 scenarios. However, mitigation periods also decreased with more than 25% for both scenarios. In addition, time-constraint operation preserved economic viability in the day-ahead market: total system costs increased by only 0.9% (2024) and 1.3% (2030), when combining battery trading with self-consumption (”value stacking”). However, for the imbalance market, total system costs increased by 3.47% and 5.09% under time-constraint operation. The study highlights key trade-offs between grid impact and business model profitability. It also identifies limitations, including single-node focus and perfect foresight assumptions.
Practical recommendations include enabling congestion-neutral R-BESS through flexible constraints, distinguishing day-ahead and imbalance market, and clear coordination between DSOs and aggregators. Future research should extend to multinode grids, explore dynamic real-time signals, and further integrate market design for congestion-neutral flexibility services. All results of this thesis are open source. The complete model developed for this research is publicly available at: https://github.com/Tanneheemsbergen/pypsa-NL2025

Heavy-duty trucks contribute significantly to greenhouse gas emissions in the transport sector,
despite making up only a small portion of the total vehicle fleet. As the EU targets a 90% reduction
in truck emissions by 2040, Electric Road Systems (ERS) have emerged as a potential solution by
enabling trucks to charge while driving, removing the need for large, heavy batteries. However, little
is known about the temporal and spatial energy demand of such an infrastructure and the impact
it would have on the electricity grid—particularly in the Netherlands. This study investigates the
expected temporal distribution of energy demand resulting from an ERS corridor between Rotterdam and Venlo. A quantitative approach is used to model freight flow, ERS adoption potential, and estimate energy consumption. BasGoed origin-destination data is used to map freight volumes,
and a set of spatial criteria determines which trips are eligible for ERS usage. By combining the data and demand characteristics, a temporal and spatial demand pattern can be identified, that can be used by the industry and policy makers to understand ERS and what is needed to support future implementation.

Empty Container Repositioning (ECR) remains one of the most persistent and costly inefficiencies in global container logistics. To balance asymmetric trade flows at global, regional, and local scales, empty containers must be relocated from surplus locations to areas facing deficits. These movements typically generate no revenue for shipping lines. While the ECR problem has been widely studied at the global level, regional and local repositioning remain underexplored. This study investigates key barriers preventing direct inland repositioning between surplus and deficit locations within Maersk's hinterland networks of Rotterdam and Antwerp. A multi-method research approach was adopted, encompassing network analysis using internal Maersk data, stakeholder identification through semi-structured interviews, operational feasibility assessments, and financial analysis of repositioning corridors. Only 12% of container movements currently use direct repositioning, underscoring an overreliance on hub-based repositioning. Critical barriers were identified at both depot and corridor levels. Depot-level barriers include limited inter-vendor collaboration, fluctuating stock levels, container quality requirements, and seasonal flow variations. Corridor-level barriers encompass off-route positioning, fixed transportation schedules, lack of appropriate services, and physical constraints such as barge sizes. Financial assessments demonstrate clear cost advantages for direct repositioning by avoiding additional handling steps associated with hub-based movements. Operational insights highlight the impact of stakeholder interactions, coordination constraints, and planning routines on repositioning efficiency. These findings underscore the need for better stakeholder coordination and more flexible planning routines to make direct inland repositioning viable. By framing ECR as a coordination problem rather than purely an optimization task, this study offers practical insights for improving inland container flows in complex multi-actor networks.

Container terminals worldwide are increasingly adopting automation solutions to improve operational efficiency and maintain competitiveness. However, the success of automation solutions, particularly in Ship-to-Shore (STS) crane operations, varies significantly across different regions. While existing research has explored automation benefits in individual and general terms, a clear understanding of how regional contexts influence value creation and implementation success has been lacking. This research addresses this knowledge gap by examining both the operational performance improvements and stakeholder dynamics across different regional contexts.

The primary objective was to quantify the value creation of STS crane automation while understanding how regional factors affect this value creation. Through a comprehensive methodology combining a quantitative operational analysis with a stakeholder and risk analysis, this study examined three major ports: Antwerp, Kaohsiung, and Los Angeles.

The research findings reveal that automation value shows in three dimensions. Operational value was demonstrated through improved cycle times, enhanced consistency in performance, and reduced human error. Economic value showed through reduced labor costs, improved energy efficiency, and decreased maintenance requirements. Strategic value emerged through environmental sustainability benefits and competitive positioning, although realization depends heavily on regional contexts.

The stakeholder analysis identified six key groups affected by automation, each with distinct priorities and concerns. For example, terminal operators consistently seek efficiency improvements, while labor organizations prioritize job security and skills development. However, the interaction between these stakeholders varies heavily by region. Los Angeles faces substantial union resistance and complex regulatory requirements, while Kaohsiung confronts technical expertise gaps and cybersecurity concerns. Antwerp represents a middle position, where established regulatory frameworks and structured stakeholder relationships create more predictable implementation processes compared to other regions.

This research provides concrete insights into how automation value differs across regions. In North America, the primary challenge is not technical but social, with labor relations directly determining implementation success. In Asia, value creation is limited more by technical expertise gaps than by stakeholder resistance. In Europe, success requires balancing established regulatory requirements with structured stakeholder negotiations.

The findings demonstrate that while automated systems can achieve similar technical performance across regions, the path to realizing this value varies based on local conditions. Based on this research, three key recommendations emerge for successful STS crane automation implementation. Firstly, terminal operators must adapt their automation strategy to regional risk profiles. Secondly, technology providers should move away from standardized solutions and instead develop region-specific implementation strategies that address local challenges identified in this study. Thirdly, both parties should create structured stakeholder engagement programs to identify regional priorities, as this research shows stakeholder dynamics significantly impacts implementation success. Following these recommendations can reduce implementation timelines and possibly improve project success rates.

This improved understanding of regional variation in automation value creation provides a practical foundation for future terminal automation projects, while contributing to theoretical knowledge.

Today, companies face increasing pressure to report their sustainability practices, particularly greenhouse gas emissions, due to new regulatory requirements such as the Corporate Sustainability Reporting Directive (CSRD) and European Sustainability Reporting Standards (ESRS). This thesis explores how Enterprise Resource Planning (ERP) systems, specifically SAP, can effectively support organizations in complying with emissions reporting under ESRS E1. An exploratory qualitative approach combining desk research, a detailed case analysis of SAP functionalities, and expert interviews was undertaken to investigate reporting requirements, data integration challenges, and best practices.

The research identified critical emission metrics required by ESRS E1 and evaluated SAP's capability to manage these metrics through its Sustainability Control Tower. Key challenges were found in the accurate and complete collection of emission data, particularly Scope 3 emissions. Furthermore, organizational and strategic obstacles, such as unclear responsibilities and viewing emissions reporting purely as compliance rather than a strategic advantage, were highlighted.

To address these challenges, the study proposes a structured 12-step roadmap, emphasizing data integration, clear internal governance, and strategic alignment of emissions reporting with broader business objectives. The roadmap facilitates accurate, compliant reporting while enhancing strategic decision-making capabilities. The thesis concludes that, although further validation of this roadmap in practice is necessary, ERP systems like SAP, when properly integrated, provide robust tools for effective emissions reporting and strategic sustainability management.

This study presents two novel strategies for identifying outlier parcels in urban deliveries, focusing on cost and environmental impact. With the growth of Business-to-Customer (B2C) e-commerce, the logistics industry faces increased pressure to improve last-mile delivery (LMD) efficiency. Outlier parcels, characterized by higher costs and emissions, pose significant challenges to logistics service providers (LSPs). Using the Marginal Cost Method and the COFRET method, this study develops cost-based and emission-based identification strategies to help LSPs address inefficiencies. The elbow point method is introduced to set objective thresholds for identifying outliers. Results from simulations in the South Holland region reveal significant differences in outlier parcel distributions across various carriers. Additionally, a sensitivity analysis assesses the impact of carbon pricing on parcel identification. The findings provide actionable insights for LSPs to optimize delivery operations and achieve sustainability goals. Future work will explore the application of these methods in different regions and consider alternative delivery methods for handling outlier parcels.

Abstract— This research aims to explore the potential of selfservice technologies (SSTs) within football stadiums, focusing on Stadion Feijenoord ”De Kuip”. The potential benefits of these SSTs includes reducing waiting times, lowering costs, and enhancing the supporters experience. The approach begins with a review of existing literature on SSTs in the hospitality industry. Following this review, the study will employ stated choice experiments, alongside data analysis and observations, to explore the potential benefits and impacts of these SSTs. This research provides insights about operating efficiency and effectiveness of SST and traditional counters in football
stadiums. Besides, the importance of human interaction at these different types of counters is assessed. Keywords - Selfservice technologies, stadiums, human interaction, supporters experience, services times, productivity

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.

The increasing parcel demand is resulting in increasing traffic congestion and emission problems in urban freight system. Crowdshipping service is an innovative logistics solution which envisions using the excess capacity in existing passenger transport to perform the delivery tasks. However, it may bring extra vehicle kilometres travelled due to detours and new trips generated. To address this challenge, most studies focus on designing and evaluating the crowdshipping service for all parcel demand, while one study points out the potentially larger benefits of crowdshipping service for outlier parcels.

Therefore, this study aims to investigate the transport impacts of crowdshipping service for outlier parcels, which are defined as the parcels with high environmental impacts. A case study is conducted in The Hague. First, the parcel carbon footprint is calculated to segregate the outlier parcels. Then, a public transport-based crowdshipping delivery scenario is proposed, with parcel lockers at train stations as the transfer points and train travellers as the potential occasional couriers. The simulation results show that outsourcing the outlier parcels to crowdshipping service is beneficial to the transport system and prioritising outlier parcels of logistics service providers with low market shares can achieve more savings in transport and higher service efficiency.

The growth of e-commerce has increased the demand for last-mile delivery. This increased demand
poses the sector of last-mile delivery with challenges such as traffic congestion, route optimization and environmental concerns. Delivery to a Service Point or a Parcel Locker, self-collection alternatives, have to potential to address these challenges. This research employs a discrete choice experiment to gather insights into consumer preference for regular parcel delivery and to uncover previously unexplored consumer preference for alternative delivery preference in the case of delivery failure. This second aim constitutes the main addition of this study. An online survey was conducted which resulted in 210 valid responses. The results show that in the case of anticipated failed delivery, most consumers prefer delivery to their neighbours or have the parcel left at an agreed place around the house. The distance to a Service Point or Parcel Locker is the most important delivery attribute guiding this decision. However, both now and in the future, demand for the PL as an alternative delivery option in case of delivery failure seems low, with few policy options to increase this demand. Regarding parcel delivery preference at checkout, the price of Home Delivery is most dominant in the trade-off consumers make. In contrast to other studies, the opening hours or the delivery moment do not contribute significantly. To best increase the demand for self-collection alternatives, parcel delivery companies should focus on: shortening the distance to the Parcel Lockers or Service Points, locating Parcel Lockers in commercial buildings as opposed to public spaces, and increasing the awareness of Parcel Lockers and increasing the awareness of the benefits of self-collection in general. However, the results of this study indicate that in order for the PL to become dominant ’at online checkout’, both a price incentive and a shortening of the distance from consumer to PL are necessary, but at significant cost. Further research should aim to investigate the demand for changing delivery options through notifications and the viability of
the last-mile delivery market agreeing on lower prices for self-collection as proposed in scientific literature.

In the context of striving for zero emissions in cities in the future, finding new logistics methods is of paramount importance. Inspired by the concept of the Physical Internet, a parcel transportation method called ”crowdshipping” has begun to gain attention. In this study, a new form of crowdshipping is investigated, where parcel lockers are introduced as transfer points within crowdshipping. The research examines the impact of parcel lockers on crowdshipping services from the supply side in two aspects: carrier's choice behavior and the status of crowdshipping task completion in the simulation of Delft network with and without parcel lockers. The results suggest that the application of parcel lockers has a positive impact on crowdshipping services, and this new form of crowdshipping has potential for further development.

Autonomous delivery robots are a promising alternative for last-mile delivery. To realise successful implementation of delivery robots in the public space, it is important to study the interaction between robot and environment. The traffic environment includes the physical infrastructure, traffic conditions and the people using the environment. This research proposes an assessment method that can be applied to determine the ‘roboreadiness’ of a traffic environment. This expresses whether the environment is ready for delivery robots to drive there. The performance of new transport concepts and the acceptance of innovations in the transport system are studied in a literature review, leading to the important factors. This is translated into a conceptual model which is the basis for the development of the method. To be able to assess the factors, suitable sub-methods are chosen and elaborated. To study the performance of the robot in its traffic environment a test-case can be performed and to examine the social acceptance a survey can be conducted. Analysing the resulting data leads to the level of roboreadiness. As a final step in the development of the method, a validation is carried out. While demonstrating the assessment method, it follows that the method is suitable for determining the level of performance, social acceptance and consequently the roboreadiness. In addition, first insights regarding the performance and social acceptance of the delivery robot at the campus of the Erasmus University Rotterdam are presented. The proposed assessment method can be used to collect data that can be useful for future projects. Although the method is valid, suggestions for improvements are made for further research.

Road freight transport has a major impact on society with external effects such as congestion, air pollution and carbon emissions. Therefore, the European Commission stimulates the more sustainable alternative Intermodal Freight Transportation (IFT). To increase the share of IFT, it is needed to know the performance of the current IFT-network. In this research, a methodology to assess performance of chains in IFT is developed. The developed Weighted Slacks-Based Data Envelopment Analysis model takes into account parallel and overlapping divisions and different structures of chains. The method is tested with a numerical example and a sample of real European IFT chains and solves issues of a compared Data Envelopment Analysis model. The methodology is then implemented to the rail and transshipment part of the North Sea – Mediterranean and Rhine – Alpine freight corridors.

The synergic effect between the spatial organisation and freight transport is crucial for transport planners to understand. It will help in improving freight transport planning. The absence of freight data has made such a study difficult. This research aims to understand the relation between spatial organisation and freight transportation by using the 1681 logistics facility database and the database of 2.65 million shipments of the Netherlands collected by CBS in 2015. The logistics facilities are categorised based on different spatial and logistics characteristics. The indicators of freight activity for the logistics facilities are studied, and the transport efficiencies are analysed subsequently. The analysis concluded on three main points. First, there are eight main types of logistics facilities in terms of spatial characteristics. Second, spatial characteristics have an impact on freight activity. Finally, the transport efficiency of the different logistics facilities can not be directly compared due to their objective and position in the supply chain.

Urban freight transport is a significant cause of CO2 emissions. This creates the need to implement CO2 mitigation measures for freight transport in cities. The International Transport Forum (ITF) is currently working on an EU-funded programme, the Decarbonising Transport initiative, to assess CO2 mitigation measures. However, there is no model yet that is suitable to analyse urban freight transport on a European level. Therefore, the research question of this thesis is: How can a model for urban freight transport in the urban region of Rotterdam (Groot-Rijnmond) be created, that allows for estimation of CO2 impacts of policy measures for decarbonisation and that can be transferred to other European urban areas? To answer this question, a literature study has been done to set the context of the project. This was followed by an identification of available data sources for European freight transport and the creation of a transferable modelling methodology. Based on the data and the established methodology, a model has been estimated. With this model, seven policy scenarios have been tested.

A nation’s main port is a crucial component that contributes to the economic development of a country. Therefore, the role of the port becomes more critical nowadays. However, due to the existing hub-and-spoke structure of the European multimodal transportation network, polarisation and regionalisation are visible in the network. The increasing regionalisation and polarisation that happens in the European region widen the inequality in the network. Moreover, the inequality in the network will impact the sensitivity and resistance of the whole network to targeted disruptions, such as infrastructure failures, natural disasters, or potential terrorist attack. Then, on the real aspect, the widening of inequality in the network also inhibits the well-distributed economic development in the region. In this study, various methods will be employed to have multiple points of view of the network itself, such as the multilayer network analysis, community detection, and Network-based Hub Port Assessment (NHPA). Furthermore, the study will be structured into three building blocks that shapes as a foundation to perform the final analysis and provide a multifaceted overview of the overall network, which is versatility analysis, community structure analysis, and quantification of collaboration-connectivity of the container hubs. Afterwards, three determinants as measurements of network performance are defined, to perform the criticality analysis. This study concludes that the development of connections between different communities can help to decrease the existing inequality in the network. Then, the appearance of new community structure in the network can help to decrease the inequality in the network, which lead to more well-distributed economic development in the region.

The term last-mile delivery refers to the final leg of a business-to-customer service, in which a product is shipped from a depot to a final destination point by means of land transportation, such as vans and small trucks. Although they provide a common and easy way to consign products, companies are striving for new transport technologies to reduce congestion problems, infrastructure limitations and air pollution. Recently, a valid alternative to road-bounded vehicles that is has gained attention is the adoption of drones in the delivery fleet. Drone applications range from military training, surveillance, path recognition and shipment of perishable products in emergency situations. Research on drones as delivery vehicles is still on its early stages, with some practical trials carried out by leader companies such as Google and Amazon. However, the application of drones in the pharmaceutical sector, and specifically for home deliveries of medical products, has not been investigated yet. To gain new insights into the feasibility of introducing drones in the delivery fleet composition, drone applications were studied for the delivery operations of the pharmacy BENU t Slag, in Rotterdam. Two scenario alternatives were tested using the Vehicle Routing Problem (VRP) formulation and a Large- scale Neighbourhood Search (LNS) algorithm was implemented to estimate the performance indicators associated with each scenario. Performances were then analysed through a comparative analysis. Conclusively, indicators were found to improve the delivery performance when drones are included in the fleet composition, with gains in environmental aspects, service time and delivery costs. Results provide important information for further research on the implications of using drones in the pharmaceutical sector. Moreover, results are also useful for BENU t Slag, providing a valid feasibility assessment of using drones for their home delivery operations.

Small and Medium-sized Enterprises (SMEs) tend to focus upon short-term profit in a crisis period, however the EU advised SMEs’ to invest in innovation and quality of products. How SMEs balance between these two contradicting strategies is seldom addressed. Therefore, this study explores how SMEs align their organization upon short term exploitation of current products and explore long term product innovations simultaneously.
The results of this multiple case study research identify Exploitative activities are supported by commonality among organizational goals and Exploration requires investment in knowledge sharing. A moderating effect upon exploitation and exploration, as identified in literature about Organizational Ambidexterity, is also identified among SMEs.

This thesis explores the possibilities to improve order allocation for petrol delivery with the aim to lower the travel distances. In this research a simulation model has been designed that can test different order pairing strategies for fuel delivery to petrol stations. The Multi–Period Split Compartment Vehicle Routing Problem with Time Windows and Vehicle Restrictions (MP-SCVRPTWVR) used in the simulation is an extension to the petrol station replenishment problem. This optimization model could find optimal solutions for up to 20 stations. To test for larger cases, a heuristic has been proposed for the original model. This proved to have a significant impact on the amount of daily orders that could be handled, with an increase of 25 percent.