The European Central Bank (ECB) is developing the digital euro, a retail central bank digital currency (CBDC) aimed at providing a secure and efficient digital payment option. While the ECB prioritizes financial stability through features like holding limits and no remuneration, the success of the digital euro largely depends on consumer adoption. This thesis examines what design choices the ECB can make to enhance consumer adoption of the digital euro.
Using a two-phased approach, design science research was first applied to map the digital euro’s design space, followed by a discrete choice experiment assessing Dutch consumers’ adoption preferences. Findings reveal that holding limits are the most significant factor in adoption, with higher limits increasing appeal. Interest rates and privacy protections also play important roles, while the issuing institution (ECB vs. commercial banks) has little effect.
Results suggest that current design choices may limit adoption, raising concerns about the digital euro’s viability. The study recommends increasing flexibility in holding limits, exploring financial incentives and improving communication on privacy and offline functionality. It also shows how commercial banks influenced the design, leading to restrictive features. This highlights the need for more balanced governance in future policy decisions. The thesis provides recommendations for enhancing the digital euro’s design and adoption potential while highlighting broader implications for designing consumer-facing financial innovations.

A transmission system operator (TSO) is responsible for balancing (BA) and congestion management (CM) of the high voltage grid. BA matches supply and demand while CM ensures the save transport of electricity. For both functions the TSO uses procured upward or downward reserves from connected parties, called flexibility. Five flexibility markets exist: Frequency Containment Reserve (FCR), automatic Frequency Restoration Reserve (aFRR), manual Frequency Restoration Reserve directly activated (mFRRda), Reserve Other Purposes (ROP), and Capacity Restriction Contracts (CRCs). FCR, aFRR, and mFRRda are used for BA, while ROP and CRCs are used for CM. Each product, as these are called, has distinct bid requirements and renumeration schemes. Therefore, flexibility providers commit their capacity to specific products in advance according to their needs and capabilities. Consequently, a TSO lacks the ability to address potential flexibility shortfalls in one area by drawing on capacity reserved for another. Mismatches can arise, possibly leading to stressful situations for operators, higher costs, and even regional power outages. In addition, the various market options create complexities for participants potentially increasing the likelihood of inefficiencies and misallocations of flexibility resources.

To address this issue and improve system efficiency, this study explored the possible integration of these markets, combining two or more of the current products into a single flexible reserve product, which offers can be used universally. This provides TSOs with more leeway to mix and match, increasing the use of the available capacity, and simplifies the offering process for market participants. The study specifically analyzed a combination of the capacities currently offered through aFRR and ROP in context of the Dutch system operations. These products turned out to have notable similarities, including moderate response times, overlapping procurement timelines, and comparable system properties, which increases the likelihood that their capacities can be used universally. In addition, these products had the highest accessibility of historical data, which was important for the proposed quantitative analysis, an area identified as a significant gap in the existing literature. The simulation compared the current market design, where aFRR and ROP handle distinct BA and CM issues, with an integrated system where capacities are interchangeable. Performance was measured by problem-solving capacity, failure frequency, capacity usage for BA and CM, and costs. Historical data over five days was used, simulating various imbalance and congestion scenarios.

Results showed a significant improvement: BA and CM costs for the TSO dropped by 70% and 80%, respectively, thanks to better utilization of low-priced bids. The problem-solving capacity, especially in the upward balancing direction, rose by 360%, attributed to complementary reserves from aFRR and ROP. CM capacity usage increased by 11%, as low-priced aFRR bids overruled the increased effectivity of bids for CM. While integrating aFRR and ROP showed significant benefits, combining markets like FCR and CRC, which have specific characteristics, is less promising. A partial integration of more general markets, while keeping specialized products, appears more feasible and still offers flexibility for TSOs. Challenges remain, including the need for locational information in all bids and potential auction structure adjustments. Further research should explore the best auction designs and operational rules for integrated market designs.

The integration of non-dispatchable renewable energy and the electrification of society pose significant challenges to maintaining grid stability and efficiency. Currently, balancing and redispatch services in the Dutch electricity market operate as two separate markets, each managed by the Transmission System Operator (TSO). However, this separation leads to inefficiencies such as conflicting price signals, competition for the same flexible capacity, and increased congestion. This thesis evaluates three new market design options aimed at integrating redispatch and balancing services: 1) Simultaneous co-optimization 2) Separate two-step optimization with net capacity use, and 3) Separate two-step optimization with gross capacity use. A simulation model was developed using a simplified small-scale electricity network, testing the impact of these market designs under different pricing approaches: Marginal Pricing (MP), Pay-As-Bid (PAB), and Locational Marginal Pricing (LMP). The results demonstrate that while co-optimization can reduce capacity requirements by 21%, up to 81% of this improvement can be achieved by integrating redispatch and balancing with net capacity usage, without co-optimization. The study concludes that net capacity usage offers a practical alternative to co-optimization, with significant cost and capacity improvements. Further research should explore the operational feasibility of these new designs and the impact of network scale on market performance.

The latest state-of-the-art large language models (LLMs) are implicit computational models of humans due to how they are trained and designed. This implies that LLMs can be used as participants in economic and behavioural experiments. However, their technical and ethical limitations have sparked ongoing debate about the usefulness of LLMs in experimental research. This study contributes to the research area by reproducing the “Flip a Coin or Vote” experiment conducted by Hoffmann & Renes (2021), with GPT-3.5 and GPT-4o as participants.

The findings indicate that GPT-3.5 (1) struggles to fully understand the rules of the experiment, especially in calculating payoffs; (2) has difficulties interpreting negative and positive valuations; (3) fails to match the percentage of rational choices observed in the lab results; and (4) demonstrate results that deviate too much with the lab results to be considered human-like.

In contrast, GPT-4o shows greater promise as a ‘good’ participant. GPT-4o understands the rules of the game correctly and demonstrates a much stronger ability to make rational choices, even matching, and sometimes surpassing, the percentage of rational choices made by human participants. However, in the second part of the experiment, GPT-4o's decision-making becomes "inhumanly" accurate. Moreover the results deviate too much with the lab results to be considered human-like.

Future research should be focused on how to steer the results of LLMs towards more human-like results, possibly through enhanced prompting techniques or further model training and fine-tuning. Furthermore, future research should focus on establishing best practices for developing a more standardised approach to conducting simulation research with LLMs.

Achieving 100% carbon-free electricity production in the Netherlands by 2035, while ensuring reliability and affordability; this aim was established by the Dutch government, which intensified the national climate ambitions (Minister voor Klimaat en Energie, 2023a). However, even without considering this
intensified sustainability aim, the reliability of the electricity system is expected to decline beyond 2028 and surpass its norm by 2033, with an expected loss of load of 14.2 hours per year (TenneT, 2024). Central to this challenge is the crucial need for system flexibility to secure reliability (TNO, 2023). This need is heightened by the widespread integration of variable renewable energy sources (VRES) and
an expected surge in demand due to electrification efforts (TenneT, 2023).

Several technologies, such as demand-side response, interconnection, and storage, can partially provide for system flexibility (Aurora Energy Research, 2021). However, during situations with high demand and low VRES supply, such as ’kalte dunkelflaute’, there is a need for firm dispatchable generation capacity. However, projections on the expected operating hours and needed capacity during these hours vary widely. Different scenarios project a range between 4 GW and 20 GW by 2050 (Sijm, 2024). Currently, about 18 GW of firm capacity is installed in the form of gas power plants, compared
to a total of 56 GW of installed generation capacity in the Netherlands (ENTSO-E, 2024). Given the sustainability aim, this capacity would need to be decarbonized. However, only 58% of the capacity is technically feasible for retrofitting to operate on hydrogen (den Ouden et al., 2023). Therefore, this
thesis is built on the premise that investments in carbon-free firm capacity are crucial to achieving the 2035 sustainability aim, with a main focus on retrofitting current gas power plants to hydrogen power plants and potentially investing in new power plants.

Therefore, this thesis researched policy instruments that stakeholders and experts perceive as effective for incentivizing investments in firm carbon-free dispatchable electricity generation capacity while considering the 2035 100% carbon-free electricity production aim, overall system sustainability, reliability, and affordability. Additionally, this thesis aimed to provide explanations for differences in perceptions.

The research employed a qualitative exploratory and explanatory approach, using semi-structured interviews as the data collection method. A total of 14 interviews were conducted: 5 with stakeholders from (semi-)governmental organizations, 4 with stakeholders from electricity generation companies, 3
with experts from research institutes, 1 with a financial expert, and 1 with a stakeholder from an environmental organization. The interview data was analyzed using thematic analysis. First, to identify patterns of uncertainty factors that can challenge investments. Second, to identify potential policy instruments to mitigate uncertainties and enhance investment incentives. Third, to examine the perceived effects of these policy instruments regarding their effectiveness and impacts on sustainability, reliability, and affordability. Lastly, an explanatory approach was applied to identify potential explanations for differences in perceptions.

Several interconnected factors were identified that increase uncertainty in projecting the viability of investment business cases compared to conventional practices. These factors include, but are not limited to, uncertainty in operational costs, operating hours, electricity prices, and potential price cap
implementation. Additionally, these uncertainties are influenced by factors including base load capacity, intermittent VRES supply, flexibility-providing technologies, and inflexible load...

As a result of decreasing competition within the procurement of large construction projects in the Dutch construction sector, the need arises to understand the mechanisms behind the competition. Especially how decisions by clients on the procurement of construction projects impact the number of competitors. When this is understood, clients can contribute to solving the problems in the construction market. In an attempt to supply clients with insights to impact the number of competitors, this thesis tries to answer the main research question "To what extent do client decisions in the procurement of construction projects in the Dutch construction sector affect the number of competitors?".

In an attempt to answer the question, it has been tried to create a model that predicts the number of competitors in the tender phase of construction projects. To be able to make predictions, data on factors that potentially affect the number of competitors is inserted in a regression analysis. Values are included that represent the variables project type, project value, project duration, client, contract type, market conditions, need for work, and tender method. The regression coefficients determined in this analysis can reveal how individual variables affect the predicted number of competitors. But the usability of these coefficients depends on the performance of the analysis set-up, i.e. the used regression model, chosen variables, and input data.

It turned out that the achieved prediction performances were unsatisfactory. The best-performing model reached a prediction accuracy of 44.9%, just 8.7% better than a constant guess. As a result, it is concluded that the relationship between the client factors and the number of competitors could not be quantified. Additional research on the predictability within the data affirmed that it would be hard to make any predictions. The Entropy and Mutual Information within the data, identifying the predictability, showed that the independent variables in the data could only solve approximately 30% of the 'chaos' within the distribution of the number of competitors.

The unsatisfactory model accuracies are an interesting result, given the fact that, for almost every factor considered influential on the number of competitors, a value has been included in the calculations. The question arises whether even a relation exists between client factors and the number of competitors. On top of that, the identified marginal relations pointed at the market conditions as most influential to the number of competitors. Further indicating that clients have a marginal effect on the competition within tenders. Therefore, it seems that clients are unable to solve the decreasing number of competitors in the construction industry.

In order to show the absence of a relation between the number of contractors and client factors, further research is necessary. It is yet impossible to prove this absence because improvements can still be made to the utilized data and methodology.

The thesis identifies critical implementation barriers to collective battery storage on business parks in the Netherlands. Subsequently, using a mixed methods research approach, different assessment frameworks are applied to propose three policy interventions that can overcome the identified critical implementation barriers and stimulate the adoption of collective battery storage in the Netherlands.

Wind energy is deemed important in the Netherlands in sustainable energy transitions. While Commercial Wind Energy Project Developers (CWEPDs) bring professionalism, Local Energy Cooperatives (LECs) promote local renewable initiatives. The Dutch Klimaatakkoord aims for 50% community-owned renewable electricity, but real-world implementation of community involvement is unclear. The Institutional Analysis and Development (IAD) framework helps understand 'rules-in-use' for decision-making. This study explores how LECs and CWEPDs interact with these rules, focusing on Dutch onshore wind farm projects. Using 14 case studies, the research compares organisational forms in project outcomes, employing interviews and written sources for data collection and statistical testing and QCA for analysis. Key findings include LECs completing projects faster and with fewer objections than CWEPDs and the importance of transparent information sharing. The study suggests policy and development implications, highlighting the need for more inclusive and transparent decision-making in wind energy projects.