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R. van Bergem
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12 records found
1
Efficiency Versus Permission
Transaction Cost Economics and Regulatory Feasibility of Battery Energy Storage for System Services in the Dutch Electricity System
The retirement of conventional power plants is removing stability functions that the Dutch electricity system can no longer take for granted. Battery energy storage systems (BESS) are technically capable of filling the gap, but unlike conventional generators, every service must be explicitly contracted, specified, and monitored. Prior research has focused on technical feasibility and economic optimisation, leaving the governance dimension unaddressed. The Energy Act 2026 opened conditional pathways for TenneT to own storage assets directly for the first time, creating an institutional landscape that existing frameworks do not yet address. This raises the central question: what is the efficient governance structure for BESS providing system services in the Dutch electricity system, does the Energy Act 2026 permit it, and where it does not, what is the best feasible alternative?
This thesis applies Williamson's transaction cost economics to derive service-specific governance predictions for six system services, tests those predictions against the Energy Act 2026, and integrates both analyses into the System Services Governance Framework.
Results show that the same physical BESS receives a different governance prediction depending on which service it provides. Balancing can be procured through competitive tendering. Voltage control and congestion management require long-term bilateral contracting. Synthetic inertia, system strength, and black start require direct ownership by TenneT. The Energy Act 2026 permits the efficient form for two services and not by default for three.
The study shows that standardisation decisions are simultaneously governance design decisions. Where product definitions exist, competitive markets are feasible. Where they do not, contracting becomes impossible. Closing the governance gaps requires product standardisation at the European level and published regulatory guidance on exception routes. ...
This thesis applies Williamson's transaction cost economics to derive service-specific governance predictions for six system services, tests those predictions against the Energy Act 2026, and integrates both analyses into the System Services Governance Framework.
Results show that the same physical BESS receives a different governance prediction depending on which service it provides. Balancing can be procured through competitive tendering. Voltage control and congestion management require long-term bilateral contracting. Synthetic inertia, system strength, and black start require direct ownership by TenneT. The Energy Act 2026 permits the efficient form for two services and not by default for three.
The study shows that standardisation decisions are simultaneously governance design decisions. Where product definitions exist, competitive markets are feasible. Where they do not, contracting becomes impossible. Closing the governance gaps requires product standardisation at the European level and published regulatory guidance on exception routes. ...
The retirement of conventional power plants is removing stability functions that the Dutch electricity system can no longer take for granted. Battery energy storage systems (BESS) are technically capable of filling the gap, but unlike conventional generators, every service must be explicitly contracted, specified, and monitored. Prior research has focused on technical feasibility and economic optimisation, leaving the governance dimension unaddressed. The Energy Act 2026 opened conditional pathways for TenneT to own storage assets directly for the first time, creating an institutional landscape that existing frameworks do not yet address. This raises the central question: what is the efficient governance structure for BESS providing system services in the Dutch electricity system, does the Energy Act 2026 permit it, and where it does not, what is the best feasible alternative?
This thesis applies Williamson's transaction cost economics to derive service-specific governance predictions for six system services, tests those predictions against the Energy Act 2026, and integrates both analyses into the System Services Governance Framework.
Results show that the same physical BESS receives a different governance prediction depending on which service it provides. Balancing can be procured through competitive tendering. Voltage control and congestion management require long-term bilateral contracting. Synthetic inertia, system strength, and black start require direct ownership by TenneT. The Energy Act 2026 permits the efficient form for two services and not by default for three.
The study shows that standardisation decisions are simultaneously governance design decisions. Where product definitions exist, competitive markets are feasible. Where they do not, contracting becomes impossible. Closing the governance gaps requires product standardisation at the European level and published regulatory guidance on exception routes.
This thesis applies Williamson's transaction cost economics to derive service-specific governance predictions for six system services, tests those predictions against the Energy Act 2026, and integrates both analyses into the System Services Governance Framework.
Results show that the same physical BESS receives a different governance prediction depending on which service it provides. Balancing can be procured through competitive tendering. Voltage control and congestion management require long-term bilateral contracting. Synthetic inertia, system strength, and black start require direct ownership by TenneT. The Energy Act 2026 permits the efficient form for two services and not by default for three.
The study shows that standardisation decisions are simultaneously governance design decisions. Where product definitions exist, competitive markets are feasible. Where they do not, contracting becomes impossible. Closing the governance gaps requires product standardisation at the European level and published regulatory guidance on exception routes.
Decision-making under uncertainty often relies on access to accurate probabilistic forecasts. In many contexts, such forecasts are scarce or difficult to obtain. Decentralised prediction markets are widely regarded as effective tools to aggregate dispersed information that decision-makers can use as forecasts to make better decisions about an uncertain future. Recently, there have been major advances in large language models that have led to claims that large language models could complement or replace market-based forecasting by synthesising information without the need for incentive-driven markets. However, there is limited empirical evidence comparing forecasts generated by large language models to market-based aggregation under real-world conditions. This thesis puts these claims to the test by examining the extent to which large language models can replicate or complement human forecasting as reflected in decentralised prediction markets. Using Polymarket as a benchmark for collective human forecasting, probability forecasts generated by large language models are compared to live market probabilities. Forecasting performance is evaluated across different market conditions, and the decision-making relevance of forecasts generated by large language models is evaluated through trading simulations. The results show that market probabilities are consistently more accurate than the forecasts generated by large language models in terms of predictive accuracy. The findings hold across all evaluated models, model combinations, prompting strategies, market stages, and liquidity levels of markets. A regression-based aggregation model that mixes market probabilities and large language model forecasts achieves predictive performance comparable to that of the market in some cases, but it fails to generalise when put to the test under realistic conditions. The findings suggest that large language models at their current stage cannot substitute prediction markets as information aggregation mechanisms. The results challenge claims that large language models can replicate the performance of prediction markets in the generation of accurate probabilistic forecasts. The results highlight the need for caution when deploying large language models in the context of high-stakes decision-making.
https://github.com/KetillHafdal/llm-vs-prediction-markets ...
https://github.com/KetillHafdal/llm-vs-prediction-markets ...
Decision-making under uncertainty often relies on access to accurate probabilistic forecasts. In many contexts, such forecasts are scarce or difficult to obtain. Decentralised prediction markets are widely regarded as effective tools to aggregate dispersed information that decision-makers can use as forecasts to make better decisions about an uncertain future. Recently, there have been major advances in large language models that have led to claims that large language models could complement or replace market-based forecasting by synthesising information without the need for incentive-driven markets. However, there is limited empirical evidence comparing forecasts generated by large language models to market-based aggregation under real-world conditions. This thesis puts these claims to the test by examining the extent to which large language models can replicate or complement human forecasting as reflected in decentralised prediction markets. Using Polymarket as a benchmark for collective human forecasting, probability forecasts generated by large language models are compared to live market probabilities. Forecasting performance is evaluated across different market conditions, and the decision-making relevance of forecasts generated by large language models is evaluated through trading simulations. The results show that market probabilities are consistently more accurate than the forecasts generated by large language models in terms of predictive accuracy. The findings hold across all evaluated models, model combinations, prompting strategies, market stages, and liquidity levels of markets. A regression-based aggregation model that mixes market probabilities and large language model forecasts achieves predictive performance comparable to that of the market in some cases, but it fails to generalise when put to the test under realistic conditions. The findings suggest that large language models at their current stage cannot substitute prediction markets as information aggregation mechanisms. The results challenge claims that large language models can replicate the performance of prediction markets in the generation of accurate probabilistic forecasts. The results highlight the need for caution when deploying large language models in the context of high-stakes decision-making.
https://github.com/KetillHafdal/llm-vs-prediction-markets
https://github.com/KetillHafdal/llm-vs-prediction-markets
Architectural Framework for Federated Learning in Aviation Maintenance
Designing and Analyzing Key Features for Data Sharing Acceptance with ArchiMate Modeling
Master thesis
(2024)
-
B.L.J. van de Walle, G.A. de Reuver, Marcela Tuler de Oliveira, R. van Bergem, Asteris Apostolidis
Executive Summary
Current Status The aviation industry is transitioning from traditional maintenance practices, typically scheduled after a specified number of flight hours, to more advanced, data-driven approaches. These predictive maintenance techniques leverage machine learning models to enhance the accuracy of assessments. These models can reduce the frequency of unscheduled maintenance and optimize inventory management. However, such models rely heavily on large datasets, which are challenging to compile in the aviation sector due to the rarity of specific operational incidents and the diverse types of data collected by different companies. When collaborating, a tradeoff arises between the level of security measures, trust in partners, and ensuring the system still functions. Federated Learning emerges as a promising solution to these challenges. Federated Learning is a novel form of machine learning that allows multiple entities to collaboratively develop a shared model while keeping their data localized, thus maintaining privacy and data sovereignty. Question The primary objective of this research is to identify and validate the critical architectural features necessary for the acceptance of Federated Learning in the aviation maintenance industry. Architectural features refer to design choices such as security protocols and governance frameworks. By focusing on these aspects, this study addresses the technical and collaborative challenges that must be overcome to develop a Federated Learning system for predictive maintenance in aviation. Resulting in the following research question:
‘What architectural features should be included in the design of the ‘Federated Learning for aircrafts’ predictive maintenance system’ to be accepted by the stakeholders in the aviation industry?’ Approach This study employs a Design Science Research methodology. The sub-questions for this research follow the steps in the Design Science Research methodology. This is not the case for the demonstration phase which was deemed not possible due to the conceptual nature of the design.
1.
What are the challenges in sharing maintenance data, and how do they impact data safety and collaboration? Through a literature review and interviews with stakeholders, the study identified concerns about data privacy, security, and competition. These challenges significantly limit data-sharing initiatives. (Problem Identification and Motivation)
2.
What specific technical requirements should the Federated Learning system have to address these challenges? Based on the interviews and thematic analysis, a list of requirements was developed. These include robust privacy mechanisms, transparent governance, ensuring model explainability, and clear accountability mechanisms. (Defining the Objectives for a Solution)
3.
What architectural features should be included in the Federated Learning design to meet these requirements? ArchiMate modeling was used to design a system incorporating these requirements. Federated Learning, combined with encryption techniques and a consortium-managed system, was the result. (Design and Development)
4.
How do stakeholders perceive the acceptability of the designed system? After the validation interviews and the expert session, three changes were implemented: Switching from
5
differentiating on the model version to differentiating on the usages. Improving explainability
by switching to Trusted Executive Environments and removing differential privacy. Traditional contracts to increase trust towards each other were also added. (Evaluation)
5.
What lessons can be learned from the development and evaluation of the Federated Learning system for future improvements? The research highlights the importance of continuously building trust among stakeholders. Furthermore, the token-based reward system based on contribution is a good incentive to be adaptable and develop long-term collaboration. (Communication) Results
To build trust, this study employs traditional methods like legal contracts and appoints a consortium as a neutral party. Transparent governance and involving a neutral, trusted entity is necessary to gain stakeholder acceptance and ensure long-term collaboration. Blockchain technology enhances the transparency of the consortium's operations, ensuring all transactions and data exchanges are recorded on an immutable database... ...
Current Status The aviation industry is transitioning from traditional maintenance practices, typically scheduled after a specified number of flight hours, to more advanced, data-driven approaches. These predictive maintenance techniques leverage machine learning models to enhance the accuracy of assessments. These models can reduce the frequency of unscheduled maintenance and optimize inventory management. However, such models rely heavily on large datasets, which are challenging to compile in the aviation sector due to the rarity of specific operational incidents and the diverse types of data collected by different companies. When collaborating, a tradeoff arises between the level of security measures, trust in partners, and ensuring the system still functions. Federated Learning emerges as a promising solution to these challenges. Federated Learning is a novel form of machine learning that allows multiple entities to collaboratively develop a shared model while keeping their data localized, thus maintaining privacy and data sovereignty. Question The primary objective of this research is to identify and validate the critical architectural features necessary for the acceptance of Federated Learning in the aviation maintenance industry. Architectural features refer to design choices such as security protocols and governance frameworks. By focusing on these aspects, this study addresses the technical and collaborative challenges that must be overcome to develop a Federated Learning system for predictive maintenance in aviation. Resulting in the following research question:
‘What architectural features should be included in the design of the ‘Federated Learning for aircrafts’ predictive maintenance system’ to be accepted by the stakeholders in the aviation industry?’ Approach This study employs a Design Science Research methodology. The sub-questions for this research follow the steps in the Design Science Research methodology. This is not the case for the demonstration phase which was deemed not possible due to the conceptual nature of the design.
1.
What are the challenges in sharing maintenance data, and how do they impact data safety and collaboration? Through a literature review and interviews with stakeholders, the study identified concerns about data privacy, security, and competition. These challenges significantly limit data-sharing initiatives. (Problem Identification and Motivation)
2.
What specific technical requirements should the Federated Learning system have to address these challenges? Based on the interviews and thematic analysis, a list of requirements was developed. These include robust privacy mechanisms, transparent governance, ensuring model explainability, and clear accountability mechanisms. (Defining the Objectives for a Solution)
3.
What architectural features should be included in the Federated Learning design to meet these requirements? ArchiMate modeling was used to design a system incorporating these requirements. Federated Learning, combined with encryption techniques and a consortium-managed system, was the result. (Design and Development)
4.
How do stakeholders perceive the acceptability of the designed system? After the validation interviews and the expert session, three changes were implemented: Switching from
5
differentiating on the model version to differentiating on the usages. Improving explainability
by switching to Trusted Executive Environments and removing differential privacy. Traditional contracts to increase trust towards each other were also added. (Evaluation)
5.
What lessons can be learned from the development and evaluation of the Federated Learning system for future improvements? The research highlights the importance of continuously building trust among stakeholders. Furthermore, the token-based reward system based on contribution is a good incentive to be adaptable and develop long-term collaboration. (Communication) Results
To build trust, this study employs traditional methods like legal contracts and appoints a consortium as a neutral party. Transparent governance and involving a neutral, trusted entity is necessary to gain stakeholder acceptance and ensure long-term collaboration. Blockchain technology enhances the transparency of the consortium's operations, ensuring all transactions and data exchanges are recorded on an immutable database... ...
Executive Summary
Current Status The aviation industry is transitioning from traditional maintenance practices, typically scheduled after a specified number of flight hours, to more advanced, data-driven approaches. These predictive maintenance techniques leverage machine learning models to enhance the accuracy of assessments. These models can reduce the frequency of unscheduled maintenance and optimize inventory management. However, such models rely heavily on large datasets, which are challenging to compile in the aviation sector due to the rarity of specific operational incidents and the diverse types of data collected by different companies. When collaborating, a tradeoff arises between the level of security measures, trust in partners, and ensuring the system still functions. Federated Learning emerges as a promising solution to these challenges. Federated Learning is a novel form of machine learning that allows multiple entities to collaboratively develop a shared model while keeping their data localized, thus maintaining privacy and data sovereignty. Question The primary objective of this research is to identify and validate the critical architectural features necessary for the acceptance of Federated Learning in the aviation maintenance industry. Architectural features refer to design choices such as security protocols and governance frameworks. By focusing on these aspects, this study addresses the technical and collaborative challenges that must be overcome to develop a Federated Learning system for predictive maintenance in aviation. Resulting in the following research question:
‘What architectural features should be included in the design of the ‘Federated Learning for aircrafts’ predictive maintenance system’ to be accepted by the stakeholders in the aviation industry?’ Approach This study employs a Design Science Research methodology. The sub-questions for this research follow the steps in the Design Science Research methodology. This is not the case for the demonstration phase which was deemed not possible due to the conceptual nature of the design.
1.
What are the challenges in sharing maintenance data, and how do they impact data safety and collaboration? Through a literature review and interviews with stakeholders, the study identified concerns about data privacy, security, and competition. These challenges significantly limit data-sharing initiatives. (Problem Identification and Motivation)
2.
What specific technical requirements should the Federated Learning system have to address these challenges? Based on the interviews and thematic analysis, a list of requirements was developed. These include robust privacy mechanisms, transparent governance, ensuring model explainability, and clear accountability mechanisms. (Defining the Objectives for a Solution)
3.
What architectural features should be included in the Federated Learning design to meet these requirements? ArchiMate modeling was used to design a system incorporating these requirements. Federated Learning, combined with encryption techniques and a consortium-managed system, was the result. (Design and Development)
4.
How do stakeholders perceive the acceptability of the designed system? After the validation interviews and the expert session, three changes were implemented: Switching from
5
differentiating on the model version to differentiating on the usages. Improving explainability
by switching to Trusted Executive Environments and removing differential privacy. Traditional contracts to increase trust towards each other were also added. (Evaluation)
5.
What lessons can be learned from the development and evaluation of the Federated Learning system for future improvements? The research highlights the importance of continuously building trust among stakeholders. Furthermore, the token-based reward system based on contribution is a good incentive to be adaptable and develop long-term collaboration. (Communication) Results
To build trust, this study employs traditional methods like legal contracts and appoints a consortium as a neutral party. Transparent governance and involving a neutral, trusted entity is necessary to gain stakeholder acceptance and ensure long-term collaboration. Blockchain technology enhances the transparency of the consortium's operations, ensuring all transactions and data exchanges are recorded on an immutable database...
Current Status The aviation industry is transitioning from traditional maintenance practices, typically scheduled after a specified number of flight hours, to more advanced, data-driven approaches. These predictive maintenance techniques leverage machine learning models to enhance the accuracy of assessments. These models can reduce the frequency of unscheduled maintenance and optimize inventory management. However, such models rely heavily on large datasets, which are challenging to compile in the aviation sector due to the rarity of specific operational incidents and the diverse types of data collected by different companies. When collaborating, a tradeoff arises between the level of security measures, trust in partners, and ensuring the system still functions. Federated Learning emerges as a promising solution to these challenges. Federated Learning is a novel form of machine learning that allows multiple entities to collaboratively develop a shared model while keeping their data localized, thus maintaining privacy and data sovereignty. Question The primary objective of this research is to identify and validate the critical architectural features necessary for the acceptance of Federated Learning in the aviation maintenance industry. Architectural features refer to design choices such as security protocols and governance frameworks. By focusing on these aspects, this study addresses the technical and collaborative challenges that must be overcome to develop a Federated Learning system for predictive maintenance in aviation. Resulting in the following research question:
‘What architectural features should be included in the design of the ‘Federated Learning for aircrafts’ predictive maintenance system’ to be accepted by the stakeholders in the aviation industry?’ Approach This study employs a Design Science Research methodology. The sub-questions for this research follow the steps in the Design Science Research methodology. This is not the case for the demonstration phase which was deemed not possible due to the conceptual nature of the design.
1.
What are the challenges in sharing maintenance data, and how do they impact data safety and collaboration? Through a literature review and interviews with stakeholders, the study identified concerns about data privacy, security, and competition. These challenges significantly limit data-sharing initiatives. (Problem Identification and Motivation)
2.
What specific technical requirements should the Federated Learning system have to address these challenges? Based on the interviews and thematic analysis, a list of requirements was developed. These include robust privacy mechanisms, transparent governance, ensuring model explainability, and clear accountability mechanisms. (Defining the Objectives for a Solution)
3.
What architectural features should be included in the Federated Learning design to meet these requirements? ArchiMate modeling was used to design a system incorporating these requirements. Federated Learning, combined with encryption techniques and a consortium-managed system, was the result. (Design and Development)
4.
How do stakeholders perceive the acceptability of the designed system? After the validation interviews and the expert session, three changes were implemented: Switching from
5
differentiating on the model version to differentiating on the usages. Improving explainability
by switching to Trusted Executive Environments and removing differential privacy. Traditional contracts to increase trust towards each other were also added. (Evaluation)
5.
What lessons can be learned from the development and evaluation of the Federated Learning system for future improvements? The research highlights the importance of continuously building trust among stakeholders. Furthermore, the token-based reward system based on contribution is a good incentive to be adaptable and develop long-term collaboration. (Communication) Results
To build trust, this study employs traditional methods like legal contracts and appoints a consortium as a neutral party. Transparent governance and involving a neutral, trusted entity is necessary to gain stakeholder acceptance and ensure long-term collaboration. Blockchain technology enhances the transparency of the consortium's operations, ensuring all transactions and data exchanges are recorded on an immutable database...
How Information and Cost and Benefit Distribution Institutions Influence Onshore Wind Park Development
The Institutional Dissection of Three Dutch Wind Park Development Participation Cases
This thesis addresses the critical issue of advancing the transition to renewable energy by focusing on onshore wind park development. In countries like the Netherlands, where population density is high, wind energy projects often face resistance from local communities. Local Energy Cooperatives (LECs) have emerged as a potential solution, offering a way to involve citizens more directly in the ownership and development of energy resources. This approach is seen as a way to reduce opposition and enhance acceptance of wind energy projects. The core aim of the thesis is to explore how structuring local participation through LECs can contribute to accelerating the energy transition.
To investigate this, the research employs an institutional case study approach, drawing on Williamson’s New Institutional Economics Theory and Ostrom’s Institutional Grammar. These frameworks are used to analyse both formal institution, such as laws and regulations, and informal ones, such as norms and shared values that influence the development of wind parks. By examining three specific cases, the study assesses how communication and benefit distribution are managed in wind park projects and how public and private actors interact within the broader institutional context. The analysis integrates high-level national policies with the detailed processes occurring at the case level, offering a comprehensive view of how rules, norms, and strategies shape the interactions and agreements between multiple actors involved in wind park development.
The findings of the thesis highlight several key insights. Firstly, the size and authority of the jurisdiction overseeing a wind park project significantly impact its development. Larger authorities tend to have more resources, which enables them to manage the project more effectively and engage with local residents. Additionally, location-specific planning and permitting procedures, particularly where pre-selected sites have been identified in land use plans, facilitate the development process by making information more accessible and improving the dynamics between local residents and project initiators. Early stakeholder engagement and thorough upfront planning are also critical to the success of wind park projects. Transparent communication with local residents from the outset is essential to reducing opposition and building trust, while a lack of engagement tends to foster resistance and delay development. Another important finding is that the current policies governing participation and benefit distribution are often inadequately implemented. More flexible policies that allow for interpretation by local authorities and are guided by strong principles rather than strict regulations tend to yield better results. Early engagement with stakeholders, combined with tailored compensatory measures that reflect the specific needs of different resident groups, leads to more efficient project outcomes. Understanding the differences between local resident groups, such as those living close to the project versus those living in nearby cities, helps to ensure that compensatory measures are appropriate and that development processes are shortened.
The research carries important implications for advising policymakers and project initiators. It emphasises the need for early and continuous engagement with local residents to build trust and reduce opposition. Moreover, flexible policies that allow for interpretation and are supported by clear principles are more effective than rigid regulations. Educating municipalities and expanding successful strategies, such as the Regional Energy Strategies, can further enhance the effectiveness of wind park projects. These steps can help authorities select competent project initiators and improve the implementation of participation processes. The scientific contribution of this thesis lies in its novel approach of linking high-level national institutions with case-specific participatory processes. By combining these perspectives, the research provides a deeper understanding of how formal policies and spatial planning laws are translated into practical actions at the local level. This dual-level analysis sheds light on the interactions between different actors and institutions, offering insights that had not been studied in such detail before. In doing so, the thesis contributes valuable knowledge to the field of institutional analysis and renewable energy development. ...
To investigate this, the research employs an institutional case study approach, drawing on Williamson’s New Institutional Economics Theory and Ostrom’s Institutional Grammar. These frameworks are used to analyse both formal institution, such as laws and regulations, and informal ones, such as norms and shared values that influence the development of wind parks. By examining three specific cases, the study assesses how communication and benefit distribution are managed in wind park projects and how public and private actors interact within the broader institutional context. The analysis integrates high-level national policies with the detailed processes occurring at the case level, offering a comprehensive view of how rules, norms, and strategies shape the interactions and agreements between multiple actors involved in wind park development.
The findings of the thesis highlight several key insights. Firstly, the size and authority of the jurisdiction overseeing a wind park project significantly impact its development. Larger authorities tend to have more resources, which enables them to manage the project more effectively and engage with local residents. Additionally, location-specific planning and permitting procedures, particularly where pre-selected sites have been identified in land use plans, facilitate the development process by making information more accessible and improving the dynamics between local residents and project initiators. Early stakeholder engagement and thorough upfront planning are also critical to the success of wind park projects. Transparent communication with local residents from the outset is essential to reducing opposition and building trust, while a lack of engagement tends to foster resistance and delay development. Another important finding is that the current policies governing participation and benefit distribution are often inadequately implemented. More flexible policies that allow for interpretation by local authorities and are guided by strong principles rather than strict regulations tend to yield better results. Early engagement with stakeholders, combined with tailored compensatory measures that reflect the specific needs of different resident groups, leads to more efficient project outcomes. Understanding the differences between local resident groups, such as those living close to the project versus those living in nearby cities, helps to ensure that compensatory measures are appropriate and that development processes are shortened.
The research carries important implications for advising policymakers and project initiators. It emphasises the need for early and continuous engagement with local residents to build trust and reduce opposition. Moreover, flexible policies that allow for interpretation and are supported by clear principles are more effective than rigid regulations. Educating municipalities and expanding successful strategies, such as the Regional Energy Strategies, can further enhance the effectiveness of wind park projects. These steps can help authorities select competent project initiators and improve the implementation of participation processes. The scientific contribution of this thesis lies in its novel approach of linking high-level national institutions with case-specific participatory processes. By combining these perspectives, the research provides a deeper understanding of how formal policies and spatial planning laws are translated into practical actions at the local level. This dual-level analysis sheds light on the interactions between different actors and institutions, offering insights that had not been studied in such detail before. In doing so, the thesis contributes valuable knowledge to the field of institutional analysis and renewable energy development. ...
This thesis addresses the critical issue of advancing the transition to renewable energy by focusing on onshore wind park development. In countries like the Netherlands, where population density is high, wind energy projects often face resistance from local communities. Local Energy Cooperatives (LECs) have emerged as a potential solution, offering a way to involve citizens more directly in the ownership and development of energy resources. This approach is seen as a way to reduce opposition and enhance acceptance of wind energy projects. The core aim of the thesis is to explore how structuring local participation through LECs can contribute to accelerating the energy transition.
To investigate this, the research employs an institutional case study approach, drawing on Williamson’s New Institutional Economics Theory and Ostrom’s Institutional Grammar. These frameworks are used to analyse both formal institution, such as laws and regulations, and informal ones, such as norms and shared values that influence the development of wind parks. By examining three specific cases, the study assesses how communication and benefit distribution are managed in wind park projects and how public and private actors interact within the broader institutional context. The analysis integrates high-level national policies with the detailed processes occurring at the case level, offering a comprehensive view of how rules, norms, and strategies shape the interactions and agreements between multiple actors involved in wind park development.
The findings of the thesis highlight several key insights. Firstly, the size and authority of the jurisdiction overseeing a wind park project significantly impact its development. Larger authorities tend to have more resources, which enables them to manage the project more effectively and engage with local residents. Additionally, location-specific planning and permitting procedures, particularly where pre-selected sites have been identified in land use plans, facilitate the development process by making information more accessible and improving the dynamics between local residents and project initiators. Early stakeholder engagement and thorough upfront planning are also critical to the success of wind park projects. Transparent communication with local residents from the outset is essential to reducing opposition and building trust, while a lack of engagement tends to foster resistance and delay development. Another important finding is that the current policies governing participation and benefit distribution are often inadequately implemented. More flexible policies that allow for interpretation by local authorities and are guided by strong principles rather than strict regulations tend to yield better results. Early engagement with stakeholders, combined with tailored compensatory measures that reflect the specific needs of different resident groups, leads to more efficient project outcomes. Understanding the differences between local resident groups, such as those living close to the project versus those living in nearby cities, helps to ensure that compensatory measures are appropriate and that development processes are shortened.
The research carries important implications for advising policymakers and project initiators. It emphasises the need for early and continuous engagement with local residents to build trust and reduce opposition. Moreover, flexible policies that allow for interpretation and are supported by clear principles are more effective than rigid regulations. Educating municipalities and expanding successful strategies, such as the Regional Energy Strategies, can further enhance the effectiveness of wind park projects. These steps can help authorities select competent project initiators and improve the implementation of participation processes. The scientific contribution of this thesis lies in its novel approach of linking high-level national institutions with case-specific participatory processes. By combining these perspectives, the research provides a deeper understanding of how formal policies and spatial planning laws are translated into practical actions at the local level. This dual-level analysis sheds light on the interactions between different actors and institutions, offering insights that had not been studied in such detail before. In doing so, the thesis contributes valuable knowledge to the field of institutional analysis and renewable energy development.
To investigate this, the research employs an institutional case study approach, drawing on Williamson’s New Institutional Economics Theory and Ostrom’s Institutional Grammar. These frameworks are used to analyse both formal institution, such as laws and regulations, and informal ones, such as norms and shared values that influence the development of wind parks. By examining three specific cases, the study assesses how communication and benefit distribution are managed in wind park projects and how public and private actors interact within the broader institutional context. The analysis integrates high-level national policies with the detailed processes occurring at the case level, offering a comprehensive view of how rules, norms, and strategies shape the interactions and agreements between multiple actors involved in wind park development.
The findings of the thesis highlight several key insights. Firstly, the size and authority of the jurisdiction overseeing a wind park project significantly impact its development. Larger authorities tend to have more resources, which enables them to manage the project more effectively and engage with local residents. Additionally, location-specific planning and permitting procedures, particularly where pre-selected sites have been identified in land use plans, facilitate the development process by making information more accessible and improving the dynamics between local residents and project initiators. Early stakeholder engagement and thorough upfront planning are also critical to the success of wind park projects. Transparent communication with local residents from the outset is essential to reducing opposition and building trust, while a lack of engagement tends to foster resistance and delay development. Another important finding is that the current policies governing participation and benefit distribution are often inadequately implemented. More flexible policies that allow for interpretation by local authorities and are guided by strong principles rather than strict regulations tend to yield better results. Early engagement with stakeholders, combined with tailored compensatory measures that reflect the specific needs of different resident groups, leads to more efficient project outcomes. Understanding the differences between local resident groups, such as those living close to the project versus those living in nearby cities, helps to ensure that compensatory measures are appropriate and that development processes are shortened.
The research carries important implications for advising policymakers and project initiators. It emphasises the need for early and continuous engagement with local residents to build trust and reduce opposition. Moreover, flexible policies that allow for interpretation and are supported by clear principles are more effective than rigid regulations. Educating municipalities and expanding successful strategies, such as the Regional Energy Strategies, can further enhance the effectiveness of wind park projects. These steps can help authorities select competent project initiators and improve the implementation of participation processes. The scientific contribution of this thesis lies in its novel approach of linking high-level national institutions with case-specific participatory processes. By combining these perspectives, the research provides a deeper understanding of how formal policies and spatial planning laws are translated into practical actions at the local level. This dual-level analysis sheds light on the interactions between different actors and institutions, offering insights that had not been studied in such detail before. In doing so, the thesis contributes valuable knowledge to the field of institutional analysis and renewable energy development.
Renewable energy projects on land in the Netherlands face delays due to social resistance, driven by concerns over aesthetics, environment, and economics. Local energy communities have been identified as potential solutions to enhance social acceptance and overcome these barriers. The Dutch Climate Agreement targets 50% local ownership in onshore solar and wind projects to enhance public acceptance and project feasibility. Existing research highlights economic, institutional, and organizational barriers, yet limited research has been done on the internal governance structures of local energy communities. Moreover, no prior studies have explored the discrepancies between formal regulatory frameworks influencing design decisions and their practical application in Dutch local energy projects. This study employs Williamson’s four-layer model and Elinor Ostrom’s IAD framework to explore institutional design options for local energy communities in the Netherlands. Key findings reveal that European directives and Dutch laws support energy communities without specifying legal structures, allowing flexibility in governance structures. Practical implementations of institutional design options vary based on project needs and dynamics. However, most local energy communities adopt cooperative models and often establish separate entities like private limited companies to manage project associated risks. Based on the findings it is recommendated to organize local energy communities as cooperatives, addressing knowledge and resource gaps through partnerships with experienced entities, and establishing separate project entities to ensure local ownership and mitigate financial risks. This study provides practical insights for stakeholders navigating the complexities of local energy community projects.
...
Renewable energy projects on land in the Netherlands face delays due to social resistance, driven by concerns over aesthetics, environment, and economics. Local energy communities have been identified as potential solutions to enhance social acceptance and overcome these barriers. The Dutch Climate Agreement targets 50% local ownership in onshore solar and wind projects to enhance public acceptance and project feasibility. Existing research highlights economic, institutional, and organizational barriers, yet limited research has been done on the internal governance structures of local energy communities. Moreover, no prior studies have explored the discrepancies between formal regulatory frameworks influencing design decisions and their practical application in Dutch local energy projects. This study employs Williamson’s four-layer model and Elinor Ostrom’s IAD framework to explore institutional design options for local energy communities in the Netherlands. Key findings reveal that European directives and Dutch laws support energy communities without specifying legal structures, allowing flexibility in governance structures. Practical implementations of institutional design options vary based on project needs and dynamics. However, most local energy communities adopt cooperative models and often establish separate entities like private limited companies to manage project associated risks. Based on the findings it is recommendated to organize local energy communities as cooperatives, addressing knowledge and resource gaps through partnerships with experienced entities, and establishing separate project entities to ensure local ownership and mitigate financial risks. This study provides practical insights for stakeholders navigating the complexities of local energy community projects.
This research investigates the potential impact of blockchain based start-up crowdfunding. The emergence of blockchain and cryptocurrencies paved the way for a more decentralized finance system which offers alternative funding opportunities for start-ups. The scope of the research is to analyze the benefits and drawbacks of blockchain based crowdfunding for start-ups, and how it could impact the traditional financing models. The study adopts a qualitative research approach in which the Institutional Analyses and Development framework was consulted to find the key research concepts for the case studies. The research was conducted by analyzing data from blockchain protocols that consult their communities for important the decision making within its ecosystem. The findings suggest that blockchain based crowdfunding allows to raise funds for start-ups from a broader pool of investors, without the necessity to tap into the ecosystem that Silicon Valley offers, and a potential faster funding method than traditional methods. However, there are some concerns regarding trust and transparency with crowdfunding. The research found that adopting dequity, which is a new financial asset that combines both properties of debt and equity, can increase transparency and trust for the investors, while granting the crowd investors more control. The proposed solution is a dequity token with a governance that has quadratic voting, a voting multiplier and locking a large portion of the raised funds during the crowdfund. Overall, the research suggests that blockchain based crowdfunding can offer new opportunities for entrepreneurs to raise capital, in an inclusive manner, without the need of venture capitals or banks.
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This research investigates the potential impact of blockchain based start-up crowdfunding. The emergence of blockchain and cryptocurrencies paved the way for a more decentralized finance system which offers alternative funding opportunities for start-ups. The scope of the research is to analyze the benefits and drawbacks of blockchain based crowdfunding for start-ups, and how it could impact the traditional financing models. The study adopts a qualitative research approach in which the Institutional Analyses and Development framework was consulted to find the key research concepts for the case studies. The research was conducted by analyzing data from blockchain protocols that consult their communities for important the decision making within its ecosystem. The findings suggest that blockchain based crowdfunding allows to raise funds for start-ups from a broader pool of investors, without the necessity to tap into the ecosystem that Silicon Valley offers, and a potential faster funding method than traditional methods. However, there are some concerns regarding trust and transparency with crowdfunding. The research found that adopting dequity, which is a new financial asset that combines both properties of debt and equity, can increase transparency and trust for the investors, while granting the crowd investors more control. The proposed solution is a dequity token with a governance that has quadratic voting, a voting multiplier and locking a large portion of the raised funds during the crowdfund. Overall, the research suggests that blockchain based crowdfunding can offer new opportunities for entrepreneurs to raise capital, in an inclusive manner, without the need of venture capitals or banks.
Fitting Behavioural Artificial Intelligence Technology in the banking sector
A market research study
The banking sector is currently dealing with Anti-Money Laundering (AML) issues, with stricter legislation in Know Your Customer (AML) being the instigator. De Nederlandsche Bank is pursuing fully explainable and transparent models with a risk-based approach. Councyl provides such a model: Behavioural Artificial Intelligence Technology (BAIT). This study aims to analyse the current environment BAIT would be implemented, to see if the tool fits the requirements of the banking sector. The inherent features of BAIT, adding to the four functions make it an interesting tool for banks to consider.
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The banking sector is currently dealing with Anti-Money Laundering (AML) issues, with stricter legislation in Know Your Customer (AML) being the instigator. De Nederlandsche Bank is pursuing fully explainable and transparent models with a risk-based approach. Councyl provides such a model: Behavioural Artificial Intelligence Technology (BAIT). This study aims to analyse the current environment BAIT would be implemented, to see if the tool fits the requirements of the banking sector. The inherent features of BAIT, adding to the four functions make it an interesting tool for banks to consider.
Local ownership: Does It Matter?
A Cross-Case Institutional Analysis of 14 Onshore Wind Farms 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.
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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.
Master thesis
(2022)
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D.H.J. van Tongeren, P.W. Heijnen, A.F. Correlje, R. van Bergem, A. Nocentini
To provoke the needed energy transition, European Union (EU) countries initiated significant offshore wind energy investments in the North Sea. However, there also exist adverse aspects to the use of higher renewable electricity levels:
• renewable energy sources, such as offshore wind energy, may threaten the security of our energy system, since they are characterised by a high variability, and limited predictability and controllability;
• the effectiveness with respect to decreasing greenhouse gas emissions is limited, because electrification can be not applied within all sectors, such as heavy industry and heavy duty transport;
• a large increase in offshore wind capacity requires moving further off shore. This results in relatively high costs because of the energy losses within the (longer) electricity cables.
One way of coping with these challenges, is by producing hydrogen offshore, by means of wind energy, and transporting it to shore by for example repurposing the existing offshore natural gas infrastructure. Such an offshore hydrogen system located in the North Sea might sound favorable; however, the feasibility of such a system on this scale is yet to be determined.
In this thesis the possibility is investigated to design a future proof offshore hydrogen system. Such a system would consist of (current as well as new) wind farms, electrolysers to produce hydrogen by using (a part of) the electricity generated by the wind farms, and an infrastructure to bring the hydrogen to shore. Given the EU investment plans in offshore wind energy, a phasing period is used from 2030, 2040, to 2050. This research is done by:
• deriving multiple hydrogen system designs by for example optimising the transmission infrastructure;
• analysing the supply potential of these system designs.
The results show that a cost-competitive hydrogen system in the North Sea can be realised. The proposed system design has a Levelised Cost Of Hydrogen (LCOH) of 2,08 EUR/kg and a positive Net Present Value (NPV) for the most relevant pricing scenarios. This LCOH is relatively low compared to other researches, which are mostly between 2 and 3,5 EUR/kg.
An interesting result concerns including refurbished pipelines of the existing offshore gas infrastructure. When using only new pipelines, the transmission infrastructure costs increase with 36%. Furthermore, the results show that it is more cost-efficient to downscale electrolyser capacities than to use the peak of the available electricity to determine the capacity of the electrolysers. Additionally, the productivity of the wind farms can increase up to even 220% by using the different electricity surplus for hydrogen production.
Based on this research, recommendations can be given:
• National governments should formulate policy on whether or when gas extraction in the North Sea should stop. Thereupon, the (energy) transmission system operators should scope their plans towards transporting offshore hydrogen to onshore, as well as start planning the onshore hydrogen backbone.
• The EU should decide whether to build one interconnected system in the North Sea, or multiple isolated (per country) hydrogen systems. Based on this decision, it is important to start shaping rules and standards for hydrogen trade, as well as determining regulatory regimes to support offshore hydrogen production.
• Further research should be done on the electrolyser costs and efficiencies, as well as the different types of electrolyser locations; on the possibilities of hydrogen storage; and, to include (regional) hydrogen demand values. ...
• renewable energy sources, such as offshore wind energy, may threaten the security of our energy system, since they are characterised by a high variability, and limited predictability and controllability;
• the effectiveness with respect to decreasing greenhouse gas emissions is limited, because electrification can be not applied within all sectors, such as heavy industry and heavy duty transport;
• a large increase in offshore wind capacity requires moving further off shore. This results in relatively high costs because of the energy losses within the (longer) electricity cables.
One way of coping with these challenges, is by producing hydrogen offshore, by means of wind energy, and transporting it to shore by for example repurposing the existing offshore natural gas infrastructure. Such an offshore hydrogen system located in the North Sea might sound favorable; however, the feasibility of such a system on this scale is yet to be determined.
In this thesis the possibility is investigated to design a future proof offshore hydrogen system. Such a system would consist of (current as well as new) wind farms, electrolysers to produce hydrogen by using (a part of) the electricity generated by the wind farms, and an infrastructure to bring the hydrogen to shore. Given the EU investment plans in offshore wind energy, a phasing period is used from 2030, 2040, to 2050. This research is done by:
• deriving multiple hydrogen system designs by for example optimising the transmission infrastructure;
• analysing the supply potential of these system designs.
The results show that a cost-competitive hydrogen system in the North Sea can be realised. The proposed system design has a Levelised Cost Of Hydrogen (LCOH) of 2,08 EUR/kg and a positive Net Present Value (NPV) for the most relevant pricing scenarios. This LCOH is relatively low compared to other researches, which are mostly between 2 and 3,5 EUR/kg.
An interesting result concerns including refurbished pipelines of the existing offshore gas infrastructure. When using only new pipelines, the transmission infrastructure costs increase with 36%. Furthermore, the results show that it is more cost-efficient to downscale electrolyser capacities than to use the peak of the available electricity to determine the capacity of the electrolysers. Additionally, the productivity of the wind farms can increase up to even 220% by using the different electricity surplus for hydrogen production.
Based on this research, recommendations can be given:
• National governments should formulate policy on whether or when gas extraction in the North Sea should stop. Thereupon, the (energy) transmission system operators should scope their plans towards transporting offshore hydrogen to onshore, as well as start planning the onshore hydrogen backbone.
• The EU should decide whether to build one interconnected system in the North Sea, or multiple isolated (per country) hydrogen systems. Based on this decision, it is important to start shaping rules and standards for hydrogen trade, as well as determining regulatory regimes to support offshore hydrogen production.
• Further research should be done on the electrolyser costs and efficiencies, as well as the different types of electrolyser locations; on the possibilities of hydrogen storage; and, to include (regional) hydrogen demand values. ...
To provoke the needed energy transition, European Union (EU) countries initiated significant offshore wind energy investments in the North Sea. However, there also exist adverse aspects to the use of higher renewable electricity levels:
• renewable energy sources, such as offshore wind energy, may threaten the security of our energy system, since they are characterised by a high variability, and limited predictability and controllability;
• the effectiveness with respect to decreasing greenhouse gas emissions is limited, because electrification can be not applied within all sectors, such as heavy industry and heavy duty transport;
• a large increase in offshore wind capacity requires moving further off shore. This results in relatively high costs because of the energy losses within the (longer) electricity cables.
One way of coping with these challenges, is by producing hydrogen offshore, by means of wind energy, and transporting it to shore by for example repurposing the existing offshore natural gas infrastructure. Such an offshore hydrogen system located in the North Sea might sound favorable; however, the feasibility of such a system on this scale is yet to be determined.
In this thesis the possibility is investigated to design a future proof offshore hydrogen system. Such a system would consist of (current as well as new) wind farms, electrolysers to produce hydrogen by using (a part of) the electricity generated by the wind farms, and an infrastructure to bring the hydrogen to shore. Given the EU investment plans in offshore wind energy, a phasing period is used from 2030, 2040, to 2050. This research is done by:
• deriving multiple hydrogen system designs by for example optimising the transmission infrastructure;
• analysing the supply potential of these system designs.
The results show that a cost-competitive hydrogen system in the North Sea can be realised. The proposed system design has a Levelised Cost Of Hydrogen (LCOH) of 2,08 EUR/kg and a positive Net Present Value (NPV) for the most relevant pricing scenarios. This LCOH is relatively low compared to other researches, which are mostly between 2 and 3,5 EUR/kg.
An interesting result concerns including refurbished pipelines of the existing offshore gas infrastructure. When using only new pipelines, the transmission infrastructure costs increase with 36%. Furthermore, the results show that it is more cost-efficient to downscale electrolyser capacities than to use the peak of the available electricity to determine the capacity of the electrolysers. Additionally, the productivity of the wind farms can increase up to even 220% by using the different electricity surplus for hydrogen production.
Based on this research, recommendations can be given:
• National governments should formulate policy on whether or when gas extraction in the North Sea should stop. Thereupon, the (energy) transmission system operators should scope their plans towards transporting offshore hydrogen to onshore, as well as start planning the onshore hydrogen backbone.
• The EU should decide whether to build one interconnected system in the North Sea, or multiple isolated (per country) hydrogen systems. Based on this decision, it is important to start shaping rules and standards for hydrogen trade, as well as determining regulatory regimes to support offshore hydrogen production.
• Further research should be done on the electrolyser costs and efficiencies, as well as the different types of electrolyser locations; on the possibilities of hydrogen storage; and, to include (regional) hydrogen demand values.
• renewable energy sources, such as offshore wind energy, may threaten the security of our energy system, since they are characterised by a high variability, and limited predictability and controllability;
• the effectiveness with respect to decreasing greenhouse gas emissions is limited, because electrification can be not applied within all sectors, such as heavy industry and heavy duty transport;
• a large increase in offshore wind capacity requires moving further off shore. This results in relatively high costs because of the energy losses within the (longer) electricity cables.
One way of coping with these challenges, is by producing hydrogen offshore, by means of wind energy, and transporting it to shore by for example repurposing the existing offshore natural gas infrastructure. Such an offshore hydrogen system located in the North Sea might sound favorable; however, the feasibility of such a system on this scale is yet to be determined.
In this thesis the possibility is investigated to design a future proof offshore hydrogen system. Such a system would consist of (current as well as new) wind farms, electrolysers to produce hydrogen by using (a part of) the electricity generated by the wind farms, and an infrastructure to bring the hydrogen to shore. Given the EU investment plans in offshore wind energy, a phasing period is used from 2030, 2040, to 2050. This research is done by:
• deriving multiple hydrogen system designs by for example optimising the transmission infrastructure;
• analysing the supply potential of these system designs.
The results show that a cost-competitive hydrogen system in the North Sea can be realised. The proposed system design has a Levelised Cost Of Hydrogen (LCOH) of 2,08 EUR/kg and a positive Net Present Value (NPV) for the most relevant pricing scenarios. This LCOH is relatively low compared to other researches, which are mostly between 2 and 3,5 EUR/kg.
An interesting result concerns including refurbished pipelines of the existing offshore gas infrastructure. When using only new pipelines, the transmission infrastructure costs increase with 36%. Furthermore, the results show that it is more cost-efficient to downscale electrolyser capacities than to use the peak of the available electricity to determine the capacity of the electrolysers. Additionally, the productivity of the wind farms can increase up to even 220% by using the different electricity surplus for hydrogen production.
Based on this research, recommendations can be given:
• National governments should formulate policy on whether or when gas extraction in the North Sea should stop. Thereupon, the (energy) transmission system operators should scope their plans towards transporting offshore hydrogen to onshore, as well as start planning the onshore hydrogen backbone.
• The EU should decide whether to build one interconnected system in the North Sea, or multiple isolated (per country) hydrogen systems. Based on this decision, it is important to start shaping rules and standards for hydrogen trade, as well as determining regulatory regimes to support offshore hydrogen production.
• Further research should be done on the electrolyser costs and efficiencies, as well as the different types of electrolyser locations; on the possibilities of hydrogen storage; and, to include (regional) hydrogen demand values.
Governance analysis of decentralized exchange applications
An institutional economics approach
Blockchaintechnologyhasintroducedthepossibilitytoexchangevalueandinformationthroughtheinternet without the supervision or permission from any third party intermediary. While many private and public entities have seen this as a chance to increase their operational efficiency, other ventures have been utilizing this sameedgeasameantodevelopnewinstitutionalregimesgiventheimpactontransactioncostreduction, The theories central to institutional economics claim that transaction costs are the ultimate driver for shifts in institutional settings. The purpose of the following research was to investigate whether the reduction in transaction costs allowed by blockchain technology is effectively causing new forms of institutions to arise. Given that blockchain is still in its infancy, there is a current lack of academic literature addressing its governance edge. Furthermore, the few studies available adopt a comparative approach, hence failing to explore the entirety of new institutional possibilities. For this reason, the following research utilized the Institutional Analysis and development framework developed by Elinor Ostrom as a holistic and institutional agnostic methodofanalysis. The particular application analyzed was the one of financial product exchanges. Today, the exchange of financial products as securities, is coordinated by hierarchical organizations, namely firms. As a matter of fact, multiple different firms are involvedintheexchangeoftheseproducts. Exchangesareresponsibleformatching buyers and sellers, clearing houses assume counter party risks and make sure the trading parties can meet their obligations, and custodians and central security depositories are responsible for the final settlement of transactions. Furthermore, reconciliation costs are incurred by all participants when updating their respective databases. Given that blockchains are fundamentally public distributed records of transaction, they effectively undermine the economic efficiency and logic of the current systems of clearing, settlement andreconciliation. Decentralized exchanges are tackling these issues today. For the purpose of the analysis a total of three decentralized exchanges were shortlisted from the over 200 existing. The first filter of choice was to choose between exchanges native to the Ethereum blockchain. This because, being the oldest in the space, they present the most well developed and resilient communities apt for the analysis. Next, exchanges were further filtered by total liquidity in the protocol, or total value locked, and trading volume. The three exchanges selected for the analysis in the end were Uniswap, Sushiswap and Curve. Given that these protocols run on a public and permissionless blockchain, it was possible to retrieve large amounts of data on their relative performance. A number of data acquisition and analytics platforms were utilized for data analysis and visualization namely, Dune, Tally and Sybil
...
Blockchaintechnologyhasintroducedthepossibilitytoexchangevalueandinformationthroughtheinternet without the supervision or permission from any third party intermediary. While many private and public entities have seen this as a chance to increase their operational efficiency, other ventures have been utilizing this sameedgeasameantodevelopnewinstitutionalregimesgiventheimpactontransactioncostreduction, The theories central to institutional economics claim that transaction costs are the ultimate driver for shifts in institutional settings. The purpose of the following research was to investigate whether the reduction in transaction costs allowed by blockchain technology is effectively causing new forms of institutions to arise. Given that blockchain is still in its infancy, there is a current lack of academic literature addressing its governance edge. Furthermore, the few studies available adopt a comparative approach, hence failing to explore the entirety of new institutional possibilities. For this reason, the following research utilized the Institutional Analysis and development framework developed by Elinor Ostrom as a holistic and institutional agnostic methodofanalysis. The particular application analyzed was the one of financial product exchanges. Today, the exchange of financial products as securities, is coordinated by hierarchical organizations, namely firms. As a matter of fact, multiple different firms are involvedintheexchangeoftheseproducts. Exchangesareresponsibleformatching buyers and sellers, clearing houses assume counter party risks and make sure the trading parties can meet their obligations, and custodians and central security depositories are responsible for the final settlement of transactions. Furthermore, reconciliation costs are incurred by all participants when updating their respective databases. Given that blockchains are fundamentally public distributed records of transaction, they effectively undermine the economic efficiency and logic of the current systems of clearing, settlement andreconciliation. Decentralized exchanges are tackling these issues today. For the purpose of the analysis a total of three decentralized exchanges were shortlisted from the over 200 existing. The first filter of choice was to choose between exchanges native to the Ethereum blockchain. This because, being the oldest in the space, they present the most well developed and resilient communities apt for the analysis. Next, exchanges were further filtered by total liquidity in the protocol, or total value locked, and trading volume. The three exchanges selected for the analysis in the end were Uniswap, Sushiswap and Curve. Given that these protocols run on a public and permissionless blockchain, it was possible to retrieve large amounts of data on their relative performance. A number of data acquisition and analytics platforms were utilized for data analysis and visualization namely, Dune, Tally and Sybil
In recent years, false information on social media platforms has become a centre of attention due to its consequences on elections and public health. COVID-19 has shown how an infodemic fuelled by false information can be detrimental to public health. Existing measures are ineffective. Thus, the thesis takes an exploratory approach from the lens of new institutional economics. A comparative institutional analysis between public health institutions and social media platforms concerning their information discovery process and how differences between them can lead to false information on social media platforms is performed. The findings question whether false information is as widespread on social media platforms as projected, identifies the role of public health institutions and politicians in the spread of false information, how information is regulated on social media platforms and what drives the information discovery process on social media platforms. Based on the comparative institutional analysis, it is recommended to implement prediction markets to address false information on social media platforms.
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In recent years, false information on social media platforms has become a centre of attention due to its consequences on elections and public health. COVID-19 has shown how an infodemic fuelled by false information can be detrimental to public health. Existing measures are ineffective. Thus, the thesis takes an exploratory approach from the lens of new institutional economics. A comparative institutional analysis between public health institutions and social media platforms concerning their information discovery process and how differences between them can lead to false information on social media platforms is performed. The findings question whether false information is as widespread on social media platforms as projected, identifies the role of public health institutions and politicians in the spread of false information, how information is regulated on social media platforms and what drives the information discovery process on social media platforms. Based on the comparative institutional analysis, it is recommended to implement prediction markets to address false information on social media platforms.
Facilitating Tap-To-Phone adoption
Towards a portable architecture decision flow for designing a server-based payment architecture