The Netherlands faces a critical housing shortage, estimated at over 400,000 homes in 2024, while simultaneously pursuing ambitious climate goals. Prefabricated housing offers a promising solution, as it enables faster construction, minimizes material waste, and improves energy efficiency. However, despite its technical and non-technical advantages and alignment with sustainability agendas, its market adoption remains limited and fragmented in the Dutch context. This study examines the key factors influencing the market adoption of prefabricated housing in the Netherlands, with a focus on the underlying misalignments among actors from diverse sectors.

To explore this issue, the study applied a mixed-methods research design. An extensive literature review was conducted to identify factors influencing adoption in the existing literature. Subsequently, three stages of expert interviews were conducted with 12 experts from academia, industry, and government, who represent the Triple Helix model. The Best-Worst Method (BWM) was then applied to rank nine consolidated adoption factors based on expert input systematically. The process was followed by a thematic analysis and triangulation with 25 international studies to explore the reasoning behind stakeholder preferences and variation in prioritization.

The nine key factors assessed were:
1. Financial and Economic Viability
2. Consumer Perception and Market Demand
3. Policy and Regulatory Support
4. Speed and Construction Efficiency
5. Sustainability and Environmental Impact
6. Industry Collaboration and Workforce Development
7. Structural Quality and Durability
8. Technological Advancements and Standardisation
9. Supply Chain and Logistics Efficiency

As seen above, financial and economic viability ranked highest, indicating that cost-effectiveness, profitability, and affordability are decisive for both public and private actors. Consumer perception and market demand followed closely, reflecting the role of public trust and design acceptability. Policy and regulatory support was also ranked highly, which emphasizes the need for efficient permits and consistent policies. Conversely, factors such as technological advancements and supply chain logistics, often emphasised in the literature, were deprioritised by experts, who saw them as either already developed or less influential in current decision-making contexts.

BWM analysis also revealed that prioritizations were not sectorally consistent: experts within the same sector often disagreed. Instead, through thematic analysis and triangulation, it is known that factor rankings were shaped by an individual’s background, institutional mandate, and past project experience. For example, experts with experience in government focused on financial viability and regulatory support, while industry actors emphasized financial viability and sustainability. In the meantime, academic experts often stressed consumer perception, construction speed, and cross-sector collaboration.

This study presents a stakeholder-informed, decision-analytic framework for understanding the adoption of prefabricated housing. It emphasizes that accelerating adoption requires not only technical innovation but also coordinated cross-sectoral strategies, financial incentives, a shared narrative that enhances consumer perception, and policy support. The findings offer practical insights for policymakers, developers, and researchers seeking to mainstream prefabricated housing as a sustainable, scalable, and socially accepted housing solution in the Netherlands.

The global shift toward renewable energy is increasing the share of intermittent electricity sources like wind and solar, creating new challenges for electricity system stability. Demand-side management (DSM), adjusting electricity use to better align with variable supply, offers a key solution. This thesis examines the potential for DSM in the Dutch food industry, a sector well-suited for electrification due to its low-temperature processes.

The research evaluates the economic and operational impacts of fully electric DSM strategies under various 2030 grid tariff designs proposed for The Netherlands. Four DSM strategies are modelled using the Calliope optimisation framework. These strategies combine different electricity procurement methods, electricity market purchases or Power Purchase Agreements (PPAs), with flexibility options: flexible production machinery or thermal energy storage (TES).

Key findings include:

- Economic Performance: Strategies using flexible machinery combined with PPAs result in the lowest total costs. TES-based flexibility also lowers costs relative to constant production but is less cost-effective than machinery flexibility. PPAs offer additional benefits by hedging against electricity price volatility, though their effectiveness depends on the contract price.

- Grid Tariff Effects: All proposed 2030 grid tariffs lead to higher grid costs than current designs. However, they do not alter the relative cost-effectiveness of the DSM strategies, flexible machinery with PPAs remains the most economical.

- Operational Behaviour: Flexible strategies shift production to low-price periods (spring and summer) and reduce it during high-price hours. TES allows constant production by shifting heat generation instead. DSM strategies without PPAs show more adaptive behaviour to price and tariff signals, while PPA-based strategies are constrained by fixed electricity volumes.

In conclusion, DSM can improve the economic viability of electrifying the food industry and contribute to grid flexibility. Grid tariff design plays a significant role in shaping industrial electricity use and can incentivize load shifting, though it may limit flexibility in responding to real-time market prices.

This research examines how incumbent technologies can maintain their dominant position, focusing on the case of the space solar cell industry. The technological competition is centered around Gallium Arsenide (GaAs) solar cells, currently the benchmark in space applications due to their superior efficiency and radiation resistance, and Silicon (Si) solar cells, which are gaining market traction due to lower production costs and scalability, particularly in Low Earth Orbit (LEO) satellite constellations. The main research question addressed in this thesis is: “What factors contribute to an incumbent technology maintaining its dominance in the space solar cell market?”

Dominant design theory is applied to understand which characteristics and factors enable a technology to retain its position once it has become the industry standard. Meanwhile, disruptive innovation theory is used to examine how incumbent firms can respond to the entry of alternatives that compete on different performance dimensions, such as cost and scalability. After literature research and expert validation, these theories are combined into a unified list of factors, which is applied using the Best- Worst Method (BWM) to perform a quantitative prioritization. The study identifies six critical factors that are most important for maintaining technological dominance. The research also provided a detailed exploration of how each of these factors can be influenced through actionable strategies.

Note: Due to information sensitivity, the interviews have been removed from the appendix.

In the information and communication technology (ICT) sector, industry consortia play a critical role in developing compatibility standards that enable interoperability, drive innovation, and shape competitive dynamics. These consortia vary widely in size and composition and are often created to establish de facto standards through market-based coordination. While the literature suggests that structural features, such as the size of the consortium and the diversity of its members, can influence standardisation outcomes, empirical evidence quantifying these effects remains limited. This thesis investigates how the size and industry diversity of ICT consortia affect their success, defined through two key dimensions: the longevity of the consortium and its output productivity in generating technical deliverables. Drawing on theories of network effects, resource pooling, and complementary assets, the study hypothesises that both size and diversity follow an inverted-U shaped relationship with success, offering benefits up to a point, beyond which coordination complexity may reduce effectiveness...

Natural disasters pose a significant threat to critical infrastructures, particularly nuclear power plants (NPPs), where the impact of a natural hazard can have far-reaching consequences. That is why enhancing the resilience of NPPs, meaning the ability to prepare for, withstand, adapt to and recover from a disaster, is vital. This thesis aims to enhance resilience by strengthening the learning process from past disasters. And lay the groundwork for a learning process guideline document to be adopted by NPPs as an addition to their existing practices to strengthen their resilience learning. The existing resilience practices within NPPs tend to reactive rather than pro-active. With limited integration of structured learning mechanisms and digital technologies.

This research develops the Enhanced Learning Process (ELP) model. Designed to visualize a structured and digital technology integrated resilience learning approach. Employing a Socio-Technical Systems theory perspective to ensure alignment between technology adoption and organizational dynamics. The systematic literature review (SLR) performed examined the literature of resilience engineering, organizational learning and digital technology utilization. And identified existing gaps in resilience strategies, which included the underutilization of digital tools for historical data processing, simulated scenario-based learning and collaborative decision-making. The synthesized literature, analyzed from a socio-technical systems theory perspective, created the knowledge foundation to structure a theoretical enhanced learning process model proposed in this study. Leveraging digital technology capabilities from a socio-technical perspective to enhance historical disaster data processing, identifying possible underlying vulnerabilities of the plant and cascading effects in the event of a natural disaster. Serving as the foundation of a resilience learning guideline that nuclear power plants can adopt to strengthen their learning from the past capabilities to enhance their resilience practices. The proposed model consists of four stages (Data Collection, Data Analysis, Outcome Evaluation and Strategy Development). Reflecting the resilience learning process within NPPs. Where each stage leverages digital technologies to enhance learning capabilities and support the development of data-driven and sophisticated resilience strategies.

The validity and practical applicability of the model was evaluated through a case-based analysis of the Fukushima Daiichi nuclear disaster. Applying the proposed model to this case, demonstrated its’ applicability in a real-world scenario. And provided insights into points of improvement for their learning processes. Lastly, an expert in the industry was consulted to provide verification of the outcomes of this research and validation of practical application of the proposed model.

The outcomes of this study contribute to the fields of resilience engineering and organizational learning by proposing a transformation of traditional learning processes through a structured, digital technology supported, learning approach to enhance resilience strategies against natural hazards. Furthermore, this study extends the application of STS theory in resilience enhancement learning by structuring the learning process as a socio-technical system. Providing insights for researchers, policy makers and NPP operators seeking to strengthen the resilience and learning capabilities of NPPs. This study suggests further research to focus on further validating and developing the ELP-model in collaboration industry experts and further explore the influence that digital technologies have on learning capabilities.

The rapid expansion of artificial intelligence (AI) is driving an unprecedented increase in data center demand. This surge requires massive computational power and energy consumption, leading to massive constructions of data centers annually worldwide. While AI-driven solutions enhance efficiency, they also introduce challenges, particularly where greater efficiency may drive increased resource consumption rather than reducing it. Addressing these pressures is crucial to aligning technological growth with sustainability goals. Despite increasing industry focus on sustainability, the lack of standardized performance metrics limits meaningful progress. Inconsistent energy efficiency, emissions, and resource utilization measurements make it difficult to enforce sustainability initiatives across the European data center industry. Regulatory fragmentation exacerbates this issue, allowing companies to navigate loopholes in sustainability enforcement. Without harmonized policies, even technically sound performance standards struggle to gain widespread adoption.
This research identifies key adoption factors that can drive the meaningful adoption of performance standards by 2030. A structured multi-method approach was applied, integrating literature review, interviews, BWM analysis, and desk research. The findings confirm that coercive pressures (regulatory enforcement) are the most influential driver, followed by observability (industry recognition) and mimetic pressures (competitor adoption trends). Operational factors such as reliability, robustness, and resilience were also critical for ensuring long-term adaptability. Beyond these adoption factors, additional barriers, regulatory complexities, neglected lifecycle emissions, and geographic disparities, must be addressed to ensure meaningful adoption. The research highlights five essential focal points for achieving widespread adoption of performance standards in European data centers: 1) Regulatory coherence and enforcement, 2) Balancing simplicity and comprehensiveness, 3) Enhancing observability and transparency, 4) Aligning with technological innovations, and 5) Addressing geographic and economic disparities.

This thesis investigates the impact of increased value capture by a dominant platform sponsor on user behavior and platform ecosystem stability, focusing on YouTube in a single case experiment. This research aims to address the existing gap in understanding how users respond to this increase in ecosystems characterized by high switching costs. The literature review identified key concepts to build a theoretical framework. The experiment tested the direct effects of increased ad load on 79 participants by simulating a real-world YouTube experience and evaluating behavioral responses. The findings revealed that a higher ad load significantly increased user disengagement. However, the introduction of a premium subscription mitigated these effects to some extent, serving as a stabilizing mechanism. Notably, users willing to pay for premium exhibited aversion to ads independent of increased ad load. This study highlights the trade-offs platforms face between value capture and ecosystem sustainability. While ad monetization can drive short-term profits, excessive strategies risk destabilizing the ecosystem. Practical implications suggest sponsors must balance value capture with reinvestment strategies, focusing on user-centric improvements to maintain ecosystem health. Policymakers are urged to consider regulatory measures ensuring transparency and long-term user welfare in platform governance. The theoretical framework presented in this thesis can serve as a basis for future research in this field of platform research.

This thesis investigates the commercialization of next-generation nuclear fission technologies, focusing on the barriers, strategies, and timelines necessary for their deployment. With the growing need for clean and reliable energy, nuclear fission offers a low-carbon solution, but its commercialization is challenged by regulatory, financial, and technological hurdles. The research uses a dual-method approach, combining desk research and expert interviews. Through desk research, commercialization timelines of 10 key companies developing next-generation nuclear reactors were mapped. These companies are at different stages, ranging from ideation to prototyping, with varying timelines influenced by strategic partnerships, regulatory approvals, and technological progress.

The expert interviews reveal significant barriers to commercialization, including lengthy regulatory approval processes, high upfront costs, and public skepticism surrounding nuclear technology. Financial constraints, especially the difficulty in attracting investment due to long payback periods, were noted as major impediments. Experts also highlighted the need for technological innovation, particularly in materials testing and reactor designs, to meet stringent safety standards.

In response to these challenges, the thesis identifies strategies such as early engagement with regulatory bodies, diversification of funding sources, and open communication to address public concerns. Technological advancements, such as modular reactor designs and improved safety features, are critical to overcoming these hurdles. By combining the insights from commercialization timelines and expert interviews, this study offers recommendations to accelerate the commercialization process, emphasizing the need for policy support, innovative financial models, and continuous technological development. Nuclear fission remains a promising solution to the global energy crisis, but coordinated efforts are required to unlock its full potential.

The global wicked problem of the climate crisis has drawn significant interest and attention over recent years from world governments, industry leaders and researchers. In a collaborative effort to tackle this problem while maintaining economic and social development, in 2015 the United Nations developed the Sustainable Development Goals (SDGs) and countries globally committed to this initiative (United Nations Development Programme, 2024). The transport sector forms a crucial component of infrastructural development while also being a significant contributor to greenhouse gas emissions, and a sizeable share of these emissions are attributed to the use of Internal Combustion Engine Vehicles (ICEVs), dependent on petroleum fuels. The globally recognised solution to replace ICEVs as of 2024 is through electrification of the transport sector, facilitated by the use of Electric Vehicles (EVs). Given the importance and significance of this relatively emerging technology, countries across the globe have formulated various strategies and made major efforts to enhance their country’s competitive positioning in the international trade of EVs.

Enhancing competitiveness in international markets in the EV sector is a viable method for nations to improve their energy security and independence from other potentially rival countries for their energy requirements. For instance, in the aftermath of the Russia-Ukraine conflict, many countries minimized ties with Russian products, despite Russia being the world’s largest exporter of oil to global markets, further stressing upon the need for countries to strengthen their positions in electric mobility and EV trade, since the incumbent car companies that built their reputations on ICE vehicles have also started updating their vehicle line-ups and incorporating EVs due to the constantly evolving nature of the transport sector. Moreover, the government support through industrial policy subsidy measures directed towards their domestic industries to bolster EV production also communicates concerns about employment for incumbent ICE vehicle producers, as with the growth of adoption in any emerging technology, or EVs in this case. Hence, the continuously evolving trade competitiveness dynamics require focused research to support policymakers in recognising the factors that may have a positive or negative impact on EV export performance. This can further facilitate the introduction of effective policy measures to improve international competitiveness in a sector such as EVs, which is of paramount importance in the widespread uptake of Net-Zero technologies.

There is an abundance of research analysing different aspects of the adoption and uptake of EVs in global, national and regional settings. Additionally, the extant literature also contains works that analyse the determinants of international competitiveness in established industries such as agriculture, forestry and the automotive sector. However, there is a lack of research on the international competitiveness of countries in the EV sector. Hence, the primary objective of this study was to fill this knowledge gap by providing a cross-country, empirical analysis of the determinants of international competitiveness in the EV sector, such as technological innovation, cost-competitiveness, green industrial policy measures and endowments in critical metals required for EV manufacturing. The following main research question guided this study: Which factors are most strongly associated with the export competitiveness of the electric vehicle industry across countries?...

While many researchers have researched the factors affecting standard consortium success, the size and diversity of a consortium were given the most importance. However, investigating the combined effect of these two factors on standard consortium success using specific indicators of success was limited. Past research required action on applying a new approach to determine the extent to which these variables work together toward the success of standard consortia. It was also important to investigate the network configurations of consortia given the multiple factors that come into play in the process of standardization over the years. This required a configurational approach with huge consortium-level data to test. The objective of this research is to find the configurations of size and diversity that lead to standard consortium success, in the ICT and telecommunications industry, success being represented by specific indicators. The data was collected from the websites ‘consortiuminfo.org’ and LinkedIn using Python packages and was analyzed using Crisp-set Qualitative Comparative Analysis (csQCA). This analysis was done considering two indicators of success individually and combined as a single variable, summing up to three analyses. The analysis revealed that the size and diversity of consortia are necessary conditions, but only diversity is found to be a sufficient condition for standard consortium success in this sample dataset of ICT consortia. The findings suggest that researchers should continue to explore the involvement of other factors along with the size and diversity as combinations instead of only analyzing the variables’ effects individually. Furthermore, by doing this the scope of the research broadens by breadth and depth as more data and more insights about factors of standard consortium success can be gathered.

This thesis examines the interactions within standard-setting consortia within the Audio/
Video/Multimedia sector, focusing on large company dominance, geographical proximity,
and technological proximity. It aims to uncover how these factors individually
and collectively influence the success of these consortia. The guiding research question is:
“What combinations of large company dominance, geographic proximity, and technological
proximity lead to successful outcomes in standard-setting consortia?”
Using Qualitative Comparative Analysis (QCA), the study reveals that successful consortia
strike a balance in large company influence, maintain significant geographical proximity,
and ensure proper technological alignment. While large company dominance significantly
impacts consortium success, an optimal balance is essential to avoid power struggles and
foster effective collaboration. Geographical proximity, especially at the UN subregion level,
consistently contributes to success by enhancing trust and communication. Technological
proximity within industry groups is beneficial but must be complemented by other factors
to significantly impact outcomes. It’s clear that the success of consortia is best understood
through specific configurations of these variables rather than any single factor alone.
To evaluate consortium success, the study employs a multifactor framework focusing on the
creation of standards, their adoption, and scholarly recognition. This framework combines
qualitative and quantitative measures, providing a comprehensive assessment of consortium
performance.
The research makes a valuable contribution to the field by offering empirical evidence on
the strategic influence of large companies within standard-setting consortia. It extends
the understanding of how large firms drive innovation while balancing the contributions
of smaller participants. The study also offers nuanced insights into the roles of geographical
and technological proximities, emphasizing their combined effects on consortium success.
These findings are useful for both theoretical knowledge and practical applications,
informing technology management practices and shaping policies that support effective
standard-setting efforts.
From a Management of Technology perspective, this thesis demonstrates how strategic engagement
in standard-setting consortia can enhance a firm’s technological capabilities and
market positioning. Technology managers can leverage these insights to navigate standardsetting
processes more effectively, ensuring that their firms benefit from collaboration while
maintaining an optimal balance of influence.
However, this study acknowledges certain practical limitations. The findings, while insightful
for the Audio/Video/Multimedia sector, may need adaptation when applied to other
industries with different dynamics. Additionally, the reliance on publicly available data
from consortium websites and LinkedIn profiles may lead to practical challenges, such as
gaps or inconsistencies in the data, affecting decision-making. The study’s cross-sectional
approach provides a snapshot of current conditions but does not capture consortium dynamics
over time. Practitioners should consider these factors when applying the insights
to other contexts, and future research should aim to include a wider range of industries
and explore these dynamics longitudinally to inform more adaptive strategies.

Within the energy transition, green hydrogen stands as a key solution for decarbonizing sectors where direct electrification is not viable. This thesis focuses on the competitive landscape of hydrogen production in North-Western Europe, addressing the technological and geographical competition of locally produced green hydrogen. This research introduces a comprehensive analytical tool to assess the viability of various hydrogen production methods, which are competing value chains of European green hydrogen. By synthesizing institutional, economic, societal, and technical considerations, the model facilitates a direct comparison between different green hydrogen alternatives.

The research commenced by applying Hekkert’s (2011) TIS analysis as a tool for structural analysis to systematically map the system. The goal was to delineate its structure and identify potential key competing value chains within the scope of Europe. This initial phase involved a literature review and interviews to select value chains. The subsequent phase, which also used the TIS as a tool, focused on identifying key drivers and barriers within the system through a functional analysis, utilizing a structured approach to examine system functions. Expert interviews played a pivotal role in this stage, providing an understanding of the system's dynamics. In the last phase, the techno-economic analysis was performed by introducing barrier-driven scenarios. Allowing for insights into the cost components and the overall comparison in the levelized cost of hydrogen for every scenario.

The structural analysis showed that the European Commission set the scope with institutions, allowing for technologically mature low-carbon alternatives in this comparison. The functional analysis revealed the intricate interconnectivity of the system functions, illustrating how drivers and barriers can swiftly transform, reflecting the system's complex status. The primary barrier to green hydrogen adoption is its high cost, creating a deadlock with no demand or supply. Technological advancement and governmental intervention emerged as key solutions to this challenge. The techno-economic results show that the least cost-effective value chain is local green hydrogen, and the most cost-effective value chain is local blue hydrogen. Local green hydrogen faces challenges in competitiveness due to high energy prices and low capacity factors compared to other electrolyzer-based methods. Additionally, compared to other types, like blue hydrogen, it has higher overall investment and energy costs.

The ultimate aim is to navigate through the complexities of the hydrogen system, clarifying how various variables interconnect and influence each other. Tools like the one developed in this research provide a foundation for understanding this complexity. By understanding the impact of governmental interventions and other factors on final prices, stakeholders can engage in more strategic decision-making. To deepen the understanding of the system, it is recommended to conduct further interviews and research, exploring the alternatives within and outside the European system more comprehensively. Investigating what drives prices beyond mere economic factors will offer a clearer picture of their current status and potential future developments. This broader analysis will equip users with the insights needed to make informed decisions, considering both the economic and socio-technical dimensions that shape the hydrogen market's evolution.

In today’s high-tech industries, technological innovation has become a crucial strategy for businesses seeking growth and expanding competitiveness. The growth of technology-based startups is especially notable, as they employ innovation processes that are often unfeasible within larger organizations. However, despite the abundance of talent and ideas, illustrated by the countless patents filed by entrepreneurs, many innovative companies struggle to translate their breakthrough technologies into commercial success. For startups developing hardware technology, the challenges are even more complex. These firms face significant hurdles in scaling up their operations, as regulatory and industry standards compliance add layers of complexity to their development processes. These startups often encounter conflicts between the iterative innovation process and the need to meet mandatory compliance requirements, leading to delays and increased costs.

This study investigates the challenges hardware startups face with regulatory and industry standards compliance, offering insights for entrepreneurs and stakeholders. The central research question explored is: "How can technology-based hardware startups include regulatory and industry standards compliance during the development process of their technology and products?”
To answer this question, a systematic literature review is carried out to map and thoughtfully understand the existing academic concepts related to this topic. Also, more specific exploratory research is performed to create a foundational understanding of the regulatory and industry standards landscape, faced by hardware-tech startups. Thirdly and most significantly, interviews were conducted with twelve hardware tech startups across various industries. These interviews provided knowledge of participants' experiences, motivations, and insights.

The findings of this study revealed that technology-based hardware startups find consensus in balancing validated learning principles i.e. hypothesis-driven entrepreneurship and hardware development, due to inherent hardware constraints. These challenges include restrictions in producing multiple MVPs, the inability to conduct pilot testing and long development cycles. However, all startups emphasize the importance of early market interaction for validating their business and customer assumptions. In addition, technology-based hardware startups face a complex regulatory landscape that requires adherence to both mandatory technology and product regulations, and additional industry standards, impacting their development processes. Awareness in startups of relevant regulations and standards varies, with some startups engaging external experts while others rely on market feedback. Overall, it is hard for startups to accurately estimate the real impact of compliance processes, especially since lead times for certification approvals, managed by notified bodies, do not align with rapid iterative development. Compliance processes can lead to increased costs and delays, requiring startups to build internal expertise to manage these requirements effectively. Furthermore, the timing of compliance efforts is critical, to align and implement requirements with product development phases.

Ultimately, this research highlights the need for an integrated approach for compliance and product development, while stressing that the challenges that come with compliance, are often overlooked by startups, academia, and the broader ecosystem.

Currently, there is no standardised process for monitoring and evaluation of nature-based flood defenses pilots in Dutch rivers and floodplains. Thus, piloted technologies cannot be compared fairly with other nature-based flood defense technologies and conventional solutions. This study developed such a process by way of a monitoring and evaluation framework, using a research-by-design approach. This monitoring and evaluation framework is incorporated into a knowledge base that was developed in parallel to store the results of monitoring and evaluating and to effectively share knowledge about each pilot for future reference. The primary intended users of the knowledge base are researchers, therefore requirements were elicited via interviews with matter experts. Findings from the interviews, combined with literature review, formed the basis of design and development for the monitoring and evaluation framework and knowledge base. A second round of interviews was held for iterative improvements of this design via feedback and subsequent revision. In total, three design-feedback iterations were done. The last provided validation results of the improved solution. The main findings indicate that a knowledge base approach has merit and it is suggested that Rijkswaterstaat adopt and improve this solution as a template within their innovation process. The innovation process at Rijkswaterstaat is being developed right now and has incorporated evaluation of pilots. Additional results are a large number of possible avenues for further development and future research.

Technology advancements and growing demands from citizens brought about a digital transformation of the Dutch public sector. As the digital standard rises higher and higher, the Dutch public sector is faced with the task to offer a strong digital environment and can choose to do so by either maintaining current IT infrastructures or by investing in alternatives.

At the moment the most promising alternative seems to be cloud technology. Cloud technology, or more specifically public cloud technology, provides the option to ’rent’ computing resources remotely from an external party. It is already widely in use within the private sector, as well as in some European governments. However, to introduce public cloud technology some hurdles must be overcome, such as concerns related to data security or the dependence on soft- and hardware that has been superseded but is difficult to replace. To gain more insight into the issue of the public cloud being a viable option to accommodate future digital transformation, it is first and foremost important to know what variables play a role in the decision-making process: what are the incentives to answer this question with either a ’yes’ or a ’no’? The objective of this study will therefore be to investigate this landscape of variables that influence the decision to adopt public cloud technology. It starts with the identification of variables from current research and reports, and then explores possible interrelationships. The identification and classification of these relationships could eventually help to bring about a well-considered decision about public cloud adoption in the Dutch public sector.

Reviewing current research related to variables that influence cloud adoption, three research gaps emerged. Firstly, current research was delineated to the Netherlands and therefore failed to capture geographically specific variables, such as legal or cultural characteristics. Secondly, authors that analysed the decision-making process of adopting cloud technology neglected any interrelations between different variables. Thirdly, existing theories fell short in capturing the full scope of could computing adoption decisions, being either too generic or not specific enough.

To address the knowledge gaps and simultaneously fulfil the objective of this study, Interpretive Structural Modeling (ISM) and Fuzzy Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) methods are used. ISM aims to simplify complex relationships between a system of variables by providing a graphical representation of the hierarchical structure of that system. Fuzzy MICMAC is used to assess the strength of the relationship between the variables. In total, 22 interviews with experts in the field were held as input for the analysis. The experts worked in the Dutch public sector and were familiar with the decision-making process related to cloud computing adoption.

In the first step of ISM, relevant current literature and official Dutch documents and reports were used to create a list of eight variables that would have a negative effect on the decision to adopt cloud computing within the Dutch public sector. These were classified as the ’barriers’. Additionally, a list of eight positive variables was created and classified as the ’drivers’. Then, the ISM Fuzzy MICMAC steps were followed for both lists.

Key findings for ISM can be described as ’how many’ other variables are influenced by a certain variable, or by ’how many’ other variables this certain variable influences (including indirect effects). For Fuzzy MICMAC, results can be described by using the terms driving power, i.e. how ’strong’ does a variable influence other variables in the system, and dependence power, i.e. how ’strong’ is a variable influenced by other variables.

For the barriers, Regulations and government policy was the variable that had the most influence on other variables within the barrier system. The barrier that influenced other variables the strongest however (i.e. had the highest driving power), was Lack of knowledge and capabilities. Both Internal resistance to change and Negative business case were influenced by the highest number of other variables and did not affect any new variables. The variables with the highest dependence power were Internal resistance to change and Data security concerns.

For the drivers, Bigger knowledge market, Ease of use and Improved hard- and software were the variables that had the most influence on other variables within the drivers’ system. The driver with the highest driving power was Improved hard- and software. Governmental strategy was influenced by the highest number of other variables and did not affect any new variables. The variables with the highest dependence power were Lower and flexible cost and Governmental strategy.

The findings of this research have practical and theoretical implications. Practical, because they can support decisions about cloud within the Dutch public sector. Theoretical, since the findings suggest new variables, interrelations and theories related to public cloud computing. Furthermore, it uses ISM Fuzzy MICMAC, which is often used in the context of novel technologies, but never before for cloud computing adoption decisions.

Future research could address the limitations of this study, such as the exclusion of a feedback loop from the experts during the identification of the variables. Alternatively, research could use the Total Interpretive Structural Modelling (TISM) method to investigate the relationships further.

Over the past decades, global efforts have been made to address climate change and improve the well-being of our planet. The European Union (EU) has set ambitious greenhouse gas (GHG) emission reduction targets and strategies to combat climate change. Bio-energy, specifically biofuels produced from biomass, has gained significant attention as a crucial component in decarbonizing energy and production systems. While renewable energy sources like solar and wind are primarily used for electricity generation, bio-based processes focus on producing biofuels for heat, power, transportation, and biochemistry sectors. Therefore, biomass can play a crucial role in decarbonizing hard-to-abate industries that are challenging to electrify, such as the chemical industry, heavy road transport, and marine and aviation sectors. However, the chemical industry, a major energy consumer and emitter of CO2, relies heavily on fossil fuels as feedstock and energy sources, necessitating a shift to carbon-free alternatives.
The biomass-to-syngas pathway, which involves converting biomass into bio-based syngas through gasification, has emerged as a promising solution for a more sustainable chemical industry. However, the development of this value chain faces technical and commercial challenges. Technical challenges include tar formation and product impurities, while commercial challenges include financing limitations, low market maturity, and sustainable feedstock availability. Moreover, handling and using biomass as a feedstock itself present constraints such as transportation limitations, variable composition and properties, low energy density, and high moisture and oxygen content. These challenges hinder the competitiveness of bio-based syngas production against fossil fuel alternatives and impede the development of the biomass-to-syngas value chain.
To address these challenges, the integration of torrefaction technology into the value chain has been proposed as a promising approach. Torrefaction enhances biomass densification, reduces moisture content, and improves the overall viability of the biomass-to-syngas value chain. However, the commercial implementation and economic feasibility of torrefaction remain uncertain. Additionally, research primarily focuses on technological improvements and lacks a deeper understanding of system integration, practical implementations, and stakeholder perspectives.
This research aims to bridge these knowledge gaps by actively engaging with stakeholders across the value chain to address the challenges of developing the biomass-to-syngas value chain and propose comprehensive solutions through stakeholder involvement. It explores the system integration of torrefaction technology, considering industry stakeholders' perspectives. The research employs a step-wise approach, focusing on an in-depth case study of the Dutch chemical industry. Data is collected through an exploratory literature review, semi-structured interviews with stakeholders, a questionnaire, and a webinar serving as a panel discussion platform.
The research identifies 44 barriers hindering the development of the biomass-to-syngas value chain and the integration of torrefaction technology. These barriers primarily stem from deficiencies in innovation-specific institutions, network formation and coordination, and the production system. Stakeholders and experts agree that technological and logistical challenges can be overcome. However, addressing failures in innovation-specific institutions, such as the lack of economic and policy incentives and an unfavorable regulatory environment, is crucial for driving the development of the value chain. Based on these findings and insights obtained through expert reflection the research develops comprehensive solution statements and formulates five strategies to address the identified barriers, including cohesive policies, industry-tailored subsidies, standardized certifications and regulations, enhanced network formation, and decentralized torrefaction technology integration.
In conclusion, this research underscores the significance of the biomass-to-syngas pathway as a key driver for a sustainable chemical industry. By addressing technical and commercial challenges and the integration of torrefaction technology, comprehensive strategies have been formulated to overcome barriers and unlock the value chain's full potential. These findings thereby provide actionable insights for policymakers and industry stakeholders to drive the sustainable development of the biomass-to-syngas value chain.

Existing research has shown that due to the increasing digitalization and the adoption of digital technologies and complex (big) data solutions, along with higher firm-level productivity, comes a growing and more dynamic threat environment. Organisations rely on data and digital environments. These environments enlarge the potential attack surface, as every end-point device or network node is a potential entry for malicious actors. The (un)intentional insider threat is also increasingly important for the protection of Intellectual property (IP) and business assets. Not only the attack surface has grown over the years, but also the consequences of security breaches have become more severe. Loss of confidentiality, integrity and availability can heavily disrupt working practices or even threaten the continuity of organisations.

The stakes for organisational security have therefore never been higher. Current trends in coping with this new threat landscape are, among others, to increase oversight and ensure strict regulations, both via internal policy and external regulators. Extant literature also emphasises an increase in security spending, as well as technical measures to protect business assets. This paper proposes a framework for determining the maturity of security governance within organisations. Security governance is concerned with the alignment of business goals on the one hand and security goals on the other hand, i.e. working productively and working securely. Good governance would mean that both business- and security goals can be reached without conflicting interests; preferably even by complementing one another. The research argues that security governance consists of more than merely technical measures and punitive oversight. It also parts from existing views about how more security (spending, measures, policies, etc,) is better and how security is predominantly addressed in isolation. Instead, security governance should be in alignment with ’the business’ of an organisation. This brings forward the notion of security governance, as the alignment between security policies and business goals.

Literature has found that these two concepts can often be conflicting, as more security in most cases impacts productivity. Therefore, the concept of maturity is coupled with the research. Maturity emphasises the alignment between security goals and business goals. The research adopts both a conventional view of maturity, as well as a social view of maturity. The conventional view focuses on the effectiveness of security governance. A higher level of maturity indicates improving one or both of the pillars of governance, i.e. the contribution to business goals and security goals. This could mean working more productively/efficiently given certain security policies. Or - the other way around - working more securely whilst also doing projects efficiently. The social view focuses specifically on the way alignment between the two pillars of security governance is reached. It acknowledges that not all perceived governance problems in organisations have a single solution that can be imposed top-down. Instead, employees in organisations have to cope with different challenges and perceive issues related to security governance differently. The social view on maturity therefore argues that dialogue is required between a representative stakeholder group, with different viewpoints and expertise, whereby policies are drafted in concordance.

By means of a case study at Damen Naval - a large Naval shipbuilding organisation relying heavily on IP and bound by strict regulations - input was gathered regarding security governance in three individual security fields: ’access control’, ’data classification, and ’monitoring & incident response. Incorporating results from a literature review, individual interviews and
a focus group session, a framework was built with both a conventional assessment of security governance and a social aspect of how the alignment of policies (security- and business-related) can best be reached. The foundation of the framework consists of six dimensions of security governance:
1. Organisation-wide security and responsibility/accountability
2. Risk-based approach
3. Direction of acquisition and commitment of resources
4. Conformance with internal and external requirements
5. Security positive/conscious culture
6. Security performance measurement/alignment

These dimensions were used to guide and structure the individual interviews and led to a list of performance indicators. Each indicator steers on improving security (in terms of policy-setting) and/or productivity (in terms of contribution to business goals). The research showed that although the security fields were different from each other, most indicators could be applied to all the security fields, showing that the indicators are generalisable to an organisation-wide level. The indicators led to practical recommendations for security governance at Damen Naval. The most important takeaways are to better empower engineers in making decisions on data classification, as currently engineers feel uncomfortable in doing this due to the negative consequences of ’under classifying’, which leads to information being classified higher rather than lower. Also, performance expectations should be clear for employees and additional hours spent on dealing with security measures should not be absorbed by engineers. In line with this, more effort should be put into quantifying the total costs of imposed security measures, both direct and indirect. This will make current security policies better explainable or address issues that need to be improved.

The final stage of the research aimed at reaching concordance on security governance. This was researched via a focus group session in which the metaphor of a doctor-patient relationship about a negotiated treatment plan was used to see whether and to what extent this relationship would be possible in an organisation such as Damen Naval. Despite the fact that such a relationship is hard to pursue in a large organisation with multiple stakeholders as well as being limited in autonomy due to external legislators, the results indicate that concordance would be possible, although on different levels inter- and intra-organisational. Intraorganisational, this research suggests composing an organisational structure wherein employees of the business, ICT and security are represented to discuss matters that are related to security. The focus group session itself proved that this contributed to reaching alignment. Inter organisational, dialogue with external regulators should be pursued. Using the framework for security governance and the security performance indicators, potential misalignment can be determined systematically and a more comprehensive discussion can take place. Finally, future research could focus on improving the framework to enable a Capability Maturity Model (CMM) approach and to conduct a similar case study with the inclusion of an external regulator.

This thesis researches how actors of government, industry and academia in an international context should collaborate in order to successfully carry out knowledge/technology transfer. The case study is about Dutch-Moroccan international Triple Helix collaboration in horticulture.