The COVID-19 pandemic since 2020 has pressed the pause button for the whole world for almost a full year. Starting from 2021, many countries have gradually resumed their economic activities and recovered from the pandemic. China, however, despite its economy showing signs of recovery, a slowdown in economic growth is also obvious and continuous. Before the pandemic, China’s economy maintained on average an annual GDP growth rate of 9%, with the lowest still exceeding 6%. But this growth rate dropped to an average of 4.9% since 2020, with only the year 2021 exceeding 6%. The slowdown in economic growth makes people wonder what has happened to China’s economy. Meanwhile, the concurrent China also shares some similarities with Japan in the 1990s. At their respective times, both economies were the countries with the second-largest GDP in the world after the United States, had bubbles in real estate, shared export-oriented models, faced challenges posed by ageing populations, and were subject to external pressures from the United States in trade and technology. Since 1990, Japan has entered a prolonged recession which was explained as being the balance sheet recession by an economist Richard C. Koo. The similarities and comparisons have raised the question of whether China, too, might enter a similar phase of balance sheet recession. However, some China-specific features have distinguished China from Japan and other Western countries where the balance sheet recession theory can explain their recessions well. For example, China is a socialist country, it has its socialist market economy. State-owned enterprises (SOEs) have dominated critical sectors and the state can have many interventions into the market through SOEs. The differences could obscure the typical symptoms of a balance sheet recession. The research gap remains in the applicability of the balance sheet recession theory in the context of China-specific features. Therefore, this research tries to study the applicability of the balance sheet recession theory to China’s current economic performance, and give policy recommendations to reverse its economic slowdown trend accordingly. To address the research gap, several steps are taken. First is to study the balance sheet recession theory, and try to summarise the typical patterns of a balance sheet recession. The patterns are summarised as having a deflationary spiral, decoupling between monetary base, money supply, and private credit, and liquidity trap. Then, the China-specific features that are most relevant to the balance sheet recession theory are studied. Through investigation, China has specific features of high saving rates and low consumption, large occurrences of SOEs compared to private firms, and a bank-based financial system. These features are likely to influence the typical patterns of a balance sheet recession…

A creeping crisis adds a new phase to the hot and cold phases of a ‘regular’ crisis: the creeping phase. Detection of the tipping point at the end of this creeping phase is important for a timely response from the Dutch safety regions. Such a detection approach cannot be found in literature. This research tries to answer the question ‘What detection approach could help the Dutch safety regions in detecting the tipping point of a creeping crisis when the creeping phase becomes the hot phase?’ It is found that the creeping crisis is surrounded by uncertainty as this uncertainty can be found around the nature of the threat, the build-up of the threat and the tipping point itself. The research tries to find an approach that is able to deal with this uncertainty. It is found that an approach that makes use of thresholds might be suitable for the detection of a tipping point. However, further research is needed to make this method applicable in practice.

The urgency of addressing climate change has resulted in the implementation of proactive climate policies across multiple sectors. Including the business sector, where regulations aim on the energy efficiency and sustainability within companies’ facilities. In the Netherlands, recent regulations have imposed significant energy efficiency requirements on office-based companies, particularly concerning the energy efficiency and sustainability of office buildings. This research investigates the impact of Dutch climate policies on companies within the business sector, focusing on how these companies adapt their office buildings and sustainability strategies to comply with the new energy efficiency regulations. Through a combination of semi-structured interviews and thematic analysis, this research explores the practical measures companies are taking to meet energy efficiency standards, the challenges they face in implementing these measures, and the role of internal corporate motivation in driving sustainability initiatives.

Three main regulations are included and investigated in this study: the minimum energy label C for office buildings, the energy savings obligation (including the recognised measures list), and the Energy Efficiency Directive (EED) audit obligation. The study provides detailed insights into how involved companies navigate the technical and organisational complexities of complying with these policies, including negotiating with landlords for rented office spaces and balancing compliance costs with financial viability. Additionally, this research highlights the extent to which companies’ sustainability practices are driven by regulatory compliance or by a deeper commitment to social corporate responsibility in sustainability. Long term strategies and culture will be included in this research to create a more complete view of companies’ stance and strategies.
By presenting a nuanced analysis of the effects of Dutch climate policy on the business sector, this research contributes to the broader understanding of how companies are responding to the evolving sustainability landscape and energy efficiency goals in the business sector. The findings inform both policymakers and companies on effective strategies for enhancing energy efficiency in office buildings while addressing the practical and organisational barriers to implementation.

Audit analytics (AA) enables the improvement of the effectiveness and efficiency of the internal audit function (IAF). In this research, we follow Lambrecht et al.’s (2011, p.3) and define AA as “the process of identifying, gathering, validating, analyzing, and interpreting data using information and communication technology to further the purpose and mission of internal auditing”. AA is an umbrella term encompassing various forms of technology-based audit approaches, from continuous auditing to advanced machine learning. Due to the increased effectiveness and efficiency, AA enables the IAF to provide proactive and ongoing assurance services instead of periodic assessment, expand the (internal) audit service areas with the same resources, enable larger samples or even the whole population for analysis, and can provide insight and foresight for its stakeholders, in addition to the hindsight of the (possibly) already occurred risks...

Traffic congestion and accidents present increasing challenges in the Netherlands, particularly due to high population density and complex urban conditions. This research explores the potential of drones as a solution for improving road traffic management by Rijkswaterstaat (RWS), focusing on policy and technological aspects. Utilising Kingdon’s Multiple Streams framework, adapted to include problem, technology, and regulatory and policy flows, the study provides a holistic view of the innovation process within RWS.

The investigation addresses key sub-questions: the challenges RWS has faced in road traffic management, opportunities and challenges of drone technology, regulatory and policy issues, and the convergence of these factors to create innovation opportunities. Through a qualitative approach, including literature reviews, actor analysis, and semi-structured interviews, the study examines the dynamics of drone implementation.

Findings reveal complex challenges such as efficient incident management and infrastructure monitoring, compounded by budgetary constraints and the need for new technologies. Drones offer significant opportunities but face obstacles like manual control limitations and regulations for Beyond Visual Line of Sight (BVLOS) operations.

The research highlights the importance of internal and external changes for successful drone integration, recommending strategic resource allocation, increased internal awareness, and collaboration with regulatory bodies to create a supportive framework. This study aims to guide RWS in effectively adopting drone technology for road traffic management, balancing internal innovation readiness with external legislative developments.

Generative AI is expected to have a significant impact on how business is done, especially for knowledge-intensive domains. Professional usage amongst knowledge workers is already widespread and many of them believe that LLM use for work will make them more efficient, help them generate ideas, and improve the quality of their work. Yet, the technology comes with numerous potential risks, including job displacement, threats to data privacy, unreliability, cybersecurity risks, and non-compliance with new AI regulation. The decision to adopt LLMs for knowledge work is thus a significant one as organisations must carefully weigh up the benefits and drawbacks that these models present.

Using a qualitative research approach, this study was aimed at exploring employee and organisational perceptions on the benefits and risks of LLM adoption within the Dutch financial sector. This study was conducted in partnership with a global Professional Services Firm and used their existing network of people and clients to conduct interviews with experts who act as advisors to top management in the decision-making process of new technology adoption such as LLMs. 18 semi-structured interviews were done to collect qualitative data. The research question to be answered is:

- How do employees’ and organisations’ perceived benefits and risks of Large Language Models (LLMs) influence financial organisations’ LLM adoption plans?

Exactly half of participants (9/18) said that they use LLMs in their own work while the other half stated that they do not due to a lack of perceived benefits. Microsoft was found to be a significant player in the current adoption of LLMs at Dutch financial institutions with 57% of all LLMs used by participants being owned by the software vendor. The most common LLM use cases were literary and creative in nature and included preparing presentation slides (16%), text generation (12%), email composition (12%), and structuring documents (12%).

The targeted capabilities that organisations would like to achieve with their future adoption plans include helping programmers write better code, analysing help desk conversations, assisting employees via LLM chatbots, and analysing emails to predict customer questions. Employees were most excited about the potential efficiency and productivity gains that LLMs offer for their work (19%), how LLM usage could free up more time for focused, interesting, and fun work (11%), repetitive tasks becoming automated by LLM (8%), the new opportunities that LLMs present (8%) such as new business models, and improvements to customer service (5%). General overlap can be seen between the targeted capabilities of future LLMs to be adopted and employee expectations.

Instead of restricting LLM usage, it is recommended that organisations find ways to incorporate them into their employee workflows by providing clear policies and guidelines. It was found that this approach will be most beneficial to creative and literary workflows like improving writing/grammar/translation, information search, structuring documents, and text generation. To achieve this integration, organisations should write and implement clear usage policies. This will ensure that the benefits of allowing LLM usage at work are enjoyed while mitigating the most important risks.

Historically, Central Asia and agriculture have had a tempestuous relationship. The collapse of the USSR in 1999 put agriculture fully in crisis. Greenhouses, a flourishing sector in the latter days of the USSR, almost fully disappeared. In attempt to gain self-sufficiency in fruit and vegetable production, Kazakhstan, Kyrgyzstan, and Uzbekistan reconsider greenhouses to stabilize horticulture in the region’s desertifying climate. Current water governance, formed by USSR political and technological path dependencies, has not been able to bolster this transnational infrastructure transition, in which water and energy systems are interrelated and shared across borders. That bears the question: how does path dependency influence infrastructure transitions in centralist and authoritarian regimes? A multiple-case study design gathered data about water governance in Kazakhstan, Kyrgyzstan, and Uzbekistan through a literature review and semi-structured interviews. Planned transitions in those regimes did not evolve as intended due to pushback from actors and USSR induced institutions, not being ready for change. An institutional structure to support transitions in those regimes is lacking due to institutional reproduction of USSR conception, reflecting little pluralism of actors, restricted actor interaction, and top-down governance. High sunk costs make it expensive and physically challenging to change or abandon existing (water) infrastructure, particularly without clear ownership and roles. Accordingly, the USSR conception of governance and past technological decisions lead to path dependencies and impede change in this transnational infrastructure.

This thesis explores the implementation of the Corporate Sustainability Reporting Directive (CSRD), specifically the Environmental Sustainability Reporting Standard (ESRS) E1, within the logistics sector. As a major contributor to global greenhouse gas (GHG) emissions, the logistics sector faces both challenges and opportunities in aligning with the CSRD’s objectives to promote transparency and sustainability. Through a qualitative case-study approach, the research investigates how logistics companies navigate GHG reporting under CSRD ESRS E1 and identifies key factors influencing their alignment with sustainability goals. The findings highlight three forms of decoupling between policy and practice, including loose coupling between compliance and internal operations, and the gap between sustainability policies and operational realities. Additionally, the study reveals several internal and external factors contributing to these misalignments, such as resource limitations and the complexity of supply chains. The thesis concludes with actionable recommendations for businesses and policymakers to enhance the effectiveness of CSRD implementation and reduce policy-practice decoupling, contributing to meaningful progress in GHG emissions reduction.

In my thesis I was studying the interrelation between network topology and dynamics and the emergence and evolution of institutions for the governance of CPR. This research was intended to shed some light on what is the role of networks in formation of endogenous institutions and the possible insights for policy makers and users of CPR. To answer my research question, I utilized the agent-based institutional model and enhanced it by adding three dimensions of social networks and connecting them through various mechanisms to other parts of the model trying to capture the complexity of SESs. Therefore, through the combination of ABM and approaches from SNA I conducted a series of simulations that were imitating co-evolution of endogenous institutions and network topology. Through variation of input and output parameters the patterns were derived from the model and thoroughly analyzed. Notably, they suggest a positive relationship between the degree of network fragmentation and the stability of institutional structures within these communities. This implies that more fragmented social networks tend to exhibit greater stability in their institutional arrangements. Furthermore, the research reveals the presence of negative feedback mechanisms influencing network-dependent rewiring probabilities and positive feedback mechanisms governing homophily-based rewiring probabilities. These findings underscore the complexity of CPR governance, where network structures, institutional dynamics, and personal strategies interact in intricate ways. The results of this analysis were utilized to provide policy recommendations for regulation of CPRs. Mainly these recommendations evolve around: (i) identification and connection of fragments within social networks; (ii) analysis of the details of agents resource consumption, (iiI) identification of potential strategy options and (iv) enhancement of the processes that drive creation of gear- (or other attribute-) based connections. Overall, the research has the potential to inform the development of more effective and sustainable approaches to the governance of CPRs.

This thesis addresses the issue of teacher shortages in Dutch primary education. The first section of the study encompasses a multi-actor analysis of the Primary Education sector and provides a comprehensive overview of the recent efforts to reduce the teacher shortage.
Next, utilising Q-methodology, profiles of three types of teachers are drawn based on teachers' job preferences. The first is the Service-Focused teacher, who exhibits a strong commitment to assisting underprivileged children and values ethical leadership and community engagement. The second is the Classroom-Focused teacher, who prioritises pedagogical autonomy, trustworthy leadership, and stress mitigation. Lastly, the Career-Focused teacher emphasises personal growth, leadership opportunities, and career progression.
The final section of this study assesses the recent policies targeting the teacher shortage, as analysed in the first section, taking into consideration the Q-methodology outcomes. The conclusion recommends further research focusing on school leaders and teachers at schools in disadvantaged neighbourhoods.

Food safety inspections play an important role in the safety of consumers of food products. Even though food safety regulations have disciplinary power over food-related businesses, inspections are needed to ensure that regulations are followed for the well-being of consumers. Traditionally inspections did not have a goal of targeting higher risks. However, since 2004 EU regulations require all EU Member State inspectorates to follow a risk-based approach within their inspection plan. This is an effective way of inspecting and gives high results in catching violations. However, to be able to know what is happening in the overall industry representative results are needed, and performing inspections based on risks does not provide representativeness. Random inspections if performed in a representative way can provide this. Inspectorates are looking for ways to combine random and
risk-based inspections to get representativeness from risk-based approaches. To do this the inspection strategy might need to consist of a combination of random and risk-based approaches. The reason for this is to avoid bias that may result from performing risk-based inspections.
The main research question of this thesis therefore is: How can inspectorates adapt their inspection strategies to mitigate bias that results from risk-based inspections?
The exploration of how risk-based and representative inspections can be combined is aimed to
be supported with an investigation of methods that support this decision. This research aims to develop an assessment framework for evaluating such methods. In order to evaluate these methods, assessment criteria are needed that measure the methods appropriately. Since the reason to combine random and risk-based approaches is to reduce the assumed bias of risk-based inspections, there is a need to understand what bias is in risk-based inspections. Furthermore, to understand this, what risk means needs to be investigated. Therefore, the goal of the research is to find out how risk and bias affect the choice of inspection strategies, by investigating random and risk-based inspections and how these can be combined in order to leverage their advantages.

The concept of deterrence, using fear of punishment to encourage compliant behavior, is widely discussed. However, deterrence often places an emphasis on the economic side of compliance while neglecting other possibly crucial factors, as is argued by the literature. Psychological factors, notably the personal norm and the social norm, often appear to play important roles in the decision to comply or not. The personal norm describes an individual’s attitude and moral stance toward specific behaviors, such as compliance. On the other hand, the social norm revolves around perceptions of others’
behavior and opinions within one’s social network. Hence, the influence of these factors is researched within different populations, and different environments, some enabling and some impeding compliance. A new framework to encompass all these elements is explored with Agent-Based Modeling and applied to a case study in collaboration with the ILT (Inspectie Leefomgeving en Transport). Findings included the lack of a social influence on compliance, whenever the personal norm was high and the necessity to be able to comply in order for deterrence to show an effect. For future research, suggestions are done to improve the framework and to explore additional aspects.

The Nederlandse- Voedsel en Warenautoriteit (NVWA) asked the at-first-sight simple question of how to combine risk-based and random methods for inspection. Risk-based and random inspection methods have contrasting incentives. Risk-based inspection increases efficiency and allocates resources efficiently but fails to regulate low and emergent risks. Random inspection tackles unforeseen and emerging risks, ensures representativeness and prevents bias but fails to detect food hazards and non-compliance with food safety laws efficiently. A void in the literature exists on how to address the question of the NVWA. The supposedly simple question thus appeared to be a rather complex one. The research develops guidance for food safety authorities in combining risk-based and random methods through a design science approach combined with a systems view to retrieve a complete understanding while allowing it to narrow down to practical guidance.

The first step to address the literature void is the development of the construct of inspection strategy based on design science cycles fueled by literature and interviews with regulatory authorities. The following definition of the construct is retrieved: an inspection strategy entails selecting and combining methods based on inherent considerations and operationalization on contextual considerations. The construct of inspection strategy is placed between inspection method selection and food safety regulation. The construct serves as a common language and shared understanding for food safety authorities.

The systems view is introduced to understand why inspection strategy design is complex for food safety authorities because of its context. Literature shows there is value in taking a systems view to regulation. In fact, the complex systems view applied to food safety regulation brought forward systems characteristics to consider in inspection strategy design, including adaptive, emergence, unpredictable and goal-seeking. The systems view showed that an inspection strategy is to be designed within the context of food safety regulation that is continuously changing in an unpredictable manner because of emerging food safety risks. Consequently, the complex systems view provided direction on how guidance for food safety authorities designing an inspection strategy within food safety regulation is to be developed.

Following the definition of inspection strategy and the exploration of the system complexities of the food safety regulation context, the requirements for an inspection strategy are identified. The requirements originated from the systems map, interviews and literature. Fourteen requirements are defined with corresponding categories and priorities. Based on the requirements, a visual framework is constructed, providing an overview of the considerations for food safety authorities designing an inspection strategy. The framework, when applied to strategies, exposes potential trade-offs. The framework respects the complexities of the previously uncovered complex system characteristics by providing insight without imposing rigid standards.

Guidance for food safety authorities is developed based on the previous findings. The guidance is twofold. First, a scale of encountered inspection strategies from random to risk-based is evaluated based on the requirements framework, guiding food safety authorities by providing insight into the associated trade-offs and helping them select a strategy. Second, questions are developed to guide food safety authorities before, during and after the design of an inspection strategy. Food safety authorities have to implement the guidance themselves.

Ultimately, the research holds potential for food safety authorities to improve their inspection strategies combining risk-based and random methods when implementing the guidance. Consequently, improving the state of food safety in an accountable, applicable, feasible and adaptive manner. Through validation is confirmed that the guidance is helpful for the NVWA. Furthermore, the research produces academic value by creating a common language in the academic field through the construct of an inspection strategy and by demonstrating the utility of systems thinking for regulation. The recommendation stands to implement the guidance, include participatory methods, validate with various food safety authorities and continue applying systems thinking in food safety regulation for future research.

Background. Dutch universities struggle to find effective evidence-based intervention tools to reduce the high prevalence of sexual violence among their students. Reducing sexual violence means a safer student climate and thus better inclusion of women and more diversity in higher education. Interesting approaches to consider for cultural change are bystander intervention and an already existing co-designed serious game. This game aims to encourage a dialogue among students but has thus far not been evaluated on its effectiveness. Therefore, the goal of this study was to evaluate how a serious game can promote an intergroup dialogue between female and male students in Dutch universities to encourage bystander intervention in situations of sexually transgressive behaviour. Methods. Literature research and brainstorm sessions with female and male students from Delft University of Technology (TU Delft) were conducted to gain a better understanding of sexual violence among students. These methods were used as part of participatory game design research. Moreover, a quasi-controlled experimental trial was conducted with 64 TU Delft students from different nationalities and study backgrounds to evaluate the serious game on bystander attitudes, sexual violence myth acceptance, the willingness to intervene, and the effectiveness of the intergroup dialogue. Results. The results showed that the serious game session has a significant positive effect on bystander attitudes (i.e. bystander awareness and responsibility) and the willingness to intervene. No significant difference was found in sexual violence myth acceptance. Additionally, the game proved to promote an effective intergroup dialogue between the participants. Conclusion. Serious gaming proved to be effective in encouraging ethical bystander behaviour by promoting an intergroup dialogue. Therefore, universities are recommended to use serious games as an intervention tool to contribute to cultural change. Future studies should include students from other universities and focus on minimising selection bias to research whether serious games can also influence sexual violence myth acceptance.

To mitigate the effects of climate change, CO2-emmissions will have to be reduced. This can be done by substituting the use of fossil, CO2-heavy by the use of renewable, CO2-neutral energy carriers. Hydrogen is such a renewable energy carrier that can be produced in a CO2-neutral way. The potential of hydrogen is recognized by the European Commission as specific renewable hydrogen goals are stated in their Fit for 55 package, which is a plan to reduce greenhouse gas emissions within the European Union with 55% by 2030. These goals relate to both the production and use of renewable hydrogen within the European Union.  For hydrogen to be qualified as renewable, the European Commission has proposed a set of requirements that its production has to comply with. One of them is temporal correlation, requiring the amount of energy used by a hydrogen production plant to match the amount of energy generated by one or more connected renewable energy plants. Renewable energy plants generate a variable output of energy as they rely on variable energy sources such as wind. This causes the production of renewable hydrogen to be variable as well. The fact that this production of hydrogen is variable can be problematic as some industrial processes require or perform better with a constant input of hydrogen. Energy storage systems, such as lithium-ion batteries, can be integrated in hydrogen plants to stabilize the hydrogen production from a renewable energy source. This works through locally storing part of the energy generated during peaks to be used at times when there is a deficit of energy. The purpose of this study is to see how different energy storage systems influence the performance of wind-hydrogen plants. A wind-hydrogen plant is a hydrogen plant producing hydrogen with an electrolyzer powered with energy from a wind park. Based on the outcomes of the study, wind-hydrogen plants can be designed incorporating the most adequate energy storage system for its purpose. The outcomes of the study can also be used by policy-makers to see how the temporal correlation requirement of the European Commission influences the feasibility of the hydrogen goals in the Fit for 55 package. The performance of wind-hydrogen plants with different energy storage methods is evaluated using a simulation model. After performing experiments for wind-hydrogen plants with different types of energy storage systems, their influence on the performance of the wind-hydrogen plant can be analyzed.  Results show that the hydrogen production from a variable energy source is lower and less stable than that from a continuous source. These effects can be mitigated with the use of energy storage systems. However, the introduction of these systems makes wind-hydrogen plants less efficient and drive up the costs of hydrogen production. This illustrates a trade-off as energy storage systems do increase and stabilize hydrogen production, but at a lower efficiency and higher cost.  Comparing the performance of individual energy storage systems shows that the use of lithiumion batteries to store energy results in the highest and most stable hydrogen. At the same time, the use of lithium-ion batteries is by far the most expensive option. The use of a hydrogen energy storage system results in the most efficient and cheapest hydrogen production. This shows that another trade-off is at play when selecting an energy storage system to integrate in a wind-hydrogen plant.

Based on the results, the effects of the temporal correlation requirement on the feasibility of the Fit for 55 renewable hydrogen goals can be analyzed. The requirement makes the hydrogen goals in the Fit for 55 package less feasible as it causes a decrease in renewable hydrogen production. It also makes it less fit for use by the industry as the hydrogen supply will become less stable. Energy storage systems can be used to mitigate these negative effects, however, these cause a decrease in hydrogen plant efficiency and therefore an increase in loss of renewable energy. Also, it drives up the production cost, making renewable hydrogen less attractive to use by industry and increasing barriers for new renewable hydrogen production to enter the market. The recommendation is for the European Commission to investigate an alternative requirement than the temporal correlation to ensure the renewable production of hydrogen.

For the future demand prediction of identification documents the National Office for Identity Data is interested in a new prediction model based on machine learning techniques. Due to the existence of many different machine learning algorithms and the often competing model requirements regarding model performance and explainability it can be difficult to determine which machine learning algorithm to use. This research aims to find a solution to help decision-makers determine what machine learning algorithms they should use while having to account for competing model requirements. This is done by performing a case study for the National Office for Identity Data in which the use of machine learning for a new prototype prediction model is explored. Additionally, a novel explainability assessment table is designed through which the explored machine learning algorithms are assessed on their explainability. By combining the results from the case study and the explainability assessment analysis a final design is created in the form of a decision support framework. This framework aims to support decision-makers in their process of finding a suitable machine learning algorithm when dealing with competing model requirements. Future researchers are recommended to either extend upon the decision support framework by making it more accessible for people with a less technical background or to analyse how a more standardised definition of model explainability can be developed and implemented in the field of machine learning.

The digital society increasingly demands for integrated ICT transformations. Societal, technical, and institutional developments enable interorganisational and cross-sectoral integration of digital services. However, a lack of trust and legal certainty impedes electronic transactions and the development and adoption of innovative digital services. Digital trust services counter this by providing solutions for secure and trustworthy electronic transactions, which benefits the electronic society. As the development of digital trust services have the risk to develop in isolated manner, interoperability is required to allow wide adoption of these services. Collaborative ecosystems are dynamic and co-evolving communities of interdependent stakeholders, and could support valorisation of digital trust services. Nonetheless, stakeholders participating in such an ecosystem pursue different interests while envisioning different ecosystem operations. Governance contributes to efficient and effective ecosystem orchestration by providing rules on decision-making processes. In addition, the governance needs to fit with the technical architecture of an ecosystem, meanwhile, it assesses external factors and the development through time. The challenges of designing a governance model for collaborative ecosystems are relatively unexplored, as literature is sparse. Therefore, this thesis aims to design a framework which analyses and mitigates the challenges in a current collaborative ecosystem by prescribing a fitting governance model which adapts to its context through time. By following Hevner’s Design Science Research approach, the following main research question is aspired to be answered: ”How to design a governance model for a collaborative ecosystem which facilitates electronic transactions?”. By applying this framework to the current collaborative ecosystem of the Trusted Information Partners (TIP) initiative in the Netherlands, the framework is evaluated and validated. The study affirms that a framework should cogitate three components when designing a governance model for a collaborative ecosystem facilitating electronic transactions: I) Identifying the governance tensions enables context setting of factors affecting the ecosystem, II) Prescribing governance mechanisms boosts the mitigation of power dynamics, and III) Pursuing governance consistency checks whether proper governance takes place in decision-making. The framework contributes to the knowledge base of governance networks, because the research provides building blocks for establishing a governance model for collaborative ecosystems. To boost the service delivery of collaborative ecosystems, the framework could be validated by applying it to an operative collaborative ecosystem. As where the framework currently focusses on a developing ecosystem, the insights of an operative ecosystem can increase the generalisability of the framework. Future research on this can provide further alignment between the functioning of ecosystems and the governance model. Applying improved framework versions to other digital ecosystems, could also stimulate the valorisation of trusted services in society as a whole.

The recommendations in this thesis are relevant for research and consultancy firms specialized in social aspects of technology. The problem that is analyzed is how in the future society can remain inclusive, when faced with the problems of technological innovation and the possibility of it causing technological unemployment. Researching such societal problems is the goal of this thesis, and the results may be interesting for those (for example in consultancy firms) who seek to widen the concept of "inclusive society", by including ideas of what meaningful participation and individual autonomy could entail. For example, in the third model of inclusive society, maintaining individual autonomy includes providing civil society with true freedom for self-development. The discussion of how individual autonomy in this sense could be maintained, is closely related to the way work is funded, and how productivity gains in the economy are distributed to finance more work.