Multiple challenges affect the effectiveness of climate change mitigation and adaptation measures, such as accountability, intergenerational justice and developing countries’ increased participation in greenhouse gas emissions. The high complexity of information surrounding models’ assumptions, results, and scenarios related to climate change also presents a challenge, especially when communicating with policymakers. In this context, support tools such as policy platforms can help bridge the science-policy gap by allowing policymakers to understand scenarios and available policy levers, enabling a better understanding of relevant concepts and models or serving as hubs for disseminating best practices and success stories. Available literature often evaluates support tools within the context of use by regular citizens, making it unclear how policymakers perceive support tools and how well they meet their needs, pointing to an important knowledge gap. This thesis explores policymakers’ and policy advisors’ perceptions of the usefulness of climate change mitigation and adaptation (CCMA) policy platforms and the characteristics of such policy platforms they prefer in order to use them as support tools. A collective case study was conducted with ten CCMA policy platforms within the context of the EU-funded Horizon 2020 programme. In addition, interviews (11) and surveys (9) with policymakers and policymakers’ advisors in the Netherlands and seven other countries within and beyond the EU were conducted.

Nine characteristics of CCMA policy platforms were identified: Transparency & Credibility of information, Ease of use, Flexibility of use, Accessibility & Portability, Education & Awareness, Communication of complex information, Data visualisation & interactivity, Actively maintained and supported, and Security & privacy. Interviews and surveys show that accessibility, relevance, applicability, and credibility were identified as the primary factors driving the perception of policymakers about the usefulness of CCMA policy platforms and four groups of characteristics were identified with decreasing levels of priority for policymakers: mandatory or must-have (formed by communication of complex information, free and open access to the tool, transparency regarding data sources and limitations, and high level of detail for spatial and temporal data); highly desirable or should-have (formed by availability of training and learning functionalities, availability of detailed documentation on concepts and models, interactive and easy-to-navigate elements, and availability of a web-based platform); ‘nice to have’ or could-have (user stories from policymakers or communities, availability of very recent data, ability to import user data/export results, and ability to modify parameters and run custom analyses), and indifferent (availability of languages beyond English and the ability to use the tool in mobile phones or tablets).

Four main recommendations are made to improve the design and use of CCMA policy platforms: Incorporating systematic reviews of existing CCMA policy platforms as part of projects developing such platforms, involving boundary organisations in the development and use of CCMA policy platforms, developing CCMA policy platforms with longer life expectancies and developing CCMA policy platforms flexible for different needs and preferences of policymakers.

With these results, new CCMA policy platforms can be developed with a better understanding of how useful policymakers perceive them and what they want from these support tools.

The concept of the Urban Smart Factory (USF), combining urban manufacturing with Industry 4.0 technologies, has emerged as a promising solution with significant value-added opportunities. However, there is a lack of maturity models specifically designed for assessing the maturity of companies in relation to the USF. To address this gap, this research aimed to develop an integrated maturity and self-assessment model for companies operating in urban environments. The model was developed through a literature review, expert interviews, and validation with an implementation example. The Urban Smart Factory Maturity Model (USFMM) consists of four maturity levels and five core dimensions, covering technology, workforce, strategy and organization, process products and services, and urban integration. A self-assessment questionnaire was created to measure the maturity levels, which was validated with a company achieving an "Advanced Implementation" level. The assessment identified areas for improvement, particularly in the workforce dimension, leading to recommendations for employee satisfaction monitoring and comprehensive metrics and KPIs. The model proved effective in evaluating company capabilities and provided valuable insights for improvement. The development of the integrated model enhanced its usability and applicability, while the validation process led to important improvements and recognition of non-technical innovation. Overall, the model is a valuable tool for assessing and advancing urban smart factories, offering personalized strategic roadmaps and facilitating the transformation journey.

As digitization moves on, more data is produced and the value of this data increases. However, data is still transferred manually between different digital systems. Reason to manually transfer information is lacking interoperability between these systems. Huge costs are related to this lacking interoperability as they cause high data losses. Issues with interoperability and information losses are present as well in the field of asset lifecycle information management. Especially in the transition of project delivery to asset management.
This research investigated the stated problem within the Engineering office of the municipality of Rotterdam. The research followed a design science research approach consisting of five steps. First the scientific knowledge base was defined, second the local practice is researched. Third design requirements were listed based on the pre-taken steps. Fourth an ontology was designed based on these requirements. Fifth, based on the investigated scientific literature into the topic the following objective was constructed:
“Design an ontology linking assets and their related information to BIM data-schemes and domain ontologies in a general way.”

Based on the analyses of the scientific knowledge base and the in-depth research cases a list of design requirements was established. To optimize the value of the ontology additional requirements from the FAIR principles were derived. Based on the derived requirements an ontology was designed with the main features as showed below. A main limitation of the research is that the design is not tested or evaluated extensively.
• Objects are central in the design, meaning, all information should be linked, eventually indirectly, to an object.
• Information type is included as a specific entity to provide structure in the information.
• Information related to an information type can be expressed in attributes, documents, and activities.
• The information inside a document can be made explicit in attributes and activities.
• The modelling references can refer to a specific object in a specific BIM-model or to meta-object of a specific BIM data-scheme.
• The domain ontologies refer always to a specific instance within such an ontology.
• Findability and accessibility are incorporated by the means of a separate regulation entity to provide flexibility on the abstraction level of regulation.
The research has some clear contribution to as well the scientific knowledge base as the local practice. Scientific contributions of this research are the designed ontology and the analysing made of the FAIR principles in relation to their application on an ontology for governmental data instead of scientific data. It should be mentioned that no extensive literature research is performed into an earlier application of this kind. Regarding the local practice, the main recommendation, next to the designed ontology, is to state explicit what information is in what documentation. This makes it easier to align the information available and needed and thereby enhances an early consideration on the information transfer process.
To conclude some recommendations for future research are presented. Future research could validate the findings of this research by investigating the information transfer withing the engineering of Rotterdam or strengthen the generalizability by doing the investigation within other major Dutch municipalities or other organizations dealing with the same problem. In addition, the ontology design could be tested and validated. Finally, it is recommended to do research in the application of software analysing documentation and able to extract explicit attributes and activities within these documents. The current developments regarding artificial intelligence and language models may offer opportunities to derive explicit knowledge from documents and transfer it in an explicit way solving a part of the problem at hand.

Despite the potential benefits regarding data-sharing in the container supply chain, stakeholders still can be skeptical towards data-collaboration. Due to conflicting goals and objectives of companies and the competitive nature of the
industry, data-collaboration cannot be easily achieved. Previous research has little touched upon combining inter-organizational governance and data governance. Based on a case study about data-collaboration in the container supply chain and previous data governance research, a new data governance framework with possible data-sharing archetypes is developed. Three data governance archetypes are suggested in order to further enhance data-collaboration: regulate data, buy & sell data and data-fordata. Future research should focus on the further validation of the found archetypes, valorization of data and the legal basis of data-ownership.

This thesis focuses on designing a process for balancing and prioritizing the digital innovation project portfolio of a rental equipment company. The company operates in a traditional industry in which themes like digital transformation and digitalization are new emerging themes that are yet to be accepted by the industry. Therefore, in order to keep their businesses future proof, rental equipment companies need to focus on planning their digital project portfolio to meet their strategic requirements. This research was carried out in collaboration with Riwal Holding Group, a specialist in ariel work platforms (AWP) to design a process to manage their digital project portfolio and to check how feasible the process would be in a real-life setting.

Open research data sharing and reuse can bring more transparency to the research, save researcher time by preventing repetitive data collection processes, and lead to more collaborations. However, open research data sharing has not become common practice in some research fields such as Epidemiology due to a variety of issues. We propose that the negative impact of issues in front of open research data adoption can be tackled by the right institutional and infrastructural instruments. The objective of this study is to understand the roles that infrastructural and institutional instruments (or their combinations) can play in promoting open research data sharing and (re)use behavior in Epidemiology. To achieve this objective, first, we conducted a systematic review investigating what instruments could be used to lead researchers to open data practices. Then, to examine the availability and importance of the proposed instruments in Epidemiology, we conducted a case study that includes interviews with Epidemiology researchers and a research data management consultant who work at various University Medical Centers (UMCs) in the Netherlands. We also evaluated the transferability of our case study findings in a workshop with data stewards and research data officers that work in different research fields at a Dutch research university. To our best knowledge, this study is the first study that focuses on the field of Epidemiology while examining the roles of instruments in open research data adoption based on field-dependent characteristics. Our study shows that researchers in Epidemiology do not openly share or reuse research data due to many different reasons relating to the legal, cultural, technical, and organizational issues. Many of the potentially effective instruments are not fully within the reach of Epidemiology researchers. Researchers do not have sufficient access to research data managers, search engines with satisfactory functionality, overarching registries, and reward systems for data sharing contributions. Institutional instruments can support open research data adoption by reversing the lack of an open data sharing culture with the right incentivization approaches, by the provision of financing, and by actively supporting researchers via data stewards, research data managers, libraries, and data privacy officers. Infrastructural instruments have the potential for supporting open research data adoption by increasing the findability and interoperability of the research data, and making researchers’ interactions with data infrastructures easier. Our study shows that institutional instruments (especially those that target enhancing the open data sharing culture and creating data sharing incentives) are in a more vital position to open research data adoption. Nevertheless, considering that many instruments complement one another, to increase the effectiveness of the instruments, they should be combined. We recommend conducting case studies in other contexts (e.g. involving policymakers, infrastructure providers, etc.), considering that the issue that we examined in this research is a multi-actor issue and that in this single case study, we only focused on researchers.

With the rise of data, many sectors have been implementing a form of automatising in recent times. This brings a lot of possibilities. As a matter of fact, an automated system is – unlike the human brain – not dependent on food nor sleep and less prone to errors. The efficiencies that could be gained by ‘working’ 24 hours, 7 days a week without a single moment of pause is enormous. An Artificial Intelligence system (hereinafter: AI system) could provide a relief for many sectors. In the literature, the application for an AI system within the judicial system has been advocated for. Nevertheless, the judicial system, especially regarding the rights of a suspect, needs many more considerations than the workload-relief argument alone. In this thesis, the possible implementation of AI – or a robot judge – within the Dutch judicial system will be explored. In this research, a special focus will be given to the rights of a suspect as set out in article 6 of the European Convention on Human Rights (hereinafter: ECHR). Article 6 ECHR provides the right of a fair trial to a suspect, where relevant, with the following provision: “In the determination of his civil rights and obligations or of any criminal charge against him, everyone is entitled to a fair and public hearing within a reasonable time by an independent and impartial tribunal established by law”. From clause 1 of article 6 ECHR, the following components can be extracted: a fair, independent and impartial tribunal. Implicitly, article 6 ECHR also provides the right to an explanation on how this tribunal reached to its verdict. In practice, this is also referred to as the right to transparent verdicts. With the use of the research question “to what extent can Artificial Intelligence be used in the Dutch courtroom while still maintaining the rights for the parties involved, especially as how has been set out in article 6 ECHR?”, an answer is formulated on the question whether the Dutch judicial system is ready for – and capable of – the next judge: a robot judge. This research uses a systematic literature review as a starting point. With such review, information is gathered from both technical as well as legal point of views to answer each sub-question individually. This research also specifically looks at the way other countries have implemented or created a form of an AI tool in and as court. Next to this, four interviews have been held with potential stakeholders as well as persons of interest. The reason why these interviews are held is to confirm and check what has been found from the literature assessment as well as to gain new (internal) insights on this topic. As an answer to this research question, an AI system can be implemented in the Dutch courtroom if it consists of two (main) components: a linguistic system and a machine learning system. Additional rules to use this robot judge are proposed as well, for example that continuous feedback-loops (of the probabilities for example) should be built in and that the system should be continuously monitored (and adjusted) for potential biases. The robot judge can both function as and in court. Additionally, a robot judge can sit at the table of the Dutch Council for the Judiciary and their ambitions to (further) litigate digitally and publish more, if not all, cases online.

In order to combat financially-economically related crime the government implemented a new directive ensuring that virtual currency exchanges now have to adhere to requirements from legislation countering money laundering. This thesis researches what the extent is of effects that this legislation posed to the daily operations of virtual currency exchanges.

Cybercrime thrives and online anonymous markets, or darknet markets, play an important role in the cybercriminal ecosystem. Vendors active on darknet markets invest in security mechanisms to compromise the availability or usefulness of evidence to Law Enforcement Agencies. Therefore, difficulties arise in linking identities or machines to cybercrimes facilitated by darknet markets. As a result, many cybercrime investigations are ineffective. This thesis consists of an exploratory case study based on the full administration of the Hansa Market. The Hansa Market (2015-2017) was infiltrated and eventually taken over and shut down by the Dutch Police. The data used in this thesis originates from the server that hosted the market and is made available by the Dutch National High Tech Crime Unit (NHTCU) and the Fiscal Information and Investigation Service (FIOD). This data is used to answer the research question: “Which factors influence the security behaviour of darknet market vendors active on Hansa Market?”. To answer this question, vendors that are similar regarding a) their experience, b) the activity on other markets, c) the amount of physical items sold, e.g. drugs and d) the amount of digital items sold, e.g. stolen credit card information, are clustered into five `vendor types' using Latent Profile Analysis. It is researched whether these clusters of vendors differ in terms of the following security behaviours observed: a) authentication related security practices (password strength, password uniqueness and two-factor authentication usage), b) encryption of communication, in the form of PGP-adoption and PGP-key strengths used, c) the linkability of a vendors' pseudonym through PGP-key matching and d) a vendors' choice of Online Financial Service Providers within the bitcoin ecosystem, measured by querying a service that provides contextual information on bitcoin transactions and addresses. The findings indicate that approximately causal relationships may be inferred between on the one hand vendor types, that represent a combination of business success in terms of physical and digital sales, experience and activity on other markets and on the other hand security behaviour. Vendors offering digital items tend to behave less securely than vendors selling large amounts of drugs. This thesis explains the observed (differences in) suboptimal security behaviours by arguing that vendors on Hansa Market conduct subjective risk assessments. This implies that the probability of being targeted by LEA and the value of the vendors' assets that are at stake (e.g. informational assets containing incriminating evidence or `years of freedom') are of influence on security behaviour. Lastly, recommendations to Law Enforcement Agencies include to exploit the subjectiveness in cybercriminals' risk assessments and to consider focusing on vendors transacting digital items. Academics are recommended to extend this research by investigating cybercriminal security behaviours through improved measurement methodologies in larger and more recent datasets.

The usage of Industry 4.0 technologies isgaining a lot of popularity in the context of manufacturing industries. Theyoffer improvements to the traditional manufacturing environment by offeringmore connectivity and integration in the business processes. Many companies aremoving towards these technologies to harness these improvements. Using Industry4.0 technologies improves performance, efficiency and even competitive advantage.Whereas, it is not known how it affects supply chain resilience-ability of thesupply chain to react to disruptive events and quickly regain performance. Thereis a chance that Industry 4.0 changes the competencies of an organisation andmakes it more vulnerable to disruptions. The objective of this research is to ascertainhow Industry 4.0 influences supply chain resilience and in what ways it can beused to improve the latter.For investigating this problem, aqualitative case study design was used. The usage of Industry 4.0 technologieswithin the chlor-alkali supply chain was analysed. Literature reviews ofIndustry 4.0 and supply chain resilience were conducted to gain a betterunderstanding. The usage of the following Industry 4.0 technologies was considered- Internet of Things, Cyber-Physical Systems, Cloud computing, EnterpriseResource Planning, and Big data analytics. Data were gathered throughsemi-structured interviews with two respondents. The study finds that Industry 4.0 has a limitedpositive influence on supply chain resilience when the disruption arises withinthe supply chain. But, when there is disruption arises outside the supplychain, it has no impact or sometimes a negative impact on supply chainresilience. Additionally, this study proposes three strategies that can be usedto implement Industry 4.0 to have a positive impact on resilience. They are themapping of critical processes, design and programming of the system, andvisibility enhancement within the supply chain. These strategies can be used by managerswhen they are evaluating the implementation of Industry 4.0 within theirorganisations and supply chains. This is a unique study that bridges theknowledge gap and assesses the influence of Industry 4.0 on supply chainresilience.  

The publicly funded ESA Copernicus and NASA Landsat earth observation programs are publishing their data as open data in the promise of 30 billion euro of financial benefit for the EU as well as 50.000 new jobs, both by 2023. The move by these two space agencies fits in a larger pattern of ‘new space’, in which the launch and exploitation of satellites are moved from national agencies to private commercial stakeholders. The data offered by ESA and NASA are published as open data intended for reuse with the objective to create viable value-adding earth observation services, i.e. services which use big and open earth observation as a resource for analytics and provide incentives for all participants, including the client and user, to continue the service provision. Furthermore, the earth observation data are big data, as it satisfies the criteria of high volume, variety and velocity increasing the effort required for handling the data. Even though the market for value-adding earth observation services is growing and has the potential to become the most important market in the whole earth observation value chain from rocket to service, the initial promises of the release of the data are not going to be accomplished at the current pace.

Within searched academic literature and during conversations with practitioners, the lack of a structured approach to creating these viable value-adding services has been observed. Furthermore, the research articles on this topic are very much technology-oriented, with only very few articles invoking the interests of stakeholders to make a service design viable. And none of these followed a method for creating the service. This thesis addresses the lack of such a method for the creation of viable services using big and open earth observation data as a resource. Specifically, four knowledge gaps are identified: The first and second knowledge gaps concerned the lack of viable services which used a structured method for their design in the academic literature of respectively the narrow focus area of big and open earth observation data as well as in the larger area of earth observations which includes the previous narrow focus area. The third knowledge gap concerns the lack of factors of big and open earth observation data which influence the viability of a service design within the searched academic literature and the fourth concerns the actual lack of a structured method to guide the design of viable services which use big and open earth observation data as a resource. Together, these knowledge gaps lead to the formulation of the following research objective: “to design a method targeted at service providers for the creation of viable services which use big and open earth observation data as a resource.” The artefact which is developed is a method which guides a service designer through the process of creating a viable service. Following the method results in creating a service design which is both feasible, i.e. technologically possible, and viable, i.e. provides sufficient incentives for all stakeholders involved to carry on its provision. The approach for structuring the creation of the method is the design science research approach for information systems. The demarcation of the problem is the first activity within this approach, and it uses a structured literature review as well unstructured explorative interviews. This is followed by a literature review on influencing factors, using only a structured literature review as a research method. The requirements gathering activity employs a case study method, in which participant-observations and interviews are used for information gathering within three cases. Then, creative methods are used in the design activity to create the artefact. For the following demonstration of the artefact, a case study is again used. Finally, for the evaluation of the artefact a survey based on the combined UTAUT-ECT theory and observations are used to evaluate whether the artefact attains its objectives, and improvements are suggested based on the evaluation and the demonstration. During this research, the author was a research intern at CGI Netherlands in the Space, Defence and Intelligence department, which allowed for rich observations and access to cases.

The result is the SIMEO-STOF method consisting of five phases. It combines the Service Innovation Method for Earth Observation (SIMEO) with the STOF model tailored for the earth observation domain. The first phase guides a designer through the process of finding together with a client a new service idea based on the current capabilities of earth observation analytics and the business processes of the client. Linking the earth observation capabilities to the limitations of current earth observation data supply allows for the rapid exclusion of unfeasible or unviable ideas. Any ideas that pass this initial set of limitations can proceed to the second phase. In this service domain, essential aspects of the value proposition are defined. This is followed by the technology phase, where principles of security and big data computing are set as well as a first architecture of the IT systems. Then, acquisition of external resources and inter-organizational relations are discussed in the organizational phase. Finally, the amount and form of value retained by the service provider are discussed in the financial phase. As a demonstration, the artefact is applied to the case of a crude and refined oil transhipment provider in the harbour of Rotterdam. The result of the application is a service design which is most likely to be viable, considering some issues still need resolving. Whilst not being definitively viable, the identification of issues which require resolution to achieve viability is an outcome which gets as close as possible to a viable design.

The artefact is evaluated for internal and external validity, respectively whether it fulfils the quality requirements and whether it fulfils its objective. Both were included in a survey held amongst employees of a service providing company interested in the use of the SIMEO-STOF method. Whilst the limited number of responses did not allow for any statistical analysis, the descriptive statistics and observations allowed for the concussion of a generally positive evaluation. Measured by the attitude towards using the SIMEO-STOF method, the method fulfils its objective of facilitating the creation of viable services which use big and open earth observation data as a resource. Whilst there is a mixed response to the quality requirements, observations indicate that part of these can be explained by different levels of expectation. Some participants thought of a future use for the artefact and judged the quality requirement based on this instead of the actual objective.

In terms of academic contributions, this research contributes to all four identified knowledge gaps. Foremost, it provides a viable service design method in form of the SIMEO-STOF method. This extends the service design literature to the application domain of earth observations, which has not previously been viewed from this perspective. Furthermore, factors of big and open earth observation data that contribute to the understanding of its effects on viable service design have been identified, in direct response to a further knowledge gap. Ultimately, the result of the SIMEO-STOF method demonstration is a viable service design created with a structured method, which is a contribution to the first and second knowledge gaps. In terms of societal contributions, the SIEMO-STOF method may accelerate growth in the ‘value-added EO services’ market, not only allowing service providers to more efficiently and effectively design viable service and create value, it may also lead to increased market growth on the suppliers side and an argument for open data publishers for the value of their activities. Though the use of the SIMEO-STOF method, EO service providers may be able to achieve the expected breakthrough of EO services within the broader society, which is one of the objectives of the ESA open data portal.

One of the principal limitations of this research comes from the choice of case study as the main research method, which limits the generality of the results. This is valid for the environment form which requirements are gathered, the type of data used and the design perspective of a service provider which is taken. The author suggests further research to include cases which cover aspects previously not included, for example, a business to consumer service, non-satellite earth observation data, and the inclusion of cases from different service providers. Another important limitation concerns the novel application of the UTAUT-ECT theory in a novel wats, including to an information system which is not a practical implementation of a technology but a method. Combined with the reduced number of respondents in the survey, the UTAUT-ECT-model adapted from theory for this research could not be tested statistically. Future research could focus on repeating the novel application of the theory with sufficient respondents to allow for validation of its application.

The objective of this research is the design of a method targeted at service providers for the creation of viable services which use big and open earth observation data as a resource. Considering the successful demonstration, and the generally positive evaluation of the SIMEO-STOF method, the author considers this objective to be attained.

This thesis is focused on benchmarking municipal sport policy. Physical activity is used by the Dutch government as a policy tool to create a healthy society. The Ministry of Health, Welfare and Sport stimulate people to adopt active life styles in order to combat the prosperity diseases: overweight, diabetes and depression. In benchmarking municipal sport policy there are the following complexities. Firstly complexities related to the governance of municipal sport policy, there are many actors involved with contradictory interests. In addition municipal sport policy is focussed within municipal boundaries and evolves on previously pursued policies. Secondly complexities related to benchmarking. Benchmarking is from origin a method developed for the industrial industry and now is also applied in the public sector, but the applicability of the method is contested. Moreover benchmarking is not straightforward and is dependent on its design, data reliability and the way of processing data.

An essential actor in sport policy are the municipalities: they conduct sport policy in order to heave healthy citizens and focus their policy to a large extent on sport facilities. Currently municipalities lack insight in whether the output of the sport policy (namely the quantity, type, and location of sport facilities) leads to the desired effects (namely healthy citizens), which we define as a lack of insight in the effectiveness of the sport policy. This insight is crucial for municipalities, since it can be used in the policy evaluation to assess the performance of their policy.

A method that has been proven useful for measuring and comparing of performance is benchmarking. Benchmarking is the research in which the output between organisations can be compared. However, there is a lack of literature describing how sport policy by municipalities can be compared, whereas comparison with other municipalities can provide additional insights and stimulate learning. In this study a benchmarking method for municipal sport policy aspects is developed and conducted.

The benchmarking method is designed based on a benchmarking literature review. Based on the review it was established that the design of the benchmarking method consists of phases, process steps and criteria. Subsequently with the literature review a benchmarking model is designed consisting of phases, steps, and criteria directed at assessing the performance of municipal sport policy. In the benchmarking criteria common elements are: the usage of indicators, transparency in performance measurement method and self-assessment of performance. In the benchmarking models common process steps are: set objectives, define indicators, select benchmark groups, collecting data, preparing data, analyzing data, determining significant different findings and reporting findings.

With the designed benchmarking model the benchmark is conducted, resulting in the following findings. The benchmarking results found no significant correlation between the dimensions, the output and the outcome of municipal sport policy. This study found that for benchmarking both the benchmarking design as the benchmarking process are crucial. Currently literature focuses on the design of the benchmarking method. This study found that the benchmarking process confronts challenges mainly related to data analytics.