Federated learning is a promising method of distributed machine learning that can allow industries such as aviation to utilize their data without actively sharing it, but has issues regarding cooperation if proper incentives are not utilized. This thesis explores the problem and builds from a previously designed FL Framework by designing an IT system that can be used to control FL Tasks and Rewards. Using an institutional analysis to set the playing field and based on previous work, an IT artefact consisting of a set of smart contracts on a private blockchain were designed and implemented as an MVP. These contracts perform the role of organising and controlling the participants within FL tasks and can be used to distribute rewards in the form of two types of Tokens: The Reward Token which also can be utilized for voting in proposals and reward distributing as a representation of ownership, and the Model Access Token, which can be used to represent Model access.

Executive Summary
Current Status The aviation industry is transitioning from traditional maintenance practices, typically scheduled after a specified number of flight hours, to more advanced, data-driven approaches. These predictive maintenance techniques leverage machine learning models to enhance the accuracy of assessments. These models can reduce the frequency of unscheduled maintenance and optimize inventory management. However, such models rely heavily on large datasets, which are challenging to compile in the aviation sector due to the rarity of specific operational incidents and the diverse types of data collected by different companies. When collaborating, a tradeoff arises between the level of security measures, trust in partners, and ensuring the system still functions. Federated Learning emerges as a promising solution to these challenges. Federated Learning is a novel form of machine learning that allows multiple entities to collaboratively develop a shared model while keeping their data localized, thus maintaining privacy and data sovereignty. Question The primary objective of this research is to identify and validate the critical architectural features necessary for the acceptance of Federated Learning in the aviation maintenance industry. Architectural features refer to design choices such as security protocols and governance frameworks. By focusing on these aspects, this study addresses the technical and collaborative challenges that must be overcome to develop a Federated Learning system for predictive maintenance in aviation. Resulting in the following research question:
‘What architectural features should be included in the design of the ‘Federated Learning for aircrafts’ predictive maintenance system’ to be accepted by the stakeholders in the aviation industry?’ Approach This study employs a Design Science Research methodology. The sub-questions for this research follow the steps in the Design Science Research methodology. This is not the case for the demonstration phase which was deemed not possible due to the conceptual nature of the design.
1.
What are the challenges in sharing maintenance data, and how do they impact data safety and collaboration? Through a literature review and interviews with stakeholders, the study identified concerns about data privacy, security, and competition. These challenges significantly limit data-sharing initiatives. (Problem Identification and Motivation)
2.
What specific technical requirements should the Federated Learning system have to address these challenges? Based on the interviews and thematic analysis, a list of requirements was developed. These include robust privacy mechanisms, transparent governance, ensuring model explainability, and clear accountability mechanisms. (Defining the Objectives for a Solution)
3.
What architectural features should be included in the Federated Learning design to meet these requirements? ArchiMate modeling was used to design a system incorporating these requirements. Federated Learning, combined with encryption techniques and a consortium-managed system, was the result. (Design and Development)
4.
How do stakeholders perceive the acceptability of the designed system? After the validation interviews and the expert session, three changes were implemented: Switching from
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differentiating on the model version to differentiating on the usages. Improving explainability
by switching to Trusted Executive Environments and removing differential privacy. Traditional contracts to increase trust towards each other were also added. (Evaluation)
5.
What lessons can be learned from the development and evaluation of the Federated Learning system for future improvements? The research highlights the importance of continuously building trust among stakeholders. Furthermore, the token-based reward system based on contribution is a good incentive to be adaptable and develop long-term collaboration. (Communication) Results
To build trust, this study employs traditional methods like legal contracts and appoints a consortium as a neutral party. Transparent governance and involving a neutral, trusted entity is necessary to gain stakeholder acceptance and ensure long-term collaboration. Blockchain technology enhances the transparency of the consortium's operations, ensuring all transactions and data exchanges are recorded on an immutable database...

This study investigates the potential of Self-Sovereign Identity (SSI) to empower individuals within Indonesia's health data ecosystem, particularly in the context of a Low- and Middle-Income Country (LMIC). The central concern is the loss of control that individuals face when their personal data becomes part of a broader health data ecosystem, utilized by various stakeholders like the government, healthcare facilities, and insurance companies. SSI, a decentralized and blockchain-enabled system, offers a solution by giving individuals control and ownership over their data, allowing them to decide how and to what extent their data is shared with third parties.

The research question focuses on how SSI functionalities should be designed to ensure the retention of personal data sovereignty (PDS) in an LMIC context. The study employs the Design Science Research (DSR) methodology, which includes the creation and evaluation of design artifacts to advance understanding in this domain. The research process involved developing SSI interface artifacts and testing them through a qualitative study with 15 Indonesian respondents, including individuals with socially stigmatized diseases like HIV/AIDS and TB. This population was chosen to ensure the study's inclusivity, given their heightened sensitivity to data privacy issues.

The study’s findings highlight the importance of data minimization and revocation functionalities in SSI systems. Data minimization allows users to share only the necessary information, while revocation gives them the ability to withdraw their consent for data sharing. These functionalities are crucial for fostering a sense of control, which is directly linked to a feeling of ownership over one's data. The study also revealed that a user’s digital literacy and affinity with data sharing significantly affect their perception of SSI functionalities. Users with a higher understanding of data implications tend to prefer more complex interfaces that encourage careful decision-making, whereas those with limited knowledge are more comfortable with simpler interfaces.

Additionally, the study underscores the importance of trust and contractual agreements as foundational elements in a user's willingness to participate in a data ecosystem. Without these, users may be hesitant to share their data, regardless of the control mechanisms in place.

This research contributes to the growing body of knowledge on SSI, particularly in the context of an LMIC like Indonesia. By taking a user-centric approach, the study explores the link between SSI functionalities and personal data sovereignty, providing insights that are currently underrepresented in existing literature. The inclusion of vulnerable populations further enriches the study’s findings, offering a comprehensive understanding of how SSI can enhance participation in the health data ecosystem while safeguarding personal data sovereignty.

Future research should aim to broaden the respondent pool to include more diverse socio-economic backgrounds, which would improve the generalizability of the findings. Additionally, further refinement of the SSI design artifact, informed by user feedback, is recommended to enhance its usability and effectiveness. Exploring the study's hypotheses through a quantitative approach could also provide deeper insights into the relationship between digital literacy, data sharing affinity, and personal data sovereignty.

A design study was performed that investigated the feasibility of a business concept combining a unified supply chain with automated vending points in the floriculture sector. In such a business, a direct link between production (growers of flowers) and customers exists. The added value along the chain can then remain with the growers. This could provide a method for the sector to meet challenges facing them.
This study targeted the development of both a design for the physical operations in the supply chain as well as the digital system providing the coordination required for the operations in the unified chain. A systematic approach was followed to arrive at multiple design alternatives.
The physical designs were created by converting a functional design into design options on a morphological chart. The morphological chart was reviewed using SCOR performance score cards, and design alternatives were drafted from the remaining well-scoring options on the morphological chart. They were converted into a level 2 SCOR mapping. Based on the physical designs, digital designs were created using enterprise architecture modelling in Archi.
The resulting design alternatives were rated using a multiple-criteria decision analysis, by comparing them to a list of requirements and constraints, and with SWOT analyses. Based on this, a best alternative was concluded to be feasible to implement. The design alternatives were demonstrated in capability by simulating the flower journey and they were evaluated on feasibility in a workshop with clients.
The conclusion that a business concept with a unified supply chain and automated vending points could be viable to implement in the floriculture sector means that further development of the designs into practical realisation is possible for actors in the sector. Comparable industries can also take the study as an indication of possibilities in their sector when combining a data-driven approach with centralized supply chain coordination.

Privacy-enhancing technologies (PETs) have historically been used for safeguarding individual privacy from both public and private interference. But lately, tech companies have started using PETs as one instrument for the expansion of their power over different actors, as appears to be unfolding in the case of Amazon’s Sidewalk service: a United States-only privacy-preserving crowdsourced service that promises connectivity to Internet of Things (IoT) devices manufactured by third parties in smart-home, logistics, and utilities use-cases. Compatible IoT devices (‘endpoints’) are granted connectivity by ‘gateways’, namely smart-home devices from Amazon’s Echo (smart speakers) and Ring (smart cameras and doorbells) series that donate a portion of their bandwidth to endpoints that might be owned by others. Amazon pushed a software update to these Echo and Ring devices, that turned them from smart-home devices to contributors to the Sidewalk network, unless users actively opted out, yielding a coverage of at least 90% of the US population. With Sidewalk, Amazon leverages PETs (namely end-to-end encryption and device identifier obfuscation) to mitigate privacy concerns that the crowdsourced architecture yields. However, this necessitates significant investments from third-party manufacturers to make their devices Sidewalk-compatible, suggesting a power emergence shaped by PETs.

I answered the research question “How does Amazon’s use of privacy-enhancing technologies in Sidewalk affect its power over IoT manufacturers?” by reviewing grey literature, analysing the Sidewalk technology, and elite interviewing with high-ranking employees of Sidewalk-adopting manufacturers. I have shown that Amazon leveraged PETs to mitigate public security concerns, but in the meantime reshapes how manufacturers produce their devices. Part of this ploy is cementing AWS in their production processes. Amazon also uses this leverage to mobilise manufacturers’ and silicon providers’ resources to improve Sidewalk’s public reception, technology, and governance.

These reconfigurations are expensive and complicated to realise, but manufacturers stressed the importance of Sidewalk adoption to leverage Amazon’s reputation vis-à-vis suppliers and customers, and “befriend the giant” for they rely on Amazon’s Marketplace, cloud, and logistics.

Meanwhile, Amazon’s reductionist framing of privacy and security as protecting user identity and data confidentiality, means that confidentiality of manufacturers’ business-sensitive information is not discussed. With this vantage point, Amazon can learn which endpoint types are popular and how they work; but Sidewalk might also be a vehicle for Amazon to attract more IoT developers to AWS.

In sum, I have demonstrated that strictly pursuing user privacy (or confidentiality) in digital services may have unforeseen effects on production. Therefore, I call upon privacy and competition scholars, advocates, and regulators to question how privacy protection actually augments companies’ power, and stepping away from their narrow “consumer harm” lenses. These actors should debate a right to personal control over devices. A mere consumer focus in studying these developments is insufficient: I established that business-to-business relations and businesses’ production processes are more significantly affected than consumers. The production focus of this work lays bare the novel power dynamics between Amazon and manufacturers, shaped by PETs.

Dutch road transportation networks are increasingly facing challenges regarding congestion, safety and environmental pollution. These challenges are intensified by increased urbanization and a growing need for connectivity . In the past, the remedy to most of these challenges laid in expanding the physical infrastructure through new asphalt. Nowadays, information and communication technologies increasingly play a role in infrastructure management by utilizing the available infrastructure more efficiently. With that, Cooperative Intelligent Transport Systems (C-ITS), presents a new beacon of hope. Through C-ITS, vehicles and infrastructure components are connected to realize a safe and efficient flow of traffic. However, the realization and implementation of C-ITS is hindered by legal, technological, economic and organizational challenges that need resolving. One of the main challenges is the absence of a sufficing robust network infrastructure that facilitates the data transmission across devices and road users. Mobile Network Operators (MNOs), are believed to occupy a central role in the future, designing, building and operating these network infrastructures. However, MNOs are already facing challenges in making current 5G network business models profitable. New large investments already loom for MNOs to serve C-ITS, however, without profitable business models, further investments can be pushed to the future which can cause further delay of the deployment of C-ITS. Therefore this thesis aimed to identify conditions and potential forms of collaboration among Dutch MNOs for C-ITS ready networks. A literature review identified potential collaborative forms between private competing companies and provided an initial overview of conditions that can stimulate collaboration. Subsequent interview with stakeholders from the Dutch mobile network operator domain further refined these conditions and identified potential forms of collaboration that potentially can deliver viable collaborative efforts: knowledge sharing, joint R&D and passive network sharing. The research indicated that the creation of a shared vision across both the public and private domain is crucial to get an institutional environment that supports collaboration. On top of that, a sense of ‘needing each other’ needs to emerge between MNO’s in the form of individually unattainable profits. Although, regulation can also act as a pushing mechanism towards collaboration, it can’t force the creation of such networks. The realization of profitable business models is thus crucial for MNOs to build the networks. Further problems in collaboration come from severe distrust among MNOs who also have collaborative experiences which resulted in conflicts and opportunistic behavior. A public body can act as an independent ‘referee’ to mitigate these potential conflicts in future collaborative efforts. With that, a lot of challenges still need to be overcome to realize collaboration between MNOs which makes that collaborative efforts are unlikely to succeed in the near future.

Introduction and Research Approach
In the current era, there is a prevailing trend of improper dietary intake and a growing trend of social media usage. Given this growth in social media usage, the concern about misinformation, mainly health-related misinformation, is increasing. Social media plays an essential role in the prevalence and impact of health-related misinformation. More specifically, the concern of nutritional supplement misinformation and its effect on adolescents and young adults is growing and under-researched. Adolescents and young adults have unknown preferences, and current policies fail to address the problems associated with nutritional supplement misinformation. Understanding the specific preferences of adolescents and young adults and the socio-technical system is crucial to address the issue. Therefore, as the Dutch context has not been researched, this research explicitly addresses the problem of nutritional supplement misinformation among Dutch adolescents and young adults and aims to improve public health outcomes. This thesis aims to develop interventions and design requirements within the system of nutritional supplements, social media, and public health outcomes to maximize public health. The research deploys the Value-Sensitive Design (VSD) framework to address the issue.

Results
To fully address the socio-technical system, structured literature reviews were conducted to assess the influences in the system and investigate the institutional environment. The comprehensive, structured analysis of the literature and the assessment of the institutional environment pointed out the complex nature of the system and its associated stakeholders, where social media algorithms also play a significant role. Interviews and a focus group identified the values, risks, value tensions, and possible interventions at stake in the system. This extensive value analysis identified the main values to design for. In designing, the value of public health is paramount.

Based on the identified values to design, constructing value hierarchies led to the design requirements. By including the stakeholder values, the interventions are theoretically sound. The most promising interventions identified in this thesis are certificating influencers, counter campaigns, educational campaigns, and an automated enforcement tool. This research sees all four interventions as suitable interventions to implement, where the extension to the certification of influencers and the counter campaigns are most suitable to deploy first. The research mainly showed the need for prevention interventions to boost awareness and consumer education concerning health and social media.

Contributions
This research has shown that VSD can aid design in addressing a societal and policy issue, where VSD originally stems from technology design (Friedman et al., 2006). In addition, this thesis provides grounded interventions to offer novel perspectives in addressing nutritional supplement misinformation. Furthermore, the policies implied by the study are within the context of the Netherlands but could also be considered internationally. This thesis can also fuel the broader problem of health misinformation and other problems with nutritional supplements, as well as the discussion of the responsibility of social media platforms and other industrial stakeholders within the identified socio-technical system.

Circular Economy (CE) aims to achieve sustainability through recycling, refurbishing, reusing, and other similar activities. Even though the concept of CE has gained considerable interest throughout the previous years and yielded significant research contributions, many critics stress the lack of incorporating ethical and social considerations into CE. This thesis researches how to facilitate such embedding of socio-ethical aspects into CE through the support of the Responsible Research and Innovation (RRI) methodology. Thus, this thesis addresses the main research question “How can the RRI methodology complement the CE framework to assess ethical, legal, and social aspects (ELSA)?”. Within this study, a conceptual framework was developed that allows for embedding socio-ethical aspects in terms of assessing ELSA (aspects) that are seen as design points contributing to a socio-ethical responsible and just CE. This framework contains substantial elements of RRI, including its four dimensions (Inclusion, Anticipation, Reflexivity, Responsiveness) suggested by Stilgoe et al. (2013). Furthermore, the conceptual framework is inspired by a draft framework of Purvis et al. (2023) for a responsible CE, claiming their framework as a starting point and suggesting future recommendations for its further refinement. The conceptual framework developed in this thesis allows for an inclusive assessment procedure of (bounded) CE systems by addressing its various components and all involved stakeholders by actively communicating with them. The system’s components, such as of technical or organizational nature, must be thoroughly assessed to recognize potential ELSA risks/impacts that can harm a responsible CE. Defining appropriate design points serve to mitigate such risks.

In order to test and evaluate the conceptualized framework, it got applied to a case study. The Horizon Europe granted project ALICIA represents the case study environment. ALICIA intends to establish a CE for industrial automotive manufacturing equipment (machinery and robots) within Europe. Since circularity for industrial automotive manufacturing equipment constitutes, especially on this scale, an under-researched field, this research also investigates such an automotive CE approach. Through the framework’s demonstration, significant findings could be obtained. First, even though the framework manifested as effective due to the achieved insights, which are subsequently further expressed, future recommendations for further development regarding the framework's recognized limitations are suggested. Another crucial insight the case study provided emphasizes the major challenges that exist in realizing a CE for automotive production equipment. Those challenges were identified by assessing the ELSA risks of ALICIA and the design points to mitigate such. To realize equipment circularity, detailed data must be shared by companies that often contain sensitive corporational information. Originating from the automotive industry’s competitiveness, such data exchange is hard to realize as it can jeopardize companies’ privacy. To overcome this, it requires collaboration between the companies and clearly defined data-sharing policies to enable such data exchange. Such ideal data exchange should ensure that still, sufficient data is shared to realize equipment circularity but simultaneously does not infringe a corporation’s privacy which could harm their market position by disclosing it to competitors.

Additionally, since the automotive industry is a profit-driven one, socio-ethical dimensions must also be incorporated into such equipment CE from the beginning. Compared to the electric mobility transition, which is another sustainability endeavor of the automotive industry, socio-ethical dilemmas that refer to unethical origins of certain parts (e.g., lithium batteries), such as child labor or farm desiccation, are prevalent. To prevent such or similar dilemmas within the sustainability agenda of an automotive CE, it requires the embedding of socio-ethical considerations that were detected throughout the case study. These considerations contain to ensure, inter alia, an ethical origin of parts used for equipment refurbishment. Otherwise, if these socio-ethical issues are neglected from the start, potential drawbacks might be difficult to remedy during an already ongoing CE implementation. These both outlined challenges with their socio-ethical considerations must be more precisely addressed in the future by relevant experts.

Thus, this research's key findings cannot only be seen as beneficial for the methodology of assessing socio-ethical considerations in CE from the context of RRI but also for the circularity of automotive production equipment. Both results constitute fundamental groundwork for further recommended research in these lacking research fields.

Incorporating big data into decision-making provides a substantial competitive advantage, leading organisations to increasingly adopt a data-driven strategy. However, the adoption by organisations often remains unsuccessful due to limitations associated with monolithic data architectures, such as data lakes and data warehouses. Data mesh is introduced as a decentralised socio-technical approach to alternatively manage data, aiming to overcome the limitations and gain the benefits of embracing a data-driven strategy. However, there is a lack of guidance on how to implement data mesh. The availability of generic and concrete data mesh implementation steps, including a maturity assessment, would be helpful for organisations. Consequently, this research proposes the design of a Data Mesh Maturity Assessment Model (DMMAM). In response to the main research question: ”How to assess the maturity of a data mesh implementation within an organisation?”, enabling the assessment of how mature a data mesh implementation is, by means of the DMMAM, would provide the guidance that is currently lacking for organisations. The qualitative Design Science Research Methodology is employed to structure the design process. Literature research, interviews, and cases are conducted to explore the contribution of, as well as design, demonstrate, and evaluate the DMMAM.

This research shows that the developed DMMAM evaluates data mesh based on four maturity levels, classified as Level 0: Non-Initiated, Level 1: Conceptual, Level 2: Defined, and Level 3: Achieved, and that data mesh is represented by five dimensions: A. Data Foundation & Organisational Change, B. Domain Oriented Decentralised Data Ownership & Architecture, C. Data as a Product, D. Self-Serve Data Infrastructure as a Platform, and E. Federated Computational Governance. These five dimensions are collectively represented by 54 characteristics. For each characteristic, labels for the People, Process, Technology (PPT) perspectives are assigned. Additionally, questions are formulated, and criteria and requirements are provided for all characteristics at each maturity level. This enables participants to self-assess their organisation’s maturity by individually rating 54 questions based on the current and target levels. Conducting the self-assessment yields various outcomes, including an overall data mesh maturity score, individual dimensional maturity scores, and maturity scores from PPT-perspectives. Moreover, the assessment helps to identify maturity gaps and allows benchmarking to compare results across organisations, providing organisations with guidance for improvement. The demonstration and evaluation of the DMMAM through maturity assessments for three organisations have demonstrated its applicability and usefulness. However, it is important to acknowledge that this research represents the first attempt to provide a comprehensive framework for assessing data mesh maturity in organisations and is not without limitations.

Future research is proposed to further refine and improve the DMMAM, supported by data mesh SME’s and practitioners, to ensure that the model remains up-to-date with the latest available research on data mesh. In addition, including additional guidance as an outcome of the maturity assessment would make the assessment more actionable and pragmatic. Furthermore, examining the optimal assessment structure will enhance the model’s reliability and validity. Moreover, expanding the benchmark functionality will enable statistical generalisations and comparisons for organisations within and across industries. At last, it is suggested to do further research about examining the overall contribution of data mesh as a strategy element towards becoming data-driven.

In this research, I delved into the dynamic role of TikTok in shaping democratic practices, with a particular focus on its effects on informed decision-making and activism. The rapid increase in social media usage has dramatically reshaped our lives, bringing several benefits but also significant concerns, especially regarding information spread and its influence on democratic processes. To explore the mechanisms of information dissemination on TikTok and its impacts on democratic practices, I conducted an extensive literature search and performed interviews with experts in the field. The findings present a nuanced landscape where TikTok both empowers and challenges democratic practices.

I discovered that TikTok's unique features like algorithm-driven content discovery and short- form video format create a space for users to voice diverse perspectives, raise awareness, and mobilize for social change. This leads to the democratization of discourse and gives voice to individuals who might have been marginalized or overlooked, particularly in the realm of activism. However, I also identified significant challenges, including the spread of misinformation, algorithmic biases, the creation of echo chambers, manipulation by malicious entities, and many more. These issues pose substantial threats to democratic values and processes, undermining trust in reliable sources and obstructing informed decision-making.

Drawing from these findings, I designed strategies to enhance the informed and ethical usage of TikTok. However, implementing these strategies demands a collective effort from a variety of stakeholders, including TikTok as a platform, its users, regulatory bodies, and wider society. A critical challenge is balancing promoting democratic values and maintaining a user-friendly, engaging environment. Implementing all the suggested strategies may not be feasible due to the platform's profitable objectives and complexity. Therefore, I recommend prioritizing the most critical and impactful measures and committing to continuous research, monitoring, and adaptation in response to the ever-changing social media landscape.

Furthermore, I highlight that the responsibility for fostering a responsible information ecosystem extends beyond TikTok. It calls for collaboration among social media platforms, regulatory bodies, educational institutions, and society at large. With concerted effort, we can envision a future where platforms like TikTok serve as spaces for entertainment, and relaxation, as well as catalysts for positive societal change, informed civic engagement, and potent activism.

As the social media landscape continues to evolve rapidly, further research into this domain is essential. We need to keep exploring and understanding the interaction between technology, legislation, and democratic processes to effectively navigate the challenges and opportunities presented by platforms like TikTok.

This thesis studies companies which developed open source software but adopted cloud protection licenses, a novel type of software licenses which protect their business from competitors but potentially affect their open source communities. It addresses the practical problem of executives of the companies who miss information about the effects of the license change on the health of their community. From a scientific perspective, there is no existing research about cloud protection licenses. The thesis presents the required background information, including software licenses and commercial open source software. It considers community activity and community structure as indicators of community health and presents corresponding research. Five propositions about the impact of the license change are presented and examined using data from projects of MongoDB, Elasticsearch and Redis by creating visualizations using CHAOSS and Python scripts. First, we expect that changing the licensing terms from an open source license to a cloud protection license leads to reduced community activity. We evaluated both major types of community activity, technical activity and social activity, and could not find support for the proposition but contradicting developments in all projects. Second, we expect less individuals joining the community. Here, the decomposed time series data indicates contradicting developments in the projects of MongoDB and Redis. Third, we expect more community members leaving the community. When assessing this proposition, we found that the decomposed time series data is congruent with the proposition in the project of MongoDB. However, the data of the projects of Elasticsearch and Redis indicates no support for it. Fourth, we expect increased knowledge concentration among individuals in the community. To evaluate the knowledge concentration among community members, the onion model is applied which associates each member with a role for each quarter. The development of the shares of the onion roles within the community is analyzed, and the results contradict the proposition. Fifth, we expect increased knowledge concentration considering organizations in the community. To examine the last proposition, the proportion of contributions authored by employees of the respective company is determined for each month and the development evaluated. There is no contradicting evidence in the data and the developments in the projects are congruent with the proposition. In summary, the data indicates that the impact of a license change to a cloud protection license on community health is rather small and constrained to the concentration of knowledge in respect to organizations. Therefore, we can recommend executives to adopt a cloud protection license if it addresses the strategic needs of their companies. This thesis continued the research on the impact of choice and change of software licenses on open source communities by including cloud protection licenses and previously disregarded aspects of community structure. It relates to the Management of Technology study program by taking the perspective of companies to analyze the effects of their strategic choices on their open innovation processes. By studying the effects of a license change, it examines a problem that is located at the intersection of technology, organizations, and strategy.

The dynamic nature of the market with constant technological developments continuously changes expectations from users over time. This drives businesses to alter their product and service offerings to maintain a competitive advantage, stable growth and, high customer satisfaction. Since economic goals drive businesses, it is often assumed that abundance of choice options is better, and will eventually result in increased profitability for the business. However, this is not necessarily the case. Consumers may experience a subjective state of mind termed as “choice overload” when presented with a plenitude of choice options. Consequently, consumers may fall victim to indecision, reduced customer satisfaction, and increased regret, to name a few. Previous research has formulated a cohesive understanding of choice overload in consumer decision making. Extant research in the field of consumer behaviour has identified several antecedents and concomitants of choice overload experienced by consumers. A vast bulk of research has also discovered repugnant effects of choice overload, due to context-dependency and other intrinsic and extrinsic factors influencing the choice overload effect. As a result, the questions of when and whether large assortments are detrimental to consumers remains open. This, offers an opportunity to extend the literature in this field by considering different contextual factors and variables that were thus far overlooked. The present study specifically aims to reduce the research gap that exists between Human-Computer Interaction (HCI) by understanding the choice overload effect, within the domain of e-tourism. Apprehension of the choice environment and consumer purchase behaviour is essential to close this existing gap and increase customer satisfaction. In this study, choice complexity is considered as an antecedent of choice overload. Choice complexity encapsulates two structural factors of the choice set – number of alternatives and number of attributes/levels. These factors allow for the construction of a measurement variable for choice complexity (entropy) where high entropy translates to high choice complexity. Moreover, individual differences in maximizing behavioural tendency (in terms of strategy and goal) are investigated. When consumers score high on maximizing tendency strategy, they optimize choice through employing a strategy of extensive information search. Similarly, when consumers score high on maximizing tendency goals, they strive to obtain the best possible choice from the available alternatives. Post-choice satisfaction is defined as the post-decision evaluation of the choice selected by the consumer. Specifically measured on two constructs - general satisfaction and outcome satisfaction. General satisfaction measures satisfaction of the consumer related to the process of arriving at a decision. Whereas, outcome satisfaction measures satisfaction related to the certainty in the choice decision. A choice experiment practically assessed the relationship between choice complexity and post-choice satisfaction, moderated by consumer purchase behaviour. The experimental design consisted of a Low Complex (LC) choice set and a High Complex (HC) choice set (distinguished based on entropy measurements) that allowed for the measurement and comparison of perceived complexity in a complicated choice environment. Respondents conducted a post-choice questionnaire designed to assess post-choice satisfaction and perceived choice complexity. Consumer purchase behaviour was assessed in a different section of the survey based on two different scales - maximizing tendency strategy and maximizing tendency goal. Statistical analysis was conducted on the obtained data to find the relationship between the variables under study. The experiment established the existence of choice complexity in e-tourism. Results showed an inverse relationship between choice complexity and post-choice satisfaction indicating that respondents were less satisfied with their choice when presented with a choice set of high choice complexity. Moreover, maximizing tendency strategy negatively influenced this relationship. Maximizers (i.e., respondents who scored high on the scale assessing maximizing behavioural tendency for strategy), extensively search through alternatives, eventually to formulate trade-offs and comparisons between the alternatives presented. Such maximizers were less satisfied with their choice having gone through a choice set of high complexity as compared to a choice set of low complexity. No such effects were found for the scale, maximizing tendency goals. The detriments of offering too much choice are real. Businesses within service industries such as e-tourism are therefore recommended to improve the quality/quantity of content due to intrinsic (i.e., intangibility, high monetary value, less purchase frequency) and extrinsic (i.e., a high number of alternatives and number of attributes/levels) factors. Each of these factors may make the service offering more complex for consumers to choose from. Managerial implications of the present study include the perspective (technology-centered view and human-centered view) that businesses can adopt. This perspective acknowledges the existence of choice complexity and maximizing tendencies, thereby optimizing the digitized environment towards better personalization. Doing this correctly would result in increased customer satisfaction due to better adaptation of digital environments by businesses to the needs and behaviours of consumers. The inclusion of entropy accurately provides the amount of information in bits; this measurement variable could be used by businesses to improve their algorithms. Finally, some companies in e-tourism have already begun to implement similar strategies, and reported in a significant increase in customer satisfaction, reservations, and overall sales. This gives evidence towards the practical importance of this study, and further emphasizes that businesses can indeed optimize their approach specifically towards the quality/quantity of content provided to consumers. In conclusion, the present study shows a negative relationship between choice complexity and post-choice satisfaction, with the inclusion of maximizing tendencies within the domain of e-tourism. Business may derive implications from this research to optimize their digital environments through increase in content personalization and reduction in choice complexity.

The main problem hampering innovation in the Internet of Things (IoT) is the fragmentation and lack of interoperability between IoT platforms. A possible solution for IoT platform sponsors to overcome this problem is to open up towards other platforms. To better understand how the IoT platform market is evolving and to inform future decisions regarding the desired degree of openness between IoT platforms, this thesis aimed to develop a theory on the openness between IoT platforms by identifying, prioritizing and theorizing the interrelations between factors driving the decisions from IoT platform owners related to the openness of their platform towards other IoT platforms. To this end, a preliminary theoretical framework was developed which was used as input for 13 semi-structured interviews with decision makers and field experts. It was found that openness between platforms is mostly driven by complementarities. Due to the cyber-physical nature of the IoT, the domain is characterised by a high need for specialisation and platforms are often developed from a product-centric, bottom-up approach. This results in a fragmented market in which there are strong complementarities between IoT platforms. It is found that these complementarities are the main factor driving the openness between IoT platforms.

Fuzzy front-end innovation (FFEI) is the most challenging and unmanageable stage of new product development. This is due to the uncertain and dynamic nature of product, market and consumer knowledge related to innovation. Value proposition creation (VPC) process is a part of FFEI. The scope of the research of this thesis is from VPC kick-off until finalisation of the concept. It involves opportunity exploration, generation, prioritisation, validation of ideas and concepts. Although VPC is being studied in academic and by organisations since decades still organisations are going through a high number of iteration and continual change of scope of VPC process before finalising the concept which is accepted by consumers. The acceptance of the concepts is checked qualitatively and quantitative with consumers. The main reason of the failure of the concept to gain consumer acceptance is the lack of structure of VPC process, lack of understanding of attributes of VPC, lack of understanding of tools and processes required to define the key attributes, and lack of understanding of influence of innovation on these attributes of value proposition (VP). Attributes of the value proposition can be defined as the consumer, market, product, process, and organisational characteristics of value proposition. Furthermore, innovation is considered as the newness to the organisation. Hence, the objective of this research is to prepare theoretical framework showing the relationship between attributes of VP and acceptance of the concept which can be used by managers as a step by step guide to design a sprint of VPC process based on the scope of innovation. Philips is selected for this research to understand the real-life cases which involve VPC process. The initial conceptual model was prepared from literature review and desk research at Philips which is validated through semi-structured interview. Final conceptual model, theoretical framework 1, and theoretical framework 2 are prepared from case study and interview result analysis. Final conceptual model shows the key attributes of VP which influence acceptance of the concept by consumers and their role (independent variable or moderators). These key attributes are unmet consumer need, superior offer, competitive price, involvement of consumer, involvement of multifunctional team, additional cost, emotional appeal and brand influence. Theoretical framework 1 showed step by step method to guide VPC process by identifying above-mentioned key attributes for inspiration (opportunity exploration), ideation, and implementation phase. It further showed the influence of scope of innovation (incremental or disruptive) on the relationship between VP and acceptance of the concept by consumer. Theoretical framework 2 identified the tools and processes essential to define the attributes of VP to generate high concept test score from consumers. This research contributed to academia and practice by identifying key attributes of VP, establishing relationship between attributes of VP and acceptance of the concept by consumers, providing structure to the VPC sprint, defining attributes essential for different innovation type, and identifying the tools and processes needed to define each key attribute of VP.

Edge computing can deliver substantial value to the general idea of the Internet of Things (IoT). However, there is a myriad of potential IoT applications for edge computing. Stakeholders are left with uncertainty about how the business potential of edge computing for these IoT applications can be identified. This research contributes in solving this, by designing a business model tool that can be used to identify the business model potential of edge computing for distinct IoT application areas, based on business model viability and feasibility. Through the Design Science Research Methodology (DSRM), the tool has been designed, demonstrated, and evaluated. Based on the STOF ontology, and supplemented by the theoretical domains of business ecosystems and platform theory, nine generic variables have been identified to explain business model viability and feasibility. These generic variables have in turn been contextualized towards the edge computing domain, in terms of 45 contextual input variables. This is the first research that unfolds these business model variables for edge computing.

This paper analyzes how specific aspects of design and governance of platform explain complementors participation in the video game console industry. This study introduces a new dimension to measure platform openness and suggest that by opening the platform vertically to different markets, platform firms can smoothen complementors competition and incentivize them to participate in their network. This study makes a first attempt to measure platform boundary resources and highlight its positive influence on complementors participation. Finally, the analysis also explores conditions under which signing an exclusive contract is beneficial for complementors. Complementors tend to participate in exclusive contracts during the early stages of platform rather than mature stages due to intense competition among complementors in the latter stage. The results suggest that by following the correct design and governance strategies, platform firms can orchestrate a large network of complementors and proliferate a variety of complementary product offerings.

Context: SMEs make up the major share of the manufacturing and trading industry in Hong Kong. Recently, the industry is faced with growing environmental uncertainty that may result in new challenges, consequently giving rise to a different set of needs concerning B2B relationships. These needs may present opportunities for alternative B2B platforms to further reduce friction in SME trade. Therefore, from the perspective of platform providers, it is valuable to assess what factors drive SMEs likeliness of using alternative platforms. Objective: This study extends existing research on IT switching behaviour by linking it to organisational innovation theory. According to extant literature, environmental uncertainty may lead to increased innovativeness and adaptability in organisations. The aim is to assess how perceived environmental uncertainty affects the propensity to switch in the context of B2B platform technologies. Method: A research model was developed by adapting the Push-pull -mooring model. It was extended with context-specific antecedents. The model was empirically tested with PLS-SEM using 68 responses from a survey with managers of Hong Kong SMEs. Results: We find that switching propensity is directly predicted by pull (attractiveness of alternatives), push (satisfaction with incumbent) and mooring (perceived switching cost) factors. Further, perceived network size is found to influence switching propensity mediated by satisfaction. Environmental uncertainty is found to positively affect the attractiveness of alternatives and top management innovativeness. Conclusion: The results have several managerial implications. Since attractiveness of alternatives was found to have the largest effect, managers may be advised to focus on differentiating their offerings from incumbent products. Further, the results suggest that within-group effects play a role for platform switching. More research is needed to further explore this hypothesis.

Understanding target selection is a step before making a suitable proactive measure to address the complex issue of banking malware in online banking landscape. Despite several previous studies, gaps in the research of target selection are still present like the lack of attention to the non-targeted entities, the presence of other potential factors and the change in the landscape itself. Seeking to address the gaps, this research is conducted to find out what characteristics related to online banking services can affect the likelihood of the malware attack to them. The research starts with literature review to identify characteristics which can potentially explain the target selection, in accordance to aspects of Routine Activity Theory (RAT). Next, data about malware attack and the list of banks as well as several external data like language and authentication factor of online banking were collected and processed for quantitative analysis. Several metrics to approach the actual attack count were proposed and other metrics were extracted from the data. Some interesting findings were captured, like, within the period February 2014 – November 2017, from 5,039 banks in the EU, 1,188 banks were without any online banking services and from 3,851 banks with an online banking service, 1,802 banks were found targeted and 2,049 not targeted. Some malware variants were also seen performing targeted attacks. Meanwhile, it is found from explanatory analysis that some characteristics maintain their significance in explaining the likelihood of attack, like the presence of English and two-factor authentication. Services offering English language were seen to be more attacked. Contrarily, services which implemented 2-factor authentication were found to receive fewer attacks, although more entities with such authentication were targeted. Meanwhile, some other variables were getting less significant when more controlling factors are taken into account, indicating that some variables were relatively more or less important than others. Future work is needed in order to enhance the model so that more plausible conclusion can be obtained, such as improving and adding more data as well as including more factors, especially those that are financial and market related.

Today’s market environment is characterized by increasing competition. This competition forces incumbents to innovate if they want to sustain their competitive advantage. Large enterprises start to adopt methodologies pioneered within the startup world, like the lean startup methodology, the innovate. The adoption of this methodology has proven to be difficult, and incumbents face a lack of control with regards to these ventures.

The practical objective of this thesis is to enable large enterprises to control and steer internal lean ventures (ventures following the lean startup methodology) effectively. The theoretical objective is to bridge the knowledge gap concerning the understanding of internal venturing and the application of the lean startup methodology in large enterprises.

To reach the objective, a case study within a large enterprise was conducted to answer the research question and reach the research objective. 16 in-depth interviews with relevant stakeholders were conducted to collect data. Finally, the results were validated through relevant literature and by comparison to the results of six additional interviews, conducted with two other large enterprises.

The study found that two elements influence the success of the venturing process: First, the implementation of the venturing process itself (Section 5.1). Especially the alignment and coordination of different stakeholders as well as the quality of the employed metrics. Secondly, a set of additional factors arising from the context in which the process is embedded (Section 5.2). This context is made up of the mindset and culture of the company, the organizational environment as well as the quality of its adoption of the lean startup methodology. The analysis of resulted in the identification of the five recommendations to improve internal lean venturing within large enterprises. Details can be found in Section 5.4.

In conclusion, implementing the lean startup methodology can help navigate this uncertainty surrounding innovation. This implementation requires reliable metrics, company-wide alignment, and the commitment to the methodology. Additional to the implementation, company and industry specific factors mediate the success of a venturing initiative. Large enterprises are advised to take an honest self-assessment and follow a searching and learning approach to iteratively and successfully optimize their process for maximal venturing success.

Many Internet of Things (IoT) devices that are currently on the market lack security and therefore many of them got infected with malware to launch powerful distributed denial of service (DDoS) attacks. Notifications from Internet Service Providers (ISPs) to their customers play a crucial role in the fight to clean up the malware infected IoT devices. It is, however, difficult for the employees of abuse departments to explain how to cleanup an IoT malware infection to a non-technical customer and provide usable action steps to clean up the infection. In particular, because there is no “one size fits all” cleanup solution, due to the heterogeneous nature of the IoT devices. The abuse department of the Dutch ISP KPN would like to know how to notify customers with IoT malware infections and how to explain the cleanup of infected IoT devices to the customers. Therefore, the objective of this research is to make a recommendation to KPN on what notification mechanism to adopt by providing insight into: (1) how to increase the effectiveness of IoT malware notifications from an ISP to its customers in terms of IoT malware cleanup; and (2) how users perceive an IoT malware notification from their ISP. To this end, an experiment has been conducted with 190 retail customers with infected IoT devices to measure the difference in cleanup among IoT malware notifications sent via different channels and with different messages. To explore the reactions of the customers to the different notification mechanisms, telephone interviews have been conducted and the communication logs between KPN and the customers in the experiment have been analysed. We have compared the influence of the notification channel on cleanup and the reactions of customers by comparing customers that received: (1) email notifications; and (2) a combination of walled garden and email notifications. The different notification messages that have been compared in this study include: (1) the walled garden notification content that KPN’s abuse department uses to notify its customers with an IoT malware infection; and (2) a newly composed more actionable walled garden notification message which clearly defines the steps that need to be taken while avoiding technical terms. It is found that a combination of a walled garden and email notification with an actionable content is the most effective in terms of IoT malware cleanup. Furthermore, the walled garden notification is most effective in getting customers to read and react to the IoT malware notification, yet it sometimes results in customers having a low satisfaction with the service they receive. The more actionable notification content results in better understanding and trust from the customer compared to a less actionable content of the notification. However, customers’ understanding of the notification content and the satisfaction with the quarantine event remain a challenge.