The roll-out of digital identity (ID) wallets presents a multi-sided adoption challenge within a complex regulatory and ecosystem landscape. While much attention has been given to technical architectures, less is known about how wallet providers can strategically drive adoption among users and relying parties (RPs). This study addresses the question: What adoption strategies can wallet providers use when introducing digital ID wallets?Digital ID wallets function as two-sided platforms, where user adoption and RP integration are interdependent. Neither side creates value independently, leading to a “chicken-and-egg” problem, further complicated by regulatory fragmentation and uncertain demand. The European Digital Identity Wallet (EUDIW) exemplifies efforts to establish large-scale, interoperable digital ID systems within a trusted regulatory framework.The research follows a three-stage design. First, a literature review on platform strategy, digital ID, e-government, and digital wallets identified initial strategy categories. Second, 18 semi-structured interviews with industry stakeholders were analysed using the Gioia methodology. Third, age verification (AV) was examined as a use case to test the framework under regulation-driven conditions.The study identifies five interdependent strategic domains that must be configured simultaneously to drive adoption. Institutional structuring focuses on navigating regulation, certification, and government involvement. Ecosystem orchestration emphasizes onboarding RPs, which is the primary driver of user exposure and must precede consumer-focused efforts. User enablement addresses adoption drivers, with convenience and usefulness outweighing privacy concerns in most cases. Incentive alignment concerns cost distribution, where free access for users requires RP-based monetization. Trust and legitimacy focus on credibility, where users prioritize ease of use, but RPs require strong compliance guarantees. A sixth domain, structural and market context, captures external factors such as regulatory fragmentation and cultural differences in trust.A key finding is that adoption depends on the coherent interaction of all domains rather than isolated strategies. Weaknesses in one area limit overall success, making adoption a coordination challenge rather than a single strategic decision.Applying the framework to age verification shows that while the structure holds, domain importance shifts. Regulation becomes the main driver, ecosystem activation is RP-dependent, and user adoption relies more on normalization. Incentives are limited due to low willingness to pay, making AV a regulation-driven entry point rather than a natural driver of broader adoption.For wallet providers, the framework highlights key priorities: securing regulatory alignment first, focusing on RP onboarding, offering free user access, selecting high-frequency use cases, and treating trust as an institutional requirement. For consultants, it provides a structured way to diagnose adoption barriers and align stakeholders.The study contributes to theory by framing adoption as a configurational and institutionally embedded process. It shows that regulation can actively drive adoption, that trust operates differently across stakeholders, and that incentive alignment is a structural mechanism shaping ecosystem participation. Overall, the framework offers both theoretical insights and practical guidance for implementing digital ID wallets. ... Read more

The emergence of 6G networks introduces novel use cases such as holographic communication and autonomous driving. To meet these ambitious requirements, 6G is expected to adopt decentralised architectures that enhance performance by bringing computation closer to the user. However, this shift also introduces new security challenges, as the increased distribution of network components makes it harder to detect threats, prevent unauthorised access, and respond effectively to vulnerabilities. In this context, Security-as-a-Service (SECaaS) presents a promising solution by allowing enterprises to outsource their security operations to specialised providers. Yet, while most existing research focuses on SECaaS within centralised cloud environments, little is known about how it must evolve to address the unique demands of decentralised 6G networks. This thesis investigates how network decentralisation influences value co-creation among SECaaS stakeholders and explores its impact on the antecedents of customer trust. Drawing on ten qualitative interviews with experts from the telecom, infrastructure, and security sectors, the study applies the Value Network Configuration framework and the Integrative Model of Organisational Trust.

Findings reveal that decentralised 6G networks enable more distributed value co-creation, potentially even independent of the Mobile Network Operator. However, these deployments require enhanced stakeholder coordination to ensure secure service delivery meets customer expectations. While decentralisation does not significantly alter the core antecedents of customer trust, it can indirectly enhance relational trust through greater proximity, customer intimacy and contextual understanding. The study outlines key responsibilities across four stakeholder groups, identifies emerging trust-related factors such as regulatory compliance and geopolitical influences, and offers strategic recommendations for firms developing viable SECaaS business models in next-generation mobile networks. ... Read more

Executive Summary

Situation
Dutch first-line healthcare still faces major problems with how its information systems work together. Many of these systems are outdated, don't follow the same standards, and can't easily share data with each other. This makes it difficult for doctors, pharmacists, and nurses to work with complete and up-to-date patient information. It also creates obstacles for third-party developers, like those building telehealth apps or digital tools, who need to connect to these systems to offer new services.

Even though most healthcare providers use digital tools, these tools don’t speak the same language. That means that when one provider enters data, another might not be able to read or use it properly. This lack of data interoperability slows down care, increases paperwork, and limits innovation.

To address these issues, this thesis introduces a modular platform architecture that follows shared rules and standards. The goal is to help different systems work together more smoothly and allow developers to build useful tools without having to create custom connections for each system. The platform uses common APIs and reusable services to exchange data in a secure and structured way, while staying in line with Dutch healthcare policies.

Research Question
This research focuses on the following main question:
How can a platform architecture be designed to enhance data interoperability in first-line healthcare, enabling seamless integration for third-party complementors to support healthcare practitioners?

The question comes from the need to reduce technical complexity and help third-party developers deliver value to healthcare professionals faster and more reliably.

Approach
To answer this question, a systems engineering approach was used. The research started with interviews, where one was completed with a general practitioner and one with an expert from a third-party healthcare IT company. These conversations revealed key issues, such as outdated systems, mismatched data meanings, and a lack of shared standards.

From these insights, a list of requirements was created to guide the platform’s design. Then, several UML diagrams were developed to model how different components of the platform should interact. Based on these models, a working prototype was built using Python (Flask). This included core services like data validation, transformation, and user authentication.

Finally, expert software architects reviewed the prototype. Their feedback confirmed that the design made sense and had potential for real-world use. They also highlighted areas that still need improvement, especially in terms of security and handling data meaningfully and correctly.

Results and Conclusions
The research confirmed that fragmentation, outdated technology, and poor standard usage are the main barriers to data sharing in Dutch first-line healthcare. To address this, a modular platform was developed and tested.

The prototype showed that using shared components for data transformation and validation makes it easier to connect systems. Two services, the DataTransformationModule and the ExternalSystemConnector were seen as essential for creating an interoperable data platform.

The proposed design uses a layered structure and modular services. This makes it scalable, flexible, and easier for external developers to integrate with. While the technical foundation is strong, more work is needed—especially on semantic interoperability (ensuring data has the same meaning everywhere), user access control, and real-life testing in clinics.

Contribution
This thesis adds to both academic knowledge and practical system development.

From a theoretical perspective, it applies platform thinking to healthcare IT, based on Tiwana’s core–periphery model. It also builds on Deshmukh’s layered model of interoperability by turning abstract ideas into working components where each deals with structure, meaning, or security in healthcare data.

On the practical side, it provides a working system design that others can build on. The prototype shows how developers can use reusable components, like data validation or transformation services, to save time and improve data quality. This approach can help reduce technical effort and improve care delivery by making systems more connected.

Recommendations
To make this platform usable in real healthcare environments, several improvements are needed. First, authentication should be upgraded from basic API keys to more secure methods like OAuth2 or federated identity systems. These changes will better protect patient data and support real-world compliance without making the system harder to use.

Second, semantic interoperability needs more attention. Although the platform handles structure and syntax well, it still lacks tools to make sure that medical data means the same thing across systems. Future versions should include support for terminology mapping and validation using Dutch coding systems like SNOMED CT, ICPC, and LOINC.

Third, flexibility should remain a core design principle. Some services, like conflict detection, may only be useful in specific cases and should be added as optional modules rather than built-in features. This keeps the platform adaptable for different types of healthcare organizations.

Next, the platform should be tested in live clinical environments. Real-world deployment would uncover workflow issues, performance bottlenecks, and user experience gaps that are not visible in lab tests. Feedback from actual users, namely: GPs, nurses and pharmacists, is vital to make the system both effective and usable.

Finally, as data standards evolve, the platform must stay up-to-date. Future versions should be able to work with new releases of HL7 FHIR and support multiple profiles. This ensures long-term compatibility and encourages broader adoption.

In summary, this research lays the groundwork for a modular, standards-based platform that makes healthcare data more interoperable. It supports both better patient care and more efficient innovation by reducing the technical barriers that developers and healthcare professionals currently face.
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Traditional financial companies play a central role in ensuring financial stability and reliability. However, these companies face institutional problems due to inefficiencies, lack of transparency and limited innovation. For this reason, the use of distributed ledger technology, or blockchain, has been explored as an alternative and its integration into traditional finance towards a 'hybrid' approach. The Dutch mortgage market was chosen as the focus of this research and is further analyzed due to its high transaction costs, including the high cost of trust. This led to the research objective of designing a Hybrid Mortgage Lending System (HMLS) that reduces the cost of trust.

A design science research methodology was used for this research where two interwoven artefacts were developed. The first artefact was a contextualized trust model based on three trustworthiness factors: integrity, ability and benevolence. The second artefact was a demonstration for the HMLS using a technological model.

The trust model was validated through expert interviews and enriched with additional information. Based on the feedback from the expert interviews, nine meta-requirements for the technological model were developed. The proposed solution for the design of the HMLS is to automatically distribute fractional ownership of mortgages via Non-Fungible Tokens (NFTs) through an ecosystem with the traditional finance company as originator and public investors as lenders. The ownership of the NFTs is transparently tracked via the blockchain to monitor the fractional ownership of a home. These NFTs exist in mixed token pools and are controlled by the traditional finance companies. These pools are supplemented with other digital assets to create different risk profiles to suit different types of investors. A demonstration of these token pools is shown, with an overview of the architecture explaining the mortgage application and transaction processes through the different layers. Finally, a stakeholder map is shown and their roles within the ecosystem are explained. The research provided new insights by making the second model dependent on the first. The findings highlight new challenges for further research, such as prototyping or improving the versatility of the model.
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Data-driven health research, specifically the development of AI models, is hampered by poor data availability and associated administrative burdens, caused complex and fragmented data protection regulation. To reap the benefits of using high quality health data, while safeguarding data protection of patients, the synthetic data generation is seen as a promising privacy-enhancing technology to avoid the need for personal data sharing. Although synthetic data is widely discussed, research primarily focuses on a technical development and evaluation of data protection, leaving substantive matters on the use of synthetic data within its institutional context open. By combining legal and technical knowledge, this thesis aimed to bridge this gap, by analysing how synthetic data generation could enable health data sharing for research in a privacy-enhancing manner. Specifically, a design science research approach is followed to combine the requirements from the institutional environment, focusing on a use case with a Dutch healthcare provider and research institute, with scientific knowledge on synthetic data generation and data protection evaluations. The research objective was to design a framework that structures the data protection-related factors that influence the extent to which synthetic health data enables secondary use of health data for research. The identified barriers and drivers of synthetic data generation focus on the health data sharing process, the interplay between the legal definition of anonymisation and technical data protection evaluations, as well as data protection principles. Synthetic data can enable secondary use of health data for research, but, measures should be implemented in the various phases of synthetic data sharing to safeguard patients’ data protection. As policy opportunity, this thesis argues for narrower definition of personal data to support privacy-enhancing technologies such as synthetic data generation. ... Read more

The prevalence of mental health issues among adolescents and young adults is increasing, with social media usage identified as a potential contributing factor. As technology becomes more integral to daily life, the design decisions of social media platforms emerge as significant determinants of users' mental well-being.
Despite awareness of social media's general adverse effects, there is a gap in understanding the specific impact of different design features. Academic literature identifies features like likes and direct messaging as having nuanced effects on mental well-being, but lacks a comprehensive overview for developers to reference. This thesis seeks to bridge this gap, focusing on design features and their psychological impacts to propose design interventions for enhancing mental well-being.
Employing Value Sensitive Design (VSD) as an analytical framework, this study is the first to apply VSD to social media in the context of mental well-being. It involves a tripartite methodology — conceptual, empirical, and technical investigations — to identify significant design features and values related to mental well-being on social media platforms. A novel social media platform, Dime, designed with mental well-being in mind, serves as a case study for evaluating these features and proposing design requirements.
The study identifies 8 key design features affecting mental well-being and outlines 13 values divided into higher and lower levels, facilitating focus on critical values for desired outcomes. It explores value interrelationships and conflicts, particularly noting indirect tensions between values like authenticity and connection, and between personalization, control, and autonomy.
Proposed design interventions aim to resolve identified value conflicts, enhancing authenticity to support connection and enhancing personalization and control to support autonomy. ... Read more

This research explores the role and challenges of openness between digital healthcare platforms through the use of boundary resources in the Dutch healthcare system, focusing on factors influencing openness decisions. Traditionally, boundary resources facilitate arm’s-length relationships between platforms and their periphery. This study examines their specific contribution to platform-to-platform openness in digital healthcare. To properly define openness between platforms, a distinction was made between interoperability and platform-to-platform openness: interoperability focuses on the compatibility of platform resources, while openness emphasizes the provision or accessibility of these resources. Boundary resources are further divided into technical and social aspects, shaped by laws and regulations. A document analysis of key policy documents maps how these relevant boundary resources function. The importance of APIs is emphasized as a means to progress toward an interconnected digital healthcare system, however, the practical implications and impact of openness decisions leading to the formulation of API’s, particularly between platforms, remain somewhat unclear. Interviews with the most relevant stakeholders in the field provide further insight into the drivers and barriers affecting boundary resources adoption. Most emphasis is placed data exchange and transactional based platforms by the stakeholders. The distinction between interoperability and platform-to-platform openness in healthcare can help avoid conflating compatibility requirements with broader governance and strategic considerations, enabling more focused discussions on factors essential for platform-to-platform openness. Boundary resources, while holding significant potential to facilitate openness, are not clearly distinguished by platform owners in their application for inter-platform openness compared to openness toward complementors, while these two forms of openness can serve a distinct purpose. Openness concerns are further composed of involved technical costs, security and data liability issues, as well as competitive pressures, with the potential loss of operating models and market position adding additional complexity to these openness decisions. Regulatory direction stimulates the development of boundary resources to promote inter-platform openness by embedding platform connections within the broader market ecosystem. Boundary resources could be further utilized further to enable platforms to xtend their periphery and for addressing deeper infrastructural and collaborative challenges within the healthcare sector. Platform-to-platform openness is influenced not only by decisions of the platform owners themselves, but also by broader market dynamics, regulatory frameworks, and the platform environment. This research highlights the potential of boundary resources in tackling infrastructure, innovation, and data-sharing challenges in healthcare. ... Read more

As the data economy is growing, businesses increasingly utilize data marketplaces to share data with external parties. Due to the specialized nature of data products, data marketplaces exhibit a high degree of heterogeneity, often focusing on specific countries and industries. This specialization results in high transaction costs when sharing data in data marketplaces. Additionally, multi-homing costs are high, making it difficult for users to participate in multiple data marketplaces to expand their reach. The existing literature recognizes meta-platforms as a potential measure to reconcile highly heterogeneous digital platforms, thereby reducing transaction and multi-homing costs. Nevertheless, while sharing business data on a data marketplace is already difficult due to data sovereignty concerns, these concerns will likely intensify in a meta-platform setting because data may flow from one data marketplace to another. Control mechanisms can enhance data sovereignty; however, due to the novel and intricate nature of meta-platforms, existing knowledge on designing such mechanisms may not be directly transferable to this complex setting. Therefore, this research aims to create design knowledge for developing and evaluating control mechanisms for data sharing through meta-platforms for data marketplaces, focusing on investigating their efficacy in enhancing data sovereignty in the societal context of the data economy. To achieve the objective, this study employs the Design Science Research (DSR) approach. This study is structured based on the three DSR domains: the problem space, the solution space, and the evaluation space.

We find that data providers have different views on the efficacy of control mechanisms (i.e., smart contracts and certifications) to enhance data sovereignty facets in the context of business data sharing via data marketplace constellations federated by a meta-platform. Our research finds no significant differences in data providers’ perception of their ability to retain ownership and maintain control over shared data products in meta-platforms, regardless of the presence of smart contracts. In addition, our findings suggest that data providers using meta-platforms with certifications feel more confident in meeting data sharing compliance requirements compared to those using meta-platforms without certifications. Additionally, these data providers perceive a clearer division of responsibility between meta-platform and data marketplace operators. When combined with smart contracts, the responsibility divisions become even clearer. Contrary to our expectations, however, we find no significant difference in the perceived security of data providers when sharing data on meta-platforms with certifications compared to those without.

Considering the impacts of data sovereignty on the broader societal context of the data economy, we find that when data providers feel sovereign over their data products, they are more likely to trust both a) meta-platform operators facilitating data sharing and b) data consumers with whom they share data. Surprisingly, we do not identify a correlation between the trust and their willingness to share data. This suggests that when data providers possess data sovereignty, trust in platform operators and data consumers becomes a less important factor for data sharing. In addition, we discover that data providers, feeling sovereign over their data products, perceive lower risks in sharing their data. The reduced perceived risks subsequently increase their willingness to share data through meta-platforms. Therefore, our study emphasizes the significance of data sovereignty in the growth of the data economy by a) promoting trust toward meta-platform operators and data consumers, b) reducing perceived risks, and c) increasing the willingness to share business data through meta-platforms.

Our study contributes to the Information Systems literature, particularly in the intersection between data sharing and digital platform literature. We contribute by being among the first to create design knowledge to develop and evaluate control mechanisms for business data sharing through meta-platforms for data marketplaces, focusing on investigating their efficacy in enhancing data sovereignty in the societal context of the data economy. Specifically, our primary contributions are four-fold: 1) theorizing the potential impact of control mechanisms on data sovereignty, 2) outlining design options and principles as prescriptive knowledge, 3) defining goodness criteria to enhance data sovereignty, and 4) advancing context understanding of a meta-platform as a business data sharing setting. In addition, our secondary contributions are 1) providing evidence on the potential impact of data sovereignty on the broader data economy and 2) extending the applicability of theories employed in this research in the market-based data sharing context.

In conclusion, this study resolves the tensions in the European policy-making agendas that promote a single market for data and interoperable data sharing (e.g., in EU Data strategy, Data Act) while, at the same time, pushing sector-specific data marketplaces to exist (e.g., the eight verticals in the Digital Europe program). Furthermore, policy agendas also emphasize adherence to data sovereignty principles. As data sovereignty is vital for data providers to share their data via meta-platforms, addressing this concern may increase meta-platform adoptions. Hence, we hope a meta-platform can realize its potential to be one distinguished instrument to fulfill what we hope (and are optimistic) for in the data economy: a single European Data Market in 2030.
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The Dutch first-line healthcare domain faces challenges arising from an ageing population and resource limitations, accentuating the need for an effective IT domain. Inadequate interoperability and data portability between information systems used by healthcare organisations in daily processes hinder patient treatment and innovation. This study explores a platform-based information system as a solution to enhance innovation and interoperability. Previous research focused on the IS supplier perspectives, but this research aimed to examine patients and healthcare professionals' needs considering the development of a platform-based information system.

The study is conducted within a socio-technical context, guided by the Design Science Research Methodology (DSRM). This study centers around five sub-research questions distributed across design cycles within DSRM. The preliminary research (including a focus group, semi-structured interviews and expert talks) revealed inefficiencies in communication regarding care around the medication process. The statements gathered during this research phase were validated on a bigger scale by conducting a survey. The statements resulted in a number of requirements, which were formalised and categorised using a System Requirement Structure (SRS) design. The SRS resulted in five main areas: supporting healthcare professional participation, regulating access, enabling clear and concise content, supporting agreements, and supporting patient participation. The low-level requirements of each of these areas were used to construct the platform modules and platform architecture, using a layered approach (showing the business, information and technology layer). The platform architecture was developed through iterative evaluations with domain experts, enhancing quality and detail. The evaluations also resulted in a new perspective on the platform-based information system, rather seeing it as a platform-based ecosystem solution.

The practical contribution of this research lies in two areas. Firstly, the designed platform addresses the need to improve communication within the healthcare domain, offering a communication service that can significantly enhance efficiency and collaboration among healthcare providers and patients. The insights and requirements from various perspectives can also be applied to enhance communication practices in other healthcare lines and countries. Secondly, the platform-based ecosystem design provides valuable insights into the roles, responsibilities, and interactions among different stakeholders, serving as a blueprint for developing similar ecosystems in other domains. The design also aligns with the Communication Platform as a Service (CPaaS) concept, offering the potential for further exploration in other industries.

Additionally, the research contributes to the scientific literature by addressing the research agenda on digital platforms by providing a comprehensive overview of how platform-based ecosystems can be conceptualised and designed in the healthcare sector. The findings can guide further research on feasibility, financial implications, and governance in platform-based ecosystems. The study’s value also extends to other domains, such as education and government, where ISs play a crucial role. Moreover, this study found that the interoperability layers can be applied and adapted within the healthcare context and potentially in other IS ecosystems, providing strong guidance and support for designing platforms and services. The research design demonstrates the relevance and applicability of interoperability layers, and with further experimentation, these layers may have broader applicability across different domains. Overall, the study’s positioning in Design Science Research (DSR) places it as an improvement for communication and an exaptation for the platform-based ecosystem, with potential for reuse and further research in various domains and contexts. The academic contribution also entails identifying knowledge gaps that must be explored in the future: the next steps.

Several areas need further research to enhance the development of the platform-based ecosystem and communication service. Firstly, understanding the patient’s perspective through focus groups or interviews can provide valuable insights into communication preferences and platforms. Secondly, detailed research on communication variety in healthcare and specifying platform content and user details will ensure successful implementation. Thirdly, following the Architecture Development Method (ADM) cycle can optimise the business, information, and technology architecture, cost-sharing decisions and stakeholder governance. Additionally, exploring governance frameworks like the Institutional Analysis and Development (IAD) framework will facilitate feasible implementation. Lastly, developing new design principles and guidelines for digital platform (ecosystem) design will better support the platform-based ecosystem’s growth and refinement. ... Read more

The adoption of data marketplaces is lacking. Data marketplaces work differently from other information sharing platforms (such as supply chain platforms), because they are more open. This openness allows data to be shared with many more companies, bringing more potential benefits, but also increasing the risk. On data marketplaces there typically is less trust between users, however this lack of risk can be compensated by adding more control mechanisms. For these reasons I want to address the research question:

How does the interplay between control, trust and risk affect a company’s decision to share data in a data marketplace?

The objective of this research is to define and validate the relationships between control, trust, risk and willingness to share data. This will be done through a literature review and a qualitative study using structural equation modelling.

The literature review resulted in a conceptual model, which was subsequently tested using an online survey. The demographic of the survey was managers in the manufacturing industry and they were given two scenarios in which they could share data. In both scenarios their trust in other users, trust in the platform, perceived risk, perceived sensitivity of data and willingness to share data was measured.

Using structural equation modelling we found 5 significant relationships, out of the 6 that were hypothesized. Answering the research question, this study has shown that increasing trust in other users and perceived control can really help decrease the risk of sharing data, which in turn is an important predictor of willingness to share data. However, the sensitivity of data can also have an influence over risk. This insight is new in the field of data marketplaces. We now have a more clear picture of how control and trust can be used to lower the risk and in turn increase the willingness to share data. This study also provided some data that confirms these relationships in the context of the manufacturing industry. This data shows that companies are willing to share their data, if preconditions such as a fair price are met. These results contribute to the overall literature on willingness to share data in a marketplace and on the literature on control mechanisms, trust and risk. The insights from this study can be useful for people designing data marketplaces and regulators that want to encourage the sharing of data.


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Freelance platforms such as Fiverr and Upwork lower the threshold for hiring temporary workers by enabling companies to post short-term assignments or “gigs” that can be completed by freelancers worldwide (Jarrahi et al., 2020). This provides access to a global talent pool and reduces hiring time for organisations, while freelancers benefit from easier access to assignments. However, it also changes traditional work structures and introduces challenges such as aligning internal and external workers (Scully-Russ & Torraco, 2020).

Despite growing interest in freelance platforms, most research focuses on workers rather than organisational adoption. Existing studies on platform adoption often address broader B2B platforms or e-marketplaces, leaving a gap in understanding implementation in organisations. This thesis addresses this gap by investigating how B2B freelance platforms are adopted and implemented within organisations.

The study uses Rogers’ Diffusion of Innovation theory and the Technology-Organisation-Environment (TOE) framework, extended with collaboration factors. A literature review is combined with an embedded case study of a Dutch freelance platform (Platform X), involving two client organisations: one that adopted but did not implement the platform, and one that successfully implemented it. Data includes interviews and usage metrics.

Results show that adoption is driven by perceived relative advantages such as external capacity, platform support, and assignment flexibility. Low complexity and accessibility also support adoption, along with managerial openness to experimentation. Barriers include uncertainty about freelancer quality and unclear applicability of tasks.

Implementation success depends on organisational position of decision-makers and internal diffusion channels. Higher-level decision-makers facilitate adoption and implementation, while internal users require time and support to experiment with the platform. Usage is hindered by effort required to guide freelancers and uncertainty about outsourcing suitability.

The study contributes to literature by identifying drivers and barriers in freelance platform adoption and implementation, and by extending the TOE framework with collaboration factors. It provides managerial implications, suggesting organisations allocate time for internal alignment and platform-supported scoping of tasks, while providers should reduce uncertainty by improving transparency of freelancer capabilities.

Limitations include limited data availability and case diversity. Future research should test identified relationships, compare different platform types, and further explore organisational differences in adoption and implementation processes. ... Read more

In Dutch primary care, there is a dilemma that needs to be solved: caregivers using different digital platform in information system (DPIS) have difficulties in transferring necessary medical information. Although DPIS, as an emerging technology, assists in the decision making, coordination and control that occurs in the organizational environment. Its lack of openness leads to difficulties in exchanging information data. Therefore, this study focuses on the architectural requirements that can facilitate the openness of DPIS for primary care in the Netherlands. A design science approach was used to answer this question. The study first clarifies the current situation using document analysis and literature review, then defines the factors influencing openness and the requirements of stakeholders regarding openness and identifies architectural requirements. Finally, a conceptual artifact was developed and the requirements were validated in discussion with domain experts. The results of the study suggest that a clear distinction should be made between open to share or open to use when defining the openness of an architecture, and in addition, we should focus on the development of standardized data exchange regulations. ... Read more

This thesis explores the motivation of developers to initiate and sustain participation in a Platform-as-a-Service Software Ecosystem (PaaS SECO). PaaS, integral to SECOs, is gaining prominence for its cost advantages and scalability. The study focuses on understanding what drives developers in diverse roles to engage with PaaS SECOs and examines potential differences in motivation among developer groups.

The research adopts an exploratory case study approach, with the Mendix SECO, a low-code PaaS for enterprise application development, as the subject. Semi-structured interviews with developers from Independent Software Vendors (ISVs), service providers, and customers inform the study. Self-Determination Theory (SDT) is applied to structure and comprehend developers' motivators, considering intrinsic and extrinsic motivations.

The findings underscore the significance of intrinsic motivators, such as enjoyment, intellectual stimulation, and skill enhancement, in attracting developers to PaaS SECOs. Competence-related factors, like challenge and creativity, play a pivotal role. Extrinsic motivators, like knowledge exchange and community size, also contribute to initial participation, with SECO support being crucial.

In continued participation, intrinsic motivators remain vital, with skill maturation and the evolving nature of fun being emphasized. Learning new skills aligns with staying abreast of platform innovations, sometimes driven by external pressures. Developers become more aware of the SECO's offerings, with social events acting as supplementary motivators for connection and inspiration.

Extrinsic motivators, particularly in autonomous form, gain importance in sustained participation. Developers align with the platform's strategic direction, emphasizing satisfaction with the SECO and its innovative efforts. PaaS providers' reputation and engagement in social events further enhance developers' motivation.

The study reveals overarching similarities and differences between low-code and other SECO types, questioning assumptions about developer motivations. The dominance of intrinsic motivators aligns with previous research in proprietary SECOs, but nuances, such as the desire for fast and agile development, emerge as unique to PaaS SECOs.

Theoretical contributions include enriching understanding of developer motivation in PaaS SECOs, reevaluating the intrinsic-extrinsic binary scale, and offering insights into nuanced motivators through SDT. Practical implications suggest strategies for PaaS providers, emphasizing the importance of competence-related motivators and the ongoing need for intrinsic satisfaction.

In conclusion, this thesis contributes to both theoretical and practical aspects of developer motivation in PaaS SECOs, paving the way for future research and strategies to attract and retain developers in evolving software ecosystems. ... Read more

The benefit of secondary use of data leads to the belief that data can be monetized through exchanging and trading between businesses. Many new data marketplaces emerge from this, resulting in the heterogeneity of the data marketplace that leads to market fragmentation in the industry. The aggregator business model can offer various values to users in a fragmented market. Therefore, the idea of designing aggregator business models for data marketplaces could be worthwhile investigating. Design Science Research (DSR) methodology is used in this research. Business model requirements to design aggregator business models were defined in the literature review. The business models of various aggregators are analyzed with case studies. From the requirements and case studies, four new aggregator business archetypes are derived: search engine, advanced search engine, comparison sites, and one-stop shop. These four aggregator business models are distinguished by their service offerings and their degree of the network. It is also discovered from case studies that there is a connection between the degree of network and aggregators' embedded technology. The high degree of network aggregators tend to use API, while the low degree of network aggregators tend to use information crawlers. The aggregator business model archetypes are then demonstrated to the data marketplace cases by translating the business models into business activities and services that can be offered to the users. Then, we evaluate the data marketplace aggregator business model through semi-structured interviews with experts. From the evaluation, it is discovered that data marketplace aggregators could offer value to the users, e.g., navigating users to find data sales and providing a single access point to collect data. Different technology aspects that could help to realize the aggregation services have also been developed by various projects. Additionally, data providers are willing to join the aggregation services due to the economic benefit. However, although the benefit and possibilities, multiple challenges need to be addressed by the data marketplace aggregator. There are issues with technical standardizations and interoperability that could be problematic in integrating various platforms for aggregation. Maintaining collaboration is difficult due to the need to provide data assurance, which could be expensive and exhausting. Additionally, although it is beneficial to navigate users in finding sales, data marketplace aggregators might offer little value to data buyers with market knowledge because they will directly buy the data from the sellers. ... Read more

The term "digital transformation" (DT) has gained popularity, sparking interest across many academic fields and inspiring new lines of inquiry(Hausberg et al., 2019). With the adoption of new technologies helping deliver secure high-quality patient care and drive greater business efficiency, healthcare sector has gained significant benefits from digital transformation. Digital technologies, driven by the exponential rise in computing power, have successfully altered the majority of economic sectors, from finance to entertainment, with one notable exception: healthcare. The increasing advancements in medical equipment and imaging technology serve as evident illustrations of how high-tech medicine is in many aspects. Nevertheless, healthtech companies are still on a learning curve on how to transform their companies digitally, despite billions of dollars being invested in digital health solutions by both startup and established technology companies(Walsh & Rumsfeld, 2017).
This study advances the body of knowledge in the field of digital transformation by identifying the barriers to and enablers of business transformation as well as the role of IT technology as an enabler of business transformation. By creating a theoretical framework for barriers and enablers of business transformation with IT technology as an enabler, it empirically studies Philips to undertake a case study and offers a basis for theory building. On the subject of business transformation, a literature review utilizing the five-step grounded theory methodology was carried out. According to the literature study, this research highlights four primary barriers facing business transformation: organizational, knowledge, financial, and technical. Strategy, people, process, data, and technology are the different categories for business transformation enablers. The theoretical framework for this study is developed using the results of this literature review. A case study is performed on the digital transformation journey of Philips by identifying the IT technologies of the acquired firms that are part of Philip’s healthcare transformation portfolio. This research captures the goal of business transformation while identifying the barriers and enablers of business transformation at Philips by conducting inductive qualitative research by interviewing. Analysis of data is carried out by following the steps stated by Miles & Huberman (1994) and using content analysis to analyze the interview data. The results of this study show that At Philips, the organizational barrier has emerged as the most pervasive barrier to business transformation. This study demonstrates that Philips' organizational structure, or the way they are set up, is a significant impediment to business transformation. The matrix organizational structure of Philips makes organizational change challenging. According to researchers, business transformation begins with establishing a strategy and achieving the organization's aim. According to the research, this strategy is misleading, and that any business transformation strategy should be developed by first comprehending customer demands before being in line with the intended outcome of the business transformation. According to this study, people with proper experience and knowledge in the field of business transformation are the key enabler of business transformation. This study supports the resource-based hypothesis, which contends that an organization has a great chance to outperform its rivals when it possesses strategic resources that can provide it an advantage in the market and could even help it generate sizable profits. This research examines three important IT technologies provided by the acquired companies of Philips, namely Tomtec, RDT, and Capsule technologies as resources that can enable business transformation. According to this study, Philips' business transformation was made possible by the IT technologies' significant contributions to the company's sales and revenues following the acquisition of these companies. By integrating these IT resources into other products in their portfolio to facilitate business transformation, Philips can further develop these technologies and achieve their objective of becoming a fully solutions-based firm. However, the findings of this study also suggest that IT technologies have not yet reached their peak value since Philips lacks the competencies and innovation culture to fully utilize these technologies and add value as a result of preexisting limitations.
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The financial domain is losing ground to rapid-developing fraud schemes. It puts intense pressure on organizations such as banks to find new approaches to tackle financial misconduct. This financial crime has always existed and is present in the financial industry. However, the rise of technology and the use of online transactions has enhanced the presence of the impact of fraud in this industry. The increase in financial fraud cases in a technological era result from a lack of inter-organizational synergy and the privacy concerns that entail by making data available. On top of the increasing fraud cases, organizations are exposed to increasing regulatory, financial, reputational, and legal risks. Hence, the financial crime industry and fraud prevention organizations must act on this threat. Therefore, these actors need to improve their current workflow continuously to keep up with the new developments. Different studies propose that it is a potential opportunity to take the chance and bundle data together to learn from the existing environment and improve their workflows and prediction models. However, the main concern is that parties are reluctant to share data as it involves confidential and sensitive data, which malicious parties can leverage and abuse. Also, the increasing focus on privacy protection regulations makes it complex and challenging to exchange data easily. The dataset that actors are providing will contain personally identifiable information, which in fact cannot be shared and proposed without any legitimate reason and is subjected to the data privacy regulations.
The existing set of techniques for sharing and analysing data securely, such as differential privacy, homomorphic encryption and federated learning have been proposed in studies and use cases are built in the real world. However, these techniques are insufficient and capable enough to facilitate multi-actor (data owners) data exchange and analysis. Secure Multiparty Computation, however, is capable of having multiple data owners securely perform a joint analysis. For this reason, this study has been focused on SMPC. In the case of the financial crime industry, it requires the involvement of multiple stakeholders sharing data simultaneously. Especially in the case of banks, it is essential to have bundled data for all transactions as these are connected.
To understand the purpose and the concept of the study, it is essential to have a basic understanding of SMPC. Secure Multiparty Computation is a cryptographic method for parties to mutually compute a function over all parties' acquired inputs while keeping the intake private throughout the entire process. Independent computation nodes will perform and provide analysis outcomes to designated parties. The concept of Secure Multiparty Computation has been studied by academia since the 1980s (Yao, 1982). However, the applications and introduction of SMPC are relativity novel to organizations and will not be immediately accepted. A technique such as SMPC will require participating parties to share a mutual interest and willingness to contribute continuously. It is uncertain if organizations will accept and adopt SMPC as mentioned before. Therefore, the study will also incorporate the concept and theory of collective action to understand the motives and the common goal for stakeholders in the anti-fraud industry to accept the technique and collaborate. A common goal, also known as a collective goal or interest, would create acceptance among the group. In this case, it will help to identify the factors and interests that influence an organization's decision to engage in collective action for developing MPC for fraud detection in the financial industry...
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The growing aviation industry asks for innovative solutions to be able to handle the increasing amount of baggage. An example of such an innovative solution is Computer Vision Technology (CVT), which uses cameras to identify bags using data and artificial intelligence. The value of CVT for the baggage handling ecosystem is currently unknown. Besides this practical knowledge gap, a scientific gap is found as well. The majority of the literature on digital transformations has an organizational viewpoint and does not incorporate established ecosystem perspectives. It is unknown how a value proposition needs to be designed for a data driven technology to lead to a digital transformation of an established ecosystem.

A DSR approach is executed in a situated setting at Schiphol Airport to capture the value proposition of CVT for the baggage handling ecosystem by the identification of use cases. . The results show that the implementation of CVT provides value for Schiphol Airport, the baggage handling system provider, airlines, handlers, passengers, and society. The value proposition of CVT is the automated identification of bags based on visual images that provides thirteen use cases applicable throughout the whole baggage handling process, which leads to more autonomous processes, process improvement, the generation of more (types of) valuable data compared to the current identification techniques and can contribute to the achievement of sustainable goals if it replaces the current identification techniques.

The results not only contribute to the aviation industry, but the insights gained during the research are also valuable for future digital transformations within other established ecosystems. During the research, a lack of ecosystems’ support for the digital transformation was identified, caused by two factors. It was found that certain process choices had a positive influence on these two factors, which inspired the formulation of process guidelines. These guidelines contribute to the digital transformation knowledge base as they provide insights into how to enhance ecosystems support for digital transformations. In this way, it guides future digital transformation processes within established ecosystems. Furthermore, the research provides an approach to get a grip on a complex established ecosystem and a tool to specify data-driven use cases in combination with its implications for the established ecosystem. No tool existed to accommodate that. Therefore, a tool was constructed and used, which provided guidance on the use cases’ specification and could be valuable within future ideation processes of data-driven use cases for established ecosystems.
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The revision of the eIDAS Regulation proposes the implementation of a European digital identity wallet for citizens to authenticate themselves across the EU. The process to decide if a person already has an account at the service where they seek to authenticate themselves is called identity matching. Regulated and public Dutch Relying Parties and the Dutch government are not always able to assess whether a citizen authenticating themselves has a pre-existing record at the Relying Party or in the Dutch national registry. Moreover, the current dependency on the Dutch central identity matching service creates a Single Point of Failure. Besides these reliability problems, privacy issues such as profiling data minimization must be accounted for. To this end, this research proposes three possible solution directions for solving these problems: a government-centric, wallet provider-centric, and a hybrid solution direction. The design of the solution directions follows a design science research methodology. The possible solution directions are evaluated by experts in focus groups to elicit the benefits and the barriers which these experts identify as relevant factors for accepting a solution direction. These factors are categorized using the TOE model, which is adapted to suit the current context. Expert evaluations during the focus groups have resulted in factors which relate to the organizational, technological, and external environment of the solution directions. The evaluation uncovered tradeoffs which the Dutch Ministry of the Interior must make to choose between one of the proposed solution directions: reuse of infrastructure at the cost of citizen privacy, or more privacy for citizens at the cost of additional logic requirements needed for the identity wallet. Based on the privacy and reliability requirements and the objective of the Dutch government to give citizens more control over their personal data, the wallet provider-centric solution direction is the most fitting choice of the three proposed solution directions. The explication of the problem, requirements, and solution directions can be used as a starting point in the exploration of new solution directions for the identity matching problems. More research is needed on other possible solution directions than are proposed in this research and their viability to meet the objectives of the Dutch government and deadlines set by the European Commission. ... Read more