In the past years there has been increasing awareness about the benefits of collecting and using more sensor data for businesses. This has led firms to look for data outside of their boundaries and use some data commercialization mechanisms such as data brokers, and open or privately-owned data marketplace. However, these exchanges solutions are controlled by companies which have a commercial interest that differs from users, leading to lack of transparency and lack of protection of data, loss of data ownership by the provider and no guarantee of fair pricing. These centralized data exchanges call into question the willingness of both data providers and data users to share data. As an alternative, blockchain technology can be used to reduce the control and interference of any firm, leading to a more peer-to-peer and transparent data marketplace. To improve coordination between stakeholders and to enhance a more automated marketplace, the system should be context-aware. The main contribution of this thesis is a proposition of blockchain-based components integrated within a context-aware decentralized data marketplace. Other parts of the system are highlighted, as they need to be subject to more research in order to achieve a fully functional and complete system. Finally, guidelines are suggested for generalization to other types of data and ecosystems.

The advancement in digital technology provides room for innovations in many sectors, including in the financial sector. The development of digital currencies is one example of digital advancements in this sector. Digital currencies can take many forms, and cryptocurrency is one of the most popular forms of digital currencies today. Bitcoin and other cryptocurrencies (or altcoins) have slowly been adopted around the world as a means of payment. However, Bitcoin and altcoins are not issued by the central banks or other central authorities, making it difficult to regulate. At the same time, in several countries, the use of cash is declining to a very low rate. As the response to these economic phenomena, central banks in some countries are investigating the possibility of introducing their own version of digital currency which is called central bank-issued digital currency or CBDC. This research shows how to implement transaction cost economics (TCE) framework to characterize transaction costs in several CBDC design options through in-depth semi-structured interview sessions. The interviewees were the experts from central banks, commercial bank, regulatory bodies, and relevant NGOs in the European developed economies. The results of the interview sessions showed several findings. First, according to the experts, there are three main CBDC design options: Retail CBDC, Wholesale CBDC, and Full-reserve Depository Banks CBDC. Second, among the three transactional dimensions of TCE (uncertainty, transaction frequency, and asset specificity), the uncertainty aspect provides a significant contribution to overall transaction costs. Third, the central bank and commercial banks are the ones that bear most of the transaction costs, especially in Retail CBDC design option, while the households and non-financial institutions do not need to bear any transaction costs.

Although aligning business models with enterprise architecture concepts can provide insights into business model implementation aspects, current approaches that facilitate business model enterprise architecture have several limitations: they often lack a network perspective, facilitate one level analysis of the business model implementation, are heavyweight or have an informal approach. Therefore, this research presents a formal representation for business model – enterprise architecture alignment, which is developed though an iterative design process with researchers and practitioners. Findings of this study have resulted in a formal business metamodel, a formal business model – enterprise architecture metamodel, two target metamodels and a corresponding modelling procedure. These metamodels facilitate a multi-level description, visualization and analysis of the technological implementation of business models through enterprise architecture concepts. The metamodels are subsequently applied to the Industry 4.0 domain. Main contributions of this study are the formal approach, the development of an intermediate lightweight metamodel to bridge the gap between business models and enterprise architectures, and the proposal of various extensions to enterprise architecture modelling language ArchiMate. Lastly, this study also provides some first insights into Industry 4.0 business model implementation aspects. Further research could focus on the inclusion of a quantitative financial analysis in the business model implementation approach.

This research has proposed a tentative design of information flows on PI embed three PI components: (1) modular containers, (2) open interface web, and (3) global protocols. Through the design, this research has identified potentials of the primary PI elements to resolve current issues in freight logistics (i.e., inefficient space utilization on loading units and lack of their visibility). In-line with trends of the maritime logistics, PI ports in the design exploit the major PI elements in one of the value-added services, repositioning operation. In the context of PI ports, requirements on the three PI components have been elicited and reflected in the conceptual design. The adjusted RAMI 4.0 has been applied to visualize not only information flows in PI ports but also required logistics entities, activities and interactions in Track and Trace (T&T) system, and moreover operational processes. As a result, the conceptual model proposes requirements for PI ports along with potentials of each PI element.

Product master data (PMD) can be defined as a set of data that represents a selection of characteristics and aspects of its accompanying physical product. For several reasons, these data sets are increasingly exchanged between organizations within supply chains. Although this process is traditionally often supported by non-automated technologies such as Excel spreadsheet, telephone, email, and fax, the adoption of data pools is on the rise. These inter-organizational systems allow the data supplying party to publish a product’s master data set in one centralized system after which it can be accessed by all subscribed data recipients.