Blockchain Value Creation Logics and Financial Returns

With its complexities and portfolio-nature, the advent of blockchain technology presents several use cases to stakeholders for business value appropriation and financial gains. This 3-essay dissertation focuses on three exemplars and research approaches to understanding the value creation logics of blockchain technology for financial gains. The first essay is a conceptual piece that explores five main affordances of blockchain technology and how these can be actualized and assimilated for business value. Based on the analysis of literature findings, an Affordance-Experimentation-Actualization-Assimilation (AEAA) model is proposed. The model suggests five affordance-to-assimilation value chains and eight value interdependencies that firms can leverage to optimize their value creation and capture during blockchain technology implementation. The second essay empirically examines the financial returns of public firms\u27 blockchain adoption investments at the level of the three main blockchain archetypes (private-permissioned, public-permissioned and permissionless. Drawing upon Fichman\u27s model of the option value of innovative IT platform investments, the study examines business value creation through firm blockchain strategy (i.e., archetype instances, decentralization, and complementarity), learning (i.e., blockchain patents and event participation), and bandwagon effects using quarterly data of firm archetype investments from 2015 to 2020. The study\u27s propensity score matching utilization and fixed-effects modeling provide objective quantification of how blockchain adoption leads to increases in firm value (performance measured by Tobin\u27s q) at the archetype level (permissionless, public permissioned, and private permissioned). Surprisingly, a more decentralized archetype and a second different archetype implementation are associated with a lower Tobin\u27s q. In addition, IT-option proxy parameters such as blockchain patent originality, participation in blockchain events, and network externality positively impact firm performance, whereas the effect of blockchain patents is negative. As the foremost and more established use case of blockchain technology whose business value is accessed in either of the five affordances and exemplifies a permissionless archetype for financial gains, bitcoin cryptocurrency behavior is studied through the lens of opinion leaders on Twitter. The third essay this relationship understands the hourly price returns and volatility shocks that sentiments from opinion leaders generate and vice-versa. With a dynamic opinion leader identification strategy, lexicon and rule-based sentiment analytics, I extract sentiments of the top ten per cent bitcoin opinion leaders\u27 tweets. Controlling for various economic indices and contextual factors, the study estimates a vector autoregression model (VAR) and finds that finds that Bitcoin return granger cause Polarity but the influence of sentiment subjectivity is marginal and only stronger on bitcoin price volatility. Several key implications for blockchain practitioners and financial stakeholders and suggestions for future research are discussed

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Dealings on the Dark Web: An Examination of the Trust, Consumer Satisfaction, and the Efficacy of Interventions Against a Dark Web Cryptomarket

Abstract Objective. The overarching goal of this thesis is to better understand not only the network dynamics which undergird the function and operation of cryptomarkets but the nature of consumer satisfaction and trust on these platforms. More specifically, I endeavour to push the cryptomarket literature beyond its current theoretical and methodological limits by documenting the network structure of a cryptomarket, the factors which predicts for vendor trust, the efficacy of targeted strategies on the transactional network of a cryptomarket, and the dynamics which facilitate consumer satisfaction despite information asymmetry. Moreover, we also aim to test the generalizability of findings made in prior cryptomarket studies (Duxbury and Haynie, 2017; 2020; Norbutas, 2018). Methods. I realize the aims of this research by using a buyer-seller dataset from the Abraxas cryptomarket (Branwen et al., 2015). Given the differences between the topics and the research questions featured, this thesis employs a variety of methodological techniques. Chapter two uses a combination of descriptive network analysis, community detection analysis, statistical modelling, and trajectory modelling. Chapter three utilizes three text analytic strategies: descriptive text analysis, sentiment analysis, and textual feature extraction. Finally, chapter four employs sequential node deletion pursuant to six law enforcement strategies: lead k (degree centrality), eccentricity, unique items bought/sold, cumulative reputation score, total purchase price, and random targeting. Results. Social network analysis of the Abraxas cryptomarket revealed a large and diffuse network where the majority of buyers purchased from a small cohort of vendors. This theme of preferential selection of vendors on the part of buyers is repeated in other findings within this study. More generally, the Abraxas transactional network can then be viewed as set of transactional islands as opposed to a large, densely connected conglomeration of vendors and buyers. With regard buyer feedback, buyers are generally pleased with their transactions on Abraxas as long as the product arrives on time and is as advertised. In general, vendors have a relatively low bar to achieve when it comes to satisfying their customers. Based on the results of the sequential node deletion, random targeting was found to be ineffective across the five outcome measures, producing minimal and a slow disruptive effect. Finally, these strategies are based on a power law where a small percentage of deleted nodes is responsible for an outsized proportion of the disruptive impact. Conclusion. As with all applied research examining emergent phenomena, this thesis lends itself to a more refined understanding of dark web cryptomarkets. While the results and conclusions drawn from these results are not perfectly generalizable to all cryptomarkets, they should serve to inform law enforcement on the dynamics which undergird these markets. To this extent, a sombre consideration of trust, consumer satisfaction, and tactical effectiveness of interventions is a necessary step towards the development of more effective countermeasures against these illicit online marketplaces. For law enforcement to be more effective against cryptomarkets, it is advised that an evidence-based approach be taken

Actas de las VI Jornadas Nacionales (JNIC2021 LIVE)

Estas jornadas se han convertido en un foro de encuentro de los actores más relevantes en el ámbito de la ciberseguridad en España. En ellas, no sólo se presentan algunos de los trabajos científicos punteros en las diversas áreas de ciberseguridad, sino que se presta especial atención a la formación e innovación educativa en materia de ciberseguridad, y también a la conexión con la industria, a través de propuestas de transferencia de tecnología. Tanto es así que, este año se presentan en el Programa de Transferencia algunas modificaciones sobre su funcionamiento y desarrollo que han sido diseñadas con la intención de mejorarlo y hacerlo más valioso para toda la comunidad investigadora en ciberseguridad