Investigating the Intersection of
FinTech, AI, Blockchain
& Empirical Economics

This doctoral thesis investigates the evolution of blockchain scholarship and the institutional processes through which blockchain-based ventures establish legitimacy and acquire resources. It combines large-scale bibliometric analysis and computational topic modeling of 35,604 publications with empirical investigation of entrepreneurial narratives, online media, and legitimacy in ICO markets. The thesis develops an interdisciplinary account of blockchain research and examines how venture distinctiveness and media-mediated perceptions influence legitimacy and resource acquisition in decentralized entrepreneurial ecosystems.

This study challenges the conventional optimal-distinctiveness assumption that deviation from category prototypes necessarily undermines organizational legitimacy. Using data from 306 ICOs across 29 market categories, the study applies topic modeling to identify the content of entrepreneurial narratives and quantify their deviation from category prototypes. The findings indicate that greater narrative distinctiveness can enhance resource acquisition among novelty-seeking audiences, supporting the argument that distinctiveness may constitute a source of normative legitimacy rather than merely a liability to cognitive legitimacy. The study further examines the role of online media in shaping this relationship.

This study applies computational topic modeling to systematically examine the evolution of blockchain scholarship across disciplines and over time. By analyzing a large corpus of blockchain research, the study identifies dominant research themes, methodological trajectories, disciplinary convergence, and emerging areas of inquiry. The findings provide a structured map of the intellectual development of blockchain research and identify opportunities for greater methodological and interdisciplinary integration.

This study examines how national cultural dimensions influence the interpretation of Big Five personality traits from customised three-dimensional avatars. Drawing on Hofstede's six cultural dimensions and the Brunswik Lens Model, the study investigates the relationships between personality inferences and cultural characteristics using data from participants in Greece, Pakistan, Russia, and Singapore. The experimental design involves two stages: participants create customised avatars, which are subsequently evaluated by independent participants. Pearson correlation and multivariate analyses are used to examine associations between the Big Five traits, cultural dimensions, and gender. The results identify significant relationships between specific personality traits and cultural dimensions, including associations involving neuroticism and uncertainty avoidance, neuroticism and masculinity, extraversion and masculinity, and agreeableness and uncertainty avoidance. The findings indicate that cultural context is an important consideration in understanding how personality cues are interpreted in avatar-mediated environments.