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Abstract

In the evolving domain of economic behavior, the intricate dynamics of human thinking and decision-making presents a challenge to traditional theoretical frameworks. This dissertation endeavors to shed light on the ways individuals navigate the complexities of a technology-driven environment. Comprising four distinct but interconnected papers, this research explores the social norms related to personal and research data sharing, the impact of Open Science and Open Data initiatives on the scientific community, and the influence of artificial entities on human behavior.

The investigation delves into both injunctive and descriptive social norms among researchers concerning the management and dissemination of research data. It also examines the criteria under which individuals deem it appropriate to share personal data, the potential interest of various actors in accessing this data, and motivations behind why they might want it. Additionally, an experimental approach is employed to analyze the principal-agent relationship between researchers, research institutions, and funding agencies, offering insights into the current state of the scientific ecosystem. Lastly, there is the examination of social conformity in the presence of bots, questioning whether individuals align their behavior with artificial agents despite being aware of their non-human nature. This inquiry spans both objective and subjective domains, utilizing established methodologies while adapting them to novel contexts.

By maintaining a focus on scenarios that closely mimic real-life situations, this dissertation provides a contemporary perspective on economic behavior, highlighting the dynamic interplay between technology, data sharing practices, and social norms in modern society.