Using experimental data from a comprehensive field study, we explore the causal eects of algorithmic discrimination on economic eciency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing...

In current discussions on large language models (LLMs) such as GPT, understanding their ability to emulate facets of human intelligence stands central. Using behavioral economic paradigms and structural models, we investigate GPT's cooperativeness in human interactions and assess its rational...

Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees' decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of...

Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees’ decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger...

Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS)...

Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees' decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of...