We share some peeks into our recently accepted papers at AOM annual conference, ICIS paper-a-thon, and CHITA conference.

Study on Bot Abuse in Open-Source Platforms

A paper by Shahid, Subasinghage, Reichman, and Kankanhalli examines the use of bots in open-source platforms like GitHub. The research acknowledges the benefits of bots for efficiency but also addresses the issue of abuse, where contributors might use bots for undue gain. This abuse can negatively affect the quality and fairness of these platforms.

The researchers developed a framework to detect abusive bot contributions and applied it to a dataset of GitHub repositories. The study also looked at the relationship between abusive contributions and popularity indicators like stars and forks, suggesting that these indicators don't always reflect authentic contributions. The findings offer insights for open-source environments.

This research has been published as a Paper-a-thon Paper from International Conference on Information Systems: https://aisel.aisnet.org/icis2024/paperathon/paperathon/4 

Research on Platform Signaling

Sobota and Rothe's paper explores how signals from platform providers influence interactions between users and complementors. The study investigates how different ways of framing a signal, such as with abstract or concrete terms, impact user and complementor preferences.

The research considers how complementarity expectations play a role. Experiments on a lodging platform showed differences in how users and complementors react to signals. User reactions are often tied to their expectations of how complementors will react, while complementor reactions are influenced by their expectations of user reactions, especially with concrete signals. This research contributes to understanding platform signaling and entrepreneurial framing.

This research has been been accepted for publication in the Academy of Management Conference Proceedings 2025.

Insights into Biodata Ventures

Rothe, Jarvenpaa, and Lauer's paper focuses on biodata ventures and their role in life science discoveries. The growth of biodata has led to these ventures, which provide digital data objects to help solve problems in areas like drug development.

The research discusses the challenges these ventures face, including the nature of biodata, standardization issues, and interpretability. Biodata ventures use tools for data curation, ontology development, and machine learning. The study offers insights into biodata ventures and their potential in life science.

This research has been been accepted for presentation at the Conference on Health IT and Analytics (CHITA) in Austin, Texas, USA.*

These research papers contribute to ongoing discussions in digital innovation, entrepreneurship, and sustainability.