Online Reputation Systems

Timm Teubner, Professor of Digital Service Engineering at the ECDF and TU Berlin, and his team conduct research on online platforms, reputation systems, and how trust is built, maintained, and sometimes undermined on digital marketplaces. The platforms studied range from e-commerce platforms (e.g., Amazon and Zalando) to service-based marketplaces (e.g., Airbnb and Uber). The research focus lies on the questions of how network effects, platform launch strategies, and reputation mechanisms influence user behavior and market dynamics.

Teubner's work addresses critical challenges such as the cold-start problem for new users and providers, fake reviews, and the portability of reputation across platforms: "We analyze numerical ratings and text reviews to understand how the valence, volume, and perceived authenticity of reviews influence trust and decision-making. Through this research, we aim to uncover principles for designing more robust, trustworthy, and effective reputation systems that support platform growth and healthy digital ecosystems," explains Teubner.

In a recent study, Teubner and his colleague Aaron Kolleck examined customer reviews on sharing economy platforms such as Airbnb, which have been extensively studied, though their effectiveness has recently been called into question. The researchers investigated the role of reviews in relation to listing churn on Airbnb using panel data and found that listings with few or poor reviews were more likely to leave the platform. After controlling for listing characteristics, the researchers found that the best possible rating strongly predicted listing success. They concluded that the best rating is a necessary but not sufficient condition for success. //Read the paper