Business reputation ecosystems are a widely untapped research field. In these ecosystems, agents can selectively exchange (monetary) ratings to inform about the experienced quality in a market. We build a model for conducting a multi-agent simulation that can be used to simulate and evaluate business reputation ecosystems as a new system class. We explore the factual occurring voluntary payment to create positive (pay) or negative ratings (no pay), selling ratings selectively to alleviate information asymmetry, and the workings of counter-ratings to prevent buyers’ dishonest ratings. Thereby, we analyze, among others, agent profitability, the occurrence of dishonest ratings, and reputation bias and sensitivity. The results provide simulation-based empirical evidence that the concept of monetary reputation systems provides necessary incentives for participation, and high-quality sellers and honest buyers benefit from such a system. The results indicate that counter-ratings prompt buyers to rate sellers honestly, albeit incurring the monetary cost for positive ratings.