Unveiling deceptive tactics: exploring fraudulent online ratings in the restaurant industry and their impact on consumer choice

This study investigates the impact of competition on fraudulent online ratings within the restaurant industry, revealing how economic incentives drive deceptive practices, such as posting negative reviews of competitors. Utilizing data from TripAdvisor and OpenTable, we analyze factors such as proximity, price range, and cuisine type to determine their influence on cheating behavior. Results demonstrate a significant positive correlation between competition and fraud: for example, a one standard deviation increase in price index is associated with a 0.060 standard deviation increase in fraudulent activity (p < 0.01), while competition within similar ranking tiers correlates with a 0.077 standard deviation increase in deceptive practices (p < 0.01). Additionally, our findings suggest that competition from similar cuisine types does not significantly affect negative cheating, likely due to consumer clustering effects within cuisine-specific areas. This research underscores the role of competition dynamics in driving fraudulent behavior and offers insights for enhancing the integrity of online rating platforms. Robustness checks confirm these findings across bandwidth and kernel variations, highlighting the stability of competition-related coefficients.