Information Cascades and Online Rating Games
arXiv:1508.008931.2h-index: 4
Originality Synthesis-oriented
AI Analysis
For businesses and consumers relying on online ratings, this work highlights fundamental inaccuracies in rating systems.
The study analyzes online rating systems using a model with two parameters (inherent quality and customer gut feeling accuracy), finding that ratings are rarely accurate due to extreme accuracy levels in customer perceptions.
Through mathematical analysis and simulations, online ratings and their impact on businesses are characterized through two parameters: an inherent and objective restaurant quality factor, and the accuracy of customers' gut feeling about a business. Within this model, it is found that online ratings are seldom accurate mainly because of the low or high accuracy in customers' gut feelings.