Evaluation and design of online cooperative feedback mechanisms for reputation management

This research evaluates and analyzes existing mechanisms of online reputation systems based on cooperative feedbacks of past transaction information. We find existing popular feedback systems do not provide sustained incentives for sellers to behave honestly over time. We propose a new design of reputation system based on exponential smoothing. This mechanism is shown to be more robust compared to the existing systems. We relax the assumption of a static product value and have implemented a two-level exponential smoothing policy to process and aggregate reputation information. The simulation results show that the policy can serve as a sustained incentive mechanism for the seller.