Determining the optimal reporting strategy in competitive e-marketplaces

• Main Authors: Noorian, Zeinab, Zhang, Jie, Fleming, Michael, Marsh, Stephen
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer systems organization::Special-purpose and application-based systems
• Online Access: https://hdl.handle.net/10356/101246; http://hdl.handle.net/10220/16755
• Institution: Nanyang Technological University

In a reputation system for multiagent based electronic marketplaces where the number of high quality products provided by good selling agents is unlimited, buying agents often share seller information without the need to consider possible utility loss. However, when those good sellers have limited inventory, buyers may have to be concerned about the possibility of losing the opportunity to do business with the good sellers if the buyers provide truthful information about sellers, due to the competition from other buyers. In this paper, we propose an adaptive mechanism built on a game theoretic basis for buyers to determine their optimal reputation reporting strategy, by modeling both the competency and willingness of other buyers in reporting seller reputation and strategically choosing reporting behaviours that maximize their utility according to the modeling results. The results of the experiments carried out in a simulated competitive e-marketplace confirm that our proposed mechanism leads to better utility for buyers in such an environment.