Improving the Accuracy of Business-to-Business (B2B) Reputation Systems Through Rater Expertise Prediction
Digital ecosystems rely on reputation systems in order to build trust and to foster collaborations among users. Reputation systems are commonplace in the C2C and B2C contexts, however, they have not yet found mainstream acceptance in B2B environments. The authors' first contribution in this paper is to identify the particularities of feedback collection in B2B reputation systems. An issue that they identify is that the reputation target in the B2B context is a business, which requires evaluation on a large number of criteria. They observe that due to the wide variation in user expertise, feedback forms that require users to evaluate all criteria have significant negative consequences for rating accuracy.