A Bayesian Reputation System for Virtual Organizations

Abstract

Virtual Organizations (VOs) are an emerging business model in today's Internet economy. Increased specialization and focusing on an organization's core competencies requires such novel models to address business opportunities. In a VO, a set of sovereign, geographically dispersed organizations temporarily pool their resources to jointly address a business opportunity. The decision making process determining which potential partners are invited to join the VO is crucial with respect to entire VO's success. The possibility of a VO partner performing badly during the VO's operational phase or announcing bankruptcy endangers the investment taken in integrating their processes and infrastructure for the purpose of the VO. A reputation system can provide additional decision support besides the a priori knowledge from quotations and bidding to avoid events such as VO partner replacement by helping to choose reliable partners in the first place. To achieve this, reputation, an objective trust measure, is optimally aggregated from multiple independent trust sources that inherently characterize an organization's reliability. To allow for the desired predictions of an organization's future performance, a stochastic modeling approach is chosen. The paper will present a taxonomy of TIs for VO environments, a stochastic model to maintain and aggregate trust sources, so called Trust Indicators, and the inclusion of other subjective measures such as feedback.