Trusting Review Mechanisms in Knowledge Management Systems: Antecedents, Outcomes, and the Role of Perceived Risk

In recent years, the success of social media in the private realm has entailed an increasing awareness of opportunities that are linked to user-generated content in knowledge management systems. Alongside the benefits in terms of knowledge quantity, new quality risks arise from an unregulated knowledge contribution. Considering that, review mechanisms have been implemented to monitor the content and provide a basis to distinguish between good and poor quality knowledge assets. This paper proposes a model to uncover the role of trust in expert and peer reviews during the knowledge application process by considering its antecedents, its outcomes, and the influence of perceived risk. The model suggests that trust in expert and peer reviews is based on the ability, benevolence, and integrity of the respective group and is positively influenced by a higher trustor’s propensity to trust. Perceived risk in a particular situation influences the decision whether to apply knowledge based on trust in expert or in peer reviews. It is assumed that high-risk decisions are based on expert reviews more likely because the organizational and individual risk is perceived to be lowered, whereas peer reviews can only mitigate organizational risk.