Purpose This paper aims to identify knowledge risk components. The present research also tends to determine the relationship between knowledge risk components, the importance of each component and the final ranking of components. Design/methodology/approach This is applied research regarding type, as well as being a descriptive, analytical study regarding performance; it is done according to the opinion of experts. Library studies are applied to extract knowledge risk components. After extracting components, components were screened using the interview technique. In addition, network analytical process method has been used for considering the interrelationship of components and determining their values. Findings After making the required analysis and studies, a total of 17 knowledge risk components were identified in four clusters. The four clusters include knowledge cluster, knowledge map cluster, organization cluster and expert cluster. It is to be noted that the extracted components are prioritized in each cluster. In the regarded case study, different parts of the organization have been evaluated in terms of exposure to knowledge risk. Originality/value Identifying the knowledge risk components enables the organization for moving toward the implementation of the knowledge management system and informing the organization in connection with risk aversion. In fact, such components provide the chance for the organization to identify risks inherent in each department of any organization and develop the necessary measures to reduce the risk in risky areas.

Purpose This paper aims to present a specific model and method for analyzing the knowledge domains and organization knowledge map. One of the functions of the organizational knowledge map is the possibility of extracting the risk of the organization's knowledge domains and thus the ability to define knowledge-based strategies in the organization. So far, various software tools have been designed to support the process of creating, analyzing knowledge domains and structure knowledge map. However, software companies have less detail and methodology of their software analysis and less research has been addressed. Design/methodology/approach This model calculates the risk of knowledge domains using the recursive algorithm approach, assuming there is one-way communication between the knowledge domains and using specific factors. Findings The prominence of this model is to calculate knowledge domains risk, dynamic updating of knowledge domains risk after any changes in knowledge domain risk in the organization's knowledge map. The model can also be used as a simulation model and prioritize corrective actions. Originality/value This is a recursive model that by assuming one-way relations among knowledge domain computes the risk of each domain knowledge by considering the risk of its related domains, relations among different domains and pre-requisites and post-requisites. This model has no limitation in determining the number of knots and communications. Despite of simplicity, it is too efficient and any organization can localize it based on its own needs.