Iranian Journal of Information Processing and Management

Iranian Journal of Information Processing and Management

A Comprehensive framework for factors affecting the knowledge network with a meta-synthesis approach

Document Type : Original Article

Authors
1 Mazandaran University of Medical Sciences
2 Professor Emeritus; Department of Knowledge and Information Science; Faculty of Education & Psychology; Shahid Chamran University of Ahvaz
3 Associate Professor; Department of Knowledge and Information Science; Faculty of Psychology and Educational Sciences; Shahid Chamran University of Ahvaz
4 Associate Professor; Department of Knowledge and Information Science, Faculty of Literature and Human Sciences; Razi University;
Abstract
Despite the existence of a lot of research in the field of knowledge network, so far no research has been done that can provide a comprehensive framework of the factors affecting the knowledge network. In this study, 2306 related scientific texts in the period before 2022 were selected from valid databases, which were evaluated using the meta-synthesis method and inclusion and exclusion criteria. Finally, 30 studies were evaluated in line with the goal. As a result of analyzing the collected data, 7 dimensions (intra-organizational, inter-organizational, knowledge management system, knowledge network infrastructure, individual factors, external environment and results) and 38 components affecting the knowledge network were identified. In the next step, using the Shannon entropy analysis method, the support of previous studies for dimensions and components was examined. Among the dimensions, intra-organizational dimension and individual factors, and among the components, the organizational structure supporting the knowledge network and the knowledge-based organizational culture were the most important.
The results of this study can be a good tool to identify the factors affecting the knowledge network and also to evaluate the strengths and weaknesses of existing knowledge networks, so organizations can use the results of this research to design and evaluate the knowledge network.
Keywords
Subjects

فهرست منابع
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  • Receive Date 18 May 2022
  • Revise Date 06 September 2024
  • Accept Date 01 June 2022