Identifying Essential Components Affecting Intelligent Knowledge Extraction in Organizations: A Meta-Synthesis

Document Type : Original Article

Authors

1 Ph.D. Student in Knowledge and Information Science -Knowledge Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Knowledge and Information Science, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

3 Assistant Professor, Knowledge and Information Science Department, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran

4 Associate Professor, Department of Computer Science, Faculty of Mathematics, Tarbiat Modares University, Tehran, Iran

Abstract

Purpose: The importance of smartening in industrial business processes has increased significantly in recent years. On the other hand, the importance of knowledge as a competitive advantage continues growing. The purpose of this article is to identify the essential components affecting the intelligent extraction of knowledge in organizations.
Method: This Meta-synthesis study was performed by Sandelowski & Barroso seven-step method. 280 research articles were retrieved from the database, of which 32 articles were used for research purposes. Each selected research paper reported one or more components that were analyzed separately.
Findings: 48 codes were classified into 6 main topics ("Individual factors", "Education and learning", "Technology and intelligent technology factors", "Knowledge", "Dynamics and agility", "Organizational factors"). The results show that "empowering people in business" is one of
the most important components of knowledge acquisition, the strengthening of which can lead
to intelligent knowledge extraction. By empowering employees and studying the way they
think and work in the organization, intelligent models for performing tasks can be defined, and
this can lead to the extraction of useful knowledge. In other words, the greater the ability of employees, the study of human behavior in the workplace leads to the discovery of stronger intelligent patterns.
Conclusion: There is no organized study on the components affecting intelligent extraction of knowledge, and this is the first study in this field to classify topics into an organized framework for intelligent extraction of knowledge and find appropriate solutions for businesses.
 

Keywords

Main Subjects

References

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Sciences and Techniques of Information Management
Volume 9, Issue 2
July 2023
Pages 167-200

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