نوع مقاله : مقاله پژوهشی
نویسنده
علم اطلاعات و دانش شناسی، ادبیات و علوم انسانی، خلیج فارس بوشهر، ایران.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسنده [English]
Purpose: This study aims to examine the historical trajectory, conceptual evolution, and scientific structure of research on knowledge hiding in organizations, in order to identify its developmental stages, thematic clusters, and geographical patterns of scholarly production.
Method: A descriptive and evaluative bibliometric analysis was employed to explore the scientific landscape of knowledge hiding in organizational contexts. Data were retrieved from the Scopus database due to its interdisciplinary coverage and scholarly reliability. The search was conducted using a keyword query applied to titles, abstracts, and keywords, covering the period from 2003 to 2025. A total of 1,347 documents were initially identified. After the stages of identification, screening, eligibility assessment, and inclusion, data cleaning was performed and duplicate or irrelevant records were removed. Ultimately, 823 relevant documents were selected for final analysis. The data were first saved in RIS format and then converted to CSV. The screening process was conducted using Rayyan QCRI, and data analysis was performed with the Bibliometrix package (within R) to map the conceptual structure, temporal trends, and scientific collaboration networks in this field.
Findings: The results indicate that the field of knowledge hiding has transitioned over the past two decades from a conceptual formation stage (2003–2010) to theoretical maturity (2011–2019), and subsequently to thematic diversification (2020 onward). Co-occurrence analysis revealed four major thematic clusters: behavioral and psychological, organizational and managerial, theoretical and knowledge-based, and technological and data-driven. The collaboration network structure showed that scientific production is mainly concentrated in Asia—particularly China—which holds the highest linkage strength and plays a leading global role in this research domain. Furthermore, conceptual clusters revealed a shift from traditional behavioral analyses toward data-driven and AI-based models.
Conclusion: The field of knowledge hiding has reached a stage of scientific and network maturity but shows signs of theoretical saturation. Its future development depends on theoretical re-examination, the integration of advanced analytical technologies, and the expansion of cross-regional collaborations. Linking knowledge hiding with artificial intelligence, ethical leadership, and open innovation may offer new pathways for advancing both theoretical and practical contributions.
Originality: By mapping the historical, conceptual, and geographical evolution of the knowledge-hiding domain, this study provides a comprehensive understanding of its developmental stages and emerging trends, highlighting future research directions that bridge human-centered and technology-oriented approaches.
کلیدواژهها [English]
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