Related Experiment Video
Updated: Sep 21, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
A Bibliometric Analysis of Knowledge-Hiding Research
Qing Xia1, Shumin Yan1, Heng Li2
1School of Economics and Management, Tongji University, Shanghai 200092, China.
Knowledge hiding, intentionally concealing information, is a growing research area in management and psychology. This study analyzes 243 articles to map the field's progress and key topics for future research.
Area of Science:
- Management
- Psychology
- Business
Background:
- Knowledge hiding is an intentional concealment of requested information.
- It is distinct from knowledge sharing and requires conceptual clarification.
- Research in this field has rapidly expanded in the last decade.
Purpose of the Study:
- To clarify the concept of knowledge hiding.
- To explore the research progress and development trends.
- To provide a panoramic view of the field for future researchers.
Main Methods:
- Bibliometric analysis of 243 relevant articles.
- Descriptive analysis.
- Keyword analysis.
- Citation analysis.
Main Results:
- Knowledge hiding research is rapidly growing, particularly in management, business, and psychology.
- The analysis provides insights into publication performance and thematic evolution.
- Science maps illustrate influential topics within the field.
Conclusions:
- The systematic review offers a comprehensive overview of knowledge hiding research.
- It aids future authors in focusing their research more effectively.
- Understanding knowledge hiding is crucial in organizational and psychological contexts.
More Related Videos
05:47Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
07:50Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
Published on: April 18, 2025
Related Concept Videos
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Hindsight Biases
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Social Proof
Social Loafing
Epistasis Analysis