Crowd Management Research Mapping Using Citation Data and Bibliometrics Analysis
DOI:
https://doi.org/10.14456/jiskku.2023.20Keywords:
Crowd management, Bibliometrics analysis, Citation analysis, Co-citation analysis, Knowledge map analysisAbstract
Purpose: To analyze research trends, related research fields, knowledge clusters, and the researcher network in crowd management research by using citation data and Bibliometrics analysis.
Methodology: A mixed method of quantitative and qualitative examination was applied for this study by using bibliometrics and content analysis. A content analysis based on the highly cited articles in each research knowledge cluster. The bibliography data including abstracts and citation information were collected from Web of Science (WoS) on the topic “Crowd Management” with a total of 4,675 records obtained. Afterward, the statistical methods were applied to analyze and evaluate the research knowledge clusters using the bibliographic analysis program namely Clarivate and CiteSpace for citation information, author, and document co-citation examination. A Gephi was used to visualize knowledge and scholar networks in this research area.
Findings: Crowd management research has been increasing steadily. The various research categories have been involved in crowd management research such as Engineering electrical, computer science and information system, communication, and management. The research knowledge clusters combine with 11 major clusters including crowdsourcing, crowd evacuation, resource management, emergency department, social carrying capacity, crowd counting, deep learning, kinetic theory, growth, pattern, and stochastic geometry. The influential author in this research field was Jing-hong Wang. The present findings are useful for public policymakers in crowd management by incorporating computer technology, communications, and management into a policy for effective crowd management.
Applications of this study: The researchers and related organizations involved in crowd management can review the relevant knowledge in this study to develop effective crowd management methods. In addition, this research conceptual framework can be applied to study knowledge maps and be a guideline for reviewing relevant literature in other specific research fields.
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