Big Data Analytics in Decision Making: A Bibliometric Mapping of Scientific Contributions
DOI:
https://doi.org/10.58812/wsist.v3i02.2187Keywords:
Big Data Analytics, Decision Making, Bibliometric Analysis, VOSviewerAbstract
This study aims to map the intellectual, conceptual, and collaborative landscape of scientific research on Big Data Analytics (BDA) in the context of decision-making using a bibliometric approach. Drawing data from the Scopus database and analyzing it through VOSviewer, the study identifies publication trends, influential authors, high-impact journals, keyword co-occurrence patterns, and international collaboration networks. The results reveal that "big data" serves as the dominant thematic core, often interconnected with concepts such as data analytics, data mining, information management, and artificial intelligence. Temporal and density visualizations indicate a shift in research focus from traditional data management toward intelligent decision support systems and real-time analytics. Additionally, countries such as China, the United States, and the United Kingdom emerge as central actors in shaping global collaboration. The study contributes to the theoretical understanding of the field by highlighting its interdisciplinary nature and provides practical insights for policymakers, academics, and practitioners seeking to leverage BDA for more effective, data-driven decision-making. Limitations and directions for future research are also discussed.
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