Bibliometric analysis reveals increasing research in big data analytics and decision making, highlighting trends and global contributions.
This bibliometric analysis explores the research landscape of leveraging Big Data Analytics (BDA) for decision-making, covering publications from 2019 to 2024. The study systematically reviews 1,013 articles retrieved from the Scopus database to identify key research trends, influential contributions, and the geographical distribution of research output. The findings reveal a significant increase in BDA research post-2020, driven by advancements in the Internet of Things (IoT), machine learning, and the heightened need for data-driven decision-making during the COVID-19 pandemic. India, the United States, and China are identified as leading contributors, with substantial international collaborations enriching research quality and impact. The analysis highlights the predominance of computer science, engineering, and decision sciences in advancing BDA capabilities. High citation counts of key authors underscore their pivotal roles in shaping the field. This study underscores BDA's critical role in enhancing operational efficiency and strategic decision-making, providing a robust framework for navigating complex environments. Future research should focus on addressing data quality challenges, enhancing governance structures, and integrating emerging technologies to maximize BDA's potential.
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Chikon et al. (2025) studied this question.
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