Big data provides significant benefits across various sectors, including commerce. However, there remained a gap in bibliometric studies examining big data within the context of commerce, leaving research development in this field unclear. This study aimed to address this gap by conducting a bibliometric investigation into researchers' contributions to big data in commerce, including their affiliations and countries of origin. Additionally, the study sought to identify the most productive journals and highlight relevant and under-researched topics within this field. A bibliometric analysis approach was employed, analyzing 396 Scopus-indexed documents and using VOSviewer visualization to identify major recurring issues in the literature. The findings revealed that in 2021, the number of publications on big data in commerce peaked at 97 documents. Maalla, A., from Guangzhou College of Technology and Business, China, emerged as the most prolific author, while China led in publication output with 308 documents. The Journal of Physics Conference Series was identified as the most productive source. Computer Science was the most explored discipline, indicating a strong integration of technology with commerce. Keyword analysis divided research focus into four main clusters: analytical technology, platform optimization, supply chain management, and marketing strategy optimization. These findings provide a foundation for future research to explore areas such as Customer Experience Management, Blockchain Technology, Cloud Computing, Predictive Analytics, and Customer Segmentation, thereby enriching the academic literature and offering practical contributions to data-driven commerce.
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