Exploring the Predictive Analytics Frontier in Business: A Bibliometric Journey

Abstract

Predictive analytics has gained significant attention in business as organizations seek to leverage data-driven insights for informed decision-making. The study uses rigorous bibliometric analysis to map the landscape of predictive analytics in business, revealing its evolution, trends, and research tendencies. A sizeable selection of academic publications from the Scopus database is chosen to identify key themes, notable authors, well-known journals, and emerging research areas in predictive analytics. The study extracts and analyses bibliographic data, including publication trends, citation patterns, and co-authorship networks, using cutting-edge tools like CiteSpace, VOSviewer, and Biblioshiny. The findings of this study provide important information regarding how predictive analytics are now being employed in the business sector. The most significant research findings, innovative breakthroughs, and major research clusters are highlighted, exposing the leading research paths and areas of interest. Additionally, emerging trends, cross-disciplinary collaborations, and potential research needs are identified in the study. The intellectual landscape of predictive analytics in business is mapped in this study to offer a comprehensive picture of the corpus of knowledge. This information will help scholars, practitioners, and policymakers navigate and contribute to this fast-developing area. The insights gained from this bibliometric analysis can guide future research endeavors, inform strategic decision-making, and foster stakeholder collaboration in leveraging predictive analytics for business success.