GLOBAL RESEARCH TRENDS ON BAYESIAN STATISTICS IN ENGINEERING BASED ON DIMENSIONS DATABASE

Abstract

This study maps research trends and identifies potential avenues for novelty in the application of Bayesian statistics to engineering. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, 336 articles published between 2004 and 2023 were retrieved from the Dimensions database and examined using bibliometric techniques implemented in VOSviewer. The findings indicate a sustained growth in citations related to Bayesian Statistics in Engineering (BSE), reflecting increasing scholarly attention. SDG-based classification shows that Good Health and Well-Being is the most represented category, while Applied Mechanics and Materials contributes the largest number of publications. Furthermore, keyword co-occurrence analysis identifies eight thematic clusters, revealing the intellectual structure of the field and potential research opportunities. Overlay visualization illustrates the temporal evolution of research themes, whereas density visualization highlights comparatively underexplored topics. Co-authorship analysis further reveals 33 collaboration clusters, providing insights into the research network. Collectively, these findings offer a structured overview of the BSE research landscape and may support future research planning. Nevertheless, because the analysis relies exclusively on the Dimensions database, the results should be interpreted with caution. Future studies could incorporate additional databases, including Web of Science and Scopus, to improve the comprehensiveness of bibliometric coverage.