Business Research and Data Mining: a Bibliometric Analysis

Abstract

The association between Business Research and Data Mining Techniques (DM) has grown considerably, providing opportunities for systematic and bibliometric evaluations. Despite this, no bibliometric study has yet been conducted on this subject. To address this gap, we used bibliometric analysis to statistically evaluate published studies and measure their impact within the scientific community. Our analysis involved 1937 Scopus indexed articles from Data Mining related Business research (DMBR) fields authored by 4560 researchers between 1997 and 2022. We utilized the R data analysis package, bibliometrix, to conduct an extensive qualitative and quantitative analysis. Our findings included insights on the most influential authors and journals, theoretical foundations, themes, and current research trends within DM and its impact on business issues. Furthermore, we examined the evolution of research streams and trends in DMBR areas and identified several potential avenues for future research.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 14 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.