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This study employs bibliometric analysis to evaluate 443 scholarly works on the topics of Indonesian Islamic banking published on 194 academic platforms, and authored by 1049 scholars. The machine learning tools i.e., R Studio and VOSviewer were employed to analyse the Scopus’ bibliographical data automatically harvested from the database. We developed four research questions based on the theories that are fundamental to bibliometric study, i.e., performance analysis, citation and co-citation analyses, bibliographic coupling and social network analysis, to identify the most impactful manuscripts, scholarly journals, authors, and institutions of affiliation. We further established the discussion of the current issues in Indonesian Islamic banking topics from the keyword analysis and the bibliographic coupling. These findings derive some recommendations for future research. This study provides a supply of scholarly novelty in the assessment of Indonesian Islamic banking publications which are both practically and theoretically importance to regulators, academia and industry professionals. Acknowledgment The authors would like to thank Bank Indonesia for the funding that made this study possible.
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Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.