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Bitcoin Research in Business and Economics: A Bibliometric and Topic Modeling Review

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dc.contributor.authorJung, Hae Sun-
dc.contributor.authorLee, Haein-
dc.date.accessioned2026-01-07T03:00:11Z-
dc.date.available2026-01-07T03:00:11Z-
dc.date.issued2025-12-
dc.identifier.issn2674-1032-
dc.identifier.issn2674-1032-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/62701-
dc.description.abstractThis study conducts a bibliometric review of Bitcoin research in the Business and Economics domains, using VOSviewer to visualize network structures and Bidirectional Encoder Representations from Transformers Topic (BERTopic) to derive semantically coherent topic clusters. The analysis identifies five major research themes: (1) Diversification, hedging, and safe-haven properties; (2) Market dynamics, efficiency, and investor behavior; (3) Bitcoin price and volatility prediction attempts; (4) Environmental impact of Bitcoin; and (5) Financial impact of Central Bank Digital Currency (CBDC). Based on these themes, the study recommends further investigation into the influence of Exchange-Traded Fund (ETF) approvals, regulatory frameworks, and institutional investor participation on Bitcoin's safe-haven potential; the role of market dynamics and regulatory interventions; early detection of herding behavior and price bubbles; the integration of machine learning and deep-learning models for price prediction; the environmental costs associated with mining; and the evolving regulatory and implementation challenges of CBDCs. Overall, this review synthesizes existing scholarship and outlines future research directions for the rapidly evolving cryptocurrency ecosystem.-
dc.format.extent37-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleBitcoin Research in Business and Economics: A Bibliometric and Topic Modeling Review-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/fintech4040068-
dc.identifier.scopusid2-s2.0-105025964682-
dc.identifier.wosid001647171600001-
dc.identifier.bibliographicCitationFinTech, v.4, no.4, pp 1 - 37-
dc.citation.titleFinTech-
dc.citation.volume4-
dc.citation.number4-
dc.citation.startPage1-
dc.citation.endPage37-
dc.type.docTypeReview-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryBusiness, Finance-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryEconomics-
dc.subject.keywordPlusSAFE HAVEN PROPERTY-
dc.subject.keywordPlusCOVID-19 EVIDENCE-
dc.subject.keywordPlusCENTRAL BANK-
dc.subject.keywordPlusPRICE-
dc.subject.keywordPlusGOLD-
dc.subject.keywordPlusVOLATILITY-
dc.subject.keywordPlusDYNAMICS-
dc.subject.keywordPlusHEDGE-
dc.subject.keywordPlusCONNECTEDNESS-
dc.subject.keywordPlusINEFFICIENCY-
dc.subject.keywordAuthorbitcoin-
dc.subject.keywordAuthorcryptocurrency-
dc.subject.keywordAuthorbibliometric analysis-
dc.subject.keywordAuthortopic modeling-
dc.subject.keywordAuthorG11-
dc.subject.keywordAuthorG12-
dc.subject.keywordAuthorG14-
dc.subject.keywordAuthorG18-
dc.subject.keywordAuthorE42-
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