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dc.contributor.authorAuthorFuentealba, Diego
dc.contributor.authorAuthorFlores-Fernández, Cherie.
dc.contributor.authorAuthorCarrasco, Raúl
dc.date.accessionedDate Accessioned2024-09-03T19:17:45Z
dc.date.availableDate Available2024-09-03T19:17:45Z
dc.date.issuedDate Issued2023
dc.identifier.citationReferencia BibliográficaRevista Española de Documentación Científica, 46(2), 13 p.
dc.identifier.issnISSN0210-0614
dc.identifier.uriURIhttp://repositorio.udla.cl/xmlui/handle/udla/1357
dc.identifier.uriURIhttps://redc.revistas.csic.es/index.php/redc
dc.description.abstractAbstractVUCA is an acronym for volatility, uncertainty, complexity, and ambiguity, used to describe an environment that defies confident predictions. An example of this environment is the Covid-19 pandemic, which has created uncer-tainty worldwide because it is an unknown and highly contagious disease that neither society nor institutions were pre-pared to face. This article aims to describe the scientific production of VUCA to understand its main research focus. This research analyzes 105 documents from the Web of Science (WoS) database using Bibliometrics and Content Analysis. The bibliometric analysis reported several production indexes: annual, personal, national, institutional, and journal productiv-ity. The content analysis analyzed 95 article abstracts in nineteen clusters selected by comparing two clustering methods, Latent Dirichlet Allocation and K-Means, using the coherence and silhouette indices, respectively. VUCA is an emerging topic with increased scientific production in the last four years. However, there are no major producers to date. The most frequent topics are management, leadership, and change, where several works emphasize the role of the leader in deal-ing with change. The literature has focused on understanding the skills needed to cope with a VUCA environment and how to teach them. In addition, the use of two methods based on machine learning techniques to estimate the number of clusters of scientific papers is highlighted as an alternative to splitting articles into topics when the dataset is small.
dc.format.extentdc.format.extent13 páginas
dc.format.extentdc.format.extent358.0Kb
dc.format.mimetypedc.format.mimetypePDF
dc.language.isoLanguage ISOspa
dc.publisherPublisherCSIC Consejo Superior de Investigaciones Científicas
dc.rightsRightsCreative Commons Attribution License (CC BY)
dc.sourceSourcesRevista Española de Documentación Científica
dc.subjectSubjectContent analysis
dc.subjectSubjectK-Means
dc.subjectSubjectLDA
dc.subjectSubjectVUCA
dc.subject.lcshdc.subject.lcshBibliometría
dc.titleTitleVUCA bibliometric and content analysis
dc.title.alternativeAlternative TitleAnálisis bibliométrico y de contenido sobre VUCA
dc.typeDocument TypeArtículo
dc.udla.catalogadordc.udla.catalogadorCBM
dc.udla.indexdc.udla.indexWoS
dc.udla.indexdc.udla.indexScopus
dc.udla.indexdc.udla.indexSocial Sciences Citation Index
dc.udla.indexdc.udla.indexIBZ Online
dc.udla.indexdc.udla.indexLatin America & Iberia Database
dc.udla.indexdc.udla.indexPeriodicals Index Online
dc.udla.indexdc.udla.indexSocial Science Premium Collection
dc.udla.indexdc.udla.indexDIALNET
dc.udla.indexdc.udla.indexDOAJ
dc.udla.indexdc.udla.indexLibrary, Information Science & Technology Abstracts - LISTA
dc.udla.indexdc.udla.indexLibrary Literature and Information Science
dc.identifier.doidc.identifier.doi10.3989/redc.2023.2.1968
dc.facultaddc.facultadFacultad de Ingeniería y Negocios


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