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Big data analytics applications in information management driving operational efficiencies and decision-making: mapping the field of knowledge with bibliometric analysis using R

Ragazou Konstantina, Passas Ioannis, Garefalakis Alexandros, Galariotis Emilios, Zopounidis Konstantinos

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URIhttp://purl.tuc.gr/dl/dias/C62F343D-C423-4770-A9FC-7031147B5907-
Identifierhttps://doi.org/10.3390/bdcc7010013-
Identifierhttps://www.mdpi.com/2504-2289/7/1/13-
Languageen-
Extent28 pagesen
TitleBig data analytics applications in information management driving operational efficiencies and decision-making: mapping the field of knowledge with bibliometric analysis using Ren
CreatorRagazou Konstantinaen
CreatorPassas Ioannisen
CreatorGarefalakis Alexandrosen
CreatorGalariotis Emiliosen
CreatorZopounidis Konstantinosen
CreatorΖοπουνιδης Κωνσταντινοςel
PublisherMDPIen
Content SummaryOrganizations may examine both past and present data with the aid of information management, giving them access to all the knowledge they need to make sound strategic choices. For the majority of contemporary enterprises, using data to make relevant, valid, and timely choices has become a must for success. The volume and format of data have changed significantly over the past few years as a result of the development of new technologies and applications, but there are also impressive possibilities for their analysis and processing. This study offers a bibliometric analysis of 650 publications written by 1977 academics on the use of information management and big data analytics. The Bibliometrix function in the R package and VOSviewer program were used to obtain the bibliographic data from the Scopus database and to analyze it. Based on citation analysis criteria, the top research journals, authors, and organizations were identified. The cooperation network at the author level reveals the connections between academics throughout the world, and Multiple Correspondence Analysis (MCA) identifies the research holes in the area. The recommendations for further study are influenced by the findings.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2025-07-10-
Date of Publication2023-
SubjectAgile managementen
SubjectBusiness modelen
SubjectData analyticsen
SubjectDecision-makingen
SubjectEfficiencyen
SubjectInformation managementen
SubjectOperational performanceen
SubjectSMEsen
Bibliographic CitationK. Ragazou, I. Passas, A. Garefalakis, E. Galariotis and C. Zopounidis, “Big data analytics applications in information management driving operational efficiencies and decision-making: mapping the field of knowledge with bibliometric analysis using R,” Big Data Cogn. Comput., vol. 7, no. 1, Jan. 2023, doi: 10.3390/bdcc7010013.en

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