A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs

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dc.cclicenceCC-BY-NC-NDen
dc.contributor.authorPena, Alejandroen
dc.contributor.authorBonet, Isisen
dc.contributor.authorLochmuller, Christianen
dc.contributor.authorTabares, Marta S.en
dc.contributor.authorPiedrahita, Carlos C.en
dc.contributor.authorSánchez, Carmen C.en
dc.contributor.authorGiraldo, Liliana M.en
dc.contributor.authorGongora, Mario Augustoen
dc.contributor.authorChiclana, Franciscoen
dc.date.acceptance2018-11-01en
dc.date.accessioned2018-11-08T15:02:17Z
dc.date.available2018-11-08T15:02:17Z
dc.date.issued2018-11-30
dc.descriptionThe file attached to this record is the author's final peer reviewed version.en
dc.description.abstractAdvances in technology and an increase in the amount and complexity of data that is generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources require big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e. its capacity in managing big data. The assessment of the maturity of an organization requires multi criteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small and medium-sized enterprises in the healthcare sector (SMEHs). The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies.en
dc.funderN/Aen
dc.identifier.citationPeña, A., Bonet, I., Lochmuller, C., Tabares, M.S., Piedrahita, C.C., Sánchez, C.C., Giraldo, L.M., Góngora, M., Chiclana, F. (2018) A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs. Soft Computing, 23 (20), pp. 10537-10550en
dc.identifier.doihttps://doi.org/10.1007/s00500-018-3625-8
dc.identifier.issn1432-7643
dc.identifier.urihttp://hdl.handle.net/2086/17137
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherSpringeren
dc.researchgroupInstitute of Artificial Intelligence (IAI)en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectBig dataen
dc.subjectHealthcareen
dc.subjectMaturity levelen
dc.subjectELECTRE methoden
dc.subjectFuzzy methodsen
dc.subjectOutrankingen
dc.titleA fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEsen
dc.typeArticleen

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