2017
DOI: 10.1108/jkm-07-2015-0300
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Big data systems: knowledge transfer or intelligence insights?

Abstract: Purpose This paper aims to bring together the existing theory from knowledge management (KM), competitive intelligence (CI) and big data analytics to develop a more comprehensive view of the full range of intangible assets (data, information, knowledge and intelligence). By doing so, the interactions of the intangibles are better understood and recommendations can be made for the appropriate structure of big data systems in different circumstances. Metrics are also applied to illustrate how one can identify an… Show more

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Cited by 96 publications
(56 citation statements)
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References 57 publications
(60 reference statements)
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“…A closely connected third cluster (N = 40) focused on how knowledge and information can be strategically developed, managed and leveraged in organizations (e.g. Erickson and Rothberg, 2013), and the role of BDA therein (Rothberg and Erickson, 2017;Tsui et al, 2014;Wang et al, 2013). Next, five smaller clusters were identified.…”
Section: Resultsmentioning
confidence: 99%
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“…A closely connected third cluster (N = 40) focused on how knowledge and information can be strategically developed, managed and leveraged in organizations (e.g. Erickson and Rothberg, 2013), and the role of BDA therein (Rothberg and Erickson, 2017;Tsui et al, 2014;Wang et al, 2013). Next, five smaller clusters were identified.…”
Section: Resultsmentioning
confidence: 99%
“…On the other hand, Murray et al (2016)as well as Uden and He (2017) take a look at IoT devices and how they can enhance knowledge management systems because of the data that are automatically generated. A strict theoretical view can be found with Rothberg and Erickson (2017), who mean to bring together the existing theory from knowledge management, competitive intelligence and BD analytics. One article is quite critical of the use of BD and elucidates that "to describe it [BD in the context of knowledge management] as 'revolutionary' is premature" (Tian 2017, p. 113).…”
Section: Knowledge Managementmentioning
confidence: 99%
“…Para intentar precisar términos como datos, información y conocimiento, que utilizaremos con frecuencia más adelante, hacemos uso del modelo DIKW (por sus siglas en inglés de Data, Information, Knowledge and Wisdom) propuesto por R.L. Ackoff en 1989 [14] y que se ha convertido en propuesta clásica y controvertida de la fundamentación teórica para la gestión del conocimiento ( [15,16] y las referencias allí citadas). Un esquema simplificado del modelo DIKW y las transiciones que se dan en la producción de datos, información, conocimiento e inteligencia, se puede resumir como [17]:…”
Section: La Jerarquía Dikw: Datos-información-conocimiento-inteligenciaunclassified

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