Interconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data

dc.contributor.authorWeibl, Johannes
dc.date.accessioned2019-01-03T00:43:24Z
dc.date.available2019-01-03T00:43:24Z
dc.date.issued2019-01-08
dc.description.abstractIn recent years, organizations manage an increasing amount of data in order to make better decisions, personalize products, or sell data. By data being combined from various sources, data assets interact with each other. When the interactions are synergistic, they create greater benefits than the sum of the value of the individual data assets. This study explores enablers, mechanisms, and potential outcomes of synergistic interactions among data assets. Based on systems theory and a synthesis of relevant synergy literature, I developed an initial synergy framework in a data context. On this basis, I conducted 14 qualitative interviews to assess the validity of my initial framework. The interview results assisted me in refining and contextualizing a unified conceptual framework of data synergies. The paper reveals that compatibility and contextual relatedness as enablers and informational complementary as a mechanism can lead to super-additive information value among data assets.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.711
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/60025
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBusiness Intelligence, Business Analytics and Big Data: Innovation, Deployment and Management
dc.subjectOrganizational Systems and Technology
dc.subjectData, Synergy, Informational Complementarity, Systems Theory, Thematic Analysis
dc.titleInterconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data
dc.typeConference Paper
dc.type.dcmiText

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