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dc.contributor.advisorOjo, Adegboyega
dc.contributor.authorAhmadi Zeleti, Fatemeh
dc.date.accessioned2018-07-31T14:08:21Z
dc.date.issued2018-07-31
dc.identifier.urihttp://hdl.handle.net/10379/7450
dc.description.abstractOpen data is increasingly becoming an essential asset for many organizations. Large numbers of new start-ups are emerging to benefit from the potential of this asset for a wide range of new products and services. However, despite of significant advances in open data technical and infrastructure capabilities, large numbers of organizations fall short when it comes to utilizing open data effectively. Consequently, they fail to fully leverage the potential of open data. There are ample evidences that this shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. The thesis addresses this knowledge gap by investigating capability areas and specific capabilities that are important for generating value from open data, enabling and improving agility and competitive advantage of organizations using open data as one of their key resources to meet their mission goals. In addition, the thesis explores the relationships among the capability areas and the structure of the dependencies among these areas. We adopt a Design Science Research Approach with a theoretical foundation constructed from the integration of Capability-based Theory and Dynamic Capability Theory. Guided by extant literature, data from a global survey of open data organizations and in-depth interviews of leadership of these organizations were analyzed based on the developed theoretical model to identify specific capabilities associated with each capability areas and how these capability areas impact one another. Structural modelling technique was employed to refine these relationships into a layered architecture specifying the dependencies among the capability areas. The structural analysis performed also enables the determination of the nature of these capability areas. Findings from the thesis do not only help validate and refine Capability-based Theory and Dynamic Capability Theory in the open data organization; they reveal hitherto unknown knowledge regarding how the capability areas affect one another in these organizations. From the practical standpoint, the resulting architecture has the potential to transform capability management practices in open data organizations towards greater competitiveness through more flexibility and increased value generation.en_IE
dc.publisherNUI Galway
dc.subjectopen dataen_IE
dc.subjectopen data organizationsen_IE
dc.subjectcapability modelen_IE
dc.subjectcapability frameworken_IE
dc.subjectcapability architectureen_IE
dc.subjectopen data capabilityen_IE
dc.subjectstructural modelingen_IE
dc.subjectqualitative studyen_IE
dc.subjectdesign science researchen_IE
dc.subjectopen data capability frameworken_IE
dc.subjectcompetitive advantageen_IE
dc.subjectdynamic capabilityen_IE
dc.subjectcompetitive capabilityen_IE
dc.subjectvalue capabilityen_IE
dc.subjectcreating value from open dataen_IE
dc.titleCapability architecture for open dataen_IE
dc.typeThesisen
dc.contributor.funderScience Foundation Irelanden_IE
dc.local.noteLarge numbers of organizations fail to effectively use open data and fully leverage the potential of it as they often do not know and have the capability to conduct data related activities. To address this knowledge gap, in this thesis, we study and investigate open data capabilities and how they relate to each other architecturally.en_IE
dc.description.embargo2019-07-31
dc.local.finalYesen_IE
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/
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