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    Capability model for open data: An empirical analysis


    Zeleti, Fatemeh Ahmadi and Ojo, Adegboyega (2018) Capability model for open data: An empirical analysis. In: ICEGOV '18: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance. Association for Computing Machinery (ACM), pp. 403-411. ISBN 9781450354219

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    Abstract

    Creating superior competitiveness is central to open data organization’s survivability in the fast changing and competitive open data market. In their quest to develop and increase competitiveness and survivability, many of these organizations are moving towards developing open data capabilities. Researchbased knowledge on open data capabilities and how they relate to each other remains sparse, however, with most of the open data literature focusing on social and economic value of open data, not capabilities required. By exploring the related literature on business and organizational capabilities and linking the findings to the empirical evidence collected through the survey of 49 open data organizations around the world, this study develops an open data capability model. The model emerged from our deductive research process improves both theoretical and practical understanding of open data capabilities and their relationships required to help increase competitiveness and survivability of these types of organizations.
    Item Type: Book Section
    Additional Information: Cite as: F. Zeleti, A. Ojo. 2018. Capability Model for Open Data: An Empirical Analysis. In Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance, Galway, Ireland, April 2018 (ICEGOV’18), 9 pages. DOI: 10.1145/3209415.3209492
    Keywords: Open Data Organizations; Big Data Capability Model; Value Capability; Dynamic Capability; Competitive Capability; Types of Capabilities;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 13378
    Identification Number: 10.1145/3209415.3209492
    Depositing User: Adegboyega Ojo
    Date Deposited: 02 Oct 2020 16:10
    Publisher: Association for Computing Machinery (ACM)
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/13378
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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