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    Agile mechanisms for open data process innovation in public sector organizations: Towards theory building


    Zeleti, Fatemeh Ahmadi and Ojo, Adegboyega (2019) Agile mechanisms for open data process innovation in public sector organizations: Towards theory building. In: Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance. Association for Computing Machinery, New York, United States, pp. 164-174. ISBN 9781450366441

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    Abstract

    Process innovation in public organizations is widely documented and has increasingly been the subject of empirical scrutiny. However, no study has attempted to investigate process innovation in open data organizations in public sector. Guided by the Dynamic Capability Theory and based on the detailed study of four open data organizations, we synthesize a theoretical model and a process model for open data process innovation in public sector organizations. Specifically, the study sought to understand how open data process agility is achieved in these organizations. The results highlight the specific agile mechanisms that enable and improve open data process innovation in public sector organizations. The results also provide perspectives on how open data organizations in public sector can change data processes to transform the way they respond to changing demands and external environment.

    Item Type: Book Section
    Additional Information: Cite as: Fatemeh Ahmadi Zeleti and Adegboyega Ojo. 2019. Agile Mechanisms for Open Data Process Innovation in Public Sector Organizations: Towards Theory Building. In Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance (ICEGOV2019). Association for Computing Machinery, New York, NY, USA, 164–174. DOI:https://doi.org/10.1145/3326365.3326387
    Keywords: Process Innovation; Open Data; Open Data Processes; Data Processes; Public Sector Organization; Agile Mechanisms;
    Academic Unit: Faculty of Social Sciences > School of Business
    Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Item ID: 14353
    Identification Number: https://doi.org/10.1145/3326365.3326387
    Depositing User: Adegboyega Ojo
    Date Deposited: 20 Apr 2021 14:36
    Publisher: Association for Computing Machinery
    Refereed: Yes
    URI:

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