• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    An orchestration approach to smart city data ecosystems 
    •   QMRO Home
    • School of Business and Management
    • School of Business and Management
    • An orchestration approach to smart city data ecosystems
    •   QMRO Home
    • School of Business and Management
    • School of Business and Management
    • An orchestration approach to smart city data ecosystems
    ‌
    ‌

    Browse

    All of QMROCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    ‌
    ‌

    Administrators only

    Login
    ‌
    ‌

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    An orchestration approach to smart city data ecosystems

    View/Open
    Accepted version
    Embargoed until: 2021-07-09
    Volume
    153
    DOI
    10.1016/j.techfore.2020.119929
    Journal
    Technological Forecasting and Social Change
    ISSN
    0040-1625
    Metadata
    Show full item record
    Abstract
    © 2020 Elsevier Inc. Research on smart cities has illustrated the use of data analytics, open data, smart sensors and other data-intensive applications that have significant potential to transform urban environments. As the complexity and intensity of these projects has increased, there is a need to understand smart city data ecosystems as an integrated view of data applications by the various city entities that operate within an institutional environment. This paper examines how authorities involved in such ecosystems coordinate data initiatives from an orchestration perspective. A case study of London's city data initiatives highlights the challenges faced in complex city data environments and the importance of an integrated view. Three elements of orchestration in smart city data ecosystems – namely openness, diffusion and shared vision– are identified as the main enablers of city data initiatives within London's local government authorities. The study contributes to our theoretical understanding of orchestration within data ecosystems, as well as the social and technological impacts of city data.
    Authors
    Gupta, A; Panagiotopoulos, P; Bowen, F
    URI
    https://qmro.qmul.ac.uk/xmlui/handle/123456789/62578
    Collections
    • School of Business and Management [525]
    Copyright statements
    © 2020 Elsevier Inc. All rights reserved.
    Twitter iconFollow QMUL on Twitter
    Twitter iconFollow QM Research
    Online on twitter
    Facebook iconLike us on Facebook
    • Site Map
    • Privacy and cookies
    • Disclaimer
    • Accessibility
    • Contacts
    • Intranet
    • Current students

    Modern Slavery Statement

    Queen Mary University of London
    Mile End Road
    London E1 4NS
    Tel: +44 (0)20 7882 5555

    © Queen Mary University of London.