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    A Framework for understanding & classifying Urban Data Business Models


    McLoughlin, Shane and Puvvala, Abhinay and Maccani, Giovanni and Donnellan, Brian (2019) A Framework for understanding & classifying Urban Data Business Models. Hawaii International Conference on System Sciences (HICSS). ISSN 978-0-9981331-2-6

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    Abstract

    Governments’ objective to transition to ‘Smart Cities’ heralds new possibilities for urban data business models to address pressing city challenges and digital transformation imperatives. Urban data business models are not well understood due to such factors as the maturity of the market and limited available research within this domain. Understanding the barriers and challenges in urban data business model development as well as the types of opportunities in the ecosystem is essential for incumbents and new entrants. Therefore, the aim of this paper is to develop a framework for understanding and classifying Urban Data Business Models (UDBM). This paper uses an embedded case study method to derive the framework by analyzing 40 publicly funded and supported business model experiments that address pressing city challenges under one initiative. This research contributes to the scholarly discourse on business model innovation in the context of smart cities.

    Item Type: Article
    Keywords: Framework; understanding; classifying; Urban Data Business Models;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 10520
    Identification Number: hdl.handle.net/10125/59765
    Depositing User: Prof. Brian Donnellan
    Date Deposited: 20 Feb 2019 15:08
    Journal or Publication Title: Hawaii International Conference on System Sciences (HICSS)
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Refereed: Yes
    URI:

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