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    Crowdsourcing and Crowdfunding Mechanisms for Scientific Research Funding Agencies – A Preliminary Entity Categorisation Matrix (PECM)


    Cullina, Eoin and Conboy, Kieran and Morgan, Lorraine (2014) Crowdsourcing and Crowdfunding Mechanisms for Scientific Research Funding Agencies – A Preliminary Entity Categorisation Matrix (PECM). In: IPP2014: Crowdsourcing for Politics and Policy, 4 - 7 September 2014, Oxford.

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    Abstract

    Research has shown that crowdsourcing and crowdfunding are accelerators and facilitators of societal, business and institutional change, presenting numerous potential benefits to the triple helix of government, industry and university. Scientific Research Funding Agencies play an important role in the triple helix and play an important role in the development and instantiation of public policy. E-participation and e-government platforms have invited a new actor to the triple helix in the form of the crowd. The citizen as a member of the crowd presents potential solutions to public needs. This paper shows that whereas numerous models are available for the private and public use of crowdsourcing and crowdfunding, a limited number of models are available for use by science funding agencies. Accordingly, this research in progress paper attempts to fill this gap by examining the actors involved in the crowd process and presenting a preliminary categorisation of the associated types of users of the crowd. This paper is part of an overall project that focuses on building a suitable crowd model for these agencies. The research herein advances a Preliminary Entity Categorisation Model (PECM) to facilitate this process.

    Item Type: Conference or Workshop Item (Paper)
    Keywords: Crowdsourcing; crowdfunding; citizen science; triple helix; scientific research funding agencies;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 6687
    Depositing User: Lorraine Morgan
    Date Deposited: 16 Dec 2015 14:57
    Refereed: Yes
    Funders: Science Foundation Ireland (SFI), Irish Research Council
    URI:

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