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Microwork platforms as enablers to new ecosystems and business models: the challenge of managing difficult tasks

Author

Listed:
  • Jean-Michel Dalle

    (UPMC - Université Pierre et Marie Curie - Paris 6)

  • Matthijs Den Besten

    (MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier)

  • Catalina Martinez

    (Consejo Superior de Investigaciones Científicas (CSIC), Institute for Public Goods and Policies (IPP), Albasanz 26, 28037 Madrid - affiliation inconnue)

  • Stéphane Maraut

Abstract

We explore how microwork platforms manage difficult tasks in paid crowdsourcing environments. We argue that as human computation becomes more prevalent, notably in the context of big data ecosystems, microwork platforms might have to evolve and to take a more managerial stance in order to provide the right incentives to online workers to handle difficult tasks. We illustrate this first through a name disambiguation experiment on Amazon Mechanical Turk (AMT), a well-known microwork platform, and second through direct analysis of the dynamics of task execution in a dataset of real microwork projects on AMT. We discuss the emergence of more specialised microwork platforms as an attempt to facilitate a better management of difficult tasks in the context of paid crowdsourcing.

Suggested Citation

  • Jean-Michel Dalle & Matthijs Den Besten & Catalina Martinez & Stéphane Maraut, 2017. "Microwork platforms as enablers to new ecosystems and business models: the challenge of managing difficult tasks," Post-Print hal-02009866, HAL.
    • Handle: RePEc:hal:journl:hal-02009866
    DOI: 10.1504/IJTM.2017.085704
    as

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