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A theoretical model of user engagement in crowdsourcing

Author

Listed:
  • Triparna de Vreede

    (University of Nebraska Omaha - University of Nebraska System)

  • Cuong Nguyen

    (University of Nebraska Omaha - University of Nebraska System)

  • Gert-Jan de Vreede

    (University of Nebraska Omaha - University of Nebraska System)

  • Imed Boughzala

    (IMT-BS - DSI - Département Systèmes d'Information - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - EESC-GEM Grenoble Ecole de Management - UEVE - Université d'Évry-Val-d'Essonne - TEM - Télécom Ecole de Management)

  • Onook Oh

    (University of Nebraska Omaha - University of Nebraska System)

  • Roni Reiter-Palmon

    (University of Nebraska Omaha - University of Nebraska System)

Abstract

Social media technology has enabled virtual collaborative environments where people actively interact, share knowledge, coordinate activities, solve problems, co-create value, and innovate. Organizations have begun to leverage approaches and technologies to involve numerous people from outside their boundaries to perform organizational tasks. Despite the success and popularity of this ‘crowdsourcing' phenomenon, there appears to be a distinct gap in the literature regarding the empirical evaluation of the factors involved in a crowdsourcing user experience. This paper aims to fill this void by proposing a theoretical model of the antecedents and their relationships for crowdsourcing user engagement. It is defined as the quality of effort online users devote to collaboration activities that contribute directly to desired outcomes. Drawing from research in psychology and IS, we identify three critical elements that precede crowdsourcing user engagement: personal interest in topic, goal clarity, and motivation to contribute. This paper examines the theoretical basis of these variables of interest in detail, derives a causal model of their interrelationships, and identifies future plans for model testing.

Suggested Citation

  • Triparna de Vreede & Cuong Nguyen & Gert-Jan de Vreede & Imed Boughzala & Onook Oh & Roni Reiter-Palmon, 2013. "A theoretical model of user engagement in crowdsourcing," Grenoble Ecole de Management (Post-Print) hal-01244682, HAL.
    • Handle: RePEc:hal:gemptp:hal-01244682
    DOI: 10.1007/978-3-642-41347-6_8
    Note: View the original document on HAL open archive server: https://hal.science/hal-01244682
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    Citations

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    Cited by:

    1. Prpić, John, 2017. "A Framework for Policy Crowdsourcing," SocArXiv pmfdx, Center for Open Science.
    2. Nguyen Hoang Thuan & Pedro Antunes & David Johnstone, 2016. "Factors influencing the decision to crowdsource: A systematic literature review," Information Systems Frontiers, Springer, vol. 18(1), pages 47-68, February.
    3. Victor Cabral & Willem Winden, 2022. "The reaction of coworking spaces to the COVID-19 pandemic. A dynamic capabilities perspective," Service Business, Springer;Pan-Pacific Business Association, vol. 16(2), pages 257-281, June.
    4. Mathis Poser & Gerrit C. Küstermann & Navid Tavanapour & Eva A. C. Bittner, 2022. "Design and Evaluation of a Conversational Agent for Facilitating Idea Generation in Organizational Innovation Processes," Information Systems Frontiers, Springer, vol. 24(3), pages 771-796, June.
    5. Prpić, John, 2017. "Health Care Crowds: Collective Intelligence in Public Health," SocArXiv 4ca42, Center for Open Science.
    6. Damianos P. Sakas & Dimitrios P. Reklitis, 2021. "The Impact of Organic Traffic of Crowdsourcing Platforms on Airlines’ Website Traffic and User Engagement," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    7. Prpić, John, 2017. "Experiments on Crowdsourcing Policy Assessment," SocArXiv qznpk, Center for Open Science.
    8. Prpić, John, 2017. "MOOCs and Crowdsourcing: Massive Courses and Massive Resources," SocArXiv uwess, Center for Open Science.
    9. Julia Troll & Ivo Blohm & Jan Marco Leimeister, 2019. "Why Incorporating a Platform-Intermediary can Increase Crowdsourcees’ Engagement," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 433-450, August.
    10. Araz Taeihagh, 2017. "Crowdsourcing: a new tool for policy-making?," Policy Sciences, Springer;Society of Policy Sciences, vol. 50(4), pages 629-647, December.

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