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Factors influencing the decision to crowdsource: A systematic literature review

Author

Listed:
  • Nguyen Hoang Thuan

    (Victoria University of Wellington)

  • Pedro Antunes

    (Victoria University of Wellington)

  • David Johnstone

    (Victoria University of Wellington)

Abstract

Crowdsourcing is currently attracting much attention from organisations for its competitive advantages over traditional work structures regarding how to utilise skills and labour and especially to harvest expertise and innovation. Prior research suggests that the decision to crowdsource cannot simply be based on perceived advantages; rather multiple factors should be considered. However, a structured account and integration of the most important decision factors is still lacking. This research fills the gap by providing a systematic literature review of the decision to crowdsource. Our results identify nine factors and sixteen sub-factors influencing this decision. These factors are structured into a decision framework concerning task, people, management, and environmental factors. Based on this framework, we give several recommendations for managers making the crowdsourcing decision.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:infosf:v:18:y:2016:i:1:d:10.1007_s10796-015-9578-x
    DOI: 10.1007/s10796-015-9578-x
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Nguyen Hoang Thuan & Pedro Antunes & David Johnstone, 2018. "A Decision Tool for Business Process Crowdsourcing: Ontology, Design, and Evaluation," Group Decision and Negotiation, Springer, vol. 27(2), pages 285-312, April.
    2. Schenk, Eric & Guittard, Claude & Pénin, Julien, 2019. "Open or proprietary? Choosing the right crowdsourcing platform for innovation," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 303-310.
    3. Gert-Jan Vreede & Pedro Antunes & Julita Vassileva & Marco Aurélio Gerosa & Kewen Wu, 2016. "Collaboration technology in teams and organizations: Introduction to the special issue," Information Systems Frontiers, Springer, vol. 18(1), pages 1-6, February.
    4. Yiwei Gong, 0. "Estimating participants for knowledge-intensive tasks in a network of crowdsourcing marketplaces," Information Systems Frontiers, Springer, vol. 0, pages 1-19.
    5. Qizhi Tao & Yizhe Dong & Ziming Lin, 0. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    6. Yiwei Gong, 2017. "Estimating participants for knowledge-intensive tasks in a network of crowdsourcing marketplaces," Information Systems Frontiers, Springer, vol. 19(2), pages 301-319, April.
    7. Ma, Yujie & Du, Gang & Jiao, Roger J., 2020. "Optimal crowdsourcing contracting for reconfigurable process planning in open manufacturing: A bilevel coordinated optimization approach," International Journal of Production Economics, Elsevier, vol. 228(C).
    8. Chiara Belletti & Daniel Erdsiek & Ulrich Laitenberger & Paola Tubaro, 2021. "Crowdworking in France and Germany," Working Papers hal-03468022, HAL.
    9. Xu, Hui & Wu, Yang & Hamari, Juho, 2022. "What determines the successfulness of a crowdsourcing campaign: A study on the relationships between indicators of trustworthiness, popularity, and success," Journal of Business Research, Elsevier, vol. 139(C), pages 484-495.
    10. Olivera Marjanovic & Vijaya Murthy, 2022. "The Emerging Liquid IT Workforce: Theorizing Their Personal Competitive Advantage," Information Systems Frontiers, Springer, vol. 24(6), pages 1775-1793, December.
    11. Xuefeng Zhang & Bengang Gong & Yaqin Cao & Yi Ding & Jiafu Su, 2022. "Investigating participants’ attributes for participant estimation in knowledge-intensive crowdsourcing: a fuzzy DEMATEL based approach," Electronic Commerce Research, Springer, vol. 22(3), pages 811-842, September.
    12. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    13. Allahbakhsh, Mohammad & Amintoosi, Haleh & Behkamal, Behshid & Beheshti, Amin & Bertino, Elisa, 2021. "SCiMet: Stable, sCalable and reliable Metric-based framework for quality assessment in collaborative content generation systems," Journal of Informetrics, Elsevier, vol. 15(2).
    14. Evangelos Mourelatos & Manolis Tzagarakis, 2018. "An investigation of factors affecting the visits of online crowdsourcing and labor platforms," Netnomics, Springer, vol. 19(3), pages 95-130, December.

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