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Investigating participants’ attributes for participant estimation in knowledge-intensive crowdsourcing: a fuzzy DEMATEL based approach

Author

Listed:
  • Xuefeng Zhang

    (Anhui Polytechnic University)

  • Bengang Gong

    (Anhui Polytechnic University)

  • Yaqin Cao

    (Anhui Polytechnic University)

  • Yi Ding

    (Anhui Polytechnic University)

  • Jiafu Su

    (Chongqing Technology and Business University)

Abstract

In knowledge-intensive crowdsourcing (KI-C), estimating proper participants is an important way to ensure tasks crowdsourcing outcomes. Participants’ attributes (PAs) act as the main decision factors which are viewed as criteria for evaluating and estimating potential participants. Actually, multiple interdependent PAs have effect on participant estimation. It is an initial and vital work in estimating participants in KI-C to identify those PAs and measure their relationships. Consequently, this study first identifies PAs for participant estimation in KI-C by integrating PAs presented in the related academic studies and some practical KI-C sites. Subsequently, this study develops an integrated 2-tuple linguistic method and decision making trial and evaluation laboratory method to describe and measure causal relationships of the identified PAs. Identification of PAs would offer a common list of criteria for participant estimation in KI-C and aid to enrich studies in this field. Additionally, measurement of the PAs’ relationships through causality and prominence can assist requesters and managers of KI-C sites to understand and deal with those PAs in practical.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:elcore:v:22:y:2022:i:3:d:10.1007_s10660-020-09408-1
    DOI: 10.1007/s10660-020-09408-1
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    References listed on IDEAS

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    1. Jasneet Kaur & Ramneet Sidhu & Anjali Awasthi & Satyaveer Chauhan & Suresh Goyal, 2018. "A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 312-332, January.
    2. Yuxiang Zhao & Qinghua Zhu, 2014. "Evaluation on crowdsourcing research: Current status and future direction," Information Systems Frontiers, Springer, vol. 16(3), pages 417-434, July.
    3. 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.
    4. Ford, Robert C. & Richard, Brendan & Ciuchta, Michael P., 2015. "Crowdsourcing: A new way of employing non-employees?," Business Horizons, Elsevier, vol. 58(4), pages 377-388.
    5. Barry L. Bayus, 2013. "Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community," Management Science, INFORMS, vol. 59(1), pages 226-244, June.
    6. Sonja Marjanovic & Caroline Fry & Joanna Chataway, 2012. "Crowdsourcing based business models: In search of evidence for innovation 2.0," Science and Public Policy, Oxford University Press, vol. 39(3), pages 318-332, February.
    7. Christian Terwiesch & Yi Xu, 2008. "Innovation Contests, Open Innovation, and Multiagent Problem Solving," Management Science, INFORMS, vol. 54(9), pages 1529-1543, September.
    8. Tracy Xiao Liu & Jiang Yang & Lada A. Adamic & Yan Chen, 2014. "Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn," Management Science, INFORMS, vol. 60(8), pages 2020-2037, August.
    9. 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.
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