TY - JOUR
T1 - Hybrid Influences of Social Subsystem and Technical Subsystem Risks in the Crowdsourcing Marketplace
AU - Liu, Shan
AU - Xia, Fan
AU - Gao, Baojun
AU - Jiang, Guoyin
AU - Zhang, Jinlong
N1 - Publisher Copyright:
© 1988-2012 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - The successful management of crowdsourcing risk has gained considerable attention because of the challenges involved in obtaining the satisfactory performance from crowdsourcing activities. However, the mechanism of how various critical risk factors affect crowdsourcing performance has been poorly investigated. Empirical evidence based on a dataset of 169 samples from China shows that three technical (i.e., complexity, requirement, and task) and three social (i.e., seeker, solver, and relationship) subsystem risks not only directly but also interactively influence the crowdsourcing task performance. Technical subsystem risk factors, while worsen performance, diminish the negative effects of social subsystem risk factors on the crowdsourcing task performance. The diminishing effects of three technical subsystem risk factors are also differentiated. High requirement and task risks lessen the negative effects of seeker, solver, and relationship risks on the task performance, whereas the high complexity risk only weakens the negative effect of the solver risk. Therefore, various crowdsourcing risk factors affect the performance in different ways and directions (either negatively or positively). Risk can perform dual roles in influencing the performance. Hybrid strategies that integrate social and technical subsystem elements may be effective in achieving a superior task performance for the crowdsourcing risk management. Managers of crowdsourcing platforms can also optimize social and technical environments to improve the fit between social and technical systems.
AB - The successful management of crowdsourcing risk has gained considerable attention because of the challenges involved in obtaining the satisfactory performance from crowdsourcing activities. However, the mechanism of how various critical risk factors affect crowdsourcing performance has been poorly investigated. Empirical evidence based on a dataset of 169 samples from China shows that three technical (i.e., complexity, requirement, and task) and three social (i.e., seeker, solver, and relationship) subsystem risks not only directly but also interactively influence the crowdsourcing task performance. Technical subsystem risk factors, while worsen performance, diminish the negative effects of social subsystem risk factors on the crowdsourcing task performance. The diminishing effects of three technical subsystem risk factors are also differentiated. High requirement and task risks lessen the negative effects of seeker, solver, and relationship risks on the task performance, whereas the high complexity risk only weakens the negative effect of the solver risk. Therefore, various crowdsourcing risk factors affect the performance in different ways and directions (either negatively or positively). Risk can perform dual roles in influencing the performance. Hybrid strategies that integrate social and technical subsystem elements may be effective in achieving a superior task performance for the crowdsourcing risk management. Managers of crowdsourcing platforms can also optimize social and technical environments to improve the fit between social and technical systems.
KW - Crowdsourcing marketplace
KW - crowd participant
KW - risk management
KW - sociotechnical systems (STS) theory
KW - task performance
UR - https://www.scopus.com/pages/publications/85101431616
U2 - 10.1109/TEM.2019.2902446
DO - 10.1109/TEM.2019.2902446
M3 - 文章
AN - SCOPUS:85101431616
SN - 0018-9391
VL - 68
SP - 513
EP - 527
JO - IEEE Transactions on Engineering Management
JF - IEEE Transactions on Engineering Management
IS - 2
M1 - 8676221
ER -