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4.2.2 Task's Final Performance Quality
In “Crowdsourcing task using crowdsourcing quality testing method”, when there is
new subtask finished in crowdsourcing task B, the corresponding quality control
feedback can send to crowdsourcing task A. Using these information, crowdsourcing
task A can work under corresponding mode and adjust strategies to identify task
attendant's quality in crowdsourcing task A, distributing more important work to high
quality task attendant while giving low quality attendants minor subtasks or not
allowing them to work anymore. By deploying similar methods, companies can
enhance the submitted task results and indirectly improve the final task performance.
This closed loop feedback working mode is the advantage that two independent
crowdsourcing tasks cannot achieve. Since in two independent crowdsourcing tasks
crowdsourcing task B starts after crowdsourcing task A finished, the low quality
submitted results in crowdsourcing task A will be maintained and bring
crowdsourcing task B some nonsense work costing time and efforts. This is a
fundamental distinction of these two concepts.
Dynamic Working Mode
In dynamic working mode, to certain task attendants, their task distribution is affected
by the submitted results' quality of other task attendants or themselves. The next
stage's task distribution has uncertainty. Task attendants have interactions, might be
competence or collaboration. Compared to static working mode, dynamic working
mode's superiority is it can take advantage of the feedback of submitted results. By
integrating the dynamic working mode with appropriate quality testing method, we
can get real-time quality feedback of submitted results and task attendants. This also
fits the quality testing method we mentioned above.
Fig. 5. Dynamic Working Mode
As showed in Fig. 5, the feedback of quality testing method distinguishes task
attendants with different quality levels and results in different task distribution
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