Research on performance improvement of crowdsourcing based on task pricing
[1]Deng Shaohong,Li Ling Guibin.Research on performance improvement of crowdsourcing based on task pricing[J].Journal of Zhengzhou University (Engineering Science),2019,40(04):15-.[doi:10.13705/j.issn.1671-6833.2019.04.019]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 04
Page number:
15-
Column:
Public date:
2019-07-10
- Title:
- Research on performance improvement of crowdsourcing based on task pricing
- CLC:
- -
- Abstract:
- First, according to the theory of space crowdsourcing, the concept of equivalent task representative points is proposed, and the relationship between the original task pricing law and task density, membership density, member average credibility and nearest neighbor reach distance is studied. On this basis, from the perspectives of the contractor, the platform and the contractor, According to the four steps of completing the task, a task pricing model based on multi-objective programming , a member dynamic grab order model, a task allocation model and a task completion probability prediction model are respectively established. Furthermore, the TOPSIS method is used to calculate the comprehensive evaluation index of different pricing schemes, and then choose the optimal task pricing scheme by the ranking result of the comprehensive evaluation index. Finally, the optimized scheme is compared with the original scheme. Under the condition that the total cost of the contractor is as low as possible, the platform task completion rate, the average individual member income and the unit reputation value conversion rewards are significantly improved, that is, the crowdsourcing performance are improved. The result verifies the feasibility and effectiveness of the model and provides reference for the task pricing of the crowdsourcing platform
- References:
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Last Update:
2019-07-29
