Research on Task Pricing of Internet Labor Crowdsourcing Platform
Kaixuan Bao, Kai Zhao, Qi-pei Qian, Lu Yin · 2019
Internet labor crowdsourcing platform is a self-service platform via mobile network. Users could download the APP and become a member of the platform to complete tasks with money in return, which makes the pricing of tasks critically significant. To find out the relation between pricing and completion rate, several factors are established according to tasks’ features. Then work out the influence ratio of each factor using PLS regression and global search. With the influence ratio obtained, optimal pricing solution could be found with multi-objective 0-1 integer programming. At last, simulation is applied to evaluate the result, which shows an improvement over both completion rate and platform cost.