基于区域定价模型的劳务众包任务定价方案

Labor Crowd Sourcing Pricing Based on Regional Pricing Model

摘要: 网络劳务众包平台的兴起，促进了电子商务任务定价机制的发展。传统任务定价方案易受地理分布、会员数量及信誉值影响，导致部分区域的任务完成率较低。本文基于区域定价模型以及任务打包方案，在控制成本前提下，对任务格局进行重新划分。运用Logistic 回归确定完成率方程，通过系统聚类法，对距离较近的任务打包分类，形成新的任务格局。以会员密集程度等参数为自变量，回归分析得到不同区域任务定价方程，进而模拟完成率，形成新定价模型。新定价模型任务价格更为合理，模型评价结果显示其可以有效提高任务完成率，降低总体成本，提高劳务众包平台交易效率，进而为平台增收。

Abstract: Internet service crowd sourcing platform has promoted business task pricing. Traditional pricing schemes are easily affected by geographical distribution, membership number and reputation value, which results in low task completion rate in some areas. Based on the regional pricing model and task packing scheme, the task is redefined. Logistic regression is used to determine the completion rate equation, and the new task pattern is formed through the systematic cluster. Taking the parameters such as member concentration as independent variables, regression analysis is applied to get different regional task pricing equations. The completion rate is simulated to form a new pricing model. The new pricing is more reasonable. The results of model evaluation show that the model can effectively improve the task completion rate, reduce cost, improve the transaction efficiency, and increase the revenue for the platform.