基于任务定价的空间众包绩效提升研究-《郑州大学学报(工学版)》

文章信息/Info

Title:: Research on performance improvement of crowdsourcing based on task pricing

Author(s):: Deng Shaohong 1; Li Ling 1Guibin 2; 1. School of Economics and Management, Changsha University of Science and Technology; 2. School of Computer Science and Technology, Huaiyin Normal University

Keywords:: Spatial crowdsourcing; task pricing; performance improvement; multi-objective programming

摘要:: 对众包这一新型分布式解决问题而言，提高众包绩效是急需解决的问题，而任务的定价策略与众包绩效的提升具有密切相关性。本文根据空间众包理论，提出等效任务代表点的概念，研究原有任务定价规律与任务密度、会员密度、会员平均信誉度、最邻近可达距离四个因素的关系。在此基础上从发包方、平台以及接包方三个角度出发，针对任务实现的四个步骤，分别建立了基于多目标规划的任务定价模型、会员动态抢单模型、任务分配模型以及任务完成概率预测模型。进而运用TOPSIS法计算不同方案的综合评价指数，排序选取最优任务定价方案。最后将优化后的方案与原方案进行对比，在保证发包方总成本尽可能低的情况下，平台任务完成率、会员个人平均收益以及单位信誉值转换的酬金均显著提高，即众包绩效得以提升。此结果验证了该模型的可行性与有效性，为众包平台的任务定价提供了借鉴与参考。

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