Worker Motivation in Crowdsourcing and Human Computation
Worker Motivation in Crowdsourcing and Human Computation
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众包和人类计算中的员工激励
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Thimo Schulze
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文献类型：
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作者：
Nicolas Kaufmann;Thimo Schulze
许多人类计算系统使用像亚马逊机械土耳其这样的众包市场来招募人类工人。这些市场的报酬通常很低，仍然收集的人口统计数据显示，参与者是一个非常多样化的群体，包括高技能的全职工人。现有的许多关于他们的动机的研究都是初级的，没有建立在既定的动机理论基础上。因此，我们将经典激励理论、工作激励理论和开源软件开发的不同模式应用于众包市场。该模型通过对431名机械土耳其人的调查进行了测试。我们发现，外在动机类别(即时回报、延迟回报、社会动机)对在平台上花费的时间有很强的影响。然而，对于许多员工来说，内在动机方面更重要，特别是基于享受的动机的不同方面，如“任务自主性”和“技能多样性”。我们的贡献是一个基于既定理论的初步模型，旨在比较不同的众包平台。
Many human computation systems use crowdsourcing markets like Amazon Mechanical Turk to recruit human workers. The payment in these markets is usually very low, and still collected demographic data shows that the participants are a very diverse group including highly skilled full time workers. Many existing studies on their motivation are rudimental and not grounded on established motivation theory. Therefore, we adapt different models from classic motivation theory, work motivation theory and Open Source Software Development to crowdsourcing markets. The model is tested with a survey of 431 workers on Mechanical Turk. We find that the extrinsic motivational categories (immediate payoffs, delayed payoffs, social motivation) have a strong effect on the time spent on the platform. For many workers, however, intrinsic motivation aspects are more important, especially the different facets of enjoyment based motivation like “task autonomy” and “skill variety”. Our contribution is a preliminary model based on established theory intended for the comparison of different crowdsourcing platforms.