Abstract

Microtasks accomplished by humans are used in many corners of the Internet. They help to make decisions where it is not possible to rely on algorithms (yet) like insult detection or fake reviews. People conducting crowdwork, crowdworkers, are often recruited via platforms where employers have more power than crowdworkers. This is sometimes misused by offering poor work conditions, which can lead to poor work quality. Online feedback systems (OFS) can discipline employers to improve work conditions and subsequently work quality. Unfortunately, the majority of crowdworkers do not contribute to an OFS and remain silent. We develop and test a model based on self-determination theory with PLS-SEM to explain their silence. Perceived cost and perceived non-relevance are deterrents to contributions. However, satisfaction in helping others and the wish to belong to the community are significant motivational factors, which could be used in the design of an OFS to foster crowdworkers’ contributions.

摘要

由人类完成的微任务被用于互联网的许多角落。它们有助于在无法依赖算法（尚）（如侮辱检测或虚假评论）的情况下做出决策。从事众包工作的人，众包工作者，通常是通过雇主比众包工作者拥有更多权力的平台招募的。这有时会因提供恶劣的工作条件而被滥用，从而导致工作质量不佳。在线反馈系统 (OFS) 可以对雇主进行纪律处分，以改善工作条件，进而改善工作质量。不幸的是，大多数众包工作者并没有为 OFS 做出贡献并保持沉默。我们使用 PLS-SEM 开发和测试基于自决理论的模型来解释他们的沉默。感知成本和感知不相关是对贡献的威慑。然而，