Fair compensation of crowdsourcing work: the problem of flat rates

BEHAVIOUR & INFORMATION TECHNOLOGY(2022)

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摘要
Compensating crowdworkers for their research participation often entails paying a flat rate to all participants, regardless of the amount of time they spend on the task or skill level. If the actual time required varies considerably between workers, flat rates may yield unfair compensation. To study this matter, we analyzed three survey studies with varying complexity. Based on the United Kingdom minimum wage and actual task completion times, we found that more than 3 in 4 (76.5%) of the crowdworkers studied were paid more than the intended hourly wage, and around one in four (23.5%) was paid less than the intended hourly wage when using a flat rate compensation model based on estimated completion time. The results indicate that the popular flat rate model falls short as a form of equitable remuneration, when perceiving fairness in the form of compensating one's time. Flat rate compensation would not be problematic if the workers' completion times were similar, but this is not the case in reality, as skills and motivation can vary. To overcome this problem, the study proposes three alternative compensation models: Compensation by Normal Distribution, Multi-Objective Fairness, and PostHoc Bonuses.
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关键词
Crowdsourcing, online data collection, fairness, compensation, research ethics
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