When does more money work? Examining the role of perceived fairness in pay on the performance quality of crowdworkers

Teng Ye, Sangseok You, Lionel P. Robert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

This research adds to the rich discussion on whether increases in payment to crowdworkers lead to increases in performance quality by introducing the concept of perceived fairness in pay (PFP). PFP refers to the belief that one is fairly compensated for their work. We examine whether PFP mediates the impact of payment amount on the performance quality of crowdworkers. We conducted a field experiment with 152 crowdworkers performing a buttonclicking (BC) task and an instructional manipulation check (IMC) task. PFP mediated the impact of payment amount on performance quality in the BC task but not in the IMC task. PFP also mediated the impact of payment amount on satisfaction and task time. Results suggest that PFP can help us better understand the relationship between payment and performance quality in crowdsourcing.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th International Conference on Web and Social Media, ICWSM 2017
PublisherAAAI press
Pages327-336
Number of pages10
ISBN (Electronic)9781577357889
StatePublished - 2017
Externally publishedYes
Event11th International Conference on Web and Social Media, ICWSM 2017 - Montreal, Canada
Duration: May 15 2017May 18 2017

Publication series

NameProceedings of the 11th International Conference on Web and Social Media, ICWSM 2017

Other

Other11th International Conference on Web and Social Media, ICWSM 2017
Country/TerritoryCanada
CityMontreal
Period5/15/175/18/17

Bibliographical note

Funding Information:
Acknowledgements. This study is part of a PhD project funded by iMinds (Interdisciplinary institute for Technology), a research institute founded by the Flemish Government.

Publisher Copyright:
© Copyright 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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