The Two Faces of Algorithmic Management in the Gig Economy

dc.contributor.authorBujold, Antoine
dc.contributor.authorParent-Rocheleau, Xavier
dc.date.accessioned2023-12-26T18:46:16Z
dc.date.available2023-12-26T18:46:16Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.631
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.othere0500d87-aa8c-45d3-840f-4e6544153af7
dc.identifier.urihttps://hdl.handle.net/10125/107016
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDigitalization of Work
dc.subjectalgorithmic management
dc.subjectgig work
dc.subjectjob autonomy
dc.subjectorganization justice.
dc.subjectwork engagement
dc.titleThe Two Faces of Algorithmic Management in the Gig Economy
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractAlgorithmic management of workers is a relatively new phenomenon which impacts workers in diverse manners. The growing literature on this disruptive and technology-mediated form of management suggest that, through different mechanisms, it can result in both beneficial and harmful consequences. Aiming to examine these two faces empirically and simultaneously, time-lagged data was collected from 366 gig workers. The results show that, on the one hand, high perceived exposure to AM is associated to greater perceived procedural justice. On the other hand, workers reporting high AM exposure also perceive lower job autonomy. This has the simultaneous effect of indirectly fostering and worsening the level of gig workers' engagement.
dcterms.extent9 pages
prism.startingpage5258

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