Fair Dealings with Algorithms? Analyzing the Perceived Procedural Fairness of Managerial Algorithms and their Impacts on Gig-Workers

Jabagi, Nura; Croteau, Anne-Marie; Audebrand, Luc; Marsan, Josianne

Fair Dealings with Algorithms? Analyzing the Perceived Procedural Fairness of Managerial Algorithms and their Impacts on Gig-Workers

Files

0414.pdf (640.96 KB)

Date

2024-01-03

Authors

Jabagi, Nura

Croteau, Anne-Marie

Audebrand, Luc

Marsan, Josianne

Starting Page

4194

Abstract

This study examines how gig-workers perceive the fairness of managerial algorithms on gig-work platforms using Organizational Justice Theory. Through a survey of 435 Uber drivers, we find that the perceived fairness of algorithmic decisions (both matching and performance evaluation decisions) is positively and significantly related to job satisfaction and perceived organizational support (POS). We also find that certain indicators of perceived algorithmic fairness are unique to the type of decision made and whether it is perceived to require mechanical or human skills. In answering calls to study the impacts of algorithmic fairness in real-world settings, we find that managerial algorithms play a key role in shaping gig-workers’ attitudes as technological artefacts and as organizational agents. Recommendations are provided to enhance perceived algorithmic fairness to address challenges in the gig-economy, like high turnover, by increasing satisfaction and POS.

Keywords

Crowdsourcing and Digital Workforce in the Gig Economy, algorithmic fairness, algorithmic management, gig economy, job satisfaction, platform work

URI

https://hdl.handle.net/10125/106889

Extent

10 pages

Related To

Proceedings of the 57th Hawaii International Conference on System Sciences

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

Collections

Crowdsourcing and Digital Workforce in the Gig Economy

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