Loading...
Paper Type
ERF
Abstract
Algorithmic rewards in gig platforms aim to address high turnover rates by fostering episodic loyalty among gig workers, a temporary partnership with the platforms. While offering extra bonuses or opportunities to supplement gig workers’ income, algorithmic rewards may have unintended negative effects on workers' autonomy experiences and continuance intention on the platform, as suggested by anecdotal evidence Therefore, this study proposes an investigation of the dual impact of algorithmic rewards on episodic loyalty. We will conduct an online experiment to assess algorithmic rewards' influence on autonomy. This paper contributes to the algorithmic management literature by offering theoretical insights into algorithmic rewards' unintended effects and making practical recommendations for gig platforms to develop an effective reward program that bolsters workers' episodic loyalty.
Paper Number
1552
Recommended Citation
Huang, Xuemei and Nguyen, Long The, "The Duality of Algorithmic Rewards on Gig Workers’ Episodic Loyalty" (2024). AMCIS 2024 Proceedings. 1.
https://aisel.aisnet.org/amcis2024/cnow/cnow/1
The Duality of Algorithmic Rewards on Gig Workers’ Episodic Loyalty
Algorithmic rewards in gig platforms aim to address high turnover rates by fostering episodic loyalty among gig workers, a temporary partnership with the platforms. While offering extra bonuses or opportunities to supplement gig workers’ income, algorithmic rewards may have unintended negative effects on workers' autonomy experiences and continuance intention on the platform, as suggested by anecdotal evidence Therefore, this study proposes an investigation of the dual impact of algorithmic rewards on episodic loyalty. We will conduct an online experiment to assess algorithmic rewards' influence on autonomy. This paper contributes to the algorithmic management literature by offering theoretical insights into algorithmic rewards' unintended effects and making practical recommendations for gig platforms to develop an effective reward program that bolsters workers' episodic loyalty.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIGCNOW