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Are algorithmically controlled gig workers deeply burned out? An empirical study on employee work engagement.
Jiao Jiao Lang1, Li Feng Yang2, Chen Cheng3
1Endicott College, Woosong University, 17-2, Jayang- dong, Dong-gu, Daejeon City, South Korea.
BMC Psychology
|October 25, 2023
Summary
Perceived algorithmic control in the gig economy can lead to burnout, but adequate technological support helps maintain gig worker engagement. This study explores the complex relationship between these factors.
Area of Science:
- Organizational Behavior
- Human-Computer Interaction
- Labor Economics
Background:
- The rise of the gig economy necessitates understanding algorithmic control's impact on workers.
- Gig workers face unique challenges related to technological management and engagement.
Purpose of the Study:
- To investigate the emotional impact of perceived algorithmic control on gig workers.
- To examine how algorithmic control influences gig workers' work engagement.
Main Methods:
- Utilized a structural equation model (SEM) with questionnaire data from gig workers.
- Applied the Job Demands-Resources model to frame the study's mechanism.
Main Results:
- Perceived algorithmic control positively impacts work engagement.
- Burnout is positively correlated with work engagement and partially mediates the relationship.
- Flow experience moderates the indirect effect of burnout on work engagement.
Conclusions:
- Algorithmic control can induce burnout, yet technological support offers resources that sustain engagement.
- Gig workers may exhibit high engagement despite experiencing burnout symptoms.
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