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Gig worker's perceived algorithmic management, stress appraisal, and destructive deviant behavior.
Linzi Zhang1, Jie Yang1, Yiming Zhang2
1School of Business Administration, Zhongnan University of Economics and Law, Wuhan, Hubei, China.
Plos One
|November 8, 2023
Summary
Algorithmic management on gig platforms can lead to destructive worker behavior. This study shows it
Area of Science:
- Behavioral Economics
- Management Science
- Sociology
Background:
- Gig platforms increasingly use algorithmic management.
- This can impose stringent demands on gig workers.
- Potential for negative worker behaviors exists.
Purpose of the Study:
- Examine the link between algorithmic management and gig worker destructive deviant behavior.
- Investigate the dual role of algorithmic management as both challenge and hindrance.
- Analyze the moderating effect of regulatory focus.
Main Methods:
- Developed a research model based on the challenge-hindrance framework.
- Collected survey data from 423 food delivery riders.
- Utilized multi-level linear regression analysis.
Main Results:
- Perceived algorithmic management is viewed as both a hindrance and a challenge.
- As a hindrance, it increases working/family deviant behavior.
- As a challenge, it decreases working/family deviant behavior.
- Regulatory focus moderates stress appraisals.
Conclusions:
- Algorithmic management's impact on gig worker behavior is complex, acting as both a hindrance and a challenge.
- Findings offer insights for platforms, workers, and policymakers to optimize algorithmic management.
- Balancing the challenge and hindrance aspects is key to mitigating negative behaviors.
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