Quantitative Analysis of Online Labor Platforms’ Algorithmic Management Influence on Psychological Health of Workers

Gengxin Sun ()
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Gengxin Sun: College of Computer Science & Technology, Qingdao University, Qingdao 266071, China

IJERPH, 2023, vol. 20, issue 5, 1-17

Abstract: Online labor platforms (OLPs) can use algorithms to strengthen the control of the labor process. In fact, they construct work circumstances with higher work requirements and pressure. Workers’ autonomy in behavior is limited, which will have a great influence on their labor psychology. In this paper, taking the online take-out platform as an example and by using a qualitative study of take-out riders’ delivery processes, which were supplemented by semi-structured, in-depth interviews with online platform executives and engineers, we used grounded theory to explore the influencing factors of OLPs’ algorithmic management on take-out riders’ working psychology. The quantitative analysis results showed that, in the context of conflict between work autonomy and algorithmic management, platform workers experienced psychological tensions relating to work satisfaction, compensation, and belonging. Our research contributes to protect public health and labor rights of OLP workers.

Keywords: public health; online labor platforms; algorithmic management; psychological health; take-out riders (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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