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How Does Algorithm Control Affect Platform Workers' Responses? Algorithm as a Digital Taylorism
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AI
DOI：10.3390/jtaer18010015.png)
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Abstract
En 中文
While many online labor platforms have adopted algorithms to monitor or control workforces as a new form of algorithm management, there is no academic attempt to empirically examine how the algorithmic control of platforms influences platform workers' behaviors in a platform context. In this study, we consider how algorithm management affects the platform workers' response from a Digital Taylorism perspective. Digital Taylorism involves management's use of technology to monitor workers by assigning and tracking work. Therefore, this study examines how algorithm control influences the platform workers' response by mediating the tension of work compensation in an online labor platform context. Survey data collected from 216 food delivery riders in South Korea are used to test the model using partial least squares analysis. Our results show that algorithm control affects platform workers' responses by mediating tensions of platform work compensation. Based upon our empirical findings, we can provide a theoretical perspective to relevant researchers who seek to find a theoretical mechanism of algorithm management. Moreover, we can offer practical insights to practitioners who are interested in algorithm management.
Keywords:
algorithm control
uncertainty
repeatability
embracing
switching
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