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      Working for an Algorithm: Power Asymmetries and Agency in Online Work Settings

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          Abstract

          Drawing on interviews with 77 high-performing eBay business sellers in France and Belgium, this article investigates the power asymmetries generated by customers’ evaluations in online work settings. Sellers revealed a high degree of sensitivity to negative reviews, which, while infrequent, triggered feelings of anxiety and vulnerability. Their accounts exposed power asymmetries at two levels: the transactional level between sellers and customers and the governance level between sellers and eBay. Our findings highlight three main mechanisms underlying power asymmetries in this context. First, online customer evaluations have created a new form of employee monitoring in which power is exercised through the construction of visibility gaps between buyers and sellers and through an implicit coalition between buyers and the platform owner, who join together in the evaluation procedures. Second, by mediating and objectifying relations, algorithms reproduce power asymmetries among the different categories of actors, thereby constraining human agency. Third, online customer evaluations prompt sellers to exploit their practical knowledge of the algorithm to increase their agency. Through the lived experience of working for an algorithm, our findings contribute new understandings of power and agency in online work settings.

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          Markets, Bureaucracies, and Clans

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            The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms

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              Frameworks of Power

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                Author and article information

                Contributors
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                Journal
                Administrative Science Quarterly
                Administrative Science Quarterly
                SAGE Publications
                0001-8392
                1930-3815
                September 2020
                July 25 2019
                September 2020
                : 65
                : 3
                : 644-676
                Affiliations
                [1 ]University of Edinburgh Business School
                [2 ]Warwick Business School
                [3 ]Nottingham University Business School
                [4 ]HEC Liège
                Article
                10.1177/0001839219867024
                2986483f-394e-4362-8b91-035b9c6dc7ec
                © 2020

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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