DOI: 10.30586/pek.1929134 ISSN: 2587-2567

Algorithmic Control on Digital Platforms: A Comparative Analysis of Rating, Scoring, Ranking, and Behavioral Nudging Mechanisms

Eren Efe
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This study examines rating, scoring, ranking, and behavioral guidance mechanisms that play a central role in the operation of digital platforms through the framework of algorithmic management literature. Contrary to the common discourse that platforms are neutral technological intermediaries, the study demonstrates that these mechanisms are not isolated technical tools that measure labor. Rather, they function as integrated systems of algorithmic control that regulate visibility, access to work, income opportunities, and continuity within the platform. The study examines the official documents of Uber, Upwork, Deliveroo, Glovo, BiTaksi, Armut, and Yemeksepeti Express comparatively using the qualitative document analysis method. The findings show that rating inputs are combined with scoring, ranking, and incentive mechanisms and related to visibility, access, status, reward, and the exclusion risk of platform workers. Furthermore, while more explicit metric systems stand out in international platforms, more implicit incentives and parametric income architectures become evident in the Turkish sample. However, the study concludes that a common managerial logic operates in both groups. The study's main contribution is that it reconstructs the discussion on algorithmic management not merely as a problem of technical opacity, but within the context of labor access, distribution of opportunity, and corporate accountability.

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