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Antitrust, Amazon, and Algorithmic Auditing

MPS-Authors
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Dash,  Abhisek
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

/persons/resource/persons144524

Gummadi,  Krishna
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

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arXiv:2403.18623.pdf
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Citation

Dash, A., Chakraborty, A., Ghosh, S., Mukherjee, A., Frankenreiter, J., Bechtold, S., et al. (2024). Antitrust, Amazon, and Algorithmic Auditing. Retrieved from https://arxiv.org/abs/2403.18623.


Cite as: https://hdl.handle.net/21.11116/0000-000F-7257-F
Abstract
In digital markets, antitrust law and special regulations aim to ensure that
markets remain competitive despite the dominating role that digital platforms
play today in everyone's life. Unlike traditional markets, market participant
behavior is easily observable in these markets. We present a series of
empirical investigations into the extent to which Amazon engages in practices
that are typically described as self-preferencing. We discuss how the computer
science tools used in this paper can be used in a regulatory environment that
is based on algorithmic auditing and requires regulating digital markets at
scale.