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SSRN Electronic Journal
Article . 2023 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
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Research . 2023
License: unspecified
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EconStor
Research . 2023
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Contesting Fake News

Authors: Rehsmann, Daniel; Roussillon, Béatrice; Schweinzer, Paul;

Contesting Fake News

Abstract

We model competition on a credence goods market governed by an imperfect label, signaling high quality, as a rank-order tournament between firms. In this market interaction, asymmetric firms jointly and competitively control the aggregate precision of a label ranking the competitors' qualities by releasing individual information. While the labels and the aggregated information they are based on can be seen as a public good guiding the consumers' purchasing decisions, individual firms have incentives to strategically amplify or counteract the competitors' information emission, thereby manipulating the aggregate precision of product labeling, i.e., the underlying ranking's discriminatory power. Elements of the introduced theory are applicable to several (credence-good) industries that employ labels or rankings, including academic departments, ``green'' certification, movies, and investment opportunities.

59 pages incl 3 appendics

Country
Austria
Keywords

ddc:330, labelling, M30, contests, 502021 Microeconomics, Product differentiation, DSA, FOS: Economics and business, Contests, CMI, BDA, Labelling, C70, product differentiation, Theoretical Economics (econ.TH), credence goods, 502021 Mikroökonomie, Theoretical Economics, d700, Credence Goods, H40

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green