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Pract."],"published-print":{"date-parts":[[2024,12,31]]},"abstract":"<jats:p>As the first nationwide reputation system, the Chinese Social Credit System (SCS) employs a plethora of information technologies to rate citizens according to a state-defined notion of trustworthiness. Complementing extant research about the SCS that highlights important concerns regarding privacy and surveillance, our work explores the economic facets of the system on the basis of microeconomic and informational theories. We identify reputational discrimination as the basic working principle of the SCS, and propose that in addition to carrots and sticks, which are often highlighted as the main tools of the SCS to incentivize individuals to trustworthy behavior, status is another important variable the planner disposes of. Using a contest model approach, we find that when status is used as a complementary instrument to rewards and punishments, a planner who cares about efficiency, morality, and strictness treats most unfair those that are already bad off. Our work adds another dimension to the policy analysis of the SCS, and advances the understanding of the informational design of the SCS by investigating the fairness-related concerns that the system raises for individuals. Our findings underscore the importance of incorporating fairness principles into the SCS, to not further widen existing economic and societal gaps.<\/jats:p>","DOI":"10.1145\/3703160","type":"journal-article","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T08:46:21Z","timestamp":1730537181000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Reputational Discrimination and Fairness in China\u2019s Social Credit System"],"prefix":"10.1145","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5470-808X","authenticated-orcid":false,"given":"Carmen","family":"Loefflad","sequence":"first","affiliation":[{"name":"School of Computation, Information and Technology, Technical University of Munich, Garching, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2876-2176","authenticated-orcid":false,"given":"Mo","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computation, Information and Technology, Technical University of Munich, Garching, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1093-1282","authenticated-orcid":false,"given":"Jens","family":"Grossklags","sequence":"additional","affiliation":[{"name":"School of Computation, Information and Technology, Technical University of Munich, Garching, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,12,16]]},"reference":[{"key":"e_1_3_4_2_2","volume-title":"The Messy Truth about Social Credit","author":"Ahmed Shazeda","year":"2019","unstructured":"Shazeda Ahmed. 2019. 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