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We consider two variants of this setting, which correspond to two objective functions:\n                    <jats:italic>binary threshold<\/jats:italic>\n                    , where the designer\u2019s utility is a non-decreasing function of the number of players with output above a certain threshold; and\n                    <jats:italic>linear threshold<\/jats:italic>\n                    , where a player\u2019s contribution to the designer\u2019s utility is linear in her output if the output is between a lower and an upper threshold, and becomes constant below the lower and above the upper threshold. For both of these objectives, we study\n                    <jats:italic>rank-order allocation<\/jats:italic>\n                    contests and\n                    <jats:italic>general<\/jats:italic>\n                    contests. We characterize the contests that maximize the designer\u2019s objective and indicate techniques to efficiently compute them.\n                  <\/jats:p>","DOI":"10.1007\/s00182-025-00964-0","type":"journal-article","created":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T09:33:55Z","timestamp":1763976835000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Contest design with threshold objectives"],"prefix":"10.1007","volume":"54","author":[{"given":"Edith","family":"Elkind","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4771-4612","authenticated-orcid":false,"given":"Abheek","family":"Ghosh","sequence":"additional","affiliation":[]},{"given":"Paul W.","family":"Goldberg","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,24]]},"reference":[{"issue":"3","key":"964_CR1","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1287\/opre.2016.1575","volume":"65","author":"L Ales","year":"2017","unstructured":"Ales L, Cho S-H, K\u00f6rpeo\u011flu E (2017) Optimal award scheme in innovation tournaments. 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