{"id":"https://openalex.org/W3177068218","doi":"https://doi.org/10.24963/ijcai.2022/45","title":"Can Buyers Reveal for a Better Deal?","display_name":"Can Buyers Reveal for a Better Deal?","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W3177068218","doi":"https://doi.org/10.24963/ijcai.2022/45","mag":"3177068218"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/45","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/45","pdf_url":"https://www.ijcai.org/proceedings/2022/0045.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0045.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103186763","display_name":"Daniel Halpern","orcid":"https://orcid.org/0000-0003-3368-7235"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Halpern","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045114890","display_name":"Gregory Kehne","orcid":"https://orcid.org/0009-0002-3375-5576"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory Kehne","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035370064","display_name":"Jamie Tucker-Foltz","orcid":"https://orcid.org/0000-0001-9174-3341"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jamie Tucker-Foltz","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00317628,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"314","last_page":"320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10646","display_name":"Experimental Behavioral Economics Studies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/impossibility","display_name":"Impossibility","score":0.7925702333450317},{"id":"https://openalex.org/keywords/odds","display_name":"Odds","score":0.6608306169509888},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.5711023807525635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5658974051475525},{"id":"https://openalex.org/keywords/ex-ante","display_name":"Ex-ante","score":0.5046283006668091},{"id":"https://openalex.org/keywords/welfare","display_name":"Welfare","score":0.4606378972530365},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.44151121377944946},{"id":"https://openalex.org/keywords/social-welfare","display_name":"Social Welfare","score":0.4273199439048767},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.34591054916381836},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.32565081119537354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1158241331577301},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.10169526934623718}],"concepts":[{"id":"https://openalex.org/C2776261394","wikidata":"https://www.wikidata.org/wiki/Q315562","display_name":"Impossibility","level":2,"score":0.7925702333450317},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.6608306169509888},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.5711023807525635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5658974051475525},{"id":"https://openalex.org/C122251271","wikidata":"https://www.wikidata.org/wiki/Q940039","display_name":"Ex-ante","level":2,"score":0.5046283006668091},{"id":"https://openalex.org/C100243477","wikidata":"https://www.wikidata.org/wiki/Q12002092","display_name":"Welfare","level":2,"score":0.4606378972530365},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.44151121377944946},{"id":"https://openalex.org/C536738050","wikidata":"https://www.wikidata.org/wiki/Q3249071","display_name":"Social Welfare","level":2,"score":0.4273199439048767},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.34591054916381836},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.32565081119537354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1158241331577301},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.10169526934623718},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2022/45","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/45","pdf_url":"https://www.ijcai.org/proceedings/2022/0045.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/45","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/45","pdf_url":"https://www.ijcai.org/proceedings/2022/0045.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3177068218.pdf"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W1888374024","https://openalex.org/W2401610261","https://openalex.org/W2615461813","https://openalex.org/W2945328365","https://openalex.org/W2998344508","https://openalex.org/W3089330505","https://openalex.org/W3125449324"],"related_works":["https://openalex.org/W2384156839","https://openalex.org/W4321602641","https://openalex.org/W2394251275","https://openalex.org/W4241392912","https://openalex.org/W2596801716","https://openalex.org/W4387391601","https://openalex.org/W2141614742","https://openalex.org/W2369846953","https://openalex.org/W2362926696","https://openalex.org/W4385605322"],"abstract_inverted_index":{"We":[0,117],"study":[1],"market":[2],"interactions":[3],"in":[4,99,135],"which":[5,96],"buyers":[6,81],"are":[7,63],"allowed":[8],"to":[9,17,66],"credibly":[10],"reveal":[11],"partial":[12],"information":[13],"about":[14],"their":[15],"types":[16],"the":[18,25,55,60,102,109],"seller.":[19],"Previous":[20],"recent":[21],"work":[22],"has":[23],"studied":[24],"special":[26],"case":[27,62],"of":[28,112],"one":[29,32,122,125],"buyer":[30,46,67,87,123,128],"and":[31,43,124],"good,":[33,126],"showing":[34,75],"that":[35,54],"such":[36],"communication":[37],"can":[38,89],"simultaneously":[39],"improve":[40],"social":[41,94],"welfare":[42],"ex":[44],"ante":[45],"utility.":[47],"However,":[48],"with":[49,77,93,101,121],"multiple":[50,79,83],"buyers,":[51],"we":[52,70,107],"find":[53,118],"buyer-optimal":[56],"signalling":[57],"schemes":[58],"from":[59],"one-buyer":[61],"actually":[64],"harmful":[65],"welfare.":[68],"Moreover,":[69],"prove":[71],"several":[72],"impossibility":[73],"results":[74],"that,":[76,119],"either":[78],"i.i.d.":[80,84],"or":[82],"goods,":[85],"maximizing":[86],"utility":[88,129],"be":[90],"at":[91],"odds":[92],"efficiency,":[95],"is":[97,130],"surprising":[98],"contrast":[100],"one-buyer,":[103],"one-good":[104],"case.":[105],"Finally,":[106],"investigate":[108],"computational":[110],"tractability":[111],"implementing":[113],"desirable":[114],"equilibrium":[115],"outcomes.":[116],"even":[120],"optimizing":[127],"generally":[131],"NP-hard":[132],"but":[133],"tractable":[134],"a":[136],"practical":[137],"restricted":[138],"setting.":[139]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
