{"id":"https://openalex.org/W3005538141","doi":"https://doi.org/10.1287/moor.2021.1245","title":"Pipeline Interventions","display_name":"Pipeline Interventions","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W3005538141","doi":"https://doi.org/10.1287/moor.2021.1245","mag":"3005538141"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1287/moor.2021.1245","pdf_url":null,"source":{"id":"https://openalex.org/S55826652","display_name":"Mathematics of Operations Research","issn_l":"0364-765X","issn":["0364-765X","1526-5471"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310315699","host_organization_name":"Institute for Operations Research and the Management Sciences","host_organization_lineage":["https://openalex.org/P4310315699"],"host_organization_lineage_names":["Institute for Operations Research and the Management Sciences"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019365634","display_name":"Eshwar Ram Arunachaleswaran","orcid":"https://orcid.org/0009-0006-2988-2491"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"funder","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eshwar Ram Arunachaleswaran","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, Pennsylvania 19104;"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, Pennsylvania 19104;","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103555404","display_name":"Sampath Kannan","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"funder","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sampath Kannan","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, Pennsylvania 19104;"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, Pennsylvania 19104;","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057693522","display_name":"Aaron Roth","orcid":"https://orcid.org/0000-0002-0586-0515"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"funder","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aaron Roth","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, Pennsylvania 19104;"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, Pennsylvania 19104;","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008250785","display_name":"Juba Ziani","orcid":"https://orcid.org/0000-0002-3324-4349"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"funder","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juba Ziani","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, Georgia 30318"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, Georgia 30318","institution_ids":["https://openalex.org/I130701444"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.19,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.521901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":59,"max":69},"biblio":{"volume":"47","issue":"4","first_page":"3207","last_page":"3238"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.9978,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.9978,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9945,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.928,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.49071515}],"concepts":[{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.623412},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5915511},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5624086},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.49071515},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4467705},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.35884088},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.27029037}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1287/moor.2021.1245","pdf_url":null,"source":{"id":"https://openalex.org/S55826652","display_name":"Mathematics of Operations Research","issn_l":"0364-765X","issn":["0364-765X","1526-5471"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310315699","host_organization_name":"Institute for Operations Research and the Management Sciences","host_organization_lineage":["https://openalex.org/P4310315699"],"host_organization_lineage_names":["Institute for Operations Research and the Management Sciences"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.48}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":14,"referenced_works":["https://openalex.org/W2079854492","https://openalex.org/W2097477220","https://openalex.org/W2130301414","https://openalex.org/W2143698439","https://openalex.org/W2150409561","https://openalex.org/W2592030152","https://openalex.org/W2773444500","https://openalex.org/W2889169527","https://openalex.org/W2897978524","https://openalex.org/W2904609718","https://openalex.org/W2962922829","https://openalex.org/W2964083839","https://openalex.org/W2965749257","https://openalex.org/W3006822506"],"related_works":["https://openalex.org/W2895916002","https://openalex.org/W2474724840","https://openalex.org/W2369683208","https://openalex.org/W2084836983","https://openalex.org/W2037938733","https://openalex.org/W2016058626","https://openalex.org/W2001839669","https://openalex.org/W1977348009","https://openalex.org/W1814049089","https://openalex.org/W1530911128"],"abstract_inverted_index":{"We":[0,133,161,204],"introduce":[1],"the":[2,58,62,75,79,88,92,97,118,126,149,152,157,166,208,215,218,224,242,261,264],"pipeline":[3,107],"intervention":[4,108],"problem,":[5],"defined":[6],"by":[7],"a":[8,14,27,66,85,101,130,141,180,229],"layered":[9],"directed":[10],"acyclic":[11],"graph":[12,25,76,127],"and":[13,70,140,223],"set":[15],"of":[16,61,91,165,210],"stochastic":[17,123],"matrices":[18,81,120],"governing":[19,121],"transitions":[20,124],"between":[21,217],"successive":[22],"layers.":[23],"The":[24,106],"is":[26,249,270],"stylized":[28],"model":[29],"for":[30,201,237,253],"how":[31,111],"people":[32],"from":[33],"different":[34],"populations":[35],"are":[36,48],"presented":[37],"opportunities,":[38],"eventually":[39],"leading":[40],"to":[41,65,78,112,117,129,147,151,172,245],"some":[42,55],"reward.":[43],"In":[44],"our":[45,213,267],"model,":[46],"individuals":[47],"born":[49],"into":[50],"an":[51,191],"initial":[52],"position":[53],"(i.e.,":[54],"node":[56,86,95],"in":[57,87,96,212,266],"first":[59],"layer":[60,90,99],"graph)":[63],"according":[64,77],"fixed":[67],"probability":[68],"distribution":[69],"then":[71],"stochastically":[72],"progress":[73],"through":[74,125],"transition":[80,119],"until":[82],"they":[83],"reach":[84],"final":[89,98],"graph;":[93],"each":[94,187],"has":[100],"reward":[102],"associated":[103],"with":[104,156,228,255],"it.":[105],"problem":[109],"asks":[110],"best":[113],"make":[114],"costly":[115],"changes":[116],"people\u2019s":[122],"subject":[128],"budget":[131],"constraint.":[132],"consider":[134,162],"two":[135,163],"objectives:":[136],"social":[137,221,225],"welfare":[138,222,226],"maximization":[139],"fairness-motivated":[142],"maximin":[143,167,230,243],"objective":[144,168,244],"that":[145,169,260],"seeks":[146],"maximize":[148],"value":[150],"population":[153],"(starting":[154],"node)":[155],"least":[158],"expected":[159],"value.":[160],"variants":[164],"turn":[170],"out":[171],"be":[173],"distinct,":[174],"depending":[175],"on":[176,263],"whether":[177],"we":[178,189,234],"demand":[179],"deterministic":[181],"solution":[182],"or":[183],"allow":[184],"randomization.":[185],"For":[186],"objective,":[188],"give":[190],"efficient":[192],"approximation":[193,199],"algorithm":[194],"(an":[195],"additive":[196],"fully":[197],"polynomial-time":[198],"scheme)":[200],"constant-width":[202],"networks.":[203],"also":[205],"tightly":[206],"characterize":[207],"\u201cprice":[209],"fairness\u201d":[211],"setting:":[214],"ratio":[216],"highest":[219],"achievable":[220],"consistent":[227],"optimal":[231],"solution.":[232],"Finally,":[233],"show":[235],"that,":[236],"polynomial-width":[238],"networks,":[239],"even":[240,252],"approximating":[241],"any":[246],"constant":[247,256],"factor":[248],"NP":[250],"hard":[251],"networks":[254],"depth.":[257],"This":[258],"shows":[259],"restriction":[262],"width":[265],"positive":[268],"results":[269],"essential.":[271]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3005538141","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-03-18T10:13:24.105818","created_date":"2020-02-24"}