{"id":"https://openalex.org/W4382239939","doi":"https://doi.org/10.1609/aaai.v37i4.25677","title":"Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing","display_name":"Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing","publication_year":2023,"publication_date":"2023-06-26","ids":{"openalex":"https://openalex.org/W4382239939","doi":"https://doi.org/10.1609/aaai.v37i4.25677"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v37i4.25677","doi":"https://doi.org/10.1609/aaai.v37i4.25677","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i4.25677","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/25677/25449","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/25677/25449","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101825066","display_name":"Hao Zhou","orcid":"https://orcid.org/0009-0008-5204-663X","observed_orcids":["https://orcid.org/0009-0008-5204-663X"]},"institutions":[{"id":"https://openalex.org/I4405259410","display_name":"Meituan (China)","ror":"https://ror.org/0272kpg92","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405259410"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhou","raw_affiliation_strings":["Meituan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan","institution_ids":["https://openalex.org/I4405259410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058413405","display_name":"Shaoming Li","orcid":"https://orcid.org/0000-0002-4915-9958","observed_orcids":["https://orcid.org/0000-0002-4915-9958","https://orcid.org/0009-0007-6379-2286"]},"institutions":[{"id":"https://openalex.org/I4405259410","display_name":"Meituan (China)","ror":"https://ror.org/0272kpg92","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405259410"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoming Li","raw_affiliation_strings":["Meituan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan","institution_ids":["https://openalex.org/I4405259410"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guibin Jiang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405259410","display_name":"Meituan (China)","ror":"https://ror.org/0272kpg92","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405259410"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guibin Jiang","raw_affiliation_strings":["Meituan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan","institution_ids":["https://openalex.org/I4405259410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101513130","display_name":"Jiaqi Zheng","orcid":"https://orcid.org/0000-0001-8403-9655","observed_orcids":["https://orcid.org/0000-0001-8403-9655","https://orcid.org/0009-0009-6454-3307"]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Zheng","raw_affiliation_strings":["Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391540","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0003-2498-4203","observed_orcids":["https://orcid.org/0000-0003-2498-4203"]},"institutions":[{"id":"https://openalex.org/I4405259410","display_name":"Meituan (China)","ror":"https://ror.org/0272kpg92","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405259410"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Meituan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan","institution_ids":["https://openalex.org/I4405259410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.9254,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.99395863,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"37","issue":"4","first_page":"5446","last_page":"5454"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.2888000011444092,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.2888000011444092,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.2858999967575073,"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"}},{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.05380000174045563,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/resource-allocation","display_name":"resource allocation","score":0.8700000047683716},{"id":"https://openalex.org/keywords/marketing","display_name":"marketing","score":0.6830000281333923},{"id":"https://openalex.org/keywords/customized-loss-function","display_name":"customized loss function","score":0.9150000214576721},{"id":"https://openalex.org/keywords/unbiased-estimation","display_name":"unbiased estimation","score":0.902999997138977},{"id":"https://openalex.org/keywords/budget-allocation","display_name":"budget allocation","score":0.671999990940094},{"id":"https://openalex.org/keywords/multiple-treatments","display_name":"multiple treatments","score":0.796999990940094},{"id":"https://openalex.org/keywords/a-b-testing","display_name":"A/B testing","score":0.7730000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.68731689453125},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5731679797172546},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.5272152423858643},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4913467466831207},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.42189744114875793},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.41995131969451904},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.4187730550765991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35638585686683655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.324766606092453},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17399609088897705},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.11989521980285645},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1609/aaai.v37i4.25677","doi":"https://doi.org/10.1609/aaai.v37i4.25677","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i4.25677","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/25677/25449","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2211.15728","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.15728","pdf_url":"https://arxiv.org/pdf/2211.15728","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:ojs.aaai.org:article/25677","doi":null,"is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/25677","pdf_url":null,"source":{"id":"https://openalex.org/S4306400155","display_name":"AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801652627","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/I2801652627"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.48550/arxiv.2211.15728","doi":"https://doi.org/10.48550/arxiv.2211.15728","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2211.15728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1609/aaai.v37i4.25677","doi":"https://doi.org/10.1609/aaai.v37i4.25677","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v37i4.25677","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/25677/25449","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-2","norway-1"],"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4724825477","display_name":null,"funder_award_id":"62172206","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4382239939.pdf","grobid_xml":"https://content.openalex.org/works/W4382239939.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W204142812","https://openalex.org/W2140899775","https://openalex.org/W2208550830","https://openalex.org/W2389937032","https://openalex.org/W2507814050","https://openalex.org/W2548641835","https://openalex.org/W2597344944","https://openalex.org/W2619014254","https://openalex.org/W2624816748","https://openalex.org/W2730059782","https://openalex.org/W2766820687","https://openalex.org/W2889676056","https://openalex.org/W2891638642","https://openalex.org/W2897367976","https://openalex.org/W2963052087","https://openalex.org/W2972267162","https://openalex.org/W2988150581","https://openalex.org/W3002424897","https://openalex.org/W3008689546","https://openalex.org/W3035175459","https://openalex.org/W3083006799","https://openalex.org/W3089065092","https://openalex.org/W3097704231","https://openalex.org/W3168586667","https://openalex.org/W3171671666","https://openalex.org/W4220930599","https://openalex.org/W4287180041","https://openalex.org/W4287864462","https://openalex.org/W4310486895","https://openalex.org/W7133192737"],"related_works":["https://openalex.org/W4416247112","https://openalex.org/W4401863265","https://openalex.org/W3019394584","https://openalex.org/W4396785996","https://openalex.org/W7202293002","https://openalex.org/W4320342537","https://openalex.org/W4398856153","https://openalex.org/W4416952936","https://openalex.org/W4415274486","https://openalex.org/W4416060391"],"abstract_inverted_index":{"Marketing":[0],"is":[1,153],"an":[2,208],"important":[3],"mechanism":[4],"to":[5,73,102,126,146,160,228],"increase":[6],"user":[7],"engagement":[8],"and":[9,13,35,57,69,92,166,239,250],"improve":[10],"platform":[11],"revenue,":[12],"heterogeneous":[14,201],"causal":[15,202],"learning":[16,55,203],"can":[17,28,172,198,213],"help":[18],"develop":[19],"more":[20],"effective":[21],"strategies.":[22],"Most":[23],"decision-making":[24],"problems":[25,34,145,231],"in":[26,76,87,99,176,232],"marketing":[27],"be":[29,90,173,214],"formulated":[30],"as":[31],"resource":[32,143],"allocation":[33,144,242],"have":[36,117],"been":[37],"studied":[38],"for":[39,141],"decades.":[40],"Existing":[41],"works":[42],"usually":[43],"divide":[44],"the":[45,62,66,74,77,81,84,103,108,112,122,127,130,148,157,170,181,187,205,217,234,240],"solution":[46,124,171],"procedure":[47],"into":[48],"two":[49,229],"fully":[50],"decoupled":[51,131],"stages,":[52],"i.e.,":[53],"machine":[54],"(ML)":[56],"operation":[58],"research":[59],"(OR)":[60],"---":[61],"first":[63],"stage":[64],"predicts":[65],"model":[67],"parameters":[68,86,114],"they":[70],"are":[71],"fed":[72],"optimization":[75],"second":[78],"stage.":[79],"However,":[80],"error":[82],"of":[83,95,211],"predicted":[85],"ML":[88,165],"cannot":[89],"respected":[91],"a":[93,118,138,162,193,221],"series":[94],"complex":[96],"mathematical":[97],"operations":[98,185],"OR":[100,167,177],"lead":[101],"increased":[104],"accumulative":[105],"errors.":[106],"Essentially,":[107],"improved":[109],"precision":[110],"on":[111,121,186,204],"prediction":[113],"may":[115],"not":[116],"positive":[119],"correlation":[120],"final":[123],"due":[125],"side-effect":[128],"from":[129],"design.":[132],"In":[133],"this":[134],"paper,":[135],"we":[136,155,191,224],"propose":[137],"novel":[139],"approach":[140,227,257],"solving":[142],"mitigate":[147],"side-effects.":[149],"Our":[150],"key":[151],"intuition":[152],"that":[154,169,197,255],"introduce":[156],"decision":[158,188,206],"factor":[159],"establish":[161],"bridge":[163],"between":[164],"such":[168],"directly":[174],"obtained":[175],"by":[178],"only":[179],"performing":[180],"sorting":[182],"or":[183],"comparison":[184],"factor.":[189],"Furthermore,":[190],"design":[192],"customized":[194],"loss":[195,218],"function":[196],"conduct":[199],"direct":[200],"factor,":[207],"unbiased":[209],"estimation":[210],"which":[212],"guaranteed":[215],"when":[216],"convergences.":[219],"As":[220],"case":[222],"study,":[223],"apply":[225],"our":[226,256],"crucial":[230],"marketing:":[233],"binary":[235],"treatment":[236],"assignment":[237],"problem":[238,243],"budget":[241],"with":[244,262],"multiple":[245],"treatments.":[246],"Both":[247],"large-scale":[248],"simulations":[249],"online":[251],"A/B":[252],"Tests":[253],"demonstrate":[254],"achieves":[258],"significant":[259],"improvement":[260],"compared":[261],"state-of-the-art.":[263]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-06-28T00:00:00"}