{"id":"https://openalex.org/W4319782001","doi":"https://doi.org/10.1109/dsaa54385.2022.10032453","title":"Enterprise Event Risk Detection Based on Supply Chain Contagion","display_name":"Enterprise Event Risk Detection Based on Supply Chain Contagion","publication_year":2022,"publication_date":"2022-10-13","ids":{"openalex":"https://openalex.org/W4319782001","doi":"https://doi.org/10.1109/dsaa54385.2022.10032453"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa54385.2022.10032453","doi":"https://doi.org/10.1109/dsaa54385.2022.10032453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa54385.2022.10032453","pdf_url":null,"source":{"id":"https://openalex.org/S4363608340","display_name":"IEEE International Conference on Data Science and Advanced Analytics (DSAA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W4319782001"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"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/A5020728580","display_name":"Chuanhui Zhang","orcid":"https://orcid.org/0000-0003-4141-5731","observed_orcids":["https://orcid.org/0000-0003-4141-5731","https://orcid.org/0000-0001-6402-0607"]},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanhui Zhang","raw_affiliation_strings":["Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021956950","display_name":"Junxiao Chen","orcid":"https://orcid.org/0009-0007-8438-3510","observed_orcids":["https://orcid.org/0009-0007-8438-3510","https://orcid.org/0009-0005-8890-7831"]},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junxiao Chen","raw_affiliation_strings":["Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101650479","display_name":"Tao Shu","orcid":"https://orcid.org/0000-0003-0417-2814","observed_orcids":["https://orcid.org/0000-0003-0417-2814"]},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Shu","raw_affiliation_strings":["Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007629733","display_name":"Jinghua Tan","orcid":"https://orcid.org/0000-0001-5011-0011","observed_orcids":["https://orcid.org/0000-0001-5011-0011"]},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghua Tan","raw_affiliation_strings":["Southwestern University of Finance and Economics, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics, Chengdu, China","institution_ids":["https://openalex.org/I204831749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204831749"],"apc_list":null,"apc_paid":null,"fwci":1.0535,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7070546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.8095999956130981,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.8095999956130981,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.09300000220537186,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.027499999850988388,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/enterprise-networks","display_name":"enterprise networks","score":0.4560000002384186},{"id":"https://openalex.org/keywords/self-supervised-learning","display_name":"self-supervised learning","score":0.9829999804496765},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.921999990940094},{"id":"https://openalex.org/keywords/risk-prediction","display_name":"risk prediction","score":0.4490000009536743}],"concepts":[{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.635353684425354},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5360873341560364},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.5150566101074219},{"id":"https://openalex.org/C149859251","wikidata":"https://www.wikidata.org/wiki/Q483426","display_name":"Enterprise private network","level":2,"score":0.4850432276725769},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.4846782982349396},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.46448570489883423},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3932371139526367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39083337783813477},{"id":"https://openalex.org/C40700","wikidata":"https://www.wikidata.org/wiki/Q1411783","display_name":"Industrial organization","level":1,"score":0.3257884383201599},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.1694439947605133},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09877660870552063},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa54385.2022.10032453","doi":"https://doi.org/10.1109/dsaa54385.2022.10032453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa54385.2022.10032453","pdf_url":null,"source":{"id":"https://openalex.org/S4363608340","display_name":"IEEE International Conference on Data Science and Advanced Analytics (DSAA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323711","display_name":"Southwest University","ror":"https://ror.org/01kj4z117"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W2059366883","https://openalex.org/W2064675550","https://openalex.org/W2116341502","https://openalex.org/W2117671523","https://openalex.org/W2153513200","https://openalex.org/W2395501422","https://openalex.org/W2761075141","https://openalex.org/W2925310892","https://openalex.org/W2950906777","https://openalex.org/W3034242908","https://openalex.org/W3065542300","https://openalex.org/W3080686571","https://openalex.org/W3101248344","https://openalex.org/W3101345273","https://openalex.org/W3130577540","https://openalex.org/W3174924631"],"related_works":["https://openalex.org/W4416345088","https://openalex.org/W4401008895","https://openalex.org/W4405827811","https://openalex.org/W7168667599","https://openalex.org/W4417443705","https://openalex.org/W7204440120","https://openalex.org/W7115942433","https://openalex.org/W7124745834","https://openalex.org/W7160263343","https://openalex.org/W7168082288"],"abstract_inverted_index":{"As":[0],"the":[1,4,16,48,59,67,80,89,98,128,134,158,181,188,201,218,234],"micro-foundation":[2],"of":[3,50,69,82,115,126,136,149,161,185,203,236],"market":[5,21],"economy,":[6],"identifying":[7,127],"and":[8,19,25,35,179,207,225,229,238],"preventing":[9],"various":[10,37],"risks":[11,131,199,228],"are":[12,55,124],"crucial":[13],"both":[14],"for":[15,20,223,233],"companies":[17,237],"themselves":[18],"regulators,":[22],"financial":[23],"institutions":[24],"investors.":[26,239],"To":[27,138],"detect":[28],"enterprise":[29,51,74,84,198,227],"risks,":[30],"many":[31],"studies":[32],"have":[33],"constructed":[34],"utilized":[36],"indicator":[38,104],"metrics":[39,105],"based":[40,151],"on":[41,66,103,152,213],"information":[42,232],"about":[43],"each":[44,83],"company":[45,170],"to":[46,107,144,156,196],"assess":[47],"level":[49],"risk.":[52],"However,":[53],"enterprises":[54,91,150,186],"not":[56,77],"independent":[57],"in":[58,92],"market,":[60],"they":[61],"form":[62],"a":[63,109,112,147,175],"complex":[64],"network":[65,148],"basis":[68],"their":[70],"production":[71],"activities.":[72],"The":[73,210],"risk":[75,99,116],"comes":[76],"only":[78],"from":[79,88,169,200],"operation":[81],"itself,":[85],"but":[86],"also":[87],"related":[90,162],"its":[93],"business":[94],"network.":[95],"In":[96],"addition,":[97],"detection":[100],"methods":[101,123],"relied":[102],"aims":[106,143],"asset":[108],"specific":[110],"or":[111],"certain":[113],"kind":[114],"faced":[117],"by":[118,133],"enterprises.":[119,137],"That":[120],"is,":[121],"these":[122],"incapability":[125],"constantly":[129],"changing":[130],"caused":[132],"uncertainty":[135],"this":[139,141],"end,":[140],"study":[142],"(i)":[145],"construct":[146],"supply":[153,204],"chain":[154,205],"relationships":[155],"incorporate":[157],"contagion":[159,206],"effect":[160],"companies,":[163],"(ii)":[164],"learn":[165],"event":[166,172],"prototype":[167],"representations":[168],"action":[171],"data":[173],"via":[174],"self-supervised":[176],"learning":[177],"method,":[178],"capture":[180],"time-varying":[182],"operational":[183],"states":[184],"using":[187],"learned":[189],"prototypes,":[190],"(iii)":[191],"adopt":[192],"graph":[193],"neural":[194],"networks":[195],"identify":[197],"perspective":[202],"comprehensive":[208],"events.":[209],"experimental":[211],"results":[212],"real":[214],"datasets":[215],"show":[216],"that":[217],"proposed":[219],"method":[220],"is":[221],"important":[222],"predicting":[224],"assessing":[226],"provides":[230],"useful":[231],"decision-making":[235]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2023-02-11T00:00:00"}
