{"id":"https://openalex.org/W2913025895","doi":"https://doi.org/10.1109/bigdata.2018.8622044","title":"Service failure prediction in supply-chain networks","display_name":"Service failure prediction in supply-chain networks","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2913025895","doi":"https://doi.org/10.1109/bigdata.2018.8622044","mag":"2913025895"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5071121876","display_name":"Monika Sharma","orcid":"https://orcid.org/0000-0003-2340-2072"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Monika Sharma","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075952219","display_name":"Tristan Glatard","orcid":"https://orcid.org/0000-0003-2620-5883"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tristan Glatard","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045401414","display_name":"\u00c9ric G\u00e9linas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eric Gelinas","raw_affiliation_strings":["ClearDestination Inc, Montr\u00e9al, Qu\u00e9bec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ClearDestination Inc, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029660367","display_name":"Mariam Tagmouti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mariam Tagmouti","raw_affiliation_strings":["ClearDestination Inc, Montr\u00e9al, Qu\u00e9bec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ClearDestination Inc, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048080334","display_name":"Brigitte Jaumard","orcid":"https://orcid.org/0000-0003-3443-4918"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Brigitte Jaumard","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montr\u00e9al, Qu\u00e9bec, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1215","issue":null,"first_page":"1827","last_page":"1836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.979200005531311,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.979200005531311,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.972599983215332,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6126297116279602},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.6031335592269897},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5425984263420105},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.5237714648246765},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48840874433517456},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.47316843271255493},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3936167359352112},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3411974310874939},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27450478076934814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2573835849761963},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.19899147748947144},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13696950674057007},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.0907236635684967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126297116279602},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.6031335592269897},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5425984263420105},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.5237714648246765},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48840874433517456},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.47316843271255493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3936167359352112},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3411974310874939},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27450478076934814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2573835849761963},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.19899147748947144},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13696950674057007},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0907236635684967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W2064853889","https://openalex.org/W2076135993","https://openalex.org/W2084789233","https://openalex.org/W2105002757","https://openalex.org/W2119097848","https://openalex.org/W2137609793","https://openalex.org/W2148143831","https://openalex.org/W2155261478","https://openalex.org/W2911964244","https://openalex.org/W3155649056","https://openalex.org/W4252403066","https://openalex.org/W6628750762"],"related_works":["https://openalex.org/W2751920613","https://openalex.org/W2415164632","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W2238349241","https://openalex.org/W3171520305","https://openalex.org/W2355668701","https://openalex.org/W2370453500","https://openalex.org/W2889302474"],"abstract_inverted_index":{"We":[0,21],"aim":[1],"to":[2,19,68,72,123,127,130],"predict":[3],"and":[4,16,35,47,87,98],"explain":[5],"service":[6,115],"failures":[7,70],"in":[8],"supply-chain":[9],"networks,":[10],"more":[11],"precisely":[12],"among":[13],"last-mile":[14],"pickup":[15],"delivery":[17],"services":[18,27],"customers.":[20],"analyze":[22],"a":[23],"dataset":[24],"of":[25,45,51,58,65,80,90,102,114],"500,000":[26],"using":[28],"(1)":[29],"supervised":[30],"classification":[31],"with":[32],"Random":[33],"Forests,":[34],"(2)":[36],"Association":[37,60],"Rules.":[38],"Our":[39],"classifier":[40],"reaches":[41],"an":[42,48],"average":[43,49],"sensitivity":[44],"0.7":[46,52],"specificity":[50],"for":[53,93],"the":[54,63,78,81,91,94,100,103,112],"5":[55],"studied":[56],"types":[57],"failure.":[59],"Rules":[61],"reassert":[62],"importance":[64,79],"confirmation":[66],"calls":[67],"prevent":[69],"due":[71],"customers":[73],"not":[74],"at":[75],"home,":[76],"show":[77],"time":[82],"window":[83],"size,":[84],"slack":[85],"time,":[86],"geographical":[88],"location":[89],"customer":[92],"other":[95],"failure":[96,108],"types,":[97],"highlight":[99],"effect":[101],"retailer":[104],"company":[105],"on":[106],"several":[107],"types.":[109],"To":[110],"reduce":[111],"occurrence":[113],"failures,":[116],"our":[117],"data":[118],"models":[119],"could":[120],"be":[121,131],"coupled":[122],"optimizers,":[124],"or":[125],"used":[126],"define":[128],"counter-measures":[129],"taken":[132],"by":[133],"human":[134],"dispatchers.":[135]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}