{"id":"https://openalex.org/W4405728535","doi":"https://doi.org/10.1080/00207543.2024.2442548","title":"Predicting complaints in semiconductor order fulfilment with machine learning","display_name":"Predicting complaints in semiconductor order fulfilment with machine learning","publication_year":2024,"publication_date":"2024-12-23","ids":{"openalex":"https://openalex.org/W4405728535","doi":"https://doi.org/10.1080/00207543.2024.2442548"},"language":"en","primary_location":{"id":"doi:10.1080/00207543.2024.2442548","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2024.2442548","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","raw_type":"journal-article"},"type":"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/A5073155730","display_name":"Patrick Moder","orcid":"https://orcid.org/0000-0003-4576-7128"},"institutions":[{"id":"https://openalex.org/I186044516","display_name":"K\u00fchne Logistics University","ror":"https://ror.org/00z9cn431","country_code":"DE","type":"education","lineage":["https://openalex.org/I186044516"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Patrick Moder","raw_affiliation_strings":["K\u00fchne Logistics University","Department of Operations and Technology, K\u00fchne Logistics University, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"K\u00fchne Logistics University","institution_ids":["https://openalex.org/I186044516"]},{"raw_affiliation_string":"Department of Operations and Technology, K\u00fchne Logistics University, Hamburg, Germany","institution_ids":["https://openalex.org/I186044516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057554568","display_name":"Kai Hoberg","orcid":"https://orcid.org/0000-0003-2835-572X"},"institutions":[{"id":"https://openalex.org/I186044516","display_name":"K\u00fchne Logistics University","ror":"https://ror.org/00z9cn431","country_code":"DE","type":"education","lineage":["https://openalex.org/I186044516"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Kai Hoberg","raw_affiliation_strings":["K\u00fchne Logistics University","Department of Operations and Technology, K\u00fchne Logistics University, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"K\u00fchne Logistics University","institution_ids":["https://openalex.org/I186044516"]},{"raw_affiliation_string":"Department of Operations and Technology, K\u00fchne Logistics University, Hamburg, Germany","institution_ids":["https://openalex.org/I186044516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057554568"],"corresponding_institution_ids":["https://openalex.org/I186044516"],"apc_list":null,"apc_paid":null,"fwci":0.8443,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78072144,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"63","issue":"13","first_page":"4776","last_page":"4799"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9975000023841858,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9975000023841858,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9742000102996826,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T10763","display_name":"Digital Transformation in Industry","score":0.9611999988555908,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.5377045273780823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4184868633747101},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.41736841201782227},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3965267837047577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38723742961883545},{"id":"https://openalex.org/keywords/manufacturing-engineering","display_name":"Manufacturing engineering","score":0.37682870030403137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34959930181503296},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.326188862323761},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.24518561363220215}],"concepts":[{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.5377045273780823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4184868633747101},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.41736841201782227},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3965267837047577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38723742961883545},{"id":"https://openalex.org/C117671659","wikidata":"https://www.wikidata.org/wiki/Q11049265","display_name":"Manufacturing engineering","level":1,"score":0.37682870030403137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34959930181503296},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.326188862323761},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.24518561363220215},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00207543.2024.2442548","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2024.2442548","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Production Research","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W83133245","https://openalex.org/W167016754","https://openalex.org/W188500255","https://openalex.org/W429766147","https://openalex.org/W1678356000","https://openalex.org/W1780158451","https://openalex.org/W1820101256","https://openalex.org/W1973774762","https://openalex.org/W1974328039","https://openalex.org/W1984045136","https://openalex.org/W1988482106","https://openalex.org/W1992955697","https://openalex.org/W2002779463","https://openalex.org/W2008657779","https://openalex.org/W2011795147","https://openalex.org/W2012874307","https://openalex.org/W2018665410","https://openalex.org/W2025266568","https://openalex.org/W2028689748","https://openalex.org/W2052231170","https://openalex.org/W2060068786","https://openalex.org/W2073510076","https://openalex.org/W2087330649","https://openalex.org/W2089314759","https://openalex.org/W2090773524","https://openalex.org/W2099801393","https://openalex.org/W2117190680","https://openalex.org/W2125055259","https://openalex.org/W2130255953","https://openalex.org/W2134345109","https://openalex.org/W2138182749","https://openalex.org/W2148143831","https://openalex.org/W2149698689","https://openalex.org/W2158698691","https://openalex.org/W2159809862","https://openalex.org/W2166058515","https://openalex.org/W2189916683","https://openalex.org/W2414921590","https://openalex.org/W2505921950","https://openalex.org/W2778911205","https://openalex.org/W2780508324","https://openalex.org/W2792848070","https://openalex.org/W2794225564","https://openalex.org/W2883455291","https://openalex.org/W2911964244","https://openalex.org/W2942640611","https://openalex.org/W2975867066","https://openalex.org/W2999615587","https://openalex.org/W3025544249","https://openalex.org/W3036451822","https://openalex.org/W3093318815","https://openalex.org/W3125255602","https://openalex.org/W3125627176","https://openalex.org/W3125937743","https://openalex.org/W3136633992","https://openalex.org/W3154914545","https://openalex.org/W3167284347","https://openalex.org/W3173523341","https://openalex.org/W3196957003","https://openalex.org/W4232178010","https://openalex.org/W4240053330","https://openalex.org/W4241545358","https://openalex.org/W4244923527","https://openalex.org/W4244958114","https://openalex.org/W4247351191","https://openalex.org/W4248012232","https://openalex.org/W4251859756","https://openalex.org/W4256669726","https://openalex.org/W4296959347","https://openalex.org/W4378770442","https://openalex.org/W4385172865","https://openalex.org/W4386207752","https://openalex.org/W4388971978","https://openalex.org/W4391656763","https://openalex.org/W4399433522","https://openalex.org/W4400120651","https://openalex.org/W6607671349"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4224009465","https://openalex.org/W4306674287","https://openalex.org/W4286629047","https://openalex.org/W4205958290","https://openalex.org/W4384212932","https://openalex.org/W4390590544","https://openalex.org/W2096195258","https://openalex.org/W2990460313","https://openalex.org/W2337755673"],"abstract_inverted_index":{"Many":[0],"customers":[1,17],"complain":[2],"when":[3,194],"informed":[4],"that":[5,99,142],"their":[6],"order":[7,60,144,169,179,195],"will":[8,63],"not":[9],"be":[10,19,30],"fulfilled":[11],"as":[12,123],"originally":[13],"confirmed,":[14],"while":[15],"other":[16],"may":[18],"able":[20],"to":[21,47,163],"tolerate":[22],"deviations.":[23],"However,":[24],"for":[25,116,189],"suppliers,":[26],"such":[27],"complaints":[28],"can":[29,44,72],"an":[31],"early":[32],"indicator":[33],"of":[34,167],"bad":[35],"publicity,":[36],"customer":[37,66,157,172],"churn,":[38],"and":[39,42,120,156,174],"lost":[40],"sales;":[41],"suppliers":[43,71],"prioritise":[45],"orders":[46],"avoid":[48],"these":[49,74],"negative":[50],"consequences.":[51],"Ideally,":[52],"they":[53],"would":[54],"know":[55],"in":[56,77],"advance":[57],"if":[58],"any":[59],"fulfilment":[61,145,170,196],"change":[62],"trigger":[64],"a":[65,78,87,92,129],"complaint.":[67],"To":[68],"analyse":[69],"how":[70],"predict":[73],"infrequent":[75],"events":[76],"business-to-business":[79],"context,":[80],"we":[81],"leverage":[82],"machine":[83],"learning":[84],"models":[85],"on":[86,113,171],"large":[88],"real-world":[89],"dataset":[90],"from":[91],"global":[93],"semiconductor":[94],"manufacturer.":[95],"Our":[96,136,183],"findings":[97],"demonstrate":[98],"extreme":[100],"gradient":[101],"boosted":[102],"trees":[103],"effectively":[104],"address":[105],"the":[106,111,125,151,165,187],"prediction":[107],"problem.":[108],"We":[109],"explore":[110],"impact":[112],"model":[114],"performance":[115],"different":[117],"sampling":[118],"approaches":[119],"cutoff":[121],"values,":[122],"tuning":[124],"decision":[126],"threshold":[127],"is":[128,197],"meaningful":[130],"calibration":[131],"strategy":[132],"before":[133],"practical":[134],"implementation.":[135],"feature":[137],"importance":[138],"analysis":[139],"provides":[140],"evidence":[141],"high":[143],"quality":[146],"lowers":[147],"complaint":[148],"tendencies.":[149],"Bridging":[150],"gap":[152],"between":[153],"advanced":[154],"analytics":[155],"behaviour":[158],"prediction,":[159],"our":[160],"research":[161],"contributes":[162],"understanding":[164],"influence":[166],"subpar":[168],"satisfaction":[173],"offers":[175],"insights":[176],"into":[177],"efficient":[178],"management":[180],"despite":[181],"disruptions.":[182],"empirical":[184],"study":[185],"lays":[186],"groundwork":[188],"proactive":[190],"supply":[191],"chain":[192],"operations":[193],"at":[198],"risk.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
