{"id":"https://openalex.org/W4409547614","doi":"https://doi.org/10.1186/s40537-025-01143-4","title":"Leveraging deep learning for risk prediction and resilience in supply chains: insights from critical industries","display_name":"Leveraging deep learning for risk prediction and resilience in supply chains: insights from critical industries","publication_year":2025,"publication_date":"2025-04-17","ids":{"openalex":"https://openalex.org/W4409547614","doi":"https://doi.org/10.1186/s40537-025-01143-4"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-025-01143-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01143-4","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01143-4","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01143-4","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062189480","display_name":"Waleed Abdu Zogaan","orcid":"https://orcid.org/0000-0002-1087-7549"},"institutions":[{"id":"https://openalex.org/I91450128","display_name":"Jazan University","ror":"https://ror.org/02bjnq803","country_code":"SA","type":"education","lineage":["https://openalex.org/I91450128"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Waleed Abdu Zogaan","raw_affiliation_strings":["Department of Computer Science, College of Engineering & Computer Science, Jazan University, Jazan, Kingdom of Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Engineering & Computer Science, Jazan University, Jazan, Kingdom of Saudi Arabia","institution_ids":["https://openalex.org/I91450128"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076021681","display_name":"Nouran Ajabnoor","orcid":"https://orcid.org/0000-0003-3409-1556"},"institutions":[{"id":"https://openalex.org/I91450128","display_name":"Jazan University","ror":"https://ror.org/02bjnq803","country_code":"SA","type":"education","lineage":["https://openalex.org/I91450128"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Nouran Ajabnoor","raw_affiliation_strings":["Management Department, Applied College, Jazan University, Jazan, Kingdom of Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Department, Applied College, Jazan University, Jazan, Kingdom of Saudi Arabia","institution_ids":["https://openalex.org/I91450128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075690391","display_name":"Abdullah Ali Salamai","orcid":"https://orcid.org/0000-0001-9679-1545"},"institutions":[{"id":"https://openalex.org/I91450128","display_name":"Jazan University","ror":"https://ror.org/02bjnq803","country_code":"SA","type":"education","lineage":["https://openalex.org/I91450128"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Abdullah Ali Salamai","raw_affiliation_strings":["Management Department, Applied College, Jazan University, Jazan, Kingdom of Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Department, Applied College, Jazan University, Jazan, Kingdom of Saudi Arabia","institution_ids":["https://openalex.org/I91450128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91450128"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":21.022,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9922886,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"12","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11864","display_name":"Supply Chain Resilience and Risk Management","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"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/T11864","display_name":"Supply Chain Resilience and Risk Management","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"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/T11357","display_name":"Risk and Safety Analysis","score":0.9592000246047974,"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/T10809","display_name":"Occupational Health and Safety Research","score":0.9495000243186951,"subfield":{"id":"https://openalex.org/subfields/3614","display_name":"Radiological and Ultrasound Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.7353460788726807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7032448053359985},{"id":"https://openalex.org/keywords/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.6869490742683411},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.6189835667610168},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4759630560874939},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43946942687034607},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38842344284057617},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.37803590297698975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32545357942581177},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.18600034713745117}],"concepts":[{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.7353460788726807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032448053359985},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.6869490742683411},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.6189835667610168},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4759630560874939},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43946942687034607},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38842344284057617},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.37803590297698975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32545357942581177},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.18600034713745117},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-025-01143-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01143-4","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01143-4","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e05a0324ee4649f9a0c4afd85f2ef7a3","is_oa":true,"landing_page_url":"https://doaj.org/article/e05a0324ee4649f9a0c4afd85f2ef7a3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 12, Iss 1, Pp 1-23 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-025-01143-4","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01143-4","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-025-01143-4","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7115353681","display_name":null,"funder_award_id":"RG24-S0217","funder_id":"https://openalex.org/F4320311223","funder_display_name":"Jazan University"}],"funders":[{"id":"https://openalex.org/F4320311223","display_name":"Jazan University","ror":"https://ror.org/02bjnq803"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409547614.pdf","grobid_xml":"https://content.openalex.org/works/W4409547614.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W3045700869","https://openalex.org/W3196732841","https://openalex.org/W4311484111","https://openalex.org/W4313310734","https://openalex.org/W4316497066","https://openalex.org/W4318989734","https://openalex.org/W4321599671","https://openalex.org/W4321850382","https://openalex.org/W4322580329","https://openalex.org/W4322631283","https://openalex.org/W4323306195","https://openalex.org/W4324363949","https://openalex.org/W4362699000","https://openalex.org/W4364358088","https://openalex.org/W4367299642","https://openalex.org/W4380742518","https://openalex.org/W4385709272","https://openalex.org/W4385755820","https://openalex.org/W4385773365","https://openalex.org/W4386072825","https://openalex.org/W4386408427","https://openalex.org/W4387015170","https://openalex.org/W4387745472","https://openalex.org/W4387813290","https://openalex.org/W4388230751","https://openalex.org/W4388535601","https://openalex.org/W4388928933","https://openalex.org/W4389349074","https://openalex.org/W4389519167","https://openalex.org/W4390570412","https://openalex.org/W4390590913","https://openalex.org/W4390870551","https://openalex.org/W4391074439","https://openalex.org/W4391822043","https://openalex.org/W4391898501","https://openalex.org/W4392161882","https://openalex.org/W4392712508","https://openalex.org/W4393321636","https://openalex.org/W4396641341","https://openalex.org/W4400020700","https://openalex.org/W4400721462","https://openalex.org/W4400877552","https://openalex.org/W4401114909","https://openalex.org/W4401984013","https://openalex.org/W4403395361"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W4375867731","https://openalex.org/W4393232657","https://openalex.org/W2767550285","https://openalex.org/W4390638272","https://openalex.org/W2620085874","https://openalex.org/W2611989081","https://openalex.org/W2064496565","https://openalex.org/W4408313902","https://openalex.org/W2327847502"],"abstract_inverted_index":{"Supply":[0],"chain":[1,45],"resilience":[2,224],"(SCR)":[3],"is":[4],"crucial":[5],"for":[6,116],"firms":[7,208],"and":[8,13,30,47,75,87,103,107,164,176,203,209,229],"organizations":[9,210],"to":[10,15,24,53,99,192,215,233],"respond":[11],"swiftly":[12],"effectively":[14],"operational":[16],"disruptions,":[17],"ensuring":[18],"smooth":[19],"transitions":[20],"from":[21],"raw":[22],"materials":[23],"final":[25],"products.":[26],"To":[27],"enhance":[28],"SCR":[29],"mitigate":[31],"risks,":[32],"this":[33],"paper":[34],"proposes":[35],"a":[36,212],"deep":[37],"learning":[38,195],"(DL)":[39],"framework":[40],"that":[41,146],"helps":[42],"predict":[43,216],"supply":[44,123,221],"risks":[46,228],"provides":[48,207],"companies":[49],"with":[50,154,211],"actionable":[51],"insights":[52],"overcome":[54],"them.":[55,235],"We":[56],"applied":[57],"five":[58],"DL":[59,95,198],"models\u2014recurrent":[60],"neural":[61,72,77],"networks":[62,73,78],"(RNN),":[63],"long-short-term":[64],"memory":[65],"(LSTM),":[66],"gated":[67],"recurrent":[68],"units":[69],"(GRU),":[70],"convolutional":[71],"(CNN),":[74],"artificial":[76],"(ANN)\u2014across":[79],"four":[80],"key":[81],"case":[82,159],"studies:":[83],"pharmaceuticals,":[84],"automotive,":[85],"agriculture,":[86,110],"energy":[88,137],"(General":[89],"Electric).":[90],"In":[91,125,161],"the":[92,111,126,129,136,147,151,157,162,167,171,181],"pharmaceutical":[93,158],"case,":[94],"models":[96,112,130,199],"were":[97],"used":[98],"optimize":[100],"drug":[101],"inventory":[102],"logistics,":[104],"reducing":[105],"wastage":[106],"stock-outs.":[108],"For":[109],"predicted":[113,131],"food":[114,163],"demand":[115],"each":[117],"country":[118],"annually,":[119],"helping":[120],"ensure":[121],"efficient":[122],"management.":[124],"automotive":[127,165],"industry,":[128],"car":[132],"demand,":[133],"while":[134,180],"in":[135,156,186,219],"sector,":[138],"they":[139],"forecasted":[140],"electricity":[141,188],"needs.":[142],"Our":[143],"results":[144],"showed":[145],"CNN":[148],"model":[149,169,183],"achieved":[150],"highest":[152],"accuracy,":[153],"99.3%":[155],"study.":[160],"sectors,":[166],"GRU":[168],"had":[170],"lowest":[172],"mean":[173,177],"absolute":[174],"error":[175],"squared":[178],"error,":[179],"ANN":[182],"performed":[184],"best":[185],"predicting":[187],"demand.":[189],"When":[190],"compared":[191],"traditional":[193],"machine":[194],"models,":[196],"our":[197],"demonstrated":[200],"superior":[201],"accuracy":[202],"performance.":[204],"This":[205],"research":[206],"valuable":[213],"tool":[214],"future":[217],"disruptions":[218],"their":[220],"chains,":[222],"improving":[223],"by":[225],"identifying":[226],"potential":[227],"taking":[230],"proactive":[231],"measures":[232],"address":[234]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}