{"id":"https://openalex.org/W4310167923","doi":"https://doi.org/10.1080/08839514.2022.2151160","title":"Machine Learning Based Method for Deciding Internal Value of Talent","display_name":"Machine Learning Based Method for Deciding Internal Value of Talent","publication_year":2022,"publication_date":"2022-11-28","ids":{"openalex":"https://openalex.org/W4310167923","doi":"https://doi.org/10.1080/08839514.2022.2151160"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2151160","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2151160","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/08839514.2022.2151160","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040174438","display_name":"Edurne Loyarte","orcid":"https://orcid.org/0000-0003-0266-7784"},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Edurne Loyarte-L\u00f3pez","raw_affiliation_strings":["Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastian, Spain"],"raw_orcid":"https://orcid.org/0000-0003-0266-7784","affiliations":[{"raw_affiliation_string":"Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastian, Spain","institution_ids":["https://openalex.org/I4210092551"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041268250","display_name":"Igor G. Olaizola","orcid":"https://orcid.org/0000-0002-9965-2038"},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Igor Garc\u00eda-Olaizola","raw_affiliation_strings":["Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastian, Spain"],"raw_orcid":"https://orcid.org/0000-0002-9965-2038","affiliations":[{"raw_affiliation_string":"Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastian, Spain","institution_ids":["https://openalex.org/I4210092551"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040174438"],"corresponding_institution_ids":["https://openalex.org/I4210092551"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":1.5897,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84917248,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource 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/T13812","display_name":"AI and HR Technologies","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource 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/T12415","display_name":"Employer Branding and e-HRM","score":0.9480000138282776,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource 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/T10809","display_name":"Occupational Health and Safety Research","score":0.9217000007629395,"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/salary","display_name":"Salary","score":0.9457525610923767},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.742469847202301},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5936152338981628},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5667061805725098},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.473755419254303},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.46450161933898926},{"id":"https://openalex.org/keywords/equity","display_name":"Equity (law)","score":0.4285967946052551},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3473059833049774}],"concepts":[{"id":"https://openalex.org/C2780090960","wikidata":"https://www.wikidata.org/wiki/Q194489","display_name":"Salary","level":2,"score":0.9457525610923767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.742469847202301},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5936152338981628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5667061805725098},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.473755419254303},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.46450161933898926},{"id":"https://openalex.org/C199728807","wikidata":"https://www.wikidata.org/wiki/Q2578557","display_name":"Equity (law)","level":2,"score":0.4285967946052551},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3473059833049774},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2022.2151160","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2151160","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f894ca5c010e467c8fe3d9114613e3c3","is_oa":false,"landing_page_url":"https://doaj.org/article/f894ca5c010e467c8fe3d9114613e3c3","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2151160","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2151160","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W643335905","https://openalex.org/W1607647184","https://openalex.org/W1678356000","https://openalex.org/W1979900513","https://openalex.org/W2003572022","https://openalex.org/W2028182325","https://openalex.org/W2096731204","https://openalex.org/W2215262963","https://openalex.org/W2413572567","https://openalex.org/W2604205238","https://openalex.org/W2753694645","https://openalex.org/W2766718657","https://openalex.org/W2887307980","https://openalex.org/W2906839688","https://openalex.org/W2909731695","https://openalex.org/W2940954969","https://openalex.org/W2963518130","https://openalex.org/W2972466596","https://openalex.org/W2978195003","https://openalex.org/W2997319569","https://openalex.org/W2999961989","https://openalex.org/W3004543754","https://openalex.org/W3007361867","https://openalex.org/W3009937232","https://openalex.org/W3022513070","https://openalex.org/W3027506574","https://openalex.org/W3045607964","https://openalex.org/W3114288695","https://openalex.org/W3119305695","https://openalex.org/W3119839364","https://openalex.org/W3120383678","https://openalex.org/W3181262202","https://openalex.org/W3208970270","https://openalex.org/W3210475940","https://openalex.org/W3213774040","https://openalex.org/W3215367316","https://openalex.org/W4206246967","https://openalex.org/W4206346145","https://openalex.org/W4211220224","https://openalex.org/W4236605067","https://openalex.org/W4238264693","https://openalex.org/W4247155454","https://openalex.org/W4288617757"],"related_works":["https://openalex.org/W2368582007","https://openalex.org/W2381014559","https://openalex.org/W2350975767","https://openalex.org/W4377081005","https://openalex.org/W2369068260","https://openalex.org/W2383301438","https://openalex.org/W2360793741","https://openalex.org/W2182802719","https://openalex.org/W748163983","https://openalex.org/W3029420775"],"abstract_inverted_index":{"This":[0,150],"paper":[1],"presents":[2,152],"a":[3,30,65,68,91,141,153],"machine-learning-based":[4,112],"method":[5,79,104],"for":[6,17,123,131],"evaluating":[7,18],"the":[8,19,25,41,51,56,78,97,138,168],"internal":[9,42,48,61,148],"value":[10,43],"of":[11,29,44,55,157],"talent":[12,87],"in":[13,50],"any":[14],"organization":[15,95],"and":[16,27,46,76,83,100,111,171],"salary":[20,31,129,174],"criteria.":[21],"The":[22,53,102],"study":[23,57,151],"assumes":[24],"design":[26],"development":[28],"predictor,":[32],"based":[33,106,177],"on":[34,107,178],"artificial":[35,158],"intelligence":[36,159],"technologies,":[37],"to":[38,59,134,137,145],"help":[39,165],"determine":[40],"employees":[45,82],"guarantee":[47],"equity":[49],"organization.":[52],"aim":[54],"is":[58,64,105],"achieve":[60],"equity,":[62],"which":[63],"critical":[66],"element":[67],"that":[69,116],"directly":[70],"affects":[71],"employees\u2019":[72],"motivation.":[73],"We":[74,114],"implemented":[75],"validated":[77],"with":[80,90],"130":[81],"more":[84],"than":[85],"70":[86],"acquisition":[88],"cases":[89],"Basque":[92],"technology":[93],"research":[94],"during":[96],"years":[98],"2021":[99],"2022.":[101],"proposed":[103],"statistical":[108],"data":[109],"assessment":[110],"regression.":[113],"found":[115],"while":[117],"most":[118,169],"organizations":[119],"have":[120],"established":[121],"variables":[122],"job":[124],"evaluation":[125],"as":[126,128],"well":[127],"increments":[130],"staff":[132],"according":[133],"their":[135],"contribution":[136],"organization,":[139],"only":[140],"few":[142],"employ":[143],"tools":[144],"support":[146],"equitable":[147,170],"compensation.":[149],"successful":[154],"real":[155],"case":[156],"applications":[160],"where":[161],"machine":[162],"learning":[163],"techniques":[164],"managers":[166],"make":[167],"least":[172],"biased":[173],"decisions":[175],"possible,":[176],"data.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}