{"id":"https://openalex.org/W7224990819","doi":"https://doi.org/10.56557/ajocr/2026/v11i411300","title":"Beyond Prediction: Bridging the AI Intervention Gap in Pavement Maintenance through Evidence-based Decision-making: A Critical Review","display_name":"Beyond Prediction: Bridging the AI Intervention Gap in Pavement Maintenance through Evidence-based Decision-making: A Critical Review","publication_year":2026,"publication_date":"2026-10-31","ids":{"openalex":"https://openalex.org/W7224990819","doi":"https://doi.org/10.56557/ajocr/2026/v11i411300"},"language":"en","primary_location":{"id":"doi:10.56557/ajocr/2026/v11i411300","doi":"https://doi.org/10.56557/ajocr/2026/v11i411300","is_oa":true,"landing_page_url":"https://doi.org/10.56557/ajocr/2026/v11i411300","pdf_url":null,"source":{"id":"https://openalex.org/S4387282279","display_name":"Asian Journal of Current Research","issn_l":"2456-804X","issn":["2456-804X"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Asian Journal of Current Research","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.56557/ajocr/2026/v11i411300","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160248346","display_name":"Vivian Chinwendu Okpalaku-Nath","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405256974","display_name":"State University of Medical and Applied Sciences","ror":"https://ror.org/04r3nef08","country_code":"NG","type":"education","lineage":["https://openalex.org/I4405256974"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Vivian Chinwendu Okpalaku-Nath","raw_affiliation_strings":["Department of Civil Engineering, State University of Medical and Applied Sciences, Igbo-Eno, Enugu State, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, State University of Medical and Applied Sciences, Igbo-Eno, Enugu State, Nigeria","institution_ids":["https://openalex.org/I4405256974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114127717","display_name":"D. A. Ekpechi","orcid":"https://orcid.org/0000-0002-8779-4098","observed_orcids":["https://orcid.org/0000-0002-8779-4098"]},"institutions":[{"id":"https://openalex.org/I16443873","display_name":"Federal University of Technology Owerri","ror":"https://ror.org/05xzf9508","country_code":"NG","type":"education","lineage":["https://openalex.org/I16443873"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Daniel Arinze Ekpechi","raw_affiliation_strings":["Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Federal University of Technology, Owerri, Nigeria","institution_ids":["https://openalex.org/I16443873"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160264155","display_name":"Ifeanyi Abazie Vitalis","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2799973717","display_name":"IHE Delft Institute for Water Education","ror":"https://ror.org/030deh410","country_code":"NL","type":"education","lineage":["https://openalex.org/I2799973717"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ifeanyi Abazie Vitalis","raw_affiliation_strings":["IHE Delft Institute for Water Education, Westvest 7, 2611 AX Delft, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IHE Delft Institute for Water Education, Westvest 7, 2611 AX Delft, The Netherlands","institution_ids":["https://openalex.org/I2799973717"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7771797,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"4","first_page":"224","last_page":"249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T13527","display_name":"Road Transport and Highway Systems","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/pavement-maintenance","display_name":"pavement maintenance","score":0.8840000033378601},{"id":"https://openalex.org/keywords/evidence-based-decision-making","display_name":"evidence-based decision making","score":0.8970000147819519},{"id":"https://openalex.org/keywords/pavement-deterioration-prediction","display_name":"pavement deterioration prediction","score":0.7590000033378601},{"id":"https://openalex.org/keywords/treatment-effect-estimation","display_name":"treatment effect estimation","score":0.8059999942779541},{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.7549999952316284},{"id":"https://openalex.org/keywords/model-validation","display_name":"model validation","score":0.5139999985694885},{"id":"https://openalex.org/keywords/digital-twin","display_name":"digital twin","score":0.6470000147819519},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.4560000002384186},{"id":"https://openalex.org/keywords/maintenance-planning","display_name":"maintenance planning","score":0.671999990940094},{"id":"https://openalex.org/keywords/outcome-monitoring","display_name":"outcome monitoring","score":0.42399999499320984},{"id":"https://openalex.org/keywords/road-authorities","display_name":"road authorities","score":0.5339999794960022}],"concepts":[{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.475600004196167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40849998593330383},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C22467394","wikidata":"https://www.wikidata.org/wiki/Q849359","display_name":"Multidisciplinary approach","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.365200012922287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36090001463890076},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3440000116825104},{"id":"https://openalex.org/C79897977","wikidata":"https://www.wikidata.org/wiki/Q5054568","display_name":"Causal chain","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.31299999356269836},{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C184356942","wikidata":"https://www.wikidata.org/wiki/Q830382","display_name":"Best practice","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.29989999532699585},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.28209999203681946},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27790001034736633},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.272599995136261},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.2653000056743622},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C108170787","wikidata":"https://www.wikidata.org/wiki/Q3951828","display_name":"Agency (philosophy)","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C186116695","wikidata":"https://www.wikidata.org/wiki/Q5249226","display_name":"Decision analysis","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.56557/ajocr/2026/v11i411300","doi":"https://doi.org/10.56557/ajocr/2026/v11i411300","is_oa":true,"landing_page_url":"https://doi.org/10.56557/ajocr/2026/v11i411300","pdf_url":null,"source":{"id":"https://openalex.org/S4387282279","display_name":"Asian Journal of Current Research","issn_l":"2456-804X","issn":["2456-804X"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Asian Journal of Current Research","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-05847642v1","doi":null,"is_oa":false,"landing_page_url":"https://hal.science/hal-05847642","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Asian Journal of Current Research, 2026, 11 (4), pp.224-249","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.56557/ajocr/2026/v11i411300","doi":"https://doi.org/10.56557/ajocr/2026/v11i411300","is_oa":true,"landing_page_url":"https://doi.org/10.56557/ajocr/2026/v11i411300","pdf_url":null,"source":{"id":"https://openalex.org/S4387282279","display_name":"Asian Journal of Current Research","issn_l":"2456-804X","issn":["2456-804X"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Asian Journal of Current Research","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9"},{"display_name":"Sustainable cities and communities","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7108331879","https://openalex.org/W4417163941","https://openalex.org/W7014607475","https://openalex.org/W7214704003","https://openalex.org/W4404780546","https://openalex.org/W7033522291","https://openalex.org/W4400663336","https://openalex.org/W7122637647","https://openalex.org/W3137685776","https://openalex.org/W7167020127"],"abstract_inverted_index":{"Road":[0],"agencies":[1,297],"are":[2,30,179,187,227,277],"investing":[3],"in":[4,47,193,273],"artificial":[5,53],"intelligence":[6,54],"to":[7,112,199],"inspect":[8],"pavements,":[9],"forecast":[10],"deterioration":[11,105],"and":[12,32,44,65,73,76,86,101,107,115,126,133,168,171,204,213,218,229,239,252,296,312,321,326],"plan":[13],"maintenance,":[14,49],"yet":[15],"the":[16,27,39,52,149,235,292,299],"value":[17],"of":[18,63,109,301,316,324],"these":[19],"tools":[20],"ultimately":[21],"depends":[22],"on":[23,140],"whether":[24],"they":[25],"improve":[26],"interventions":[28],"that":[29,97,265],"funded":[31],"delivered.":[33],"This":[34],"critical":[35],"narrative":[36],"review":[37,263],"examines":[38],"gap":[40],"between":[41],"predictive":[42],"performance":[43],"intervention":[45,55,275],"quality":[46,286],"pavement":[48,266],"termed":[50],"here":[51],"gap.":[56],"Literature":[57],"was":[58,77,196],"identified":[59],"through":[60,104],"structured":[61],"searches":[62],"multidisciplinary":[64],"regional":[66],"scholarly":[67],"indexes,":[68],"supplemented":[69],"by":[70],"citation":[71],"tracking":[72],"institutional":[74],"sources,":[75],"appraised":[78],"for":[79,122],"design":[80],"adequacy,":[81],"validation":[82,163],"practice,":[83],"causal":[84,183],"identification":[85],"decision":[87,95,285],"relevance.":[88],"The":[89,118,262],"synthesis":[90],"is":[91,120,255,281,291],"organised":[92],"along":[93,148],"a":[94,210],"chain":[96],"runs":[98],"from":[99,174,190,234],"sensing":[100],"condition":[102,128],"assessment,":[103],"prediction":[106,289],"estimation":[108],"treatment":[110],"effects,":[111],"optimisation,":[113],"implementation":[114],"outcome":[116],"feedback.":[117],"evidence":[119],"strongest":[121],"automated":[123],"distress":[124],"detection":[125],"short-term":[127],"prediction,":[129],"where":[130],"deep":[131],"learning":[132,217],"ensemble":[134],"models":[135],"frequently":[136],"achieve":[137],"high":[138],"accuracy":[139],"benchmark":[141,306],"or":[142,160],"single-agency":[143],"data.":[144],"Confidence":[145],"weakens":[146],"progressively":[147],"chain.":[150],"Performance":[151],"claims":[152],"rarely":[153],"survive":[154],"transfer":[155],"across":[156],"regions,":[157],"survey":[158],"technologies":[159],"time":[161],"periods,":[162],"designs":[164],"often":[165],"ignore":[166],"spatial":[167],"temporal":[169],"dependence,":[170],"explanations":[172],"derived":[173],"post":[175],"hoc":[176],"attribution":[177],"methods":[178],"commonly":[180],"interpreted":[181],"as":[182],"mechanisms.":[184],"Treatment":[185],"effects":[186,276],"usually":[188],"inferred":[189],"observational":[191],"records":[192],"which":[194,274],"maintenance":[195,267],"assigned":[197],"according":[198],"condition,":[200],"so":[201],"selection":[202],"bias":[203],"endogeneity":[205],"remain":[206],"largely":[207,259],"unaddressed":[208],"outside":[209],"small":[211],"econometric":[212],"causal-inference":[214],"literature.":[215],"Reinforcement":[216],"metaheuristic":[219],"planning":[220],"studies":[221],"report":[222],"cost":[223],"savings,":[224],"but":[225],"most":[226],"trained":[228],"evaluated":[230],"within":[231],"simulators":[232],"built":[233],"same":[236],"associational":[237],"models,":[238],"few":[240],"compare":[241],"recommended":[242,302],"policies":[243],"with":[244,308],"realised":[245],"outcomes.":[246],"Implementation":[247],"evidence,":[248],"including":[249],"digital":[250],"twins":[251],"language-model":[253],"assistants,":[254],"at":[256],"an":[257,269],"early,":[258],"demonstrative":[260],"stage.":[261],"argues":[264],"requires":[268],"evidence-based":[270],"decision-making":[271],"standard":[272],"explicitly":[278],"identified,":[279],"uncertainty":[280],"propagated":[282],"into":[283],"decisions,":[284],"rather":[287],"than":[288],"error":[290],"primary":[293],"evaluation":[294],"criterion,":[295],"monitor":[298],"outcomes":[300],"treatments.":[303],"Priorities":[304],"include":[305],"datasets":[307],"recorded":[309],"interventions,":[310],"quasi-experimental":[311],"pragmatic":[313],"field":[314],"evaluations":[315],"treatments,":[317],"decision-focused":[318],"model":[319],"training":[320],"prospective":[322],"comparison":[323],"algorithmic":[325],"conventional":[327],"programmes.":[328]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-11-01T00:00:00"}
