{"id":"W4400474378","doi":"10.5267/j.uscm.2024.5.005","title":"Utilizing Artificial Intelligence (AI) in enhancing customer-supplier relationship: An exploratory study in the banking industry","year":2024,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Banking industry; Exploratory research; Industrial organization; Supplier relationship management; Process management; Computer science; Operations management; Marketing; Finance; Supply chain management; Supply chain; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003362919,0.0002393505,0.0003152132,0.0009845401,0.003033023,0.001909266,0.0006352551,0.001052787,0.001733361],"category_scores_gemma":[0.007315025,0.0004284594,0.0001762356,0.0009146573,0.001239027,0.001908532,0.001204208,0.0012068,0.0003429307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007798486,"about_ca_system_score_gemma":0.00127887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364249,"about_ca_topic_score_gemma":0.003668287,"domain_scores_codex":[0.9976891,0.001684594,0.00006699712,0.00009050647,0.0002458024,0.0002230462],"domain_scores_gemma":[0.9929254,0.005395667,0.0005006046,0.0001492362,0.0005289793,0.0005001885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000286471,0.006293348,0.1326186,0.0006501594,0.00004376774,0.00387868,0.7885984,0.0006166552,0.008144722,0.003662756,0.001651725,0.0535547],"study_design_scores_gemma":[0.00002976841,0.002174328,0.07841389,0.0001909171,0.00003502782,0.001447731,0.9050883,0.002720465,0.002038412,0.0009222712,0.006897552,0.00004133387],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976126,0.00006144729,0.0005102048,0.0002320299,0.000001772728,0.00005016932,0.000006959294,0.000002869423,0.001521922],"genre_scores_gemma":[0.997548,0.0002071555,0.001068617,0.0001989234,0.000004513603,0.00005566069,0.00001097775,0.000003772739,0.0009021673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003362919,"threshold_uncertainty_score":0.01778507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04773534530649241,"score_gpt":0.2988426381306817,"score_spread":0.2511072928241893,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}