{"id":"W4385977670","doi":"10.5267/j.uscm.2023.6.011","title":"Exploring the relationship of supply chain transformational leadership and supply chain innovations performance on MSMEs satisfaction supply chain outcomes","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Transformational leadership; Structural equation modeling; Business; Nonprobability sampling; Supply chain management; Marketing; Industrial organization; Knowledge management; Economics; Management; Computer science; Population","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":[0.002823938,0.0002647147,0.0003007792,0.001312308,0.0005867987,0.001736816,0.0002447585,0.0003809566,0.005915027],"category_scores_gemma":[0.009978406,0.000110304,0.0006067751,0.001352087,0.0005755578,0.0008569782,0.001388319,0.0006949973,0.0004751993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006510498,"about_ca_system_score_gemma":0.001314089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001829484,"about_ca_topic_score_gemma":0.002204745,"domain_scores_codex":[0.9980223,0.000712394,0.0001870332,0.0001276116,0.0005580339,0.0003927346],"domain_scores_gemma":[0.9897369,0.003988037,0.002832033,0.0003357296,0.001720731,0.001386572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006048075,0.0003545861,0.9803169,0.00006979985,0.00006208814,0.0001601405,0.002773111,0.0004647544,0.0004786619,0.0004587517,0.0001728064,0.01462778],"study_design_scores_gemma":[0.00001210343,0.0006173252,0.9810439,0.00007431021,0.00006543411,0.0001256543,0.01262257,0.002943314,0.0007247756,0.0005572527,0.001194265,0.00001915052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974877,0.00003278163,0.0003236134,0.0001217538,0.000003263124,0.00001442241,0.00004452119,0.000004285795,0.001967688],"genre_scores_gemma":[0.99942,0.00003559302,0.0001358943,0.00001648704,0.000004433391,0.00001199547,0.00005111416,0.000001109256,0.0003233204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005915027,"threshold_uncertainty_score":0.01978773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08917503978892943,"score_gpt":0.259139462266217,"score_spread":0.1699644224772876,"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."}}