{"id":"W2977858028","doi":"10.1108/jm2-12-2018-0224","title":"Studying the sustainability of third party logistics growth using system dynamics","year":2019,"lang":"en","type":"article","venue":"Journal of Modelling in Management","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Competitive advantage; Business; Population; Industrial organization; Sustainability; Competition (biology); Supply chain; System dynamics; Service (business); Service provider; Sustainable growth rate; Marketing; Computer science; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001087882,0.000612538,0.000504681,0.0007952785,0.0005866706,0.001859149,0.0006807983,0.0008779229,0.002551789],"category_scores_gemma":[0.003419959,0.000252257,0.0008127236,0.0007635589,0.0006636003,0.001897139,0.001319543,0.001125985,0.0001542282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001606717,"about_ca_system_score_gemma":0.001525526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01404136,"about_ca_topic_score_gemma":0.006248909,"domain_scores_codex":[0.9994982,0.0002113412,0.00002412064,0.0001036431,0.00009220831,0.00007048199],"domain_scores_gemma":[0.9980305,0.001196326,0.0003996887,0.00006510927,0.0002252956,0.00008307993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004161383,0.00009102524,0.04145655,0.0002766133,0.0002281669,0.0005048237,0.0003755357,0.8967876,0.00195575,0.04474527,0.001221711,0.01231521],"study_design_scores_gemma":[0.0000048857,0.00004737359,0.003383196,0.00002560324,0.00001951391,0.00003388956,0.0003077311,0.9843524,0.000235024,0.01020899,0.001367055,0.00001433133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7111114,0.001754783,0.2493607,0.004001367,0.0002099714,0.000255179,0.00114129,0.0002630528,0.03190224],"genre_scores_gemma":[0.990754,0.0005679183,0.006829991,0.00007559718,0.00002210515,0.00007920295,0.0001595653,0.00001720815,0.001494414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01404136,"threshold_uncertainty_score":0.02791929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02276830706393953,"score_gpt":0.2291257996210435,"score_spread":0.2063574925571039,"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."}}