{"id":"W2975052215","doi":"10.1108/jbim-05-2018-0179","title":"Power-based behaviors between supply chain partners of diverse national and organizational cultures: the crucial role of boundary spanners’ cultural intelligence","year":2019,"lang":"en","type":"article","venue":"Journal of Business and Industrial Marketing","topic":"Global and Cross-Cultural Management","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Saskatchewan","funders":"","keywords":"Cultural intelligence; Power (physics); Supply chain; Knowledge management; Business; Organizational culture; Boundary (topology); Psychology; Computer science; Social psychology; Public relations; Marketing; Political science","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":[0.003613969,0.0003359986,0.000260084,0.0008776075,0.001965463,0.004566404,0.0004425133,0.0004466792,0.0036993],"category_scores_gemma":[0.01239197,0.0001946622,0.0002126431,0.0005955833,0.003826383,0.002284863,0.004499794,0.0009699789,0.0001858991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001049535,"about_ca_system_score_gemma":0.001398392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734571,"about_ca_topic_score_gemma":0.002846095,"domain_scores_codex":[0.9972197,0.001603254,0.0001254218,0.0002782249,0.0005025686,0.0002708116],"domain_scores_gemma":[0.9901494,0.004371675,0.002664386,0.0007773716,0.0006540269,0.001383119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002244953,0.000522267,0.6323541,0.0002199993,0.0001914403,0.001447532,0.2497187,0.0007041395,0.004055039,0.01920952,0.000353273,0.09099962],"study_design_scores_gemma":[0.00002512891,0.0003813895,0.5073103,0.0004797685,0.0001073487,0.001053072,0.451915,0.002427122,0.002744313,0.02683653,0.00663872,0.00008126331],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99004,0.0001529692,0.001379394,0.0002294687,0.000008442419,0.00001374364,0.000006635827,0.000003436455,0.008165808],"genre_scores_gemma":[0.999419,0.00005610927,0.0002749488,0.00004392449,0.000002108178,0.000005678104,0.00000480448,0.00000138639,0.0001920143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004566404,"threshold_uncertainty_score":0.01911271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03024641395442657,"score_gpt":0.3075429029676851,"score_spread":0.2772964890132585,"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."}}