{"id":"W3196432444","doi":"10.1111/1467-8551.12549","title":"The Role of Big Data Analytics in Manufacturing Agility and Performance: Moderation–Mediation Analysis of Organizational Creativity and of the Involvement of Customers as Data Analysts","year":2021,"lang":"en","type":"article","venue":"British Journal of Management","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":155,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"","keywords":"Creativity; Moderation; Big data; Business; Mediation; Analytics; Knowledge management; Resource (disambiguation); Organizational performance; Business value; Marketing; Moderated mediation; Data science; Computer science; Psychology; Economics","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":[0.01149336,0.0007472347,0.0006436979,0.001512148,0.001979203,0.003800096,0.001326573,0.00121775,0.006996844],"category_scores_gemma":[0.05082145,0.0004769301,0.001237863,0.001565815,0.002735044,0.002727786,0.006054947,0.002671982,0.0003837733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493518,"about_ca_system_score_gemma":0.004499262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009623467,"about_ca_topic_score_gemma":0.007062628,"domain_scores_codex":[0.9791275,0.01518142,0.0007373497,0.001259288,0.001631772,0.002062778],"domain_scores_gemma":[0.8652781,0.1095683,0.01103812,0.005095538,0.004392314,0.004627698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008408623,0.001287005,0.9276903,0.0002750519,0.001020949,0.000864805,0.02842472,0.002142428,0.002464357,0.0110183,0.0007443931,0.02322686],"study_design_scores_gemma":[0.0001352075,0.001081715,0.9050088,0.0004762477,0.001099319,0.0004187456,0.04815543,0.01830585,0.004262257,0.01699748,0.003907037,0.0001519286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913817,0.0001577222,0.002536222,0.001359233,0.00002832992,0.0000839475,0.0001280735,0.00002560191,0.004299127],"genre_scores_gemma":[0.9990501,0.0000305222,0.000531028,0.00004993475,0.000006964558,0.00005319264,0.00002866423,0.000006923857,0.0002427704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01149336,"threshold_uncertainty_score":0.06078339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05485632734380468,"score_gpt":0.264353157719188,"score_spread":0.2094968303753834,"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."}}