{"id":"W2977583528","doi":"10.5267/j.msl.2019.9.013","title":"Innovative performance development model based on human capital and network quality toward improved marketing performance","year":2019,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structural equation modeling; Sample (material); Quality (philosophy); Quality management; Human capital; Business; Marketing; Computer science; Knowledge management; Process management","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":[0.002177173,0.0005509297,0.0001951913,0.00112975,0.0003917141,0.001608879,0.0006313671,0.0006028581,0.002907221],"category_scores_gemma":[0.004705096,0.0001290087,0.0004049377,0.0008002292,0.0007009289,0.001542095,0.001352141,0.0006357269,0.0003170557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002160497,"about_ca_system_score_gemma":0.002401934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002998402,"about_ca_topic_score_gemma":0.002944076,"domain_scores_codex":[0.9985656,0.0005858885,0.00004999214,0.0001597571,0.0003970979,0.0002416437],"domain_scores_gemma":[0.9967679,0.001287604,0.0007186672,0.0001308878,0.000697149,0.0003979037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006362118,0.003151096,0.3990383,0.000598537,0.0003985377,0.00062666,0.005159,0.1904963,0.005230308,0.1208777,0.007308681,0.2664786],"study_design_scores_gemma":[0.0002035331,0.002412436,0.2908554,0.0004509864,0.0004910884,0.0004184153,0.004508163,0.628935,0.005133286,0.0518188,0.01465348,0.0001193518],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8224343,0.0005211066,0.09156362,0.003195534,0.00007776669,0.0004780394,0.000237171,0.0002032274,0.08128933],"genre_scores_gemma":[0.9931892,0.0001120316,0.004591682,0.00003966905,0.000007448079,0.00007776072,0.00003924864,0.000004746167,0.001938228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002998402,"threshold_uncertainty_score":0.0156756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0767333992111257,"score_gpt":0.3458261344452129,"score_spread":0.2690927352340872,"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."}}