{"id":"W2982964715","doi":"10.28945/4448","title":"Digital Logistics Capability: Factors Impacting Technology Acceptance","year":2019,"lang":"en","type":"article","venue":"Muma Business Review","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Technology acceptance model; Usability; Perception; Knowledge management; Business; Navy; Process management; Computer science; Psychology; Human–computer interaction","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":[0.01447713,0.0001625418,0.0003692947,0.00372122,0.0004709072,0.00342745,0.0004590343,0.000662747,0.002877002],"category_scores_gemma":[0.08416353,0.0001803498,0.0009769961,0.00357372,0.0006884086,0.002607016,0.001471906,0.0007662146,0.0002966074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146145,"about_ca_system_score_gemma":0.0031107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002653675,"about_ca_topic_score_gemma":0.002960647,"domain_scores_codex":[0.9876704,0.005653706,0.002135039,0.0003987825,0.003685751,0.0004562922],"domain_scores_gemma":[0.8845117,0.08484807,0.01573877,0.001340368,0.01175126,0.001809741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000318364,0.0004767997,0.7087551,0.006551556,0.0004844175,0.0005523768,0.03490533,0.000406202,0.0008581417,0.003921773,0.001438697,0.2413313],"study_design_scores_gemma":[0.00009194423,0.001425167,0.8593963,0.009520268,0.000918124,0.001936047,0.07817833,0.001777687,0.00148665,0.003291829,0.04184545,0.0001322481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9469782,0.01738498,0.001975588,0.003068819,0.00007103923,0.0003889966,0.0002611635,0.00001831364,0.02985294],"genre_scores_gemma":[0.9921389,0.005868742,0.0009403953,0.0002292807,0.00002081443,0.00008055192,0.00009659697,0.000004840407,0.000619904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01447713,"threshold_uncertainty_score":0.07656324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1219595549438404,"score_gpt":0.3934124973746829,"score_spread":0.2714529424308425,"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."}}