{"id":"W3037061226","doi":"10.3390/jrfm13070138","title":"Technology Acceptance in e-Governance: A Case of a Finance Organization","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competitive advantage; Government (linguistics); Marketing; Knowledge management; Descriptive statistics; Business; Financial institution; Population; Corporate governance; Technology acceptance model; Empirical research; Structural equation modeling; Work (physics); Computer science; Engineering; Finance; Usability","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":[0.001970052,0.0002166936,0.0002305195,0.001278646,0.003930201,0.002846146,0.0006228488,0.002120775,0.002126],"category_scores_gemma":[0.003950327,0.0001526398,0.0003434072,0.00120933,0.001982898,0.001480359,0.001286976,0.001216209,0.0002495326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002467834,"about_ca_system_score_gemma":0.001359638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01339415,"about_ca_topic_score_gemma":0.01732923,"domain_scores_codex":[0.9979133,0.001239673,0.0000520448,0.0001019548,0.0002341323,0.0004589776],"domain_scores_gemma":[0.9960068,0.002006514,0.0005957966,0.0001520461,0.0003841953,0.0008546761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002636398,0.004915494,0.5749534,0.0001779785,0.00005268998,0.07431743,0.267536,0.002986935,0.002528821,0.02108796,0.002993027,0.04818683],"study_design_scores_gemma":[0.00007094462,0.001190054,0.2918305,0.0001908059,0.0000587205,0.01244514,0.657288,0.01318796,0.001451004,0.004276381,0.01793451,0.00007595954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960258,0.00004977272,0.0002378537,0.0007155453,0.000004083942,0.00001187674,0.000006257469,0.000003295238,0.0029456],"genre_scores_gemma":[0.9990622,0.0000863586,0.0001611727,0.00006934199,0.000005872424,0.000005450858,0.000006389653,0.000001552745,0.0006017128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01339415,"threshold_uncertainty_score":0.02663237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02417272074942959,"score_gpt":0.2983021392118798,"score_spread":0.2741294184624501,"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."}}