{"id":"W3173843503","doi":"10.5267/j.ijdns.2021.6.015","title":"The effect of trust on travel agent online use: Application of the technology acceptance model","year":2021,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Consumer Behavior and Marketing Influence","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reuse; Usability; Technology acceptance model; Positive attitude; Population; Data collection; Sample (material); Psychology; Business; Advertising; Marketing; Computer science; Engineering; Social psychology; Mathematics; Statistics; Human–computer interaction; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009321051,0.00005325587,0.00009300077,0.0000677303,0.000120968,0.00009416535,0.001407623,0.00001817243,0.000002955498],"category_scores_gemma":[0.0004620446,0.00002991558,0.00002844488,0.0004235703,0.0003235039,0.0005925535,0.0005491052,0.0001112766,3.153732e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001204338,"about_ca_system_score_gemma":0.00005466098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001094683,"about_ca_topic_score_gemma":0.00002722421,"domain_scores_codex":[0.9990999,0.00001068602,0.0002569146,0.0001242814,0.0004212779,0.0000869693],"domain_scores_gemma":[0.9986989,0.0001387857,0.0004376784,0.0003001571,0.0004179538,0.000006536141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002486719,0.00009230269,0.3954751,0.0000236475,0.00004499722,0.00000569295,0.00001971341,0.005302643,0.02856247,0.008672812,0.001100092,0.5604519],"study_design_scores_gemma":[0.001147161,0.0000597633,0.6715848,0.0005416897,0.0001713012,0.00007164633,0.0001484604,0.2978729,0.008080175,0.002390348,0.01773588,0.0001958092],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952971,0.0001930467,0.002655005,0.001232761,0.0004323806,0.00006114763,0.00001872316,0.000002570091,0.0001072654],"genre_scores_gemma":[0.9991713,0.0001307974,0.000394879,0.0001279015,0.0001501251,9.095104e-7,0.000003779629,0.000002437558,0.00001791279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.560256,"threshold_uncertainty_score":0.2615738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02565879564644728,"score_gpt":0.3072630303172483,"score_spread":0.281604234670801,"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."}}