{"id":"W4226038207","doi":"10.5267/j.ijdns.2022.4.009","title":"Understanding the determinants of digital shopping features: The role of promo code on customer behavioral intention","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Brand image; Code (set theory); Usability; Psychology; Control (management); Advertising; Structural equation modeling; Technology acceptance model; Computer science; Business; Human–computer interaction; Artificial intelligence; Geography; Machine learning","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":[0.001612453,0.0002435654,0.0001969316,0.001192035,0.0003929278,0.001897732,0.000342948,0.0003820179,0.003175317],"category_scores_gemma":[0.009617234,0.0001623858,0.0003403511,0.0009957824,0.0006113016,0.002424055,0.000939374,0.0009245626,0.0003450086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005569734,"about_ca_system_score_gemma":0.002017764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004814162,"about_ca_topic_score_gemma":0.006503474,"domain_scores_codex":[0.9992977,0.0002608302,0.00004594899,0.00006591983,0.0001912516,0.0001382734],"domain_scores_gemma":[0.989446,0.005492713,0.00240186,0.0003762186,0.001533493,0.0007497485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007908356,0.0003905242,0.9548948,0.00006982787,0.0000190494,0.0001250262,0.005252943,0.0004221925,0.0006070291,0.002753444,0.0002259155,0.03516011],"study_design_scores_gemma":[0.000009124889,0.0002836454,0.9674795,0.0001760684,0.00005119608,0.0002054284,0.01845198,0.006771492,0.0007900429,0.002350059,0.003410599,0.00002100229],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938579,0.00007482668,0.000772336,0.0003094835,0.000002524134,0.00001759997,0.00004315238,0.000005610685,0.004916573],"genre_scores_gemma":[0.999037,0.00008427058,0.0004612856,0.00003117839,0.000004461376,0.00001063861,0.00004229429,0.000002033544,0.0003268738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004814162,"threshold_uncertainty_score":0.0106225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.12742142059961,"score_gpt":0.3381016280052523,"score_spread":0.2106802074056424,"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."}}