{"id":"W2961028225","doi":"10.1007/978-3-030-22335-9_17","title":"Adding ‘Social’ to Commerce to Influence Purchasing Behaviour","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Purchasing; Perception; Internet privacy; The Internet; Personally identifiable information; Social media; Phenomenon; Risk perception; Computer science; Social commerce; Social influence; Advertising; E-commerce; Business; Marketing; World Wide Web; Computer security; Psychology; Social psychology","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":[0.002018883,0.00054358,0.0005465382,0.0007071226,0.0006617387,0.003798829,0.000406891,0.001259093,0.01062574],"category_scores_gemma":[0.01433761,0.0003398194,0.0005504815,0.001147672,0.001503675,0.003005726,0.001198987,0.001313873,0.001166721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006814828,"about_ca_system_score_gemma":0.0004650827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234108,"about_ca_topic_score_gemma":0.003170503,"domain_scores_codex":[0.9975901,0.001633597,0.00008415768,0.0002388666,0.0003538787,0.00009937499],"domain_scores_gemma":[0.9822612,0.01510222,0.0006830315,0.0008500157,0.0005422327,0.000561241],"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":[0.002549148,0.003660883,0.3490615,0.001761512,0.001907774,0.001504212,0.015216,0.01787438,0.02567046,0.1210454,0.01241237,0.4473364],"study_design_scores_gemma":[0.0005277375,0.003909128,0.5230019,0.0007453774,0.002676773,0.001280634,0.008543448,0.1256716,0.01504691,0.2416397,0.07644506,0.0005116396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7956483,0.001733691,0.02866636,0.003927934,0.0005125038,0.0001018646,0.0002281122,0.0003547101,0.1688265],"genre_scores_gemma":[0.9912425,0.0002185956,0.004687207,0.0004421151,0.0001221997,0.00002913516,0.00005751804,0.00005386198,0.003146838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01062574,"threshold_uncertainty_score":0.03554666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07188499493502197,"score_gpt":0.3630331627176854,"score_spread":0.2911481677826634,"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."}}