{"id":"W2074827511","doi":"10.1287/opre.2014.1305","title":"Supporting New Product or Service Introductions: Location, Marketing, and Word of Mouth","year":2014,"lang":"en","type":"article","venue":"Operations Research","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Marketing; Word of mouth; Profit (economics); Time horizon; Computer science; Product (mathematics); Digital marketing; Service (business); Marketing mix; Business; Marketing strategy; Multi-level marketing; Phone; New product development; Economics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0199631,0.00009391771,0.0001872686,0.0007581922,0.0007583545,0.0004645565,0.0004328975,0.00004777043,0.002244618],"category_scores_gemma":[0.06478703,0.00006651448,0.00001947559,0.005186414,0.0001505181,0.000423633,0.0002484884,0.0002743177,0.0001764291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002754068,"about_ca_system_score_gemma":0.0005275056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003232657,"about_ca_topic_score_gemma":0.00107204,"domain_scores_codex":[0.996068,0.0007969158,0.0008915526,0.0005174491,0.001408168,0.0003179248],"domain_scores_gemma":[0.9911047,0.001400842,0.0001346905,0.0007733224,0.00644075,0.0001457523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000146141,0.0001214034,0.004726977,0.00005091534,0.00001340451,4.862636e-7,0.004065415,0.003392529,0.008739606,0.01018165,0.08121596,0.8873455],"study_design_scores_gemma":[0.002348543,0.0002370211,0.1363305,0.0003166191,0.00002149102,0.000113458,0.0261295,0.3490424,0.01009742,0.01024319,0.4643314,0.0007883647],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444059,0.0001024917,0.01141611,0.03426534,0.0004118698,0.0007577268,0.000006745243,0.00005239936,0.008581385],"genre_scores_gemma":[0.930587,0.00001021733,0.01221761,0.000220656,0.0005836228,0.00002479874,0.00001300865,0.00001342888,0.05632968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8865572,"threshold_uncertainty_score":0.9986675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2366794999603054,"score_gpt":0.4884130249851267,"score_spread":0.2517335250248214,"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."}}