{"id":"W2519337536","doi":"10.1142/s1363919617500189","title":"FORMALISING THE DEMAND FOR TECHNOLOGICAL INNOVATIONS: RATIONAL HERDS, MARKET FRICTIONS AND NETWORK EFFECTS","year":2016,"lang":"en","type":"article","venue":"International Journal of Innovation Management","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Product (mathematics); Microeconomics; Point (geometry); Set (abstract data type); Economics; Industrial organization; New product development; Rational expectations; Diffusion; Path (computing); Path dependence; Business; Computer science; Econometrics; Marketing; 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":[],"consensus_categories":[],"category_scores_codex":[0.007786441,0.000133175,0.0001837561,0.001107149,0.0003618081,0.000350402,0.0006922685,0.0000698411,0.0001649813],"category_scores_gemma":[0.005300933,0.00006843514,0.00006773629,0.002224777,0.0001564292,0.0007087048,0.0002141088,0.0001333908,0.000007983799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009585393,"about_ca_system_score_gemma":0.00004770629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.494621e-7,"about_ca_topic_score_gemma":0.00000114121,"domain_scores_codex":[0.9965228,0.0001092921,0.001643681,0.0002121481,0.00132645,0.0001856024],"domain_scores_gemma":[0.9917873,0.001773797,0.001410989,0.0001880232,0.004814134,0.00002575221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009834092,0.00003932813,0.003090824,0.0000039329,0.00011759,0.00000509558,0.00003186017,0.000155317,0.0003338833,0.602376,0.06044633,0.3333015],"study_design_scores_gemma":[0.002921979,0.0001531032,0.09664888,0.0002631202,0.00003730186,0.0001657672,0.0005439547,0.003314459,0.000482623,0.4726946,0.4225339,0.0002402569],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04816636,0.00005364267,0.9150008,0.03025675,0.001687385,0.0004082682,0.00001175932,0.00002564688,0.004389403],"genre_scores_gemma":[0.9679571,0.00005265133,0.0265479,0.002307324,0.000681225,0.00004722971,0.000007383978,0.00001163258,0.002387566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9197907,"threshold_uncertainty_score":0.6346095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05217713920734499,"score_gpt":0.352715737754453,"score_spread":0.300538598547108,"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."}}