{"id":"W2253181232","doi":"10.1007/s10479-016-2114-7","title":"Loyal customer bases as innovation disincentives for duopolistic firms using strategic signaling and Bayesian analysis","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Incentive; Product (mathematics); Customer base; Industrial organization; Microeconomics; Game theory; Marketing; Business; New product development; Economics; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00602683,0.0001085926,0.0002633746,0.002594346,0.0007258636,0.0004359569,0.0002847111,0.00006915817,0.001024301],"category_scores_gemma":[0.007818084,0.00006854477,0.00008468884,0.006561182,0.000365671,0.0005765817,0.000107497,0.00009916981,0.00002659613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002046469,"about_ca_system_score_gemma":0.0002465158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001610997,"about_ca_topic_score_gemma":0.00006555544,"domain_scores_codex":[0.9968853,0.0002970886,0.0008578995,0.0004117435,0.001209798,0.0003381532],"domain_scores_gemma":[0.9915097,0.001782596,0.0001328555,0.0003202304,0.006187931,0.00006662997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001983257,0.0002753167,0.01166804,0.00002835674,0.0002671043,0.000004197327,0.0009629545,0.007006609,0.1957556,0.7476683,0.001385547,0.03477966],"study_design_scores_gemma":[0.001730343,0.000636895,0.01383044,0.0002746439,0.0001223834,0.00001049203,0.01069976,0.7123902,0.08745307,0.1688292,0.003271532,0.0007510015],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208391,0.00003553999,0.07511555,0.002178627,0.00004412569,0.0002758202,0.00008674109,0.000009817949,0.001414636],"genre_scores_gemma":[0.9951769,0.00001492407,0.002502723,0.0001238272,0.00007511266,0.00002029854,0.0000199884,0.000009642467,0.002056625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7053836,"threshold_uncertainty_score":0.9998889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6269283437231469,"score_gpt":0.5722951305975785,"score_spread":0.05463321312556835,"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."}}