{"id":"W2395652083","doi":"10.1080/03155986.2000.11732420","title":"An Optimization Model For The Market-Mix Problem In The Banking Industry","year":2000,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Profitability index; Profit (economics); Marketing; Competition (biology); Business; Marketing mix; Market segmentation; Product (mathematics); Marketing strategy; Market share; Product mix; New product development; Industrial organization; Economics; Finance; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.001396734,0.001308104,0.001236102,0.000745224,0.0007366991,0.001967943,0.001387136,0.002457007,0.007889401],"category_scores_gemma":[0.003671593,0.000948104,0.0009878917,0.0008798438,0.001061432,0.001315154,0.001030307,0.001794614,0.000747797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003037512,"about_ca_system_score_gemma":0.002998913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03944455,"about_ca_topic_score_gemma":0.02366223,"domain_scores_codex":[0.9993209,0.0002754969,0.00002191439,0.0001306272,0.00009750614,0.0001536568],"domain_scores_gemma":[0.9985331,0.001112588,0.0001358996,0.00002334584,0.0001266752,0.0000683449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001880898,0.00001695128,0.000161599,0.00002578938,0.000008370477,0.00002787757,0.00001569066,0.9906145,0.0000984028,0.007069485,0.0003684992,0.001573999],"study_design_scores_gemma":[0.00001482844,0.0000134986,0.00007412507,0.000004636587,0.000004724574,0.000007016243,0.00001073649,0.9966234,0.00003764846,0.002715985,0.0004890995,0.000004322545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06777987,0.001097883,0.8952859,0.001974125,0.0001112562,0.000314185,0.001110251,0.0004316886,0.03189481],"genre_scores_gemma":[0.8144522,0.001307344,0.1517523,0.0003563917,0.00009638985,0.0009767018,0.0008173497,0.0001390555,0.03010219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03944455,"threshold_uncertainty_score":0.07842994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06978605709956906,"score_gpt":0.3311740870358564,"score_spread":0.2613880299362874,"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."}}