{"id":"W2591166615","doi":"10.1111/joie.12112","title":"Dynamic Spatial Competition Between Multi‐Store Retailers","year":2016,"lang":"en","type":"article","venue":"Journal of Industrial Economics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cannibalization; Competition (biology); Competitor analysis; Oligopoly; Revenue; Markov chain; Panel data; Industrial organization; Microeconomics; Econometrics; Economics; Computer science; Business; Marketing; Cournot competition","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":[0.0009077585,0.000718999,0.001452252,0.0008778362,0.001203138,0.00332333,0.003914898,0.002931224,0.01140011],"category_scores_gemma":[0.002610515,0.001166328,0.001160923,0.001903283,0.001911552,0.003206282,0.001909455,0.001665247,0.001135316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003044063,"about_ca_system_score_gemma":0.002323279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03819449,"about_ca_topic_score_gemma":0.0326467,"domain_scores_codex":[0.9990053,0.0003309435,0.00003549407,0.0002869627,0.0001241508,0.0002172221],"domain_scores_gemma":[0.9982132,0.0007728362,0.0003933945,0.0001036674,0.0002333387,0.0002835436],"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":[0.0001003996,0.0001041211,0.002069256,0.00004643332,0.00004326155,0.0003580629,0.0001070099,0.8730046,0.0005728596,0.1192554,0.001523449,0.002815082],"study_design_scores_gemma":[0.00006870546,0.00003938671,0.0004405463,0.000008283742,0.00001848075,0.0000555412,0.00008454238,0.977868,0.00006548067,0.0201002,0.001226975,0.00002385455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4775441,0.0008766294,0.4550954,0.005204431,0.0002168515,0.0003008729,0.002482456,0.0004892604,0.05779],"genre_scores_gemma":[0.9618614,0.0004214592,0.01764449,0.0001821951,0.00004171842,0.000180693,0.0003677888,0.00003016372,0.01927004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03819449,"threshold_uncertainty_score":0.0759443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0546361397564134,"score_gpt":0.2414143168011098,"score_spread":0.1867781770446964,"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."}}