{"id":"W4412160770","doi":"10.1287/msom.2024.0801","title":"Multiproduct Dynamic Pricing with Reference Effects Under Logit Demand","year":2025,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Logit; Dynamic pricing; Computer science; Microeconomics; Mixed logit; Dynamic demand; Operations research; Logistic regression; Business; Economics; Operations management; Econometrics; Industrial organization; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003362681,0.0004373755,0.0003001374,0.0007073496,0.0007271772,0.0009133682,0.0006120992,0.00006735152,0.000202851],"category_scores_gemma":[0.00001048125,0.000372986,0.00005817002,0.000757532,0.00004411316,0.001103193,0.0007077813,0.0002164179,0.0004941979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002020532,"about_ca_system_score_gemma":0.00001742663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007243627,"about_ca_topic_score_gemma":0.002090776,"domain_scores_codex":[0.9978335,0.0000284035,0.0003908616,0.0008277933,0.000385265,0.000534203],"domain_scores_gemma":[0.9988486,0.00003418542,0.0001042832,0.0008618146,0.0001273213,0.00002385604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002688698,0.001161202,0.001913409,0.01158373,0.001645225,0.000180581,0.0003125579,0.647853,0.00091506,0.2867423,0.006786354,0.04063775],"study_design_scores_gemma":[0.00905521,0.0001274327,0.277949,0.002793,0.002197134,0.000006547493,0.006412847,0.1653623,0.007001551,0.008329923,0.517264,0.003501091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6191623,0.0002580007,0.07758097,0.01748224,0.001333112,0.004720062,0.000003462848,0.001206443,0.2782535],"genre_scores_gemma":[0.9735779,0.00003214804,0.002112938,0.0153832,0.0001299656,0.0003268955,0.000113957,0.00004741118,0.008275538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5104777,"threshold_uncertainty_score":0.9998722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021799508738116,"score_gpt":0.2221595651484745,"score_spread":0.2119415700610933,"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."}}