{"id":"W2403910177","doi":"10.1111/itor.12300","title":"Enhancing revenue by offering a flexible product option","year":2016,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Ticket; Revenue; Product (mathematics); Business; Revenue management; Preference; Computer science; Industrial organization; Operations research; Marketing; Microeconomics; Economics; Finance; Computer security; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006752579,0.0004685281,0.0003794012,0.0005208356,0.0003724757,0.001586283,0.0007803314,0.0005136169,0.009762966],"category_scores_gemma":[0.001898544,0.0002161657,0.0004939978,0.0004333005,0.0007403412,0.001504936,0.0008854188,0.0008279418,0.0004505769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006146556,"about_ca_system_score_gemma":0.0005942757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001057673,"about_ca_topic_score_gemma":0.001676638,"domain_scores_codex":[0.9995809,0.0001417003,0.00001068169,0.00004693271,0.00007382292,0.0001458539],"domain_scores_gemma":[0.9983404,0.0007991277,0.0003171134,0.0001491302,0.0001175841,0.0002766497],"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":[0.004081364,0.002974917,0.05713756,0.0005983001,0.0002676585,0.00298571,0.0004712352,0.5261633,0.0460373,0.1514883,0.003780106,0.2040141],"study_design_scores_gemma":[0.0003588871,0.006477393,0.05330501,0.0001863671,0.0004798018,0.002478452,0.002523703,0.7988108,0.01956078,0.09599274,0.01954613,0.0002798937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9389021,0.0005374655,0.02989151,0.000508305,0.00003298126,0.00009144335,0.0001232392,0.00006968642,0.0298432],"genre_scores_gemma":[0.997436,0.00005649697,0.001631053,0.0000128246,0.000006982531,0.00000473092,0.00001122071,0.000002504857,0.0008381887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009762966,"threshold_uncertainty_score":0.03266042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07014577841220812,"score_gpt":0.3458426279694891,"score_spread":0.275696849557281,"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."}}