{"id":"W2016945629","doi":"10.1287/msom.2013.0449","title":"Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay","year":2013,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":193,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Revenue; Incentive; Revenue management; Queueing theory; Incentive compatibility; Computer science; Queue; Scope (computer science); Mechanism design; Microeconomics; Scheduling (production processes); Operations research; Business; Economics; Operations management; Finance; Computer network","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005195644,0.0004557784,0.0004012814,0.0009552639,0.0005136692,0.00142102,0.0007442593,0.00007552957,0.0005711956],"category_scores_gemma":[0.000005044268,0.0004687305,0.00009854983,0.001002036,0.00003399382,0.002644543,0.0006881161,0.0002647277,0.002324265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266167,"about_ca_system_score_gemma":0.000008126738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006039484,"about_ca_topic_score_gemma":0.001889023,"domain_scores_codex":[0.9972938,0.00006496695,0.0007482932,0.000772997,0.0004412843,0.0006786038],"domain_scores_gemma":[0.9987943,0.00002706593,0.0002079721,0.0007922222,0.0001415313,0.00003691572],"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":[0.00001906593,0.0001953291,0.0002663812,0.0008916198,0.0002368452,0.0001067843,0.0001318889,0.9198311,0.00005188281,0.0754029,0.0003472024,0.002519024],"study_design_scores_gemma":[0.0031468,0.00002941667,0.01510971,0.001280918,0.0007540545,0.000008084796,0.01901658,0.9090466,0.0003398656,0.01625482,0.03268205,0.002331139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454707,0.00009911272,0.005672548,0.001100617,0.000435451,0.002184209,0.000004904178,0.0003104363,0.04472201],"genre_scores_gemma":[0.9899808,0.0000379713,0.004106301,0.001615279,0.0002750321,0.0007910474,0.0001089126,0.000071761,0.003012897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05914808,"threshold_uncertainty_score":0.9997764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557171129881954,"score_gpt":0.2259616641810344,"score_spread":0.2103899528822148,"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."}}