{"id":"W4353050218","doi":"10.1016/j.omega.2023.102874","title":"Returns operations in omnichannel retailing with buy-online-and-return-to-store","year":2023,"lang":"en","type":"article","venue":"Omega","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"National University's Basic Research Foundation of China; Science and Technology Commission of Shanghai Municipality; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Fujian Province; National Natural Science Foundation of China","keywords":"Omnichannel; Business; Marketing; Advertising","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":[0.001399752,0.0005922277,0.001039969,0.0006396372,0.001009275,0.004328466,0.002423898,0.001578377,0.01423829],"category_scores_gemma":[0.004046405,0.0007537729,0.001422343,0.0009011758,0.002067948,0.003657305,0.002627736,0.001753355,0.001231876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003225984,"about_ca_system_score_gemma":0.00222046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0460126,"about_ca_topic_score_gemma":0.05456164,"domain_scores_codex":[0.9983792,0.0003404868,0.0000705128,0.0004717234,0.0001946683,0.0005433782],"domain_scores_gemma":[0.9972522,0.001053698,0.0008785552,0.0001813228,0.0001735578,0.0004607099],"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":[0.003235442,0.004687465,0.1949501,0.0006502172,0.0005640953,0.006383683,0.001120055,0.4830104,0.004450128,0.2277728,0.01143478,0.06174082],"study_design_scores_gemma":[0.0006897782,0.001495459,0.08379779,0.0001849648,0.0006611043,0.001090838,0.004909535,0.7126808,0.003259736,0.1788492,0.01194181,0.0004389352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9142932,0.000774689,0.03149084,0.002257987,0.00009477947,0.0002933905,0.001136761,0.0003416066,0.04931671],"genre_scores_gemma":[0.9896718,0.000170699,0.001979672,0.0001164761,0.00002459668,0.00004156384,0.0002022757,0.00001825976,0.007774636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0460126,"threshold_uncertainty_score":0.09148955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03629398189731583,"score_gpt":0.2624303204039248,"score_spread":0.2261363385066089,"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."}}