{"id":"W3034746540","doi":"10.5267/j.msl.2020.6.011","title":"How to anticipate and manage customer satisfaction and brand loyalty by investigating emotional aspects in the B2B setting","year":2020,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Customer satisfaction; Business; Loyalty; Marketing; Loyalty business model; Psychology; Brand loyalty; Customer delight; Advertising; Service quality; Service (business)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001468745,0.0003075381,0.000263693,0.0006667799,0.0005000104,0.003338404,0.0003402605,0.001022503,0.002400744],"category_scores_gemma":[0.003651138,0.0001731991,0.000246272,0.0005953347,0.0005931598,0.002621855,0.0006365484,0.0007543748,0.000446483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004767771,"about_ca_system_score_gemma":0.0006771923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00349727,"about_ca_topic_score_gemma":0.003676459,"domain_scores_codex":[0.9993514,0.0003643242,0.00002283648,0.00006172898,0.00009654302,0.0001031492],"domain_scores_gemma":[0.9981079,0.0007408749,0.000484314,0.00006511046,0.0002570647,0.0003447183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007261848,0.001817556,0.722726,0.000360689,0.0002326899,0.0009217742,0.00792849,0.008418354,0.01415971,0.01454254,0.003070161,0.2250959],"study_design_scores_gemma":[0.00005795218,0.001189573,0.8651815,0.0002008637,0.0001280168,0.000442615,0.02473385,0.06840739,0.003588297,0.03087952,0.005061717,0.0001287464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672233,0.000548046,0.01082825,0.001936231,0.00003075533,0.00007423422,0.00006491078,0.00003408386,0.01926014],"genre_scores_gemma":[0.996128,0.0002074755,0.002889207,0.0001839569,0.00001526157,0.00001855291,0.00003098712,0.000005086876,0.0005214419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00349727,"threshold_uncertainty_score":0.008031309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315750513166287,"score_gpt":0.2383914112314384,"score_spread":0.2152339060997756,"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."}}