{"id":"W2054706026","doi":"10.1108/08876040810862895","title":"Toward a measure of service convenience: multiple‐item scale development and empirical test","year":2008,"lang":"en","type":"article","venue":"Journal of Services Marketing","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":262,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Nomological network; Generalizability theory; Scale (ratio); Sample (material); Context (archaeology); Empirical research; Psychology; Reliability (semiconductor); Service (business); Service quality; Test (biology); Marketing; Applied psychology; Business; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.002560633,0.0002184746,0.0004717619,0.0002718881,0.0002518168,0.00008517163,0.0004013302,0.0001074144,0.00006040269],"category_scores_gemma":[0.000300247,0.0001873441,0.00009367423,0.0006824317,0.0000557498,0.00112624,0.0002558873,0.0002930356,0.00001513049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003319568,"about_ca_system_score_gemma":0.0001018127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002879452,"about_ca_topic_score_gemma":0.000525674,"domain_scores_codex":[0.997762,0.00005697742,0.0009769642,0.0002128697,0.0006993797,0.0002917605],"domain_scores_gemma":[0.9969847,0.0005763444,0.001234021,0.0001485096,0.00100347,0.00005301215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003729552,0.0002123042,0.9843326,0.003609477,0.00006038795,0.00005189678,0.004334609,0.0000214841,0.001098785,0.000007222236,0.0001777498,0.005720553],"study_design_scores_gemma":[0.001629223,0.00002672144,0.9589392,0.001283238,0.00009605999,0.0002004254,0.01095916,0.004101561,0.0004049261,0.00002782758,0.02198646,0.00034519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957227,0.0005080093,0.00003320783,0.001776738,0.000184577,0.0001086225,0.000001440228,0.0000266234,0.001638157],"genre_scores_gemma":[0.9926635,0.00002899116,0.002183678,0.004552181,0.0005228585,0.000002077514,0.000003121392,0.00002131296,0.00002225315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02539337,"threshold_uncertainty_score":0.763967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04696864260130799,"score_gpt":0.2528351494912759,"score_spread":0.2058665068899679,"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."}}