{"id":"W2234458975","doi":"10.5267/j.msl.2015.12.008","title":"Analyzing key performance indicators of e-commerce using balanced scorecard","year":2016,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Balanced scorecard; Key (lock); Process management; Computer science; Business; Performance indicator; E-commerce; Knowledge management; Marketing; Computer security; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002801476,0.0001386065,0.0002195838,0.001989482,0.0002977662,0.00009853053,0.002044524,0.00004153924,0.0001442099],"category_scores_gemma":[0.0001690707,0.00008754013,0.00007889554,0.003838325,0.001271712,0.0008763862,0.0005023602,0.00009073473,0.0001201376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001121255,"about_ca_system_score_gemma":0.00001390435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005124911,"about_ca_topic_score_gemma":8.683076e-7,"domain_scores_codex":[0.9969761,0.00005202481,0.0005086649,0.0006235774,0.001393773,0.0004458808],"domain_scores_gemma":[0.9985446,0.0000824633,0.0003485857,0.0008842153,0.0000483545,0.0000918279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006433012,0.00001694349,0.8938994,0.000003313367,0.000006331936,0.000004088744,0.00007125647,0.0000914315,0.03880819,0.001032048,0.0006656325,0.06539487],"study_design_scores_gemma":[0.0003264576,0.00002057266,0.9879596,0.00005821462,0.00001564956,0.000002268566,0.0001898672,0.0003590891,0.008892588,0.0001584885,0.001855043,0.000162161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659776,0.000006571413,0.02795647,0.004441936,0.000332119,0.0001423538,0.00000162232,0.00007142974,0.001069883],"genre_scores_gemma":[0.9944198,0.00001444161,0.004400332,0.0008536803,0.00001342293,0.000004964614,1.576368e-7,0.000006628693,0.0002865944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09406015,"threshold_uncertainty_score":0.4685674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06029384851139346,"score_gpt":0.3381288435592907,"score_spread":0.2778349950478972,"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."}}