{"id":"W2115285426","doi":"10.1057/palgrave.ejis.3000528","title":"Understanding enterprise systems-enabled integration","year":2005,"lang":"en","type":"article","venue":"European Journal of Information Systems","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Science Foundation","keywords":"Salient; Enterprise information integration; System integration; Enterprise application integration; Data integration; Computer science; Business process; Information integration; Field (mathematics); Knowledge management; Process (computing); Process management; Reciprocal; Enterprise integration; Data science; Business; Data mining; Enterprise systems engineering; Marketing; Enterprise software; Enterprise architecture; Artificial intelligence; Database","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":[0.004093466,0.0004543289,0.0003456245,0.002839049,0.001610402,0.00756782,0.0008650372,0.001623336,0.001620942],"category_scores_gemma":[0.00764127,0.0005407953,0.0005193279,0.003897922,0.005963224,0.01941312,0.004792035,0.001879785,0.000144294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00393434,"about_ca_system_score_gemma":0.002759645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005958241,"about_ca_topic_score_gemma":0.003762773,"domain_scores_codex":[0.9970043,0.001331181,0.0001999038,0.0003081603,0.0007626605,0.0003936968],"domain_scores_gemma":[0.99595,0.002540772,0.0005336253,0.0004005976,0.0004366625,0.0001382832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002203446,0.00008598644,0.0220324,0.0002199591,0.00005033878,0.0005447706,0.04031701,0.007145556,0.00159347,0.8673089,0.0008693405,0.05981023],"study_design_scores_gemma":[0.00001553488,0.00007086918,0.02643499,0.000363296,0.00005060988,0.0005972934,0.04067305,0.03442762,0.001458689,0.8470179,0.04885476,0.00003542974],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6366265,0.00379697,0.1879955,0.01265297,0.00007434857,0.0001308509,0.0001200104,0.0001556924,0.1584471],"genre_scores_gemma":[0.9784209,0.001085822,0.01904677,0.0002534347,0.00002077797,0.00005312083,0.00008329637,0.00001509363,0.001020748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00756782,"threshold_uncertainty_score":0.02854574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07079019266842405,"score_gpt":0.2565073860338867,"score_spread":0.1857171933654626,"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."}}