{"id":"W2098081408","doi":"10.5267/j.msl.2014.11.014","title":"Investigating different factors for regional market entrance","year":2014,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cronbach's alpha; Structural equation modeling; Likert scale; Business; Government (linguistics); Population; Market orientation; Product (mathematics); Scale (ratio); Marketing; New product development; Industrial organization; Competitive advantage; Distribution (mathematics); Customer satisfaction; Business administration; Operations management; Economics; Mathematics; Statistics","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":[0.002620799,0.0002442785,0.0003261968,0.001880724,0.0009984242,0.002419305,0.0007446102,0.0005817835,0.0124721],"category_scores_gemma":[0.01350232,0.0002142697,0.0007122719,0.001295083,0.001861139,0.002025408,0.001677183,0.0008883072,0.0006336434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203387,"about_ca_system_score_gemma":0.001809081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005165305,"about_ca_topic_score_gemma":0.00734243,"domain_scores_codex":[0.9977148,0.0009105285,0.0001726135,0.0002449288,0.0005164884,0.0004407054],"domain_scores_gemma":[0.9785568,0.007908829,0.007975406,0.0007332717,0.002097812,0.002727829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001249422,0.0003998885,0.974663,0.00007978603,0.00004848811,0.0005691975,0.00483059,0.0002443003,0.0005039228,0.002735257,0.0003107259,0.01548992],"study_design_scores_gemma":[0.000005382467,0.0001388934,0.9890895,0.00004014771,0.0000283765,0.0001340574,0.00820512,0.0003475824,0.0001723417,0.0002794436,0.001543039,0.00001597404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889711,0.0001337699,0.0003715476,0.0001927741,0.00000617009,0.0000496015,0.00004424567,0.00001355639,0.01021724],"genre_scores_gemma":[0.9993212,0.00003879097,0.0001701563,0.00001114663,0.000004331213,0.00000563644,0.00002832136,0.000002327143,0.0004180898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0124721,"threshold_uncertainty_score":0.04172331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03604848521089123,"score_gpt":0.29124304416426,"score_spread":0.2551945589533688,"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."}}