{"id":"W4396808345","doi":"10.1016/j.intman.2024.101155","title":"Are proactive outbound cross-border mergers and acquisitions effective for firms' R&D? New evidence from emerging market enterprises","year":2024,"lang":"en","type":"article","venue":"Journal of International Management","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Major Program of National Fund of Philosophy and Social Science of China; National Office for Philosophy and Social Sciences","keywords":"Business; Mergers and acquisitions; Industrial organization; Commerce; Monetary economics; Finance; Economics","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":[0.004099688,0.0002675111,0.0002831063,0.0007853407,0.0008592248,0.003888791,0.001045572,0.001467142,0.006641981],"category_scores_gemma":[0.01399399,0.0002347414,0.0002525937,0.0006796172,0.001596597,0.002459142,0.001324064,0.00123172,0.0006287433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006878534,"about_ca_system_score_gemma":0.001222407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00526612,"about_ca_topic_score_gemma":0.01230195,"domain_scores_codex":[0.9985372,0.0005317028,0.0001045755,0.0001798882,0.0002872378,0.0003593857],"domain_scores_gemma":[0.9580328,0.02296061,0.01284807,0.001682169,0.001898234,0.002578088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00395749,0.001646703,0.8927705,0.0003807876,0.000365248,0.001003408,0.004551561,0.0005353029,0.001749232,0.006035224,0.001782952,0.08522165],"study_design_scores_gemma":[0.0002181177,0.0007662001,0.9727413,0.0003108025,0.0003290568,0.0003124981,0.01630585,0.0003592968,0.001502617,0.001994708,0.005137612,0.00002189794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884003,0.001428272,0.0001438678,0.001318456,0.00001517337,0.00001308603,0.00008099247,0.000004938095,0.008594861],"genre_scores_gemma":[0.9983035,0.0006845646,0.00005584252,0.0002381107,0.00001419814,0.000002953573,0.00004810732,0.000001615039,0.0006510481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006641981,"threshold_uncertainty_score":0.02221966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196467321326163,"score_gpt":0.3490219852442227,"score_spread":0.3293752531116064,"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."}}