{"id":"W3047014368","doi":"10.1111/caim.12399","title":"Improving new product development innovation effectiveness by using problem solving tools during the conceptual development phase: Integrating Design Thinking and TRIZ","year":2020,"lang":"en","type":"article","venue":"Creativity and Innovation Management","topic":"Design Education and Practice","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"TRIZ; Automotive industry; New product development; Conceptual design; Computer science; Conceptual framework; Process (computing); Product (mathematics); Process management; Manufacturing engineering; Fuzzy logic; Systems engineering; Management science; Engineering; Artificial intelligence; Business; Mathematics; Marketing; Human–computer interaction","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":[0.02507165,0.001300188,0.001077708,0.007958991,0.00113116,0.008830428,0.00203319,0.001551668,0.001779378],"category_scores_gemma":[0.03231603,0.0006296143,0.00138626,0.004078897,0.002793254,0.009202911,0.003488783,0.002105754,0.0005123179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003946038,"about_ca_system_score_gemma":0.008711742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008620535,"about_ca_topic_score_gemma":0.0009441201,"domain_scores_codex":[0.9749191,0.01455694,0.001929382,0.001487529,0.006357519,0.0007494575],"domain_scores_gemma":[0.9532374,0.03473844,0.004197809,0.002208954,0.005120201,0.000497316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001367318,0.001035173,0.004366746,0.008580434,0.0002144208,0.0001684861,0.01160666,0.006708786,0.006930765,0.1164566,0.00151268,0.8422825],"study_design_scores_gemma":[0.0008630835,0.005198333,0.02785595,0.0201584,0.001759577,0.002914472,0.04454047,0.1288793,0.07976565,0.434761,0.2526966,0.0006071346],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1167194,0.02081495,0.7882098,0.005687927,0.0002158806,0.002007173,0.00007865674,0.0006247719,0.06564137],"genre_scores_gemma":[0.3274203,0.009596207,0.6580293,0.0006441667,0.00006558871,0.001345423,0.0001064784,0.00007950287,0.002713042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02507165,"threshold_uncertainty_score":0.1325932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07056966816608355,"score_gpt":0.2871356976381303,"score_spread":0.2165660294720468,"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."}}