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组织双元性创新模式演化路径研究——两种“次优”能力陷阱讨论 被引量:8
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作者 王寅 张英华 +1 位作者 王饶 张建宇 《科技进步与对策》 CSSCI 北大核心 2016年第8期93-100,共8页
优秀的创新型组织通过对开发性创新与探索性创新进行有效的双元性管理,追求创新绩效和效率最大化。很多学者讨论了"开发路径依赖"和"探索持续失败"两种双元性创新能力陷阱的存在及其诱因,但并未讨论其对立情况。在... 优秀的创新型组织通过对开发性创新与探索性创新进行有效的双元性管理,追求创新绩效和效率最大化。很多学者讨论了"开发路径依赖"和"探索持续失败"两种双元性创新能力陷阱的存在及其诱因,但并未讨论其对立情况。在论证组织双元性创新必要性的基础上,分类并对比了7种创新型组织,讨论了与先前研究对立情境下的"探索路径依赖"与"开发持续失败"能力陷阱,并详细说明了组织双元性创新均衡模式退化的4种路径。 展开更多
关键词 组织创新 双元性创新 探索性创新 开发性创新 能力陷阱 次优模式 演化路径
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Quadratic investigation of geochemical distribution by backward elimination approach at Glojeh epithermal Au(Ag)-polymetallic mineralization, NW Iran
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作者 Darabi-Golestan Farshad Hezarkhani Ardeshir 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第2期342-356,共15页
The correspondence analysis will describe elemental association accompanying an indicator samples.This analysis indicates strong mineralization of Ag,As,Pb,Te,Mo,Au,Zn and to a lesser extent S,W,Cu at Glojeh polymetal... The correspondence analysis will describe elemental association accompanying an indicator samples.This analysis indicates strong mineralization of Ag,As,Pb,Te,Mo,Au,Zn and to a lesser extent S,W,Cu at Glojeh polymetallic mineralization,NW Iran.This work proposes a backward elimination approach(BEA)that quantitatively predicts the Au concentration from main effects(X),quadratic terms(X2)and the first order interaction(Xi×Xj)of Ag,Cu,Pb,and Zn by initialization,order reduction and validation of model.BEA is done based on the quadratic model(QM),and it was eliminated to reduced quadratic model(RQM)by removing insignificant predictors.During the QM optimization process,overall convergence trend of R2,R2(adj)and R2(pred)is obvious,corresponding to increase in the R2(pred)and decrease of R2.The RQM consisted of(threshold value,Cu,Ag×Cu,Pb×Zn,and Ag2-Pb2)and(Pb,Ag×Cu,Ag×Pb,Cu×Zn,Pb×Zn,and Ag2)as main predictors of optimized model according to288and679litho-samples in trenches and boreholes,respectively.Due to the strong genetic effects with Au mineralization,Pb,Ag2,and Ag×Pb are important predictors in boreholes RQM,while the threshold value is known as an important predictor in the trenches model.The RQMs R2(pred)equal74.90%and60.62%which are verified by R2equal to73.9%and60.9%in the trenches and boreholes validation group,respectively. 展开更多
关键词 correspondence analysis first order interaction reduced quadratic model (RQM) optimized model order reduction and validation strong genetic effects
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