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动态能力与创新类型——战略导向的调节作用 被引量:9

Dynamic Capability and the Types of Innovation: The Moderate of Strategic Orientation
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摘要 给定战略导向下的企业选择什么样的创新类型关系到企业的成长与创新绩效的提升。基于434家中国企业的调查数据,首先对动态能力与创新类型的关联进行分析,继而探讨了战略导向对企业动态能力与创新类型之间关系的调节作用。结果表明:(1)捕获能力的增强使企业倾向于选择技术型创新或者联合型创新;感知能力和变换能力的提升使企业倾向于选择联合型创新。(2)市场导向不仅正向调节感知能力与市场型创新的关系,也正向调节捕获能力与联合型创新的关系;企业家导向正向调节感知能力与联合型创新的关系。提供了战略导向对创新类型选择的影响机制,也为企业从自身动态能力出发,结合战略导向优化创新类型提供参考。 What type of innovation a company under a given strategic orientation should choose is vital to the company's development and the performance in innovation. Based on the survey data of 434 companies in China, the paper analyzes the relation between dynamic capability and the types of innovation, then discusses the regulating role of the strategic orientation over the relation between a company's dynamic capability and the types of innovation. The study shows that:(1) A company with enhanced seizing capability tends to choose technological innovation or associative innovation; while the company with improved sensing capability or transformation capability prefers associative innovation.(2) Market orientation not only has a positive effect over the relation between sensing capability and the marketing innovation, but also has the effect over the relation between the seizing capability and the associative innovation; and the entrepreneurial orientation has positive impact on the relation between the sensing capability and the associative innovation. The study comes out an influencing mechanism of the strategic orientation on the choice of the types of innovation, and provides reference for a company to optimize its types of innovation by combing its strategic orientation and based on its own dynamic capability.
出处 《科学学与科学技术管理》 CSSCI 北大核心 2016年第4期45-58,共14页 Science of Science and Management of S.& T.
基金 国家自然科学基金项目(71172200) 陕西省自然科学基础研究计划项目(2015JM7375) 西安理工大学青年社会科学学术创新团队(105-451215007) 陕西省重点学科建设专项(107-00X901)
关键词 感知能力 捕获能力 变换能力 多项logistic回归 sensing capability seizing capability transformation capability multinomial logistic regression
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