机构地区:[1]广东财经大学工商管理学院,广东广州510320 [2]湖南大学工商管理学院,湖南长沙410082
出 处:《科技进步与对策》2023年第13期113-122,共10页Science & Technology Progress and Policy
基 金:国家自然科学基金面上项目(72174058);广东省基础与应用基础研究区域联合基金青年项目(2020A1515110775);广东省哲学社会科学规划青年项目(GD20YGL06)。
摘 要:跨越组织边界获取并组合异质性知识资源,是企业创新成功的重要路径。采用资源编排理论,从知识元素关系结构视角,将知识跨界搜寻划分为领域知识搜寻与架构知识搜寻两种,探讨知识跨界搜寻对企业迭代创新的差异化影响,同时,验证关系嵌入与政府支持政策对两者关系的调节作用。通过对搜集的262份高新技术企业调研数据进行实证分析,研究发现:①领域知识搜寻与企业迭代创新呈倒U型关系,而架构知识搜寻正向影响企业迭代创新;②关系嵌入正向调节领域知识搜寻与企业迭代创新关系;③政府支持政策与知识跨界搜寻活动的匹配更能促进企业迭代创新,具体表现为企业在实施领域知识搜寻策略时,政府采用财税支持政策更有利于企业迭代创新,而当企业开展架构知识搜寻活动时,政府出台创新环境支持政策更能促进企业迭代创新。研究结果为充分利用组织内外情境因素、选择恰当的知识搜寻活动以促进企业迭代创新提供了理论基础。In the new era of digital economy,more and more companies have taken advantage of digital platforms to actively interact with customers to collect their feedback,iteratively upgrade and improve products.It has become an important path by acquiring and combining different areas of knowledge across organizational boundaries for firms'innovation success.The existing literature mainly emphasizes the important role of heterogeneous knowledge acquisition and possession in the growth of enterprises and the construction of core competitiveness.But it fails to meet the needs of quickly identifying and repeatedly editing the knowledge elements required for enterprises from massive knowledge sources in the digital age.The resource arrangement theory puts forward that the dynamic process of creating sustainable competitive advantage for organizations by effectively arranging resources to realize the rational allocation of internal and external resources.From the perspective of resource arrangement,this paper defines two dimensions of knowledge cross-boundary searching:domain knowledge searching and architecture knowledge searching.Then,this paper aims to explore the different mechanism of knowledge coupling affects firm's iterative innovation,it also tries to verify the moderating effects of relationship embedding and government support policies on knowledge coupling-iterative innovation relationship.This study collects data by means of on-site and online questionnaires.The samples are mainly from Hunan,Sichuan,Guangdong and Liaoning,involving six high-tech industries with knowledge intensive characteristics,such as machinery manufacturing,electronic information technology and biomedicine.Considering the subjects'understanding and familiarity with enterprise innovation activities,the respondents are mainly middle and senior managers and other comprehensive executives in technology R&D,production and manufacturing departments who have worked in the enterprise for a long time,as well as some core employees(such as technical ba
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