知识转移的多维互动如何影响数字创新能力?

IF 3.2 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Knowledge Management Research & Practice Pub Date : 2023-10-02 DOI:10.1080/14778238.2023.2261892
Zhen Che, Changqi Wu, Weishi Qu, Naichuan Zhang
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引用次数: 0

摘要

摘要本研究从宏观-全球(本土、跨境)和微观-知识类型(辅助和互补)两方面建立了知识转移路径与数字创新能力的多维互动关系。利用中国企业的数据,我们发现本地知识网络“供给”与辅助知识“需求”的匹配比互补知识“需求”的匹配更有利于数字创新能力的提升。跨界知识网络的“供给”与互补知识的“需求”相匹配,比与辅助知识的“需求”相匹配更有利于数字创新能力的提升。数字环境扫描能力和知识流耦合调节了互补和辅助知识转移与数字创新能力的关系。研究结果对构建数字化创新网络系统具有重要的启示意义。关键词:知识转移数字创新能力数字环境扫描能力知识流耦合程度披露声明作者未报告潜在利益冲突。数字技术通常指ABCD: A:人工智能(AI), B:区块链,C:云计算,D:大数据或更广泛的SMACIT技术(S是与社会相关的技术,Social;M是移动相关技术,Mobile;A是分析相关技术,Analytics, C是云相关技术,Cloud;IT是物联网技术(IoT)。详见链接:https://www.ibm.com/garage/method/.3。《数字经济及其核心产业统计分类(2021年)》已于2021年5月14日国家统计局第十次常务会议通过。本研究得到国家社会科学基金重大项目[20&ZD083]的支持。
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How does multidimensional interaction of knowledge transfer affects digital innovation capability?
ABSTRACTThis study establishes the link between multi-dimensional interaction of knowledge transfer paths and digital innovation capability from both macro−global (native, cross−border) and micro−knowledge type (auxiliary and complementary) perspectives. Using the data of Chinese firms, we find that the matching of the “supply” of native knowledge network and auxiliary knowledge “demand” is more conducive to the improvement of digital innovation capability than matching of the “demand” of complementary knowledge. The matching of the “supply” of cross−border knowledge network and the “demand” of complementary knowledge are more conducive to the improvement of digital innovation capability than matching with the “demand” of auxiliary knowledge. Digital environment scanning capability and knowledge flow coupling moderates the relationship between complementary and auxiliary knowledge transfer and digital innovation capability. Our findings have important implications for the construction of digital innovation network systems.KEYWORDS: Knowledge transferdigital innovation capabilitydigital environment scanning abilitydegree of knowledge flow coupling Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. Digital technology often refers to ABCD: A: Artificial Intelligence (AI), B: Blockchain, C: Cloud Computing, D: Big Data or a broader SMACIT technology (S is social-related technology, Social; M is mobile-related technology, Mobile; A is analysis Related technology, Analytics, C is cloud-related technology, Cloud; IT is Internet of Things technology, IoT).2. See the link for details: https://www.ibm.com/garage/method/.3. The “Statistical Classification of the Digital Economy and Its Core Industries (2021)” has been adopted at the 10th executive meeting of the National Bureau of Statistics on May 14, 2021. http://www.gov.cn/.Additional informationFundingThe work was supported by the National Social Science Foundation major project of China [20&ZD083].
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来源期刊
CiteScore
7.00
自引率
15.60%
发文量
52
期刊介绍: Knowledge management is a term that has worked its way into the mainstream of both academic and business arenas since it was first coined in the 1980s. Interest has increased rapidly during the last decade and shows no signs of abating. The current state of the knowledge management field is that it encompasses four overlapping areas: •Managing knowledge (creating/acquiring, sharing, retaining, storing, using, updating, retiring) •Organisational learning •Intellectual capital •Knowledge economics Within (and across) these, knowledge management has to address issues relating to technology, people, culture and systems.
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