| 多维邻近创新网络中知识扩散模型与仿真研究 |
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| 引用本文： | 余谦,朱锐芳.多维邻近创新网络中知识扩散模型与仿真研究[J].情报科学,2020,38(5):65-72. |
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| 作者姓名： | 余谦 朱锐芳 |
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| 作者单位： | 武汉理工大学经济学院,湖北武汉430070;武汉理工大学经济学院,湖北武汉430070 |
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| 基金项目： | 国家自然科学基金面上项目“多维邻近性视角下创新网络的自适应演化机理与政府治理”(71774128)。 |
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| 摘 要： | 【目的/意义】知识扩散是企业创新过程中获取知识的重要途径,在创新网络中多维邻近性作为外部知识获取的影响因素,对企业知识水平增长有重要作用。【方法/过程】定义了多维邻近创新网络,并将邻近性因素纳入扩散函数,建立了不同邻近性网络中知识扩散的过程模型,探讨产业发展不同阶段多维邻近性对知识增长水平的影响及其形成原因,并通过实证分析验证所构建的知识扩散机制在真实网络中的有效性。【结果/结论】研究结果表明:不同邻近性网络中的平均知识水平呈S形曲线演化规律;地理邻近因素在产业发展初期对网络中知识扩散发挥主要作用;技术邻近性是网络中知识增长的核心因素;网络中知识扩散受社会邻近性影响最小,但时间持续最长。
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| 关 键 词： | 多维邻近性 创新网络 知识扩散函数 知识增长 |
Knowledge Diffusion Model and Simulation in Multi-dimensional ProximityInnovation Network |
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| YU Qian,ZHU Rui-fang.Knowledge Diffusion Model and Simulation in Multi-dimensional ProximityInnovation Network[J].Information Science,2020,38(5):65-72. |
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| Authors: | YU Qian ZHU Rui-fang |
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| Affiliation: | (School of Economics,Wuhan University of Technology,Wuhan 430070,China) |
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| Abstract: | 【Purpose/significance】Knowledge diffusion is an important way to acquire knowledge in the process of enter prise innovation.In the innovation network,multi-dimensional proximity as an influentialfactor of external knowledge ac quisition plays an important role in the growth of enterprise knowledge level.【Method/process】This paper defines multi-di mensional proximity innovation networks and incorporates proximity factors into the diffusion function,constructs a process model of knowledge innovation and diffusion in different proximity networks,discusses the influence of multi-dimensional proximity on knowledge growth at different stages of industrial development and its causes,and through empirical analysis to verify the effectiveness of the constructed knowledge diffusion mechanism in real networks.【Result/conclusion】The results show that the average knowledge level in different proximity networks is S-shaped curve;geographical proximity factor plays a major role in knowledge diffusion at the initial stage of industrial development;technology proximity is the core fac tor of knowledge growth in the network;social proximity has the least impact on knowledge diffusion,but the duration lasts the longest. |
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| Keywords: | multi-dimensional proximity innovation network knowledge diffusion function knowledge growth |
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