| 开放式创新下科技人才流动的知识与社会路径 |
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| 引用本文： | 徐茜.开放式创新下科技人才流动的知识与社会路径[J].科学学研究,2020,38(8):1397-1407. |
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| 作者姓名： | 徐茜 |
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| 作者单位： | 山东财经大学 |
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| 基金项目： | 教育部人文社会科学研究项目 |
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| 摘 要： | 开放式创新环境下，科技人才流动成为创新资源跨界流动的重要组成部分，其流动路径影响知识的流转，进而对创新发展产生深刻影响。因此，深入探究科技人才流动路径的形成机理有很强的理论和实践意义。鉴于以往研究对人才流动路径的解释囿于微观心理和宏观市场/制度两个层面，本研究从网络中观层面研究了科技人才的流动路径，探讨了知识网络和社会网络对科技人才流动路径的影响。采用多案例扎根分析，对通信行业5名科技人才样本的案例研究结果表明：科技人才的流动存在知识路径和社会路径。其中，知识路径包含了知识关联性路径和专业化路径，关联性路径源于知识网络中知识间的关联性，影响力来自于匹配效应、网络效应和增值效应；专业化路径源于知识网络中知识模块化所导致的知识专业性，影响力来自于学习曲线效应、声誉效应和转换成本效应。社会路径则包含了社会联系性路径和认知一致性路径，社会联系性路径源于社会联系对科技人才流动的牵引作用，强联系和弱联系分别起到了为科技人才提供高质量的和多样性的人—职信息的作用；认知一致性路径源于知识互动所需要的共同认知框架，影响力来自于知识背景、文化背景和专业能力评价。
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| 关 键 词： | 开放式创新 科技人才流动 知识路径 社会路径 |
| 收稿时间： | 2019-09-27 |
Knowledge Path and Social Path of Science and Technology Talents Flow in Open Innovation Network ——A Multiple case grounded theory method to telecommunication industry |
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| Abstract: | Under the open innovation environment, the flow of scientific and technological talents has become an important part of the cross-border flow of innovative resources. Its flow path affects the flow of knowledge, and then has a profound impact on the development of innovation. Therefore, it is of great theoretical and practical significance to explore the formation of the flow path of scientific and technological talents. In view of the fact that previous studies have constrained the interpretation of talent flow paths from the micro-psychological and macro-market/system levels, this study studies the flow paths of scientific and technological talents from the network perspective, and explores the impact of knowledge network and social network on the flow paths of scientific and technological talents. Based on the multiple case analysis, this paper makes a case study of five samples of scientific and technological talents in the telecommunication industry. The results show that there are knowledge and social paths in the flow of scientific and technological talents. The path of knowledge includes the path of knowledge relevance and the path of specialization. The path of relevance originates from the relationship between knowledge in the knowledge network, and the influence comes from matching effect, network effect and value-added effect. The path of specialization originates from the knowledge specialization caused by knowledge modularization in the knowledge network, and the influence comes from learning custom curve effect, reputation effect and switching cost effect. Social path includes social connection path and cognitive consistency path. Social connection path originates from the pulling effect of social connection on the flow of scientific and technological talents. Strong connection and weak connection play the roles of providing high-quality and diverse human-professional information for scientific and technological talents respectively. Cognitive consistency path originates from knowledge interaction. The common cognitive framework needed for action comes from knowledge background, cultural background and professional competence evaluation. |
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