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论文编号：	5360
作者编号：	2120112359
上传时间：	2013/6/6 21:00:26
中文题目：	基于元分析的网络属性与企业创新绩效关系研究
英文题目：	A Meta-analysis on the Relationship of Network Properties and Firm’s Innovative Performance
指导老师：	林润辉
中文关键字：	网络属性；创新绩效；元分析；文化差异
英文关键字：	Network Properties Innovative Performance Meta-analysis Cultural Differences
中文摘要：	网络与企业创新绩效的关系一直是网络结构理论研究的重要关注点，但是在研究过程中也出现一些问题。有学者认为网络中的结构洞与企业创新绩效的关系很显著，而其他学者则不赞同这个观点。还有诸多对强联系、弱联系的争论，或者对中心性和结构洞的争论等等，这为本文利用元分析对网络属性影响企业创新绩效的研究创造了可能，也成为本研究的必要条件。 国内对网络与企业创新绩效的研究历程短且研究的学者也比较少，而且也没有学者采用元分析对这个领域进行研究。本文则采用元分析方法梳理了1980-2012年期间发表的网络属性与企业创新绩效关系的相关文献，首先本文对筛选出来的30篇实证文献进行元分析，得出了比较具有普遍性的关于网络属性与企业创新绩效关系的结论；并把文献中的研究对象根据所处的文化背景分成两类，对比研究了网络各维度在不同文化下对企业创新绩效影响的变化；同时采用随机效应模型模型对效应值进行修正和优化。 本文通过元分析得到的主要结论有： （1）网络关系强度对企业创新绩效的影响比较大； （2）网络规模对企业创新绩效的影响比较小； （3）文化因素对中心度与企业创新绩效关系的影响比较小； （4）文化因素对网络规模与企业创新绩效关系的影响比较大； （5）文化因素对网络密度与企业创新绩效关系的影响比较大；
英文摘要：	Network and enterprise innovation performance has been an important concern of the network structure of theoretical research, but there are some problems in the research process. Some scholars believe that structural holes in the network have an positive effect on enterprise innovation performance, while other scholars do not agree with this point of view. There are many other arguments about strong ties or weak ties, structural holes or centricity and so on. This is a necessary condition for the use of meta-analysis to study this area. Domestic study of network and the enterprise innovation performance started relatively late, and the research results are still in its infancy, and there is no scholars using the component analysis method to summary and analysis on the existing literature in both English and Chinese. This meta-analysis method combing the period 1980-2012 published network properties and enterprise innovation performance relationship literature Firstly, We screened out 30 empirical literature meta-analysis to come to a universal conclusion on the relationship of the network properties and enterprise innovation performance; Then we comparative study of the role of each dimension of the network in different cultures on innovative performance; using a random effects model to amend and optimize the effect values. Through analysis the main conclusions are as follows: (1) Network intensity has a great impact on the performance of enterprise innovation; (2) Network scale is relatively small effect on the performance of enterprise innovation; (3) The impact of cultural factors on the relationship between the Center and Corporate Innovation Performance is relatively small; (4) The impact of cultural factors on the relationship between network size and enterprise innovation performance is relatively large; (5) The impact of cultural factors on the relationship between the network density and enterprise innovation performance is relatively large;
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