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On optimal regimes of knowledge exchange: a model of recombinant growth and firm networks

机译:关于知识交流最优制度:重组生长与企业网络模型

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The literature has documented two patterns of knowledge exchange: free sharing of knowledge and barter exchange. The former has been coined as collective invention, while the latter is observed in the form of R&D alliance. This study, for the first time, compares these two modes of cooperation in creating and diffusing new knowledge. Doing so, we take seriously the network character of knowledge and the skewed distribution of innovation size by proposing a novel model. In this model, knowledge is represented by distinct letters and words constructed thereof and accumulated by agents over time. Discovering new words agents recombine available knowledge pieces not randomly but following certain ideas, semi-definite structures on what words can be further constructed. We proceed by allocating agents in a network and allowing them to cooperate over direct ties either in a regime of collective invention or bilateral R&D alliances. We find networks with skewed degree distribution as most productive under R&D alliances and perfect IPR since they best concentrate scarce resources in discovering different knowledge combinations. In contrast, under collective invention and imperfect IPR, clustered networks better diffuse valuable ideas and knowledge resulting in the overall superior performance. Furthermore, under imperfect IPR, collective invention raises the inequality in payoffs among agents in networks with skewed degree distribution but reduces it for clustered topologies. The latter brings a novel explanation on why industries in the past have experienced a shift in the dominant pattern of knowledge exchange.
机译:该文献已记录两种知识交流模式:自由分享知识和易货交易所。前者已被丛准为集体发明,而后者以研发联盟的形式观察到后者。这项研究首次比较了这两种合作模式,在创造和扩散新知识方面。这样做,我们通过提出一种新型模型来认真对知识的网络特征和创新规模的偏斜分布。在该模型中,知识由其构造的不同字母和单词表示并随时间累计。发现新的单词代理重新组合可用知识件不是随机而是遵循某些想法,可以进一步构建的单词的半定结构。我们通过在网络中分配代理商进行分配,并允许他们在集体发明或双侧研发联盟的制度中与直接联系进行直接关系。我们发现具有偏斜度分布的网络,因为它们在R&D联盟和完善的知识产权下最为富有成效,因为它们最适合发现不同的知识组合来稀缺资源。相比之下,在集体发明和不完美的知识产权下,聚类网络更好地弥漫着贡献的思想和知识,从而导致整体卓越的性能。此外,在不完美的知识产权下,集体发明在网络中具有倾斜程度分布的网络中的代理商中的不等式,但为集群拓扑减少了它。后者给为什么过去的工业造成了一部新颖的解释,经历了知识交流的主导模式的转变。

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