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The role of multiple ties in knowledge networks: Complementarity in the Montefalco wine cluster

机译:多个关系在知识网络中的作用:蒙特法尔科葡萄酒集群的互补性

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摘要

After decades of studies about pervasive, wide, and inclusive knowledge externalities and the advantages of being there, recent literature on management, industrial marketing, economic geography, regional studies, and related fields has stressed that knowledge spreads imperfectly, unevenly, and selectively within regional and cluster contexts. In this respect, little is known about the role played by heterogeneous knowledge ties among the same set of actors and to what extent they follow overlapping or different routes of exchanging knowledge. Thus, an investigation of multiple knowledge networks in clusters is a fundamental approach to interpret the reasons for innovation and economic performance.With an original dataset comprised of data collected by surveys directly administered in local wineries in the Montefalco wine region of Italy, this paper aims to analyse the roles played by different local knowledge ties within a sector that is critically driven by the exchange of knowledge among economic actors. Social network analysis and exponential random graph modelling were applied to investigate the driving forces of the knowledge flows. The empirical results showed that economic and social ties positively affect the spread of knowledge, but the former has a higher magnitude impact than the latter. Moreover, they follow complementary routes of exchange rather than overlapping ones. We suggest that such a structure has implications for understanding the diffusion of knowledge and structures of innovation in cluster contexts.
机译:经过几十年的普遍存在,广泛和包容性知识外部的研究以及在那里的优势,最近的管理,产业营销,经济地理,区域研究和相关领域的文献强调,知识不完全,不均匀,选择性地在区域内传播和群集上下文。在这方面,关于同一组演员之间的异构知识联系的作用很少,以及他们在多大程度上遵循重叠或不同的交换知识路线。因此,对集群中的多个知识网络的调查是一种基本的方法,可以解释创新和经济表现的原因。在本文的目标中,由直接在意大利蒙特法尔科葡萄酒地区的当地葡萄酒厂直接管理的数据收集的数据组成的原始数据集分析由经济行动者交流知识交流批判性地推动的不同本地知识联系所扮演的角色。应用社交网络分析和指数随机图建模,以研究知识流动的驱动力。经验结果表明,经济和社会关系积极影响知识的传播,但前者的幅度高于后者。此外,它们遵循互补的交换路线而不是重叠的互补路由。我们建议这样的结构对理解集群环境中的知识和结构的扩散有影响。

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