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Multi-scale urban innovation networks are important channels for intra- and inter-city knowledge spillovers and play an important role in urban industrial innovation and growth. However, there is a lack of direct evidence on the impact of multi-scale urban innovation networks on industrial development. Drawing upon the "buzz-and-pipeline" model, this paper analyzes the impact of multi-scale urban innovation networks on industrial development by taking the automobile manufacturing industry in China's five urban agglomerations as an example. Firstly, based on the Form of Correlation between International Patent Classification and Industrial Classification for National Economic Activities (2018) and co-patents, we construct urban innovation networks on three different geographical scales, including intra-city innovation networks, inter-city innovation networks within urban agglomerations, and innovation networks between cities within and beyond urban agglomerations. Then, we employ the ordinary least squares model with fixed effects at the urban agglomeration level to explore the impact of urban multi-scale knowledge linkages on the development of the automobile manufacturing industry and the results showed that urban innovation networks at three different geographical scales have different impacts on industrial development. Specifically, intra-city innovation networks have a facilitating effect on industrial development, while both inter-city innovation networks within urban agglomerations and innovation networks between cities within and beyond urban agglomerations have an inverted U-shaped impact on industrial development. The interactions between urban innovation networks on three different geographical scales have a negative effect on industrial development. Simultaneously, the agglomeration level of urban industry plays a positive moderating role in the impacts of multi-scale urban innovation networks on industrial development. [ABSTRACT FROM AUTHOR]

This article sets out to investigate the relationship between the knowledge spillovers and the potential for high-value inventions to emerge. We study knowledge spillovers through the lens of knowledge networks: a web of interrelated knowledge elements with structural patterns. Knowledge spillovers influence the productivity of a technology sector and hence their pattern should impact the pathways for knowledge appropriation in the sector. It is hypothesized that a robust knowledge network is associated with knowledge appropriation leading to valuable inventions. We test the hypothesis using patent citation network of 1821 patents from 78 inventions belonging to two different technological sectors. Based upon the findings, we suggest network robustness as a new metric for determining the technical value of inventions. [ABSTRACT FROM AUTHOR]

The main sources of technological development are from abroad rather than domestic in many countries. The global networks for knowledge and technology flows are becoming sophisticated. This article examines how a country's embeddedness in the global knowledge spillover networks, particularly trade and FDI, is related to national innovation performance. Network closure and structural hole, the main arguments in network theory literature, represent the main objectives of our network analysis. The results are subsequently used to assess how these network characteristics are related to national innovation performance via panel negative binomial regression analysis. The findings show an overall tendency of a negative effect of network closure and a positive one of structural holes on a country's innovative outcome. In conclusion, this article not only highlights the significant role of network characteristics in national innovation performance, but also provides implications on how to leverage such network resources to improve national innovation systems. [ABSTRACT FROM AUTHOR]

Many firms find it challenging to develop innovations, evidenced by the ever-mounting number of university-industry research alliances. This study examines the strategic choices of actors who participate in collaborative innovation alliances involving partnerships between industry and universities (U-I) based on a stochastic evolutionary game model. White noise was introduced to reflect uncertainty and the stochastic interferences caused by the differences between actors. Using the Itô stochastic differential equation theory, we analyze stability issues of player behaviors in the evolution of a collaborative innovation alliance. The results illustrate that improvements in innovation efficiency can contribute to U-I collaborative innovation alliances. High knowledge complementarity appears to be unbeneficial to the stability of these alliances, and controlling knowledge spillovers may suppress free-rider problems from both sides of the game. Our study contributes to innovation research by providing a decision-making reference for the design of U-I cooperation. [ABSTRACT FROM AUTHOR]

Open innovation, in the form of inbound and outbound open innovation, is an ever-increasing research field. Research into outbound open innovation (i.e., the inside-out process) focused mostly on the commercialisation of internal knowledge. However, we know very little about firms' voluntary nonpecuniary knowledge disclosure. This paper sheds light on this understudied research field by conducting a quantitative study that identifies which internal and external conditions foster firms' knowledge disclosures. The results show that firms' strategies to influence (i) the market and the competition and (ii) external spillovers are drivers of firms' knowledge disclosures. Further, the moderating roles of environmental characteristics are shown. Firms' environmental technological dynamism is found to strengthen the positive relationships between influencing external spillovers and knowledge disclosure. In contrast, the relationships between influencing the market and the competition and knowledge disclosure are negatively moderated by a firm's environmental technological dynamism. [ABSTRACT FROM AUTHOR]

The article is devoted to the study of the influence of social capital on the ability of countries to produce innovations. The analysis of the achievements of economic science in the field of studying social capital and innovation revealed the ambiguity of views on the relationship between these categories, as well as wide discussions about the influence of the stock of social capital on the nature of economic growth. The authors associated the existing difficulties of the research process with insufficient attention of scientists to different levels and forms of manifestation of social capital, which have different potential in promoting innovation. On the basis of the methodological approach, in which individualistic and holistic ideas about economic activity are combined in the framework of institutional theory, the decomposition of public social capital into its individual and organizational levels and corresponding functional forms is carried out. On this basis, the nature of their interaction and role in the innovation process is shown. In order to quantify social capital in view of its ability to promote innovation, an integral indicator "Index of Innovative Social Capital" was constructed as a combination of three key components: close cooperation between the university and R&D, Information & communication technologies, and social capital itself. In a sample of 26 countries of different levels of development, a strong two-way direct relationship with an average degree of significance was found between the "Index of Innovative Social Capital" and GDP per capita. The presence of such dependence serves as another explanation for the unevenness of innovative development in the world, and therefore, opens up guidelines for poor countries to increase their innovative potential in view of social and institutional factors. [ABSTRACT FROM AUTHOR]