4.6 Article

Knowledge acquisition and innovation quality: The moderating role of geographical characteristics of technology

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TECHNOVATION
卷 125, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.technovation.2023.102766

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Technological learning; Geography of innovation; Patent quality; Deployment technology; Solar photovoltaics

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Acquiring and absorbing knowledge at different geographic levels is crucial for firms' technological learning and innovation processes. This study discovers localized learning in citation networks within the solar photovoltaic balance-of-systems (PV BOS) sector, with the extent of localized learning varying based on the relevance of technologies to local contexts. Therefore, this research suggests that the impact of local and non-local knowledge on patent quality depends on technological characteristics. By examining the different levels of local dependence on four types of technologies in the PV BOS industry, it is found that local knowledge has a greater influence on innovation quality for technologies more rooted in local contexts, while non-local knowledge has a greater influence for technologies less relevant to local contexts.
Acquiring and absorbing knowledge at different geographic levels is an important step in the technological learning and innovation processes for firms. Geographically bounded knowledge searching and spillover have been shown in various network formats, industries, geographic scopes, and country contexts. This study finds evidence of localized learning in citation networks in the solar photovoltaic balance-of-systems (PV BOS) in-novations, and that the levels of localized learning vary based on the degree to which technologies are relevant to local contexts. Thus, this study proposes that the value of local and non-local knowledge on patent quality is contingent on technological characteristics. Leveraging the different degrees of local dependence on four types of technologies in the PV BOS industry, we find that the impact of local knowledge on innovation quality is higher for technologies that are more rooted in local contexts and that the impact of non-local knowledge is higher for technologies that are less relevant to local contexts.

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