Investigating Network-based Proximity in American Biotechnology

Lee, Der-Shiuan

doi:10.1016/j.procs.2015.08.146

Cited by 1 publication

(9 citation statements)

References 24 publications

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“…Polanyi [83] argued that knowledge is embedded in inventors who reside in a city. Figure 1 shows the framework of inter-city networks of co-invention and the social networks of inventors [25]. The upper framework refers to a co-inventive region within city A to F, while all nodes from its social network counterpart signify the individual inventors who reside in these cities.…”

Section: Framework Of Inter-city Network Of Co-inventionmentioning

confidence: 99%

“…I follow Ó hUallacháin and Lee [24] and Lee [25] by distinguishing four possible patterns in a LISA cluster map, either network or spatial, along with non-significant areas.…”

Section: Network and Spatial Dependencies At Local-levelmentioning

confidence: 99%

“…In contrast, if the same neighbors compose a co-inventive core in a spatial LISA cluster map, co-patenting relationships of inventors are explained by spatial proximity. Moreover, the network LISA cluster map should appear for co-inventive core cities that are spatially scattered, as inter-city relationships often support co-patenting by inventors residing in dispersed cities [25,90]. A majority of low co-inventive islands occurring in the network LISA cluster map is assumed to be common because few national centers exist and most cities' linkages are confined to the regional nexus [11,16,90].…”

Section: Network and Spatial Dependencies At Local-levelmentioning

confidence: 99%

“…Owing to the wide variation in geographical spacing and the 'island' characteristic, this article uses the number of nearest neighbors (also known as an area's k value) as the most appropriate choice to identify neighboring structures in the contiguous U.S. cities [24,25,90]. Numbers of cities ranging from three to 20 are considered to determine the appropriate number of nearest cities.…”

Section: Network and Spatial Weightsmentioning

confidence: 99%

“…I follow Ó hUallacháin and Lee [24], Lee [25], Hall et al [91], Cortright and Mayer [92], and Hevesi and Bleiwas [93] by selecting the 3-digit classes (424, 435, 514, and 800) into the sub-category of biotechnology. Class 435 covers chemical groupings and includes molecular biology and microbiology inventions.…”

Section: Patent Data and Geographical Units Of Analysismentioning

confidence: 99%

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Towards Urban Resilience through Inter-City Networks of Co-Invention: A Case Study of U.S. Cities

Lee

2018

Sustainability

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Knowledge creation involves social and collaborative processes with local and extra-local partners. The space of knowledge flows functions as a system of networks where knowledge is transmitted around different alignments of agents in distant places. Scholars argue that the concept of urban resilience combines local and extra-local competencies to develop an inter-city system, this is a major strategy for cities to mitigate and adapt to climate change and economic recession. Little attention has been given to the role of networks in co-invention and few empirical studies have been conducted. This article provides insights into the structure of inter-city networks of co-invention by examining the relative importance of the network compared with spatial proximity in biotechnology co-patenting across 150 American cities from 1983 to 2013. Results show that the U.S. inter-city structure gradually becomes more explicit, apparent, and identifiable in the network-based system. Network proximity better defines the biotechnology co-patenting relationships among the U.S. cities compared with spatial proximity. The current inter-city networks of co-invention are mostly regional, with some national but few local ties. This structure provides a way to develop mitigation and adaptation policies for climate disasters or economic recessions.

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Section: Framework Of Inter-city Network Of Co-inventionmentioning

confidence: 99%

“…I follow Ó hUallacháin and Lee [24] and Lee [25] by distinguishing four possible patterns in a LISA cluster map, either network or spatial, along with non-significant areas.…”

Section: Network and Spatial Dependencies At Local-levelmentioning

confidence: 99%