Geographical or relational: What drives technology-specific R&amp;D collaboration networks?

Neuländtner, Martina; Scherngell, Thomas

doi:10.1007/s00168-020-01002-5

Cited by 13 publications

(14 citation statements)

References 61 publications

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“…Boschma, 2017). Our results are also in line with Neuländtner and Scherngell (2020) and Capello and Caragliu (2018) who emphasized interrelations and some form of complementarity between cognitive and geographical distance. In the case of repeated R&D projects, statistically significant shift towards a higher cognitive proximity was identified, particularly in case of manufacturing sector.…”

Section: Discussionsupporting

confidence: 92%

“…The intensity of regional and inter-regional co-operation should be balanced to allow companies to reap both the benefits of localized learning and of knowledge accumulated within the region and to combine these with absorption of extra-regional knowledge to respond properly to fast global changes and challenges. This is in line with Neuländtner and Scherngell (2020) who show that dissimilar regions have lower potential to collaborate.…”

Section: Importance Of Randd Collaboration From the Perspective Of Ge...supporting

confidence: 92%

“…This paper follows the findings on network dynamics in collaborative research (Balland et al, 2019) and the results of a comparative analysis of regional embeddedness in European knowledge networks (Neuländtner & Scherngell, 2020; Wanzenböck et al, 2014; Wanzenböck et al, 2015) and applied proximity approach. The analysis focuses on inter‐ /intra‐ regional R&D collaborations in small former command economies with differently developing regional innovation systems (Kostić & Květoň, 2020).…”

Section: Discussionmentioning

confidence: 86%

“…In addition to various partners and types of networks, the role of geographic distance varies among sectors depending on complexity of knowledge applied within different industries (Plotnikova & Rake, 2014). Furthermore, Neuländtner and Scherngell (2020) revealed geographical barriers and negative country border effects when looking at collaboration in key Enabling technologies projects.…”

Section: A Conceptual Framework For Explaining Variation In Randd Col...mentioning

confidence: 99%

“…However, existing research on R&D collaboration has insufficiently addressed several issues. Surprisingly, to the best of our knowledge, limited number of studies has empirically tested the extent to which inter‐firm R&D co‐operation networks across the spectrum of manufacturing industries, knowledge‐intensive services and other relevant sectors for R&D co‐operation follows the propositions stemming from the proximity framework (the exception is Neuländtner & Scherngell, 2020 studying spatial and network structural determinants of cross‐region R&D collaboration regarding the six key enabling technologies). Further, the role of cognitive proximity has been tested upon various levels of the industrial disaggregation, and very often on the example of a single industries (e.g., Fornahl et al, 2011, on the role of relatedness in the case of German biotech firms, or Broekel & Boschma, 2012, on the Dutch aviation industry).…”

Section: Introductionmentioning

confidence: 99%

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The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects

Květoň

Novotný

Blažek

et al. 2022

Papers in Regional Science

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This paper explores effect of proximities on R&D collaboration and focus on a prime mechanism of intentional search for knowledge-joint R&D projects-using data on R&D projects co-financed by various public sector bodies in the period 2003-2018. Our findings show that R&D collaboration based on cognitive proximity is intentional and firms prefer partners with technological distance smaller than expected based on a reference population. In the case of repeated R&D collaboration among the same companies in manufacturing, there is a statistically significant shift towards a higher cognitive proximity. As for geographical proximity, we found relatively low intra-regional R-D collaboration and high openness of regional innovation systems.

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Section: Discussionsupporting

confidence: 92%

Section: Importance Of Randd Collaboration From the Perspective Of Ge...supporting

confidence: 92%

Section: Discussionmentioning

confidence: 86%

Section: A Conceptual Framework For Explaining Variation In Randd Col...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects

Květoň

Novotný

Blažek

et al. 2022

Papers in Regional Science

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show abstract

The case of sleeping beauties in nanotechnology: a study of potential breakthrough inventions in emerging technologies

2022

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This study aims to determine whether innovation depends on long-term patterns of interactions in technology and science, using patents in nanotechnology. The previous literature has distinguished between a technology’s degree of novelty (science-base) and degree of technological impact, highlighting that links to the science-base will lead to more breakthrough inventions, due to distant recombinations. We extend the debate by distinguishing two types of science linkages, “direct and strong science-base” and “indirect and more diverse science-base.” To find long-term patterns, we developed an empirical strategy to study nanotechnology patents through the metaphor of “sleeping beauties”, e.g., delayed recognition and high impact. We show that sleeping beauties occur more frequently in nanotechnology than in the general population of patents, so nanotechnology is an emerging technology that may delay breakthrough inventions. As expected, both types of science linkages create a higher impact. Contrary to expectations, however, neither “direct and strong science-base” (proxied by university ownership) nor “indirect and more diverse science-base” (proxied by the non-patent literature) are significant. Although this emerging technology has many science linkages, these do not cause a delayed impact. Control variables of IPC application class and company ownership do matter. We conceptualize that these are typical characteristics when firms combine several technologies for industrial innovation. Among other contributions, we propose that the non-patent literature should not be considered a proxy for science linkages in general, but instead this reflects a search amongst various types of codified as well as informal technological and scientific knowledge. We suggest that the long-term patterns of delayed recognition and high impact in science-based technologies may require the firms to recombine multiple technologies, specializations, and industrial applications in order to do industrial invention.

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Structural Dynamics of Inter-city Innovation Networks in China: A Perspective From TERGM

Zinilli,

Gao,

Scherngell

2024

Netw Spat Econ

Self Cite

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Innovation networks play a key role in advancing knowledge transfer, collaboration, and technological progress across sectors and regions. Central to the understanding of the mechanisms driving such networks is their dynamic evolution and structure. Much of the literature explores spatial and socio-economic drivers of innovation networks, focusing on geographic, institutional, and cultural influences. However, many of these studies tend to overlook the intricate properties that govern the behavior and dynamics of these networks. This study seeks to address this research gap, delving deeper by investigating Chinese intercity innovation networks between 2007 and 2018. Specifically, we examine: (i) the preferential attachment dynamics within intercity innovation networks, (ii) transitivity effects that underscore the interconnectedness of these networks, and (iii) the persistence and recurrence of connections. We find that cities show indeed a remarkable tendency to form ties with others that already have numerous connections. Such transitivity effects are important in highlighting the formation of innovation clusters. Moreover, the influence of link memory suggests that past collaborations significantly determine future partnerships, similar to the persistent nature of relationships in agglomeration theories.

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Geographical or relational: What drives technology-specific R&D collaboration networks?

Cited by 13 publications

References 61 publications

The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects

The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects

The case of sleeping beauties in nanotechnology: a study of potential breakthrough inventions in emerging technologies

Structural Dynamics of Inter-city Innovation Networks in China: A Perspective From TERGM

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