Technological Distance and Breakthrough Inventions in Multi-Cluster Teams: How Intra- and Inter-Location Ties Bridge the Gap
Document Type
Article
Publication Date
2022
Keywords
groups and teams, geographic dispersion, group identification, intergroup relations, faultlines, entitativity, network density, small worlds
Abstract
Multi-cluster R&D teams have the potential to generate breakthrough inventions because they can tap into the distinct knowledge of the different geographic hot spots in which team members are located. Having access to a variety of knowledge offers these teams great recombinatorial potential. To succeed, however, the geographically dispersed members must share and integrate the different local knowledge pools available to them. We argue that the density of intra-team co-patenting ties shapes intra-team knowledge sharing and integration and hence the extent teams benefit from the knowledge they can access. Whereas greater density of intra-cluster team ties (within a given location) hinders sharing and integration of locally tapped knowledge across locations, greater density of inter-cluster ties (across cluster locations) facilitates it. Our empirical analysis of 834 multi-cluster nanotechnology R&D teams shows that the technological distance (the difference in knowledge) between clusters in which inventors are located has an inverted-U relationship with the likelihood of the team generating a breakthrough. Further, we find that the density of multi-cluster team intra- vs. inter-cluster ties influences the effect of technological distance on the likelihood of breakthrough invention.
Digital Object Identifier (DOI)
https://doi.org/10.1177/00018392211027512
Citation / Publisher Attribution
Administrative Science Quarterly, v. 67, issue 1, p. 167-206
Scholar Commons Citation
Vestal, Alex and Danneels, Erwin, "Technological Distance and Breakthrough Inventions in Multi-Cluster Teams: How Intra- and Inter-Location Ties Bridge the Gap" (2022). School of Marketing and Innovation Faculty Publications. 32.
https://digitalcommons.usf.edu/mai_facpub/32
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