Publication: Quantifying knowledge exchange in R&D networks: a data-driven model
Quantifying knowledge exchange in R&D networks: a data-driven model
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Vaccario, G., Tomasello, M. V., Tessone, C. J., & Schweitzer, F. (2018). Quantifying knowledge exchange in R&D networks: a data-driven model. Journal of Evolutionary Economics, 28(3), 461–493. https://doi.org/10.1007/s00191-018-0569-1
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We propose a model that reflects two important processes in R&D activities of firms, the formation of R&D alliances and the exchange of knowledge as a result of these collaborations. In a data-driven approach, we analyze two large-scale data sets, extracting unique information about 7500 R&D alliances and 5200 patent portfolios of firms. These data are used to calibrate the model parameters for network formation and knowledge exchange. We obtain probabilities for incumbent and newcomer firms to link to other incumbents or newcomers ab
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- Vaccario, Giacomo
- Tomasello, Mario V
- Schweitzer, Frank
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Vaccario, G., Tomasello, M. V., Tessone, C. J., & Schweitzer, F. (2018). Quantifying knowledge exchange in R&D networks: a data-driven model. Journal of Evolutionary Economics, 28(3), 461–493. https://doi.org/10.1007/s00191-018-0569-1