The evolution of R&D networking in the biotech industries

International Journal of Entrepreneurship and Innovation Management

Volumn 5, Issue 1-2, 2005, Pages 49-68

  Pyka, Andreas ^a   Saviotti, Paolo ^b  

^a University of Augsburg   (Denmark)

^b CNRS   (France)

Author keywords

biotech industries; evolutionary economics; R D networks; simulation

Indexed keywords

EID: 33847716798     PISSN: 1368275X     EISSN: 17415098     Source Type: Journal    
DOI: 10.1504/ijeim.2005.006337     Document Type: Article

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31. For a detailed survey of R&D cooperations see Caloghirou et al., 2003 and for a survey with a focus on cooperation in the pharmaceutical industry see Martin, 2003.
32. See also Powell et al. (2003) who give a visualisation of network evolution in the life sciences industries from 1988 to 1999.
33. The description of the model is given in a non-mathematical form not explicitly introducing details. Interested readers may obtain a comprehensive description of the model by writing to the authors.
34. In this respect, a major methodological advantage of simulation studies shows up in the construction of the innovation processes. Whereas in traditional optimisation models there is no difference between the modeller and the modelled agents, simulation analysis allows for the programming of random numbers, their statistical distribution is unknown to the agents in the model, see Pyka (1999, pp.189 ff.).
35. Our data are covering worldwide collaborations in the biopharmaceutical industries for the years 1977 to 1999 (INRA-SERD Database).
36. An interesting application of graph theory on biotechnology innovation networks can be found in Pammolli and Riccaboni (2003).