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Università degli Studi di Brescia
Facoltà di Ingegneria
Corso di Laurea Magistrale in Ingegneria Gestionale




                                 Boroncini Annamaria
                                 Brianza Alberto
                                 Ghio Andrea
   Explore how public research and private research interface
    each other, how they complement each other (particular
    attention to the linear model and to the chain-linked model);

   Focus on the biotechnology sector;

   Some suggestions concerning the model (linear Vs. chain-
    linked) that better explains the innovation processes in this
    sector  personal opinions
   Stephan P. (1996), “The Economics of Science”
    (http://www.jstor.org/stable/2729500 )
   Balconi M., Brusoni S., Orsenigo L. (2008), “In Defence of the
    Linear Model: An Essay”
    (http://ftp.unibocconi.it/pub/RePEc/cri/papers/WP216Balconi
    BrusoniOrsenigo.pdf )
   McMillan S.G., Narin F., Deeds D.L., (2000), “An analysis of
    the critical role of public science in innovation: the case of
    biotechnology”
    (http://www.sciencedirect.com/science/article/pii/S00487333
    9900030X)
   The public nature of knowledge and the reward structure of
    science;
     No rivalry, no excludability;
     Difficulty for providers to capture the economic returns;

   Public research vs. Private research;

    Main assumption: public research is conducted mainly by
    universities (basic research) and private research is conducted
    mainly by firms (applied research)
    (Balconi, Brusoni and Orsenigo (2008))

   Interaction between basic research and applied research.
   LINEAR MODEL VS. CHAIN-LINKED MODEL
     Linear Model:
   Linear model starts from basic research (mainly
    in universities) and then the knowledge is
    transferred to the firms  marketable products;

   To do this, firms need to undertake a long and
    uncertain development activity.
 Chain-linked model:
   Firms want to satisfy the needs or the requests of
    the market  collaboration with universities;

   Linear model is “technology push” while the
    Chain-Linked model is “market pull”.
   Balconi, Brusoni and Orsenigo (2008):
    Pharmaceutical Industry Linear Model;

   McMillan, Narin and Deeds (2000): biotechnology and pharmaceutical
    industries are mainly based on basic science
       Our interpretation: Linear Model
                                     Pharmaceutical   Biotechnology Firms
                                     Companies

         Percent of science                 79.1%             83.1%
         references originating in
         public science



Research question: is it always right in every biotechnology’s sector?
Example of sub-sectors that seem to be much chain-linked:

   Agriculture Industry
      Crops that reduce the use of fertilizers
   Food Industry
      Improved taste or appearance of food


Several biotech sub-sectors are mainly “market pull”.
   In some biotechnology’s fields the innovation processes seem
    to follow the linear model, in others the chain-linked
    one, and this depends very much on the intrinsic
    characteristics of each field.


        Our goal: some sectors analysis and the
             relative knowledge transfer.

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Biotechnology: Linear or Chain Linked Model

  • 1. Università degli Studi di Brescia Facoltà di Ingegneria Corso di Laurea Magistrale in Ingegneria Gestionale Boroncini Annamaria Brianza Alberto Ghio Andrea
  • 2. Explore how public research and private research interface each other, how they complement each other (particular attention to the linear model and to the chain-linked model);  Focus on the biotechnology sector;  Some suggestions concerning the model (linear Vs. chain- linked) that better explains the innovation processes in this sector  personal opinions
  • 3. Stephan P. (1996), “The Economics of Science” (http://www.jstor.org/stable/2729500 )  Balconi M., Brusoni S., Orsenigo L. (2008), “In Defence of the Linear Model: An Essay” (http://ftp.unibocconi.it/pub/RePEc/cri/papers/WP216Balconi BrusoniOrsenigo.pdf )  McMillan S.G., Narin F., Deeds D.L., (2000), “An analysis of the critical role of public science in innovation: the case of biotechnology” (http://www.sciencedirect.com/science/article/pii/S00487333 9900030X)
  • 4. The public nature of knowledge and the reward structure of science;  No rivalry, no excludability;  Difficulty for providers to capture the economic returns;  Public research vs. Private research; Main assumption: public research is conducted mainly by universities (basic research) and private research is conducted mainly by firms (applied research) (Balconi, Brusoni and Orsenigo (2008))  Interaction between basic research and applied research.
  • 5. LINEAR MODEL VS. CHAIN-LINKED MODEL  Linear Model:
  • 6. Linear model starts from basic research (mainly in universities) and then the knowledge is transferred to the firms  marketable products;  To do this, firms need to undertake a long and uncertain development activity.
  • 8. Firms want to satisfy the needs or the requests of the market  collaboration with universities;  Linear model is “technology push” while the Chain-Linked model is “market pull”.
  • 9. Balconi, Brusoni and Orsenigo (2008): Pharmaceutical Industry Linear Model;  McMillan, Narin and Deeds (2000): biotechnology and pharmaceutical industries are mainly based on basic science Our interpretation: Linear Model Pharmaceutical Biotechnology Firms Companies Percent of science 79.1% 83.1% references originating in public science Research question: is it always right in every biotechnology’s sector?
  • 10. Example of sub-sectors that seem to be much chain-linked:  Agriculture Industry  Crops that reduce the use of fertilizers  Food Industry  Improved taste or appearance of food Several biotech sub-sectors are mainly “market pull”.
  • 11. In some biotechnology’s fields the innovation processes seem to follow the linear model, in others the chain-linked one, and this depends very much on the intrinsic characteristics of each field. Our goal: some sectors analysis and the relative knowledge transfer.