Proceedings of the 12th European Conference on Knowledge ...

Francesco Calza, Rossella Canestrino and Chiara Cannavale
Donor’s
intentionality
High
Low
Fruitless systems
Brazil, Philippines, Egypt
Never‐born systems
Hungary, Turkey, Greece,
Morocco, Italy
Low
R&D
Investments
Receiver’s inclination
Figure 2: The drivers <strong>of</strong> innovation spreading: A country perspective
5. Conclusions
Milieu innovateur
Denmark, Finland,
Sweden, Germany
“Catching up” systems
China, France, New
Zeland
The capability to innovate can be rightly considered as <strong>the</strong> main source <strong>of</strong> competitive advantage,
both for firms and countries. Because <strong>of</strong> <strong>the</strong> increasing competition and <strong>the</strong> high level <strong>of</strong>
environmental turbulence, firms have to fasten in developing innovation and in deriving pr<strong>of</strong>its from its
spreading. Above all for territories, <strong>the</strong> spreading <strong>of</strong> innovation is a unique guarantee <strong>of</strong> welfare and
productivity.
In order to better understand <strong>the</strong> nature <strong>of</strong> innovation spreading and it functioning, our research has
been focused on <strong>the</strong> players <strong>of</strong> <strong>the</strong> process more than on mechanism. We are interested in
understanding <strong>the</strong> conditions upon which an effective knowledge transfer may develop, thus fostering
innovation systems born. As we noted above, knowledge transfer is a very complex and <strong>of</strong>ten
misunderstood process. Its effectiveness depends not only on <strong>the</strong> existence <strong>of</strong> knowledge “casual
ambiguity”, but also on <strong>the</strong> willingness <strong>of</strong> <strong>the</strong> involved parties to transfer and acquire knowledge. Both
<strong>the</strong> propensity to transfer and to acquire new knowledge is culturally embedded; as a consequence
innovation spreading is affected by culture, too.
As far as many contributions exist on <strong>the</strong> linkage between culture and innovation, nobody has defined
cultural dimensions, which could speed up, or avoid, innovation widespread. Given that innovation
spreading depends on two dimensions: donor’s intentionality and receiver’s inclination to learn, our
research aimed to highlight <strong>the</strong> cultural dimensions, which mainly affect this process. We focused on
two dimensions <strong>of</strong> <strong>the</strong> Globe project: Future Orientation, and Uncertainty Avoidance.
Future Orientation impels people to plan and to consider long terms benefits more important than <strong>the</strong>
short terms ones.
Uncertainty avoidance leads people to refuse ambiguity. It is positively related to learning, since
people used to consider knowledge as a way to reduce <strong>the</strong> uncertainty <strong>of</strong> what <strong>the</strong>y do not know, as
well as <strong>the</strong> better way for managing risks.
We hypo<strong>the</strong>sized a positive relationship between future orientation and donor’s intentionality, on one
side, and between uncertainty avoidance and receiver’s inclination to learn from <strong>the</strong> donor, on <strong>the</strong>
o<strong>the</strong>r.
Crossing donor’s intentionality and receiver’s inclination to learn, we obtain four kinds <strong>of</strong> innovation
systems. After developed our <strong>the</strong>oretical model, we used <strong>the</strong> Globe country classification in order to
identify those countries that show a high (or low) donor intentionality to transfer knowledge and which
ones present a high (or low) propensity <strong>of</strong> local players to accept knowledge. After considering <strong>the</strong>
cultural characteristics <strong>of</strong> <strong>the</strong> selected countries, and <strong>the</strong>ir impact on <strong>the</strong> effectiveness <strong>of</strong> local
knowledge transfer, we used <strong>the</strong>m for giving an empirical support to our <strong>the</strong>oretical model. Each
country has been putted into one <strong>of</strong> <strong>the</strong> innovative situation presented into our model.
The validity <strong>of</strong> our choice has been <strong>the</strong>n verified by considering <strong>the</strong> level <strong>of</strong> innovation for each <strong>of</strong> <strong>the</strong>
mentioned countries. We particularly referred to <strong>European</strong> Union sources, and Eurostat data reported
into <strong>the</strong> “<strong>European</strong> Innovation Scoreboard 2008. Competitive Analysis <strong>of</strong> innovation performance”.
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High