Abstract
This dissertation aims to explore the effects of public research funds on innovation in life sciences
by elaborating an agent-based model of a regional life sciences innovation system. Life sciences
are a research-intensive field and though have a major impact on economic growth. Industrial and
scientific organisations operate in a highly dynamic environment characterised by fast-expanding
scientific knowledge and scattered expertise, and the ability to create innovations is crucial for the
competitiveness of firms. In general, organisations operate under high uncertainty, and, in order to
keep pace with innovation, they engage in research networks. The demand for external knowledge
and a high degree of tacitness lead the agents to interdisciplinary cooperation with regional and
extra-regional partners, facilitating different kinds of knowledge exchange. Moreover, the
interactions within collaboration networks provoke feedback loops on the agents´ behaviour and
strategies, thus generating non-linear dynamics and evoking additional unpredictability.
Interdependencies among agents are manifold, fostering dynamics and complexity in the system.
Extending previous models of innovation networks, this specific model serves as a tool for policy
makers to explore potential future impacts of different public research funding mixes. In order to
improve the credibility and usability of the simulation findings, a modelling strategy is adopted that
accounts for a high degree of empirical detail in the spirit of history-friendly modelling. Empirical
calibration and testing is provided by detailed agent-level data on research activities, innovation
output and performance of life sciences organisations in the innovation system of the Vienna
Region during the period 1999 to 2010.
Original language | English |
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Award date | 1 Jun 2012 |
Publication status | Published - 2012 |
Research Field
- Former Research Field - Innovation Systems and Policy