Netherlands, Utrecht

Measuring and modeling dynamics in innovation systems

when 17 August 2015 - 21 August 2015
duration 1 week
credits 3 EC
fee EUR 600

The concept of the innovation system stresses that the flow of knowledge between people, firms and other organizations is key to innovation It stresses the interaction between actors in order to turn an idea into a successful process, product or service in the marketplace.

Arguably, many innovation systems are characterized by flaws that hamper the development and diffusion of innovations. These flaws are often labeled as system failures or system problems. Intelligent and evidence based innovation policy, therefore, evaluates how innovation systems are functioning, attempts to create insight into the system’s problems and develops policies and strategies accordingly.
Over the last decades the innovation system concept has attracted scholarly attention and has become a widely accepted starting point in understanding the innovation process. More recently emphasis was placed on understanding the dynamics of innovation systems.

Many studies on the topic have limited themselves to a descriptive understanding of the innovation system. The idea is that an innovation system consists of multiple interacting components, such as firms who supply innovations, the demand for innovation, knowledge infrastructure, and institutions that support or hamper innovation. The interaction between the components is central in innovation studies. For example, the supply side is often conceptualized as to create variety in technology, while the demand side acts as a selector of new technologies.
Each of these components has been studied by different scientific disciplines and traditions. The supply side, for example, is studied extensively by scholars in management, organization studies, and industrial economics. The demand side is largely dominated by scholars in marketing and consumer psychology. Therefore, understanding the innovation system as a dynamic whole is a multi-disciplinary effort in which engineering knowledge about technologies is combined with a range of disciplinary social science approaches. For this reason studying innovation system dynamics is challenging.

This course offers an introduction to analyzing innovation systems dynamics, and to analyzing the different components that make-up the innovation system. It provides a set of tools to scientifically measure and model dynamics in each component of the innovation system and the system as a whole.

The goal is to provide a comprehensive overview of the most important theories and methods to study the innovation system. Further, students will use these to explain dynamics in innovation systems, thus enriching their theoretical basis. The course contributes to formulating theoretical explanations for findings on a system level, and it prevents ‘rediscovering’ phenomena that are already known within the disciplinary traditions. Finally, it enriches insights about the effects of systemic policy instruments on different components of the innovation systems.

The course is at an introductory level and therefore beneficial to researchers at the beginning of their career (e.g. recently started PhD-students, junior researchers, young professional researchers). It lays a solid theoretical and methodological foundation for students that wish to participate in advanced courses about specific topics.

Course leader

Frank van Rijnsoever

Target group

The primary target audience consists of academic researchers in the early stages of their career, such as PhD students (primarily 1st and 2nd year), junior researchers or researchers that recently received their PhD, but that are new to the field. Further, we are open to receiving a limited number of non-academic researchers that are interested in the topic. In total we hope to welcome 30 participants.

Course aim

After the course participants have accomplished the following objectives. They:
• Become acquainted with the use of models in the social sciences.
• Become acquainted with theories about dynamics in the innovation system as whole and dominant theories on its separate components.
• Are able to apply these theories to explain specific innovation problems they encounter in their own research projects.
• Have an overview of possibilities to test theories by measuring and modeling empirical data.
• Are able to interpret the outcomes of these models in terms of theory and policy.

More concretely this means that after the course have learned a number of skills:
• Students have a broad understanding of theories in different components of the innovation systems. This enables them to combine insights from different traditions into new research ideas. Further, being aware of different theories is helpful for future collaboration with other scientists.
• Students are able to read, understand and critically assess scientific studies that are conducted in the field of innovation systems.
• Students have a basic level of knowledge that allows them expand their knowledge on the topic by themselves or though other courses.

Credits info

3 EC
+ certificate of attendance

Fee info

EUR 600: Including housing

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