Innovation System Functions Analysis
Also known as: Functions of innovation systems, Seven functions approach, Event-history innovation analysis
Functions of Innovation Systems analysis explains technological change by examining how well an innovation system performs seven key functions—entrepreneurial activities, knowledge development, knowledge diffusion, guidance of the search, market formation, resource mobilisation, and the creation of legitimacy. Associated with Hekkert, Suurs, and colleagues at Utrecht, the approach operationalises these functions through event-history analysis: a chronological dataset of innovation events is coded, functional performance is tracked over time, and the reinforcing feedback loops—the 'motors' of cumulative causation—that drive a system's rise or stagnation are identified.
Key highlights
- Makes innovation-system dynamics concrete and traceable by grounding them in a dated, coded record of real events.
- Captures temporal dynamics and feedback explicitly, revealing the cumulative-causation motors that static frameworks miss.
- Provides a structured, comparable set of seven functions that supports cross-case and cross-country comparison.
- Links diagnosis directly to intervention by showing which functions and feedbacks are weak and where policy could ignite a motor.
- Has a substantial empirical track record across renewable-energy and other emerging-technology cases.
Intuition
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How it works
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When to use it
Use functions analysis when you want a fine-grained, dynamic explanation of how a technological innovation system formed or stalled over time, and when rich chronological source material—especially trade press—is available to build an event history. It suits longitudinal single-technology case studies and comparisons of the same technology across countries or periods. The approach assumes that the seven functions capture the essential processes of system development and that events can be reliably coded to them. It is less appropriate when sources are too thin to construct a credible event history, when a static structural snapshot suffices, or when the question concerns whole-system regime change rather than the dynamics of one technology.
Strengths & limitations
- Makes innovation-system dynamics concrete and traceable by grounding them in a dated, coded record of real events.
- Captures temporal dynamics and feedback explicitly, revealing the cumulative-causation motors that static frameworks miss.
- Provides a structured, comparable set of seven functions that supports cross-case and cross-country comparison.
- Links diagnosis directly to intervention by showing which functions and feedbacks are weak and where policy could ignite a motor.
- Has a substantial empirical track record across renewable-energy and other emerging-technology cases.
- Building the event history is labour-intensive and depends heavily on the coverage and bias of the available sources, especially trade press.
- Coding events to functions and scoring their contributions involves judgement, raising inter-coder reliability and comparability concerns.
- The seven functions overlap and their boundaries are contestable, so different analysts may attribute the same event differently.
- Its single-technology, function-internal focus gives limited purchase on the surrounding landscape, regime, and broader political economy.
Common pitfalls
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Applications
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Frequently asked
What are the seven functions of innovation systems?
F1 entrepreneurial activities (experiments and ventures that turn knowledge into business opportunities); F2 knowledge development (learning by searching and by doing); F3 knowledge diffusion through networks; F4 guidance of the search (the articulation of expectations and visions that direct resources); F5 market formation (creating space and demand for the new technology); F6 resource mobilisation (financial, human, and physical resources); and F7 creation of legitimacy and counteraction of resistance to change. The approach asks how well each is fulfilled and how they reinforce one another.
What is a 'motor of innovation'?
A motor of innovation is a recurring pattern of cumulative causation—a self-reinforcing feedback loop among the seven functions—that drives a system through a phase of development. Suurs and Hekkert describe several, including a science and technology push motor (knowledge development driving the system), an entrepreneurial motor (ventures and market formation reinforcing each other), a system-building motor (actors deliberately constructing networks and institutions), and a market motor (demand pulling the system forward). Diagnosing which motor is running explains the system's trajectory.
How does this differ from the Bergek et al. TIS scheme?
Both use the functions vocabulary, but they emphasise different things. The Bergek et al. Technological Innovation Systems scheme is a broader analytic frame that starts from structural components, assesses the functional pattern, compares achieved with desired functionality, and diagnoses inducement and blocking mechanisms for policy. The functions-of-innovation-systems approach here concentrates on the seven functions operationalised through event-history analysis and on identifying cumulative-causation motors over time. The two are complementary and often combined; this library cross-links them.
Sources
- 1.Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: a new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413-432.
- 2.Suurs, R. A. A., & Hekkert, M. P. (2009). Cumulative causation in the formation of a technological innovation system: the case of biofuels in the Netherlands. Technological Forecasting and Social Change, 76(8), 1003-1020.
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Cite this page
ScholarGate. (2026, June 22). Innovation System Functions Analysis. ScholarGate. https://scholargate.app/science-technology-studies/innovation-system-functions-analysis