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A complex systems methodology to transition management

A complex systems methodology to transition management. DIMETIC, Maastricht, 15-19 Oct 2007 Koen Frenken (k.frenken@geo.uu.nl). Structure of the talk. Some remarks on NK-models The power of decomposition and the example of the Wright Brothers inventing the airplane

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A complex systems methodology to transition management

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  1. A complex systems methodology to transition management DIMETIC, Maastricht, 15-19 Oct 2007 Koen Frenken (k.frenken@geo.uu.nl)

  2. Structure of the talk • Some remarks on NK-models • The power of decomposition and the example of the Wright Brothers inventing the airplane • A complex systems methodology to transition management with an application to future sustainable car technologies

  3. Properties of NK • N stands for the number of components in a system • K stands for the number of interdependencies between components • The number of possible strings, called design space or state space or possibility space: S = 2N • The number of local optima for K is maximum can be derived analytically # = 2N/(1+ N) • The fitness of local optima tends towards the mean for increasing K and N (complexity catastrophe) • Fitness of the one global optimum increases for increasing K and N

  4. Some thoughts • Henderson/Clark classification • Incremental • Modular • Architectural • Radical • Search strategies • Design space search • Function space search • Decomposability and search [Next slides] K. Frenken (2006) Innovation, Evolution and Complexity Theory (Edward Elgar)

  5. Finding the global optimum • Given that local optima exists, finding the global optimum generally requires ‘exhaustive search’ involving 2N trials • Except for decomposable systems • If complexity refers to problem-solving difficulty, K is not always a reliable complexity indicator

  6. Testing the glider subsystem

  7. Testing the system as a whole

  8. ‘Doing it Wright’

  9. A complex systems methodology to transition management Remainder is based on joint work with: Malte Schwoon (Max Planck Institute Hamburg) Floortje Alkemade (Utrecht University) Marko Hekkert (Utrecht University) Paper available at DRUID summer conference 2007 and via DIMETIC website

  10. Objective • To develop an empirically-based policy framework for technology assessment • that takes into account path dependence in the design of complex technologies

  11. Technological transition “A technological transition is the substitution of a complex technological system by an alternative system”

  12. Complex systems theory • Technological systems contain many interdependent subsystems • Changes in one part of the system create unexpected effects in other parts • System evolution is path dependent in that a choice at one moment in time affects the likelihood of subsequent choices

  13. Flexibility of initial step • Design flexibility (how many optima can be reached after the initial step) • Path flexibility (how many routes exist towards an optimum) • Time flexibility (how many transition steps are involved in the transition)

  14. Assumptions • Local search • Up-hill moves only

  15. Properties • 7×2×7×9×3 = 2646 possible designs • Majority of designs has lower fitness than current system • Many neighbouring designs have similar fitness values creating plateaus in the fitness landscape

  16. Conclusions • Complex patterns of mapping can be traced empirically by collecting comprehensive data on design space and fitness values • Choice of subsystem innovation affects flexibility in many respects • Applicable to many technologies • Assumptions about search behaviour and number of agents should be qualified

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