White Spaces Innovation in Sweden - Innovation policy for ... - Vinnova

WHITE SPACES INNOVATION IN SWEDENpaths are downhill, i.e. to lower fitness) and valleys (regions from which most pathslead uphill). A fitness landscape with many local peaks surrounded by deep valleys iscalled rugged. The Dolomites is a good illustration of the topology.A useful way of visualizing this is as ontogenetic landscapes depicting a “series ofchanges of relative stability and instability” over time (Thelen & Smith, 1994). Figure 2.If a system accessed every point or region in change over time with the same frequencyas every other (that is, randomly), its ontogenetic landscape would be smooth and flat.A completely flat, smooth initial landscape would portray an object with no propensitiesor dispositions; that is, with no attractors. It would describe a “system” with no identity,a logical impossibility. The deeper the valley, the greater the propensity of its beingvisited and the stronger the entrainment that its attractor represents.Ontogenetic landscapes are constantly modified, dynamical portraits of the interactionsbetween a system and its environment over time: they capture, in short, a timelapseportrait of individual systems. Attractors embody the system‟s current controlparameters (its self-organized controls), which have been constructed and continue to bemodified as a result of the persistent interactions between the dynamical system and itsenvironment.Attractors can be of several kinds. Of special interest for our purposes are thosecalled strange attractors. All attractors represent characteristic behaviours or states thattend to draw the system toward themselves, but strange attractors are “thick” (Juarrero,2002) allowing individual behaviours to fluctuate so widely that even though capturedby the attractor´s basin they appear unique. Strange attractors describe ordered globalpatterns with such a high degree of local fluctuations, that is, that individual trajectoriesappear random. Complex adaptive systems are often characterized by strange attractors.The strange attractors of seemingly “chaotic” phenomena are therefore often not chaoticat all. Such intricate behaviour patterns are evidence of highly complex dynamic organisation.This is essential if innovation processes are to be thoroughly understood as „recombinations‟of knowledge, new and old.Quantitative research has articulated the strange attractors that shape a variety of dynamicalhuman systems. Such quantitative analysis requires that the systems incorporatea small number of deterministic variables (dimensions). If the dimensionality of thesystem is too high (the commonly-used limit is eight variables), the system is consideredto be random because the pattern cannot be discerned by current manipulativepractices and analytical algorithms. Qualitatively, however, the strange attractor hasbeen used as a metaphor to describe highly complex, but patterned, behavior in humansystems. Whenever the behavior of the system is bounded, includes infinite freedomwithin the bounds, and generates coherent patterns over time, the human system can bemetaphorically described as a strange attractor regime. Examples of human systemaspects that fit this qualitative description include organizational culture, patterns ofprofessional practice, or the behaviors of firms within a given industry. In each case,29