institutionalism theory is ‘path dependencies.’ All transformation researchers use it,
albeit giving different degrees of attention to the technological, economic, institutional, sociocultural and ecological dimensions that path dependencies combine. So
depending on the camp and also the individual researcher, such path dependencies
include more directly visible political laws and regulations, infrastructural or
technological limitations, market patterns and scientific knowledge, but also consumer behavior, power plays, firm strategies and economic transaction cost considerations (WBGU 2011a: 418–419). Moreover, socio-psychological aspects like
norms, role expectations, lifestyles and self-images or shared beliefs play important
yet less tangible roles (Welzer 2011). Complex system theory would say that path
dependencies harbor important ‘feedback loops’ in that particular system. All of
these usages of path dependencies capture processes within a system that hamper a
change of course. So at least some of them need to be ‘unlocked’ if the problem or
undesirable trend should discontinue.
Path dependencies also form the link between the MLP and the second concept
for explaining transformational change, the s-curve or multiphase concept: path
dependencies behind one particular problem do not necessarily adhere to one of the
levels but might cut across them. The set of path dependencies behind the rebound
effect was one example of this. And each context shows a different, historically
grown setup of path dependencies, which means that one niche proposal or initiative may work in one region but not in another. And here we depart from any
notions of and demands for blueprinting. Even if a solution is doing magic in one
place, this does not mean that replicating it in another will lead to success.
Hence, the starting point of strategic transformative research designs is always
one particular wicked problem in one defined context. After the challenge has been
defined, the system that is relevant for understanding its existence and persistence is
mapped, including aspects or elements from any MLP level if suitable. The results
portray unique system boundaries: constellations with different scope, dynamics,
impulses, agents, and room for maneuver. The next step then lies in developing
ideas on how to intervene in these system constellations so that desired outcomes—
like avoiding the rebound effect—become likely. This is where the multiphase
concept as another key iconography of the transition community comes in. It is
basically a very coarse model of a theory of change for complex systems and shows
at which stages which intentional change initiatives seem promising.
The multiphase concept illustrated in Fig. 2.2 shows that transformational
changes in complex systems do not unfold in an obvious and linear manner where
the dosage of change-input equals that of change-output. Unless they are triggered
by some drastic shocks from neighboring or overarching systems, system transformations require a build-up in which not much is visibly happening before tipping
points are reached, after which a lot of change happens in a short period of time.
After this chaotic and contested phase either a restabilization of the system or its
collapse can follow. When this change pattern is captured in an illustration it
resembles an ‘s’, which is why the multiphase concept is also called the ‘s-curve.’
Sequencing is typically divided into four stages:
24
2 What Political Economy Adds to Transformation Research
albeit giving different degrees of attention to the technological, economic, institutional, sociocultural and ecological dimensions that path dependencies combine. So
depending on the camp and also the individual researcher, such path dependencies
include more directly visible political laws and regulations, infrastructural or
technological limitations, market patterns and scientific knowledge, but also consumer behavior, power plays, firm strategies and economic transaction cost considerations (WBGU 2011a: 418–419). Moreover, socio-psychological aspects like
norms, role expectations, lifestyles and self-images or shared beliefs play important
yet less tangible roles (Welzer 2011). Complex system theory would say that path
dependencies harbor important ‘feedback loops’ in that particular system. All of
these usages of path dependencies capture processes within a system that hamper a
change of course. So at least some of them need to be ‘unlocked’ if the problem or
undesirable trend should discontinue.
Path dependencies also form the link between the MLP and the second concept
for explaining transformational change, the s-curve or multiphase concept: path
dependencies behind one particular problem do not necessarily adhere to one of the
levels but might cut across them. The set of path dependencies behind the rebound
effect was one example of this. And each context shows a different, historically
grown setup of path dependencies, which means that one niche proposal or initiative may work in one region but not in another. And here we depart from any
notions of and demands for blueprinting. Even if a solution is doing magic in one
place, this does not mean that replicating it in another will lead to success.
Hence, the starting point of strategic transformative research designs is always
one particular wicked problem in one defined context. After the challenge has been
defined, the system that is relevant for understanding its existence and persistence is
mapped, including aspects or elements from any MLP level if suitable. The results
portray unique system boundaries: constellations with different scope, dynamics,
impulses, agents, and room for maneuver. The next step then lies in developing
ideas on how to intervene in these system constellations so that desired outcomes—
like avoiding the rebound effect—become likely. This is where the multiphase
concept as another key iconography of the transition community comes in. It is
basically a very coarse model of a theory of change for complex systems and shows
at which stages which intentional change initiatives seem promising.
The multiphase concept illustrated in Fig. 2.2 shows that transformational
changes in complex systems do not unfold in an obvious and linear manner where
the dosage of change-input equals that of change-output. Unless they are triggered
by some drastic shocks from neighboring or overarching systems, system transformations require a build-up in which not much is visibly happening before tipping
points are reached, after which a lot of change happens in a short period of time.
After this chaotic and contested phase either a restabilization of the system or its
collapse can follow. When this change pattern is captured in an illustration it
resembles an ‘s’, which is why the multiphase concept is also called the ‘s-curve.’
Sequencing is typically divided into four stages:
24
2 What Political Economy Adds to Transformation Research