Unruh 2000 – Understanding Carbon Lock-in
Problem Lock-in of technological and institutional co-evolution driven by path-
dependent increasing returns to scale
Method Exploration of interlocking technological, institutional and social forces
that can create policy inertia towards the mitigation of global climate
change
Aim It is therefore hoped that this exploration will illustrate a set of issues
that has been underappreciated in climate change policy debates
Deliver conceptual framework for carbon lock-in
Key concept Techno-institutional complex; carbon lock-in
Theories Path dependency (lock-in; increasing-returns)
Explore issues of lock-in towards a framework of interaction between technologies,
organisations, and institutions:
- Technological lock-in (LTS; RBV; IS)
o Technological systems: emphasizes positive feedback economics in creating
lock-in among large systems of interrelated technologies
- Institutional lock-in (neo-institutional)
o Role of private institutions in enhancing technological lock-in
o Examination of the impact created by formal governmental institutions
Barriers to the diffusion of carbon-saving technologies
Climate change results from consumer demand adoption of non-fossil fuel energy is both a
technological (bottom-up) and an economic (top-down) challenge: cost debate
Bottom-up studies find technology reduces carbon emission and lowers cost. If this is so, the
question arises “why don't carbon-saving technologies and practices diffuse faster if they exist,
save money and reduce climate impacts?”. Top-down models point toward technologies
cannot be cost saving when the total, economy-wide costs of their adoption are considered
Evidence for energy-saving opportunities exist but there are barriers to adoption
Technological systems
Fossil fuel energy is a large technological system: inter-related components connected in a
network or infrastructure that includes physical, social and informational elements.
Technological systems interconnected: overarch complex technological system; overarch
architecturally linked technological components/artifacts multilevel (levels of analysis)
1
, The evolution of technological systems
After era of competition a dominant design emerges, and a shift occurs from product
(Schumpeterian) innovation to incremental process (Usherian) improvement. Inferior design
can become dominant design over superior design in a path-dependent process due to
strategy, timing, historical circumstances. S-curve visualises increasing returns process:
Traditional economics focus on upper (decreasing returns) half: long-run equilibrium returns.
However, lower (increasing returns) half can create indeterminacy in competitive outcome
Four classes of increasing returns (positive feedback economics):
- Scale economies: production cost decline as fixed costs are spread over increasing
production volume
- Learning economies: reduce cost and improve performance as specialised skills and
knowledge accumulate through production and market experience
- Adaptive expectations: increasing adoptions reduces uncertainty, both users and
producers become increasingly confident about quality, performance, and permanence
- Network economies: emerge due to the interrelations among technical systems
After industry shake-out surviving oligopolistic firms shift from product to process
innovation and specialised knowledge development (market demand; complementary assets)
Logic of specialisation: continued refinement of dominant design can define a technological
trajectory along which firms incrementally develop know-how repeat incremental
investments commit firm to dominant design trajectory and create lock-in at firm level
incumbents are rarely source of radical innovations: core competencies become core rigidities
2
Problem Lock-in of technological and institutional co-evolution driven by path-
dependent increasing returns to scale
Method Exploration of interlocking technological, institutional and social forces
that can create policy inertia towards the mitigation of global climate
change
Aim It is therefore hoped that this exploration will illustrate a set of issues
that has been underappreciated in climate change policy debates
Deliver conceptual framework for carbon lock-in
Key concept Techno-institutional complex; carbon lock-in
Theories Path dependency (lock-in; increasing-returns)
Explore issues of lock-in towards a framework of interaction between technologies,
organisations, and institutions:
- Technological lock-in (LTS; RBV; IS)
o Technological systems: emphasizes positive feedback economics in creating
lock-in among large systems of interrelated technologies
- Institutional lock-in (neo-institutional)
o Role of private institutions in enhancing technological lock-in
o Examination of the impact created by formal governmental institutions
Barriers to the diffusion of carbon-saving technologies
Climate change results from consumer demand adoption of non-fossil fuel energy is both a
technological (bottom-up) and an economic (top-down) challenge: cost debate
Bottom-up studies find technology reduces carbon emission and lowers cost. If this is so, the
question arises “why don't carbon-saving technologies and practices diffuse faster if they exist,
save money and reduce climate impacts?”. Top-down models point toward technologies
cannot be cost saving when the total, economy-wide costs of their adoption are considered
Evidence for energy-saving opportunities exist but there are barriers to adoption
Technological systems
Fossil fuel energy is a large technological system: inter-related components connected in a
network or infrastructure that includes physical, social and informational elements.
Technological systems interconnected: overarch complex technological system; overarch
architecturally linked technological components/artifacts multilevel (levels of analysis)
1
, The evolution of technological systems
After era of competition a dominant design emerges, and a shift occurs from product
(Schumpeterian) innovation to incremental process (Usherian) improvement. Inferior design
can become dominant design over superior design in a path-dependent process due to
strategy, timing, historical circumstances. S-curve visualises increasing returns process:
Traditional economics focus on upper (decreasing returns) half: long-run equilibrium returns.
However, lower (increasing returns) half can create indeterminacy in competitive outcome
Four classes of increasing returns (positive feedback economics):
- Scale economies: production cost decline as fixed costs are spread over increasing
production volume
- Learning economies: reduce cost and improve performance as specialised skills and
knowledge accumulate through production and market experience
- Adaptive expectations: increasing adoptions reduces uncertainty, both users and
producers become increasingly confident about quality, performance, and permanence
- Network economies: emerge due to the interrelations among technical systems
After industry shake-out surviving oligopolistic firms shift from product to process
innovation and specialised knowledge development (market demand; complementary assets)
Logic of specialisation: continued refinement of dominant design can define a technological
trajectory along which firms incrementally develop know-how repeat incremental
investments commit firm to dominant design trajectory and create lock-in at firm level
incumbents are rarely source of radical innovations: core competencies become core rigidities
2
