Table of Contents
LECTURE 1 ................................................................................................................................................. 2
• HENDERSON, R.M., CLARK, K.B. ............................................................................................................. 2
• VINCENTI, W.G ........................................................................................................................................ 3
• FRENKEN, K. ( .......................................................................................................................................... 3
• ARGOTE, L., EPPLE, D .............................................................................................................................. 8
LECTURE 2 ................................................................................................................................................. 9
• FRENKEN, K. ............................................................................................................................................. 9
LECTURE 3 ............................................................................................................................................... 13
• HALL, B.H .............................................................................................................................................. 13
• HALL, B.H., HELMERS, C., ROGERS, M., SENA, ...................................................................................... 16
• TEECE, D ................................................................................................................................................ 19
LECTURE 4 ............................................................................................................................................... 22
• KLEPPER S. ............................................................................................................................................. 22
• BALDWIN, C., VON HIPPEL, E ................................................................................................................. 23
• FRENKEN, K............................................................................................................................................ 28
LECTURE 5 ............................................................................................................................................... 31
• HIDALGO, C., HAUSMANN, R. ................................................................................................................. 31
• AUTOR, D.H. .......................................................................................................................................... 33
• FRENKEN, K. ........................................................................................................................................... 34
LECTURE 6 ............................................................................................................................................... 38
• BOSCHMA, R.A ....................................................................................................................................... 38
• FLORIDA, R. ............................................................................................................................................ 41
• HALL, P. A., SOSKICE, D......................................................................................................................... 42
• FRENKEN, K............................................................................................................................................ 45
LECTURE 7 ............................................................................................................................................... 47
• BLIND, K. ............................................................................................................................................... 47
• RAINVILLE, A. ........................................................................................................................................ 51
LECTURE 8 ............................................................................................................................................... 53
• MILES, I. ................................................................................................................................................. 53
• DELGADO, M. AND MILLS, K.G .............................................................................................................. 55
1
,Summary literature Economics of Innovation
Lecture 1
• Henderson, R.M., Clark, K.B. (1990). Architectural innovation: The reconfiguration of
existing product technologies and the failure of established firms. Administrative Science
Quarterly 35(1), pp. 9-13.
The traditional categorization of innovation as either incremental or radical is incomplete, it does not
account for the sometimes-disastrous effects on industry incumbents of seemingly minor
improvements in technological products. Incremental innovation introduces relatively minor changes
to the existing product, exploits the potential of the established design, and often reinforces the
dominance of established firms. Radical innovation, in contrast, is based on a different set of
engineering and scientific principles and often opens up whole new markets and potential applications
and can be the basis for the successful entry of new firms or even the redefinition of an industry.
Existing models that rely on the simple distinction between radical and incremental innovation
provide little insight into the reasons why such apparently minor or straightforward innovations
should have such consequences.
Architectural innovation = innovations that change the way in which the components of a product
are linked together, while leaving the core design concepts (and thus the basic knowledge underlying
the components) untouched. The distinction between the product as a system and the product as a set
of components underscores the idea that successful product development requires two types of
knowledge:
1. It requires component knowledge, or knowledge about each of the core design concepts and
the way in which they are implemented in a particular component.
2. It requires architectural knowledge or knowledge about the ways in which the components are
integrated and linked together into a coherent whole.
Types of technological change
The horizontal dimension captures an innovation's impact on components, while the vertical captures
its impact on the linkages between components. This framework is useful because it focuses on the
impact of an innovation on the usefulness of the existing architectural and component knowledge of
the firm.
- Radical innovation: establishes a new dominant design à new set of core design concepts
embodied in components that are linked together in a new architecture.
- Incremental innovation: refines and extends an established design. Improvement occurs in
individual components, but the underlying core design concepts, and the links between them,
remain the same.
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,The essence of an architectural innovation is the reconfiguration of an established system to link
together existing components in a new way. This does not mean that the components themselves are
untouched by architectural innovation. The important point is that the core design concept behind
each component-and the associated scientific and engineering knowledge- remain the same.
For example, for the maker of large, ceiling-mounted room fans, however, the introduction of a
portable fan would be an architectural innovation. While the primary components would be largely
the same (e.g., blade, motor, control system), the architecture of the product would be quite different
may be useful to define radical and incremental innovation. The use of the term architectural
innovation is designed to draw attention to innovations that use many existing core design concepts in
a new architecture and that therefore have a more significant impact on the relationships between
components than on the technologies of the components themselves.
Architectural innovation presents established firms with a more subtle challenge. Much of what the
firm knows is useful and needs to be applied in the new product, but some of what it knows is not
only not useful but may actually handicap the firm. Recognizing what is useful and what is not, and
acquiring and applying new knowledge when necessary, may be quite difficult for an established firm
because of the way knowledge- particularly architectural knowledge- is organized and managed.
• Vincenti, W.G. (1994). Variation—selection in the innovation of the retractable airplane
landing gear: the Northrop ‘anomaly’. Research Policy 23, pp. 575-582.
Variation selection model
This model builds on the epistemological ideas of Campbell (1987) and their initial application to
technical design and development by Constant (1980). As mentioned in the introduction, it sees the
growth of engineering knowledge (in this case, whether one ought to use a retractable or some other
kind of landing gear) in terms of the introduction of candidate variants, followed by selective
retention of those which, on balance, best meet the pertinent requirements. The model takes it as
essential (and unavoidable) that any search for knowledge that is new, i.e. not attained before, must
involve an element of what Campbell calls ‘blindness’ and what I have come to refer to (Vincenti,
1994) as ‘unforesightedness’.
Variation-selection shows up in the landing- gear story in the solution of two kinds of problems,
specific and generic. Individual designers, using variation-selection in some form, make decisions in
the course of solving specific problems. Over time, the design community, through replication of the
same decision by a cumulation of designers, arrives at a variation-selection solution to the generic
problem. Solution of the specific problem is the work of an individual designer (or design team). In
the present instance, the variation-selection process led ultimately to replacement of the fixed landing
gear by the new retractable gear. This, however, is not always the case, even when much is logically
anticipated of the new technology.
• Frenken, K. (2006). Innovation, Evolution and Complexity Theory. Cheltenham: Edward
Elgar, pp. 10-38.
The evolution of a complex system is the joint effect of environmental demands and internal
constraints resulting in rather rigid trajectories of incremental change. As-if justification = claims that
no matter the actual decision algorithms employed by real decision makers, those who make a
decision closest to the one a profit- or utility-maximizing agent would make, will eventually prevail
under market selection. It is often for this reason that many neoclassical economists still adhere to the
use of models of maximizing agents.
Competitive markets do not ensure that the optimal technology will be among the set of technologies
explored, because markets only select on available variety not on possible varieties. To understand the
process of technological development, then, one is in need of a theory of search that takes into
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, account the bounded rationality of agents and a theory of evolution that takes into account the path
dependent nature of successive rounds of search and selection.
Technology landscapes
In a nutshell, optimising is simply too costly because it takes too much time. For this reason agents
resort to heuristic procedures to find reasonable solutions in short time. Selection, then, takes place on
the basis of the relative success of the solution found by each agent.
The NK-model
Complexity as epistasis
Epistatic structures in complex systems are not refined to biological organisms but are also present in
artefacts. Artefacts = man-made systems made up of elements that collectively attain one or a number
of goals. The complexity in designing an artefact is caused by the interdependencies in the working of
its elements. Only some combinations between elements fit well together in the sense that they are
complementary. Substituting one of these elements by a new element may improve some of the
functions an artefact is expected to provide, yet generally produces negative by-effects on other
functions, which may imply a loss in overall functioning of the artefact as a whole.
The existence of epistatic relations between a system’s elements thus implies that the performance of
elements can only be fully understood from a priori knowledge of the workings of individual
elements. The strategy of evaluating all possible combinations between elements is called global trial-
and-error or exhaustive search. Contrary to complex systems, simple systems are characterised by
independence between its elements and can be optimised by local trial-and-error. As epistasis is
absent in the latter case, each element can be optimized locally i.e. independently of the state of other
elements. The problem of finding the right combination of all ten elements can be decomposed in ten
sub-problems, which can be solved independently. Combinatorial complexity vanishes and the
problem becomes feasible to handle.
Combinatorial design spaces
An stands for the number of possible states of element n. The size of the space is then given by:
Technologies can be described as consisting of N elements where An stands for the number of states of
element n. In design theory, the N-dimensional possibility space S is called the design space of a
technology. The design space of a technology describes all possible combinations of alleles of its
elements.
Innovation can then be understood as a walk through design space. For example, by replacing the
steam engine by a gasoline engine, the designer moves in design space from string 000 to string 100
(as they were coded). In this view, innovation is formally equivalent to a mutation in biology
(changing a gene from 0 into 1 or vice versa).
The combinatorial nature of the design space of a system requires that elements are orthogonal to one
another as they represent dimensions. Therefore, an element of a system cannot correspond with a
state of another element in the same system.
Kauffman’s NK-model
The NK- model is a tool to simulate the effects of interdependencies on the fitness of complex
systems. Dependencies between the functioning of elements in a complex system are called epistatic
relations. An epistatic relation from one element to another element implies that when the state of one
element changes, this change affects both the functioning of this element itself and the functioning of
the other element(s) that it epistatically affects. The ensemble of epistatic relations among elements in
a technological system is called a technology’s architecture. For each pair of elements in a system,
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