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    <title>Notes on Dosi 1988</title>
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    <h1>Notes on [[dosi_1988]]</h1>

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			Aim
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				(pp. 1121) <q>
					The discussion will aim to identify (a) the main characteristics of the innovative process (b) the factors that are conducive to or hinder the development of new processes of production and new products, and (c) the processes that determine the selection of particular innovations and their effects on industrial structure.
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			Measuring R &amp; D
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				(pp. 1124-1125) <q>
					... however, in addition to formalized rnd, and in many ways complementary to it, a significant amount of innovation and improvements is originated through design improvements, &quot;learning by doing,&quot; and &quot;learning by using&quot;(see ...). Such informal effort is generally embodied in people and organizations (primarily firms) ([references]...), and its cost is hard to trace.
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				(pp. 1126) <q>
					... even in these rather science-based activities and, more so, in other technologies, public knowledge is complementary to more specific and tacit forms of knowledge generated within the innovating units (for evidence ...). for example, in mechanical engineering (e.g., machine tools) an important part ofthe knowledge base consists of tacit knowledge about the performance of previous generations of machines, their typical conditions of use, the productive requirements of users, and so on.	
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			Tacitness of Knowledge and Technology
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				Dosi poses the question as a section title: (pp. 1130) <q>Technology: Freely Available Information or Specific Knowledge</q>
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				Information presented so far suggests that technology is <em>not</em> the same as information. That information is only a subset of technology. (pp. 1131) <q>In each technology there are elements of <em>tacit and specific</em> knowledge that are not and <em>cannot</em> be written down in a &quot;blueprint&quot; form, and cannot, therefore, be entirely diffused either in the form of public or proprietary information</q>
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				As evidence for this: (pp. 1131) <q>It has been found that <em>information</em> about what other firms are doing spreads quite quickly (Edwin Mansfield 1985); however, the ability to produce or replicate innovative results is much more sticky.</q>
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			Determinants of Innovation
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		<p>Section IV: <te:Cite page="1135ff" /></p>
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				Identifies main factors:
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						Technological opportunities: Exogenous science and Specific Learning
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						Appropriability of innovations.
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						Driving forces of technological change (Demand factors): (pp. 1140) <q>The levels and changes in demand (market size and growth, income elasticities of the various products), and the levels and changes in relative prices, in particular the price of labor to the price of machines and also to the price of energy and other influential factors.</q>
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						Inducements factors (demand factors?), patterns of innovation and irreversibility. Path dependence? Improvements tend to not happen all along technological frontier but around the best practice techniquest. Furthermore traditional factor availability arguments (e.g. Habbakuk on labour saving progress) for direction and pace of change are undermined by fact that much tech progress leads to an entire outward shift of entire production posssibility frontier rather than shift within it (that is often save on <em>all</em> factors at once.
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			Appropriability of innovations
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			Various devices for appropriability:
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				patents
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				secrecy
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				lead times
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				costs  and time required for duplication
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				learning-curve effects
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				superior sales and service efforts
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				(pp. 1139) <q>
					In an extreme synthesis, Levin et al. (1984) find that for most industries, &quot;lead times and learning curveadvantages, combined with complementary marketing efforts, appear to be teh principle mechanisms of appropriating returns for product innovations&quot; (p. 33). Learning curves, secrecy and lead times are also major appropriation mechanisms  for process innovations.  Patenting often appears to be a <em>complementary</em> mechanism which however does not seem to be the central one, with some exceptions (e.g. chemicals and pharmaceuticals). Moreover, by comparing the protection of processes and products, one tends to observe that lead times and learning curves are relatively more effective eays of protecting process innovations, while patents are a relatively better protection for product innovations.
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				(pp. 1140) <q>
					.... it must be noticed that the partly tacit nature of innovative knowledge and its characteristics of partial private appropriability makes imitation, as well as innovation, a creative process .... and which is economically expensive - sometimes even more expensive than the original innovation (...[cites] ...) This applies to both patented and non-patented innovations.
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			Interesting
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					We observe that technological progress in a particular area tends to advance down a trajectory. Non-technically this means that we tend to observe improvements in clusters of features with the improvements related in the same way over time (even simpler: improvements look similar over time). Technical version: technological characteristics (+ improvements?) can be seen as some n-dimensional space. Technological progress is described by movement through some very narrowly defined subspace of this. (obviously actual progress lies on a single dimensional subspace - the trajectory parametrised by time. so this claim is more that this subspace has special characteristics (e.g. parametrised in a particularly simple way).
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					Dosi quotes example of aircraft technology: (pp. 1128) <q>technological progress in aircraft technology has followed two quite precise trajectories (one civilian and one military) characterized by log-linear improvements in the trade-offs between horsepower, gross takeoff weight, cruise speed, wing loading, and cruise range ...</q>.
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					So why is this: 
					(pp. 1129) <q>
						Of course, there is no a priori economic reason why one should observe limited clusters of technological characteristics at any one time and ordered trajectories over time. Indeed, given consumers with different preferences and equipment users with different technical requirements, if technology had the malleable attributes of information and if the innovative search were a purely random process, one would tend to observe sorts of &quot;technological indifference curves&quot; at any one time, and over time, random search all the n-dimension characteristics space. Of course, &quot;how different&quot; are consumers and users of goods ....is an empirical question. However relatively wide differences .... cannot be ruled out by either casual empiricism or theoretical arguments. .... Were technologies simply pieces of information (or &quot;recipes&quot;) that could be added, convexly combined, etc., one would also tend to observe an increasingly dispersed variety of technical and performance combinations in actual products and production inputs. Over time this would lead toward the exploration of the entire characteristics space .... It is precisely the paradigmatic cumulative nature of technological knowledge that accounts for the relatively ordered nature of the observed patterns of technological change.
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					But this isn't true about information. Information cannot just be 'combined'. In fact this is a characteristic of all human knowledge. Why? Dosi gives at least one major reason: knowledge is cumulative. 
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				<te:Cite page="1132ff" /> Most rnd has been inhouse. Has not been supplied in the market (as Stigler e.g. hypothesized would happen). This seems to be an example of the Coasian buy or build decision where build has predominated. Why?
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						Contracting issues:
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								if knowledge is tacit then can't contract for it very well.
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								lack of adequate protection for proprietary info
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								possibility of lock-in with research suppliers who can use their power
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								weak incentives for cost performance (though why better in house?)
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								monitoring costs
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						Need to tightly integrate innovation and other parts of production such as manufacture, marketing etc (evidence (e.g. see discussion and citations in <te:Cite refId="kamien_ea_1982" page="58ff" />) innovations that aren't well integrated don't do well - obviously - i.e. technology on own is no good)
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						better information flow inhouse (though this is always true - pertinent question is why is the tradeoff made where it is)
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						to use others innovation still need inhouse expertise to apply it.
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				(pp. 1135) <q>
					Internalization and routinization in the face of the uncertainty and complexity of the innovative process also point to the importance of particular organizational arrangements for the success or failur of individual innovative attempts.
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