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Technological trajectories
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TECHNOLOGICAL TRAJECTORIES Leonardo Biondi and Riccardo Galli
The issue of technological trajectories is discussed with reference to the mechanism of technological evolution. It is shown how the process of innovation tends to follow a general prohibitive-permissive rule, leading to continuous improvements in one or more aspects of performance which is appreciated by users. This fact generates technological sequences according to preferential paths, which can be considered as trajectories. As examples, a few paths have been identified, such as market segmentation, product customization, cost reduction, reduction of resource use (time, space, energy, materials), etc. The constraints on and possibilities of technological forecasting are discussed in relation to the existence of trajectories.
A number of authors have found empirical evidence that technological progress follows preferential paths. The term ‘natural trajectories’ was certain aspects of technology, coined by Nelson and Winter ’ to describe such as the exploitation of scale economies and the mechanization of processes. The concept was later taken up by Dosi,2 who pointed out that contains strong prescriptions as to which each ‘technological paradigm’ directions change must take and which must be rejected. Technological paradigms have a powerful exclusionary effect: efforts and imagination are focused in fairly precise directions, but remain ‘blind’ to other technological possibilities. These authors thus recognize the existence of basic trends in technology, but consider them specific to each paradigm. The purpose of this article is to identify general rules of technological development underlying those which are specific to any one paradigm. The evolution of technology is determined by the periodic appearance of innovations-pulled by the market or pushed by new knowledgecounterbalanced by the symmetrical elimination of earlier innovations (or restriction of their range of application). While such eliminations are the result of rational human decisions based on costs and benefits, the appear-
Leonardo Biondi is a management consultant, Milan, and Riccardo Galli is at the University of Milan. They can be contacted at FAST, p R. Morandi, 2-20121 Milan, Italy (Tel: 39 2 76006260; Fax: 39 2 783126). This article is based on a previous text, ‘Alla ricerca di una legge dell’evoluzione tecnologica’, L’Impresa-Rivista italiana di management, 33(6), December 1991, pages 136-144.
0016-3287/060580-13
@ 1992 Butterworth-Heinemann
Ltd
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ante of novelties depends partly on factors beyond human will. The a priori possibifities in this connectian are two: (a) The genesis of ~nnuvat~~~ is purely casuaf; that is, the innovations which have appeared to date might have come forth in any era and with any frequency, and might have had different characteristics and numbers. In this case, technological forecasting would be impossible, and there would be no recognizable trajectory. The ways in which innovations have historica~fy appeared (their discontinuous concentration in certain eras, the appearance of preferential paths, the importance of market demand for innovation) argue against this thesis. fb) The genesis of innovation is affected to some extent by cau~~~~~~;that is, by human decisions. tn this case, both technological forecasting and the identification of trajectories are possible. This means identifying factors correlated to the characteristics attributed to j~novat~on~ and finding the continuous or discontinuous trend they (or their derivatives) take over time. In this second case, we again have two possibilities: (b 3) The genesis of innovation is purdy caud; in this case we woutd expect a proscriptive faw of technological evolution (like the law of heat transmission); that is, it would exhaustively state what must happen in given circumstances. (b 2) The genesis of in~~vatj~n is ~~~~~~ caausal and ~~r~~y casuaf; in this case the relevant taw is prohibitive-permissive (like the second law of thermodynamics~. This type of law states, in general and fur all contexts, that certain phenomena with certain characteristics are untikely to occur, whiie other phenomena may appear, each with equal probability. The fundamental laws of nature are of this second type They then translate into prescriptive laws, because of the presence of constraints expressed in their formulae. If we wish to use such a law, we must know the values of its constraints. If our knowledge of its constraints is only statistical, a prohibitive-permissive law expresses probabiiistic outcomes for the phenomena it allows. If we are only interested in the average outcome in a great number of cases, the prohjbitiv~-permissive law appears to be prescriptive, and its effects are in fact deterministic (Eke those of the second law of thermodynamics). The purpose of this articte is to verify the existence of temporal correlations of techno~~g~ca~ ~nnuvat~ons to given characteristics. Tu this end, we may start with the definitions of severai terms that will be used later on.
Technology is an ensemble of knowledge, practical and theoretical (but susceptible of application), including what is embodied in tools and equipment. Process means a way to satisfy, or help to satisfy, a human need. ~nffo~~~~on means a process, put into practice, that differs from its predecessors. In every process we can d~stjngu~sh the 9ua~~~~~~~~easpect of the
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service rendered and the qualitative aspect expressed in terms of a characteristic set of performances appreciated by users. For instance, the ‘quality’ of a vehicle depends on the values of factors such as roominess, image, speed, fuel consumption, price, and so forth. Performance can be expressed in terms of a continuous sequence of values (eg price or speed) or of discontinuous levels (eg black-and-white or colour TV screen). Processes that have the same set of performances can be ordered in an increasing series of overall quality levels. When a process contains an extra performance, in addition to a certain set, its overall ‘quality’ will be greater and may give rise to a new homogeneous line of processes. Processes are manifested in equipment (which can even be intangible, like a computer program) and their operation. A piece of equipment is qualified by the level of its performances, by its power (quantity of performance over a given unit of time), by the capital cost and by its lifetime. Its operation requires a cost over the unit of time. From these data we can find the capital cost per unit of performance, and the unit cost of operation. The total lifecycle cost of any process is the sum of its capital cost and all the operating costs incurred during its lifetime; its annual unit cost is found by dividing its life cycle cost by the number of years of its lifetime. A valid process is one which has the lowest total annual cost of all those with equivalent performances. Invalid processes eventually disappear from the current body of technology and become irrelevant in practice. It should be noted, however, that the approach taken in this article is perforce simplified. The choice of a process is a complicated affair in which both rational factors (comparative technical and financial assessments) and symbolic values, tastes etc) play their irrational factors (image, customs, part. The concept of the validity of a process is not absolute; the appreciation of a process’s various performances can vary over time and space. This explains why some older technologies may be taken up again, why market niches remain for some obsolete technologies, and why markets can be differentiated according to geography, age of users, social classes etc. Valid processes of different quality co-exist and share the market. The market share of any process consists of the fraction of buyers who consider its quality more cost-effective than that of its rivals. A small or even inexistent market share is not sufficient reason to exclude a process from the current body of technology (though it could well exclude it from actual use in production), because there may be reasons that make it worthwhile to wait for a drop in costs or an increase in the appreciation of its quality, and accordingly an increase in its market share.
Working
hypotheses
We now formulate some hypotheses from which to draw indications of general trends in the evolution of technology. We give priority to the above-defined characteristics of ‘quality’ (ie a set of performance criteria appreciated by users) and annual unit cost (which we shall abbreviate to ‘cost’). This is a discretionary choice, but justified by the fact that these are the elements by which we judge the validity of any process. An enormous amount of equipment (in the sense indicated above) can
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be conceived to serve any particular purpose, but only a tiny fraction will provide what we judge to be valid quality, and the probability of our stumbling on a piece of equipment through random research (serendipity) is extremely low. Let us now suppose that: o ‘quality’ is expressed in terms of a set of performances appreciated by users (in a vehicle, for instance, these would be weight, speed, size, fuel economy, price etc); * overall ‘quality’ is related to the number and level of such features; l the above sets of performance criteria are similar enough for us to gauge intuitively and seek, albeit with difficulty, other higher-quality configurations of the same sets of performance criteria; and for it to be assumed that their similarity decreases with their distance from the starting point; such as throwing a stone, using a 0 some common poor-quality ‘processes’, sharpened stick, or using a natural cave for shelter, were discovered by chance, albeit after many attempts over long periods of time. This set of hypotheses could explain the evolution of technology; that is, the transition from a technology of a particular quality level to one of higher level. Such transitions can occur only with contiguous orders of quality; studded with difficulties, they proceed step by step, each built on the information contained in the previous one. In practical terms, this model corresponds to the well known concepts of ‘lifecycle of technology’ and ‘learning curve’.3 This model has the advantage of reflecting a particular characteristic of technological evolution: since technical knowledge is cumulative, evolution proceeds by increasing segregation of step-by-step results. While this is the usual form of technological evolution, it naturally does not preclude the rarer eventuality of more radical progress achieved through ‘technological discontinuity’. From the foregoing we can draw the obvious enough conclusion that if quality is related to the presence and level of particular sets of performance criteria; some of these sets can be harder to achieve than others, so that other things being equal, greater quality corresponds to greater cost as well as a more complex process of realization. If the development of innovations is difficult, and occurs by contiguity, the degree of difficulty increases exponentially when intermediate steps are lacking. Accordingly, if intermediate steps have not been discovered, we must conclude that they do not exist, and that they will not be discovered in the future either. This is the kind of situation in which we expect to find that technology proceeds through discontinuities.
Mechanisms
of technological
evolution
From the foregoing postulates technological evolution: l
we can formulate
a sufficiently
general
rule of
The quality level of an innovation is necessarily greater than that of the one previously discovered in the same line of development; it cannot lie in an intermediate position between the quality of two existing processes.
In other words, it would be impossible (or highly unlikely) to discover a new process whose quality is somewhere between that of two existing
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processes. The reason for this is not that the existence of a greater quality would vitiate the usefulness, appreciation or search for a lesser quality, because the latter might well be associated with lower cost or other factors appreciated in given circumstances, and so could coexist with the greater quality. Instead, it is highly likely that if a lesser quality does exist, it will have been discovered before the greater quality. The rule formulated above is a probabilistic statement and belongs to the aforementioned category of prohibitive-permissive laws. In fact, it does not state that an innovation with given characteristics will appear at a certain time, but simply rules out the appearance, after a given moment, of any innovation of a certain type. (What seem to be technological flashbacks are actually due to greater appreciation of existing qualities, for instance when bygone usages are revived, or new symbolic values appear). In fact, when a new process comes forth, its technological quality usually appears as a quantum jump, that does not admit intermediate solutions. Let us take, for example, the case of lighting technology. Various techniques have been introduced over the course of time, each with greater energy efficiency (expressed in terms of lumen/Watt): wax candles (5), gas lights (IO), incandescent bulbs (201, fluorescent tubes (50), mercury lights (IOO), sodium lights (200). These techniques, even the oldest of them, coexist in specific market segments: candles for emergency situations and circumstances that call for their symbolic value (romantic dinners, prayer etc); gas lights for areas not connected to the electricity grid, incandescent bulbs for homes, fluorescent tubes for offices and stores, mercury lights for streets, sodium lights for foggy areas. Their coexistence is due to the fact that energy efficiency is not the only parameter on which we base our choice among the available options; we also assess cost (price and lifetime) and other performances (colour, stability, autonomy etc) which we value differently according to our individual tastes and needs. The sequence in which various classes of processes appear in time is generally ordered according to increments in a particular performance. This is evident in the foregoing example of lighting and in the following: l
l
l
vehicle speed: animal-drawn carts, trains, automobiles, propellor, jet and supersonic aircraft; communication effectiveness: messengers, visual signals, telegraph, telephone, radio, television; weapon range: clubs, spears, bows, guns, cannons, missiles.
We now see how the ‘natural trajectories’ of technologies can be derived looking at several fundamental process parafrom these general trends, meters such as cost, market segmentation, resource use, power and so forth. The approach taken in this analysis of a highly complex reality is each parameter will be investigated individually, necessarily simplified: considering all the others constant.
Innovation
and market segmentation
The mechanism of technology the quality of each innovation
development we have described implies that is greater than what was previously available.
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The relevant process will never be advantage that no earlier process unsatisfied users who appreciate offered by the innovative process. l l
rejected out of hand, because it offers an did. Its market will consist of previously (and can afford) the increment in quality It follows that:
each innovation that increases performance level adds to the current number of processes; each innovation that offers equal performance at lower cost enters the current number of processes, but cancels out an earlier one, so that the total remains the same.
Naturally, if a higher-quality innovation it will eventually cancel them cesses, infrequently, for two reasons: l
l
585
also costs less than existing proall out. However, this happens
better performance is unlikely to cost less (though this may eventually be the case, due to the effects of learning curves and scale economies); as the effects generated by cost reduction are time-dependent (because of the learning curve), a better performing process is usually younger.
A better process is thus unlikely to cost less than an inferior (and older) process. Hence, technological evolution is likely to increase the number of processes in use. Each process determines a quality range in market offers; to all effects, each interval corresponds to a market segment. Accordingly, ~e~~noi~gy evuiut~on also increases the number of segments. Market segmentation due to the penetration of technological innovations is a phenomenon easily detectable in economic reality. In overland transportation, for instance, while only a very few primitive alternatives were available up to the industrial age, we now have a whole complex structure of vehicle types (bicycles, motorcycles, cars, trucks, buses, trolleys, trains), each further segmented by types and models that address more and more specialized segments (road/rail, local/long-distance, freight/passengers, private/public and so forth). Our earlier example of lighting techniques shows the same effect: the diverse quality of available options produces market segmentation. Pervasive radical innovation, which replaces a wide range of earlier techniques, is rare, but when it does occur it leads to revolutionary changes in a system’s economic and institutional arrangements. These are the ‘technological revolutions’ or, to use Perez’s term, ‘changes in the technoeconomic model’.”
Some technological
trajectories
Based on the hypotheses discussed above, we can technological trajectories by identifying performances (other things being equal) is appreciated by users.
infer some possible whose improvement
Cost re~uct;o~ This trajectory is determined by the innovation-selection mechanism. In fact, while it is possible to develop ever more costly versions of a given process,
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they will be rejected and become irrelevant unless they better its performances. Less costly versions will be accepted in any case, and will represent the points on a curve leading in that direction. In agreement with the above general rule, innovations associated with lower cost form a trajectory. It may peter out at some time, but can never be reversed. The trend towards lower-cost processes is general, and thus represents one of technology’s fundamental trajectories.
Incidence
of capital cost
Were it not for equipment (artificial tools), the capital cost required to meet a need would be nil, but the operating cost (labour and resources used in the process) would be very high. Indeed, technology was born to reduce operating costs: capital investments in research, development and implementation are acceptable when they are assumed or hoped to lead to corresponding reductions in total costs. Accordingly, the reduction of operating costs can be seen as the primary, indicative parameter of quality, and also a parameter of difficulty. that reductions in operating and total It is highly unlikely, however, costs will correspond to a decrease in capital costs as well. They are much and in this case an accepted innovation will be more likely to increase, considered to correspond to reductions in both operating and total costs, and thus to an increase in the ratio of capital cost to total cost. This trend is most markedly bourne out in the case of advanced technologies, where capital inputs do away with much labour and resources. An illuminating example of this trajectory appears from the cost of electricity generated by a succession of technologies: capital cost accounts for 30-50% of the cost per kWh generated at gas or oil or coal-fired plants, from 7040% at nuclear plants, and almost 100% at photovoltaic and other types of plants that exploit free renewable sources of energy.
Space-time
dimensions
of goods and services
Time and living space have always been precious resources, instrumental to 5 Available space is a limiting factor for the most key choices of humankind. utilization of goods and time is a limiting factor for the exploitation of services. Therefore, in obedience to the utilitarian side of human nature, we would expect that innovations lead either to smaller and lighter equipment or speedier services. It is easy to see how closely these trends are followed in practice. For instance, the transition from thermoionic vacuum tubes to transistor electronics and successive generations of integrated circuits enormously reduced the size of electronic goods and computers and hugely increased their speed. As to services, an obvious example is the long history of ever faster transportation means, The concept can be extended to a vast number of cases. All indicating that change proceeds in one direction only. In general, faster services are made possible by the use of special equipment, and in limiting cases machines can take over human activities
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like washing altogether (goods for services substitution). 6 Home appliances machines and driers, for instance, have completely eliminated most of the labour involved in laundry, and automatic bank tellers now stand in for their human counterparts.
Incidence
of specific
resource
consumption
The achievement of the same performance in terms of quality and quantity with smaller resource inputs (due to greater energy efficiency, smaller processing waste, lighter-weight outputs etc) is a ‘quality’ appreciated not only for its potential to reduce costs, but also for other advantages in a product’s manufacture and use (less waste to recycle or eliminate, easier installation and use, greater environmental compatibility etc). However, any innovation in this direction that increases costs will be rejected and remain a dead letter unless the higher cost justifies a significant improvement in the product’s utilization. Those which are accepted will represent points on a trajectory shaped by increasingly efficient use of materials and energy in processes, and smaller weight and size of products. This trend, predicted in our theoretical picture, is spectacularly borne out by historical facts since the beginning of the industrial age,’ and especially over the past 20 years. Steady reductions in energy- and resource-intensity (expressed as the ratio between a country’s demand for energy and materials and its GDP, ie kcal or kg per $ of GDP) have given birth to the new concept of ‘dematerialization of the economy’. Obviously this trajectory is limited by ergonomic and physical constraints, and there are exceptions in which a product’s greater size or weight is considered a positive feature (eg with the aim to give stability to a machine).
Lifetime Other things being equal, the longer lifetime of a material, component or piece of equipment can be considered a valuable additional performance, in terms not only of potential cost reduction, but also the user’s convenience (greater reliability, less need for servicing, less probability of incurring downtime costs etc). However, an innovation that lengthens a product’s lifetime will be judged positive only if it promises to lead to a smaller total operating cost. Following the same reasoning as before, we thus have a technological trajectory pointed in the direction of longer lifetime; in effect this trend is generally observable in respect of components and materials. The same cannot be said for finished products, for which the only criterion of value is lower operating cost; accordingly, longer lifetime cannot be interpreted a priori as an increase in quality. For certain products and in certain circumstances, longer lifetime may be an advantage; in others it may be more advantageous to use shorter-lived products that lead to lower costs for other items. In actuality, there is no general unambivalent trend as regards the lifetime of finished products; consider, for instance, the popularity of ‘throwaway’ products in modern society.
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From therapy
trajectories
to prevention
and diagnostics
A subordinate trajectory can be identified as regards the technical ways and means of achieving the ‘longer lifetime’. Like living organisms attacked by disease, any material, component, equipment or system deteriorates over time, and since the damage mounts up exponentially, remedies are ever more difficult. The earlier a therapy is attempted, the more effective it will be, so that the availability of methods of early diagnosis is a key factor. Obviously prevention of deterioration through suitable design of products and processes is still more effective. Experience shows that innovations aimed at preventing disease and deterioration tend to proceed in a single direction-a shift in emphasis from remedies to prevention and diagnostics. Examples of this fairly general trend can be found in myriad areas of technology, the most obvious being the care of human and animal health, with the new emphasis placed on vaccines and diagnostics thanks to the capabilities of the emerging biotechnology,8 which are increasingly extending their scope to plants as well, with the diffusion of diagnostic techniques (biotests, biosensors, pheromones, genetic tests) and methods of prevention (transfer of genes for resistance to pests, diseases and environmental stresses). Similar trends can be identified as to materials, machines and processes.
Size and scale effects Power increase in equipment promises cost benefits (scale economies), but these can be offset by drawbacks that increase on the same scale-rigidity, risk concentration, operational complexity, and so forth. Difficulties must be overcome to lessen such drawbacks and thereby increases the benefits of scale, but the effort can be interpreted as the incorporation of extra quality, ie a valuable additional performance. Obviously such an effort will be judged worthwhile only if it leads to cost reduction. Following previous reasoning, we should find a trajectory characterized by a progression of power increase. This trend was largely true of the past for most industrial processes and equipment, but more recently has become problematic. The doubtful cases depend not on technological countertrends, but on the correction of mistakes in the evaluation and acceptance of innovations. In fact, they have often been found not to counter the drawbacks of large scale as well as promised, or sufficiently. A countertrend would appear if the same type of product were built smaller than ever before, but this is never actually the case. In practical terms, we can say that each type of equipment has an optimal level of potential that can vary the diffusion of information according to the technology adopted. Thus technology enables decentralized production and smaller optimal equipment sizes than in the past. A trend that mirrors this one is miniaturization, which similarly offers advantages offset by drawbacks. Increasing difficulties must be overcome in the effort to achieve more and more advanced cost-effective miniaturizations and results that can be judged as added quality. The same observations made above a propos of gigantism apply to this area as well.
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Like the longer/shorter-lifetime trends considered in the previous section and similar examples that we can imagine and discover, these twin trends with opposite goals may coexist in time, but in general they appear in different sectors, according to their specific applicability. In some extreme cases they even appear in the same sector, as expressions of two opposite orientations. One obvious example is in data processing, where the advent of large parallel-processing computers has been mirrored by that of ever smaller logic units. In such cases, it takes more sophisticated analysis to identify the trend; merely gathering and comparing data that argue in opposite directions cannot lead to any definitive conclusion. What we can do is see whether the results pointing in one or the other direction have gathered more steam than before. We might even find, as a general conclusion inferrable from our theoretical scheme, that an element common to all technological trajectories is the progressive radicalization of differences in all the directions we can imagine. This general trend of technology towards differentiation is an anti-entropic feature which well reflects its intrinsic nature: in effect, the role of technology is to modify the entropic and casual trend of nature towards shapeless homogeneity.
Possibilities and limits of technology The picture l
l
l
we have drawn
forecasting
so far shows three
determining
factors:
man’s propensity for attributing quality to certain results, ie appreciating certain performances, and for seeking greater quality; nature’s tendency to allow, for any one problem, various solutions whose quality we believe increases in given directions; man’s ability to jump from a traditional to an innovative process, overcoming technical and commercial difficulties which increase with the gap between the two.
This situation is similar to what a mariner would meet in exploring an archipelago of variously distributed ‘valid’ islands (so judged by the explorer). The difficulty of navigation increases exponentially with the distance to be travelled in the open sea. Exploration is possible precisely because the subject is an archipelago, where overall distances are broken up by the islands. The explorer does not know what type or number of islands he/she will encounter, only that if none has been discovered far from base, it is highly unlikely that any will be found nearby, or in the tract of sea between two known islands. Our propensity for innovation grows out of our desire to satisfy our needs, and is thus determined by our identification of unsatisfied needs. The latter may appear in the form of discrete thresholds (in space exploration, for instance, where success appears only after the difficulties involved in reaching a specific planet have been overcome) or an unbroken series of targets (such as speed levels in transportation). Success is more likely in cases of the second type, where any result that tops the earlier record will be considered valid. However, these cases are affected by the law of
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diminishing returns, according to which appreciation of increases in performance progressively declines. Depending on the degree to which it operates in any specific case, the likelihood of success will be greater or lesser. In at least two areas, the reduction of physical labour (costs) and better healthcare, our appreciation of quality is continuous, and the law of diminishing returns may not apply at all: any progress in these areas, small though it may be, is always appreciated. As innovation is most likely in these areas, this is where it is most frequent. The frequency of innovation in the past has little bearing on forecasts; it simply indicates one characteristic of technological development in a certain area. (In our metaphorical archipelago, this is represented by the frequency of islands in the last area explored, which cannot be thought applicable a priori to a subsequent area.) What is an important parameter is the amount of time elapsing since the last innovation along a particular trajectory. If long, it means that no easy solution exists, and difficult ones are hard to find. The likelihood of innovation in any paradigm thus decreases as the time gap increases. In other words, in any sector where innovation stagnates, more stagnation is likely to follow. Another important factor is whether or not an innovation is revolutionary. This characteristic is generally associated with a considerable buildup of scientific and technological knowledge in a particular area, which drives the research that develops around a radical innovation. The likeliness of incremental innovations thereafter may be particularly high (as in the concept of Schumpeter’s ‘swarms’). Stability of technological
trends
It may be worthwhile to see whether the trajectories we have discussed are valid only for modern technological development since the Industrial Revolution, or if they apply to technology in general. It is also important to check how far projections depend on the general prohibitive-permissive rule. We derived that rule from still more general hypotheses, but its contents imply the general stability of all trends characterized by variations in quality parameters (capital cost, lifetime and so forth). For instance: (a) The stability of the trend towards reduction of total cost is assured by the intervention of human will, as we select innovations according to how we judge their cost-effectiveness. (b) The general rule makes unlikely a reversal in the trend towards an increasing number of market segments (equal to the number of competing processes at any given time). In fact, since the most recent better-quality process will probably be more costly, at least initially, than it is unlikely to be more cost-efficient than older its predecessors, processes whose learning curves have been exploited for longer periods of time. Lastly, we may note that while the various technological appeared in the course of history may have followed
paradigms that have one trajectory more
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Technological
Human
goals
-
Utilitarian Censorship
591
Trajectories
nature
acceptance
trajectories
in the of
innovation
r
I Cost *
labour
*
energy
*
materials
*
time
*
space
Meeting *
*
I Cost reduction Greater incidence Longer lifetime (from therapy to
minimization
Scale
of
capital
cost
prevention)
economies
Market
segmentation
Faster
services
-i Goods
needs E
customization optimum
I’
for
services
substitution
Dematerialization
performances
v
Figure 1. Mechanisms
closely than another, described above.
involved in the formation of technological
they
have
all
kept
within
the
trajectories
general
framework
Conclusions We began by setting out several hypotheses from which to derive a general Its limited predictive potential makes this a rule of technological evolution. prohibitive-permissive type of rule rather than a prescriptive one. It generates ‘natural trajectories’ that coincide with what we find in the reality of technological development. This approach enables us to logically attribute the characteristic of intrinsic stability to the trajectories discerned so far, and points to a way of identifying others that known facts may not yet corroborate. Figure1 shows the relationships between these trajectories and some fundamental human goals-minimization of labour cost and resources use materials), product customization, optimization of (time, space, energy, performances. Man’s judgments in these matters determine the trajectories through utilitarian choices and the censorship exercised in accepting or rejecting innovations. Technological evolution as it appears in this scheme has the nature of an ordered progression of differentiation in process performances. This for it fits technology’s actual role and purpose of trend is significant, countering nature’s own trend towards disorder (which in this context is synonymous with uniformity). We are sceptical about the possibility of formulating hypotheses from which to derive prescriptive laws and deterministic predictions. In our opinion, the minimum requisite for even the most modest predictions is the identification of a law that would rule out, by reason of the most recent innovation discovered, any new innovation in the same category and with similar characteristics. The wider the area of interdiction, the greater will be the predictive power associated with such a law.
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Notes and references 1. R. Nelson and S. Winter, ‘In search of a useful theory of innovation’, Research Policy, I(6), 1977, pages 66-76. 2. C. Dosi, ‘Technological paradigms and technological trajectories’, Research Policy, 11(3) 1982, pages 147-163. 3. Boston Consulting Group, Perspective on Experience (Boston, MA, BCG, 1970). 4. C. Perez, ‘Structural change and the assimilation of new technologies in the economy and social system’, Futures, V(4), October 1983, pages 357-375. 5. 0. Bernardini, ‘The urban determinants of economic growth and energy demand’, Economia de//e fonti di energia, 13, 1981, page 119. 6. J. F. Rada, ‘Tecnologie dell’informazione e servizi’, L’lmpresa, 29(4), 1987, pages 19-23. 7. UNCTAD, Impact of New and Emerging Technologies on Trade and Development, TD/B/C.6/136 (Geneva 1986); R. Galli, ‘La rivoluzione annunciata delle biotecnologie’, L’lmpresa, 30(3), 1988, pages 87-95. 8. Ibid; and OECD Biotechnology: Economic and Wider impacts (Paris, OECD, 1989), pages 52-53.
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TECHNOLOGICAL TRAJECTORIES Leonardo Biondi and Riccardo Galli
The issue of technological trajectories is discussed with reference to the mechanism of technological evolution. It is shown how the process of innovation tends to follow a general prohibitive-permissive rule, leading to continuous improvements in one or more aspects of performance which is appreciated by users. This fact generates technological sequences according to preferential paths, which can be considered as trajectories. As examples, a few paths have been identified, such as market segmentation, product customization, cost reduction, reduction of resource use (time, space, energy, materials), etc. The constraints on and possibilities of technological forecasting are discussed in relation to the existence of trajectories.
A number of authors have found empirical evidence that technological progress follows preferential paths. The term ‘natural trajectories’ was certain aspects of technology, coined by Nelson and Winter ’ to describe such as the exploitation of scale economies and the mechanization of processes. The concept was later taken up by Dosi,2 who pointed out that contains strong prescriptions as to which each ‘technological paradigm’ directions change must take and which must be rejected. Technological paradigms have a powerful exclusionary effect: efforts and imagination are focused in fairly precise directions, but remain ‘blind’ to other technological possibilities. These authors thus recognize the existence of basic trends in technology, but consider them specific to each paradigm. The purpose of this article is to identify general rules of technological development underlying those which are specific to any one paradigm. The evolution of technology is determined by the periodic appearance of innovations-pulled by the market or pushed by new knowledgecounterbalanced by the symmetrical elimination of earlier innovations (or restriction of their range of application). While such eliminations are the result of rational human decisions based on costs and benefits, the appear-
Leonardo Biondi is a management consultant, Milan, and Riccardo Galli is at the University of Milan. They can be contacted at FAST, p R. Morandi, 2-20121 Milan, Italy (Tel: 39 2 76006260; Fax: 39 2 783126). This article is based on a previous text, ‘Alla ricerca di una legge dell’evoluzione tecnologica’, L’Impresa-Rivista italiana di management, 33(6), December 1991, pages 136-144.
0016-3287/060580-13
@ 1992 Butterworth-Heinemann
Ltd
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ante of novelties depends partly on factors beyond human will. The a priori possibifities in this connectian are two: (a) The genesis of ~nnuvat~~~ is purely casuaf; that is, the innovations which have appeared to date might have come forth in any era and with any frequency, and might have had different characteristics and numbers. In this case, technological forecasting would be impossible, and there would be no recognizable trajectory. The ways in which innovations have historica~fy appeared (their discontinuous concentration in certain eras, the appearance of preferential paths, the importance of market demand for innovation) argue against this thesis. fb) The genesis of innovation is affected to some extent by cau~~~~~~;that is, by human decisions. tn this case, both technological forecasting and the identification of trajectories are possible. This means identifying factors correlated to the characteristics attributed to j~novat~on~ and finding the continuous or discontinuous trend they (or their derivatives) take over time. In this second case, we again have two possibilities: (b 3) The genesis of innovation is purdy caud; in this case we woutd expect a proscriptive faw of technological evolution (like the law of heat transmission); that is, it would exhaustively state what must happen in given circumstances. (b 2) The genesis of in~~vatj~n is ~~~~~~ caausal and ~~r~~y casuaf; in this case the relevant taw is prohibitive-permissive (like the second law of thermodynamics~. This type of law states, in general and fur all contexts, that certain phenomena with certain characteristics are untikely to occur, whiie other phenomena may appear, each with equal probability. The fundamental laws of nature are of this second type They then translate into prescriptive laws, because of the presence of constraints expressed in their formulae. If we wish to use such a law, we must know the values of its constraints. If our knowledge of its constraints is only statistical, a prohibitive-permissive law expresses probabiiistic outcomes for the phenomena it allows. If we are only interested in the average outcome in a great number of cases, the prohjbitiv~-permissive law appears to be prescriptive, and its effects are in fact deterministic (Eke those of the second law of thermodynamics). The purpose of this articte is to verify the existence of temporal correlations of techno~~g~ca~ ~nnuvat~ons to given characteristics. Tu this end, we may start with the definitions of severai terms that will be used later on.
Technology is an ensemble of knowledge, practical and theoretical (but susceptible of application), including what is embodied in tools and equipment. Process means a way to satisfy, or help to satisfy, a human need. ~nffo~~~~on means a process, put into practice, that differs from its predecessors. In every process we can d~stjngu~sh the 9ua~~~~~~~~easpect of the
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service rendered and the qualitative aspect expressed in terms of a characteristic set of performances appreciated by users. For instance, the ‘quality’ of a vehicle depends on the values of factors such as roominess, image, speed, fuel consumption, price, and so forth. Performance can be expressed in terms of a continuous sequence of values (eg price or speed) or of discontinuous levels (eg black-and-white or colour TV screen). Processes that have the same set of performances can be ordered in an increasing series of overall quality levels. When a process contains an extra performance, in addition to a certain set, its overall ‘quality’ will be greater and may give rise to a new homogeneous line of processes. Processes are manifested in equipment (which can even be intangible, like a computer program) and their operation. A piece of equipment is qualified by the level of its performances, by its power (quantity of performance over a given unit of time), by the capital cost and by its lifetime. Its operation requires a cost over the unit of time. From these data we can find the capital cost per unit of performance, and the unit cost of operation. The total lifecycle cost of any process is the sum of its capital cost and all the operating costs incurred during its lifetime; its annual unit cost is found by dividing its life cycle cost by the number of years of its lifetime. A valid process is one which has the lowest total annual cost of all those with equivalent performances. Invalid processes eventually disappear from the current body of technology and become irrelevant in practice. It should be noted, however, that the approach taken in this article is perforce simplified. The choice of a process is a complicated affair in which both rational factors (comparative technical and financial assessments) and symbolic values, tastes etc) play their irrational factors (image, customs, part. The concept of the validity of a process is not absolute; the appreciation of a process’s various performances can vary over time and space. This explains why some older technologies may be taken up again, why market niches remain for some obsolete technologies, and why markets can be differentiated according to geography, age of users, social classes etc. Valid processes of different quality co-exist and share the market. The market share of any process consists of the fraction of buyers who consider its quality more cost-effective than that of its rivals. A small or even inexistent market share is not sufficient reason to exclude a process from the current body of technology (though it could well exclude it from actual use in production), because there may be reasons that make it worthwhile to wait for a drop in costs or an increase in the appreciation of its quality, and accordingly an increase in its market share.
Working
hypotheses
We now formulate some hypotheses from which to draw indications of general trends in the evolution of technology. We give priority to the above-defined characteristics of ‘quality’ (ie a set of performance criteria appreciated by users) and annual unit cost (which we shall abbreviate to ‘cost’). This is a discretionary choice, but justified by the fact that these are the elements by which we judge the validity of any process. An enormous amount of equipment (in the sense indicated above) can
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be conceived to serve any particular purpose, but only a tiny fraction will provide what we judge to be valid quality, and the probability of our stumbling on a piece of equipment through random research (serendipity) is extremely low. Let us now suppose that: o ‘quality’ is expressed in terms of a set of performances appreciated by users (in a vehicle, for instance, these would be weight, speed, size, fuel economy, price etc); * overall ‘quality’ is related to the number and level of such features; l the above sets of performance criteria are similar enough for us to gauge intuitively and seek, albeit with difficulty, other higher-quality configurations of the same sets of performance criteria; and for it to be assumed that their similarity decreases with their distance from the starting point; such as throwing a stone, using a 0 some common poor-quality ‘processes’, sharpened stick, or using a natural cave for shelter, were discovered by chance, albeit after many attempts over long periods of time. This set of hypotheses could explain the evolution of technology; that is, the transition from a technology of a particular quality level to one of higher level. Such transitions can occur only with contiguous orders of quality; studded with difficulties, they proceed step by step, each built on the information contained in the previous one. In practical terms, this model corresponds to the well known concepts of ‘lifecycle of technology’ and ‘learning curve’.3 This model has the advantage of reflecting a particular characteristic of technological evolution: since technical knowledge is cumulative, evolution proceeds by increasing segregation of step-by-step results. While this is the usual form of technological evolution, it naturally does not preclude the rarer eventuality of more radical progress achieved through ‘technological discontinuity’. From the foregoing we can draw the obvious enough conclusion that if quality is related to the presence and level of particular sets of performance criteria; some of these sets can be harder to achieve than others, so that other things being equal, greater quality corresponds to greater cost as well as a more complex process of realization. If the development of innovations is difficult, and occurs by contiguity, the degree of difficulty increases exponentially when intermediate steps are lacking. Accordingly, if intermediate steps have not been discovered, we must conclude that they do not exist, and that they will not be discovered in the future either. This is the kind of situation in which we expect to find that technology proceeds through discontinuities.
Mechanisms
of technological
evolution
From the foregoing postulates technological evolution: l
we can formulate
a sufficiently
general
rule of
The quality level of an innovation is necessarily greater than that of the one previously discovered in the same line of development; it cannot lie in an intermediate position between the quality of two existing processes.
In other words, it would be impossible (or highly unlikely) to discover a new process whose quality is somewhere between that of two existing
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processes. The reason for this is not that the existence of a greater quality would vitiate the usefulness, appreciation or search for a lesser quality, because the latter might well be associated with lower cost or other factors appreciated in given circumstances, and so could coexist with the greater quality. Instead, it is highly likely that if a lesser quality does exist, it will have been discovered before the greater quality. The rule formulated above is a probabilistic statement and belongs to the aforementioned category of prohibitive-permissive laws. In fact, it does not state that an innovation with given characteristics will appear at a certain time, but simply rules out the appearance, after a given moment, of any innovation of a certain type. (What seem to be technological flashbacks are actually due to greater appreciation of existing qualities, for instance when bygone usages are revived, or new symbolic values appear). In fact, when a new process comes forth, its technological quality usually appears as a quantum jump, that does not admit intermediate solutions. Let us take, for example, the case of lighting technology. Various techniques have been introduced over the course of time, each with greater energy efficiency (expressed in terms of lumen/Watt): wax candles (5), gas lights (IO), incandescent bulbs (201, fluorescent tubes (50), mercury lights (IOO), sodium lights (200). These techniques, even the oldest of them, coexist in specific market segments: candles for emergency situations and circumstances that call for their symbolic value (romantic dinners, prayer etc); gas lights for areas not connected to the electricity grid, incandescent bulbs for homes, fluorescent tubes for offices and stores, mercury lights for streets, sodium lights for foggy areas. Their coexistence is due to the fact that energy efficiency is not the only parameter on which we base our choice among the available options; we also assess cost (price and lifetime) and other performances (colour, stability, autonomy etc) which we value differently according to our individual tastes and needs. The sequence in which various classes of processes appear in time is generally ordered according to increments in a particular performance. This is evident in the foregoing example of lighting and in the following: l
l
l
vehicle speed: animal-drawn carts, trains, automobiles, propellor, jet and supersonic aircraft; communication effectiveness: messengers, visual signals, telegraph, telephone, radio, television; weapon range: clubs, spears, bows, guns, cannons, missiles.
We now see how the ‘natural trajectories’ of technologies can be derived looking at several fundamental process parafrom these general trends, meters such as cost, market segmentation, resource use, power and so forth. The approach taken in this analysis of a highly complex reality is each parameter will be investigated individually, necessarily simplified: considering all the others constant.
Innovation
and market segmentation
The mechanism of technology the quality of each innovation
development we have described implies that is greater than what was previously available.
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Technological trajectories
The relevant process will never be advantage that no earlier process unsatisfied users who appreciate offered by the innovative process. l l
rejected out of hand, because it offers an did. Its market will consist of previously (and can afford) the increment in quality It follows that:
each innovation that increases performance level adds to the current number of processes; each innovation that offers equal performance at lower cost enters the current number of processes, but cancels out an earlier one, so that the total remains the same.
Naturally, if a higher-quality innovation it will eventually cancel them cesses, infrequently, for two reasons: l
l
585
also costs less than existing proall out. However, this happens
better performance is unlikely to cost less (though this may eventually be the case, due to the effects of learning curves and scale economies); as the effects generated by cost reduction are time-dependent (because of the learning curve), a better performing process is usually younger.
A better process is thus unlikely to cost less than an inferior (and older) process. Hence, technological evolution is likely to increase the number of processes in use. Each process determines a quality range in market offers; to all effects, each interval corresponds to a market segment. Accordingly, ~e~~noi~gy evuiut~on also increases the number of segments. Market segmentation due to the penetration of technological innovations is a phenomenon easily detectable in economic reality. In overland transportation, for instance, while only a very few primitive alternatives were available up to the industrial age, we now have a whole complex structure of vehicle types (bicycles, motorcycles, cars, trucks, buses, trolleys, trains), each further segmented by types and models that address more and more specialized segments (road/rail, local/long-distance, freight/passengers, private/public and so forth). Our earlier example of lighting techniques shows the same effect: the diverse quality of available options produces market segmentation. Pervasive radical innovation, which replaces a wide range of earlier techniques, is rare, but when it does occur it leads to revolutionary changes in a system’s economic and institutional arrangements. These are the ‘technological revolutions’ or, to use Perez’s term, ‘changes in the technoeconomic model’.”
Some technological
trajectories
Based on the hypotheses discussed above, we can technological trajectories by identifying performances (other things being equal) is appreciated by users.
infer some possible whose improvement
Cost re~uct;o~ This trajectory is determined by the innovation-selection mechanism. In fact, while it is possible to develop ever more costly versions of a given process,
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they will be rejected and become irrelevant unless they better its performances. Less costly versions will be accepted in any case, and will represent the points on a curve leading in that direction. In agreement with the above general rule, innovations associated with lower cost form a trajectory. It may peter out at some time, but can never be reversed. The trend towards lower-cost processes is general, and thus represents one of technology’s fundamental trajectories.
Incidence
of capital cost
Were it not for equipment (artificial tools), the capital cost required to meet a need would be nil, but the operating cost (labour and resources used in the process) would be very high. Indeed, technology was born to reduce operating costs: capital investments in research, development and implementation are acceptable when they are assumed or hoped to lead to corresponding reductions in total costs. Accordingly, the reduction of operating costs can be seen as the primary, indicative parameter of quality, and also a parameter of difficulty. that reductions in operating and total It is highly unlikely, however, costs will correspond to a decrease in capital costs as well. They are much and in this case an accepted innovation will be more likely to increase, considered to correspond to reductions in both operating and total costs, and thus to an increase in the ratio of capital cost to total cost. This trend is most markedly bourne out in the case of advanced technologies, where capital inputs do away with much labour and resources. An illuminating example of this trajectory appears from the cost of electricity generated by a succession of technologies: capital cost accounts for 30-50% of the cost per kWh generated at gas or oil or coal-fired plants, from 7040% at nuclear plants, and almost 100% at photovoltaic and other types of plants that exploit free renewable sources of energy.
Space-time
dimensions
of goods and services
Time and living space have always been precious resources, instrumental to 5 Available space is a limiting factor for the most key choices of humankind. utilization of goods and time is a limiting factor for the exploitation of services. Therefore, in obedience to the utilitarian side of human nature, we would expect that innovations lead either to smaller and lighter equipment or speedier services. It is easy to see how closely these trends are followed in practice. For instance, the transition from thermoionic vacuum tubes to transistor electronics and successive generations of integrated circuits enormously reduced the size of electronic goods and computers and hugely increased their speed. As to services, an obvious example is the long history of ever faster transportation means, The concept can be extended to a vast number of cases. All indicating that change proceeds in one direction only. In general, faster services are made possible by the use of special equipment, and in limiting cases machines can take over human activities
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like washing altogether (goods for services substitution). 6 Home appliances machines and driers, for instance, have completely eliminated most of the labour involved in laundry, and automatic bank tellers now stand in for their human counterparts.
Incidence
of specific
resource
consumption
The achievement of the same performance in terms of quality and quantity with smaller resource inputs (due to greater energy efficiency, smaller processing waste, lighter-weight outputs etc) is a ‘quality’ appreciated not only for its potential to reduce costs, but also for other advantages in a product’s manufacture and use (less waste to recycle or eliminate, easier installation and use, greater environmental compatibility etc). However, any innovation in this direction that increases costs will be rejected and remain a dead letter unless the higher cost justifies a significant improvement in the product’s utilization. Those which are accepted will represent points on a trajectory shaped by increasingly efficient use of materials and energy in processes, and smaller weight and size of products. This trend, predicted in our theoretical picture, is spectacularly borne out by historical facts since the beginning of the industrial age,’ and especially over the past 20 years. Steady reductions in energy- and resource-intensity (expressed as the ratio between a country’s demand for energy and materials and its GDP, ie kcal or kg per $ of GDP) have given birth to the new concept of ‘dematerialization of the economy’. Obviously this trajectory is limited by ergonomic and physical constraints, and there are exceptions in which a product’s greater size or weight is considered a positive feature (eg with the aim to give stability to a machine).
Lifetime Other things being equal, the longer lifetime of a material, component or piece of equipment can be considered a valuable additional performance, in terms not only of potential cost reduction, but also the user’s convenience (greater reliability, less need for servicing, less probability of incurring downtime costs etc). However, an innovation that lengthens a product’s lifetime will be judged positive only if it promises to lead to a smaller total operating cost. Following the same reasoning as before, we thus have a technological trajectory pointed in the direction of longer lifetime; in effect this trend is generally observable in respect of components and materials. The same cannot be said for finished products, for which the only criterion of value is lower operating cost; accordingly, longer lifetime cannot be interpreted a priori as an increase in quality. For certain products and in certain circumstances, longer lifetime may be an advantage; in others it may be more advantageous to use shorter-lived products that lead to lower costs for other items. In actuality, there is no general unambivalent trend as regards the lifetime of finished products; consider, for instance, the popularity of ‘throwaway’ products in modern society.
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From therapy
trajectories
to prevention
and diagnostics
A subordinate trajectory can be identified as regards the technical ways and means of achieving the ‘longer lifetime’. Like living organisms attacked by disease, any material, component, equipment or system deteriorates over time, and since the damage mounts up exponentially, remedies are ever more difficult. The earlier a therapy is attempted, the more effective it will be, so that the availability of methods of early diagnosis is a key factor. Obviously prevention of deterioration through suitable design of products and processes is still more effective. Experience shows that innovations aimed at preventing disease and deterioration tend to proceed in a single direction-a shift in emphasis from remedies to prevention and diagnostics. Examples of this fairly general trend can be found in myriad areas of technology, the most obvious being the care of human and animal health, with the new emphasis placed on vaccines and diagnostics thanks to the capabilities of the emerging biotechnology,8 which are increasingly extending their scope to plants as well, with the diffusion of diagnostic techniques (biotests, biosensors, pheromones, genetic tests) and methods of prevention (transfer of genes for resistance to pests, diseases and environmental stresses). Similar trends can be identified as to materials, machines and processes.
Size and scale effects Power increase in equipment promises cost benefits (scale economies), but these can be offset by drawbacks that increase on the same scale-rigidity, risk concentration, operational complexity, and so forth. Difficulties must be overcome to lessen such drawbacks and thereby increases the benefits of scale, but the effort can be interpreted as the incorporation of extra quality, ie a valuable additional performance. Obviously such an effort will be judged worthwhile only if it leads to cost reduction. Following previous reasoning, we should find a trajectory characterized by a progression of power increase. This trend was largely true of the past for most industrial processes and equipment, but more recently has become problematic. The doubtful cases depend not on technological countertrends, but on the correction of mistakes in the evaluation and acceptance of innovations. In fact, they have often been found not to counter the drawbacks of large scale as well as promised, or sufficiently. A countertrend would appear if the same type of product were built smaller than ever before, but this is never actually the case. In practical terms, we can say that each type of equipment has an optimal level of potential that can vary the diffusion of information according to the technology adopted. Thus technology enables decentralized production and smaller optimal equipment sizes than in the past. A trend that mirrors this one is miniaturization, which similarly offers advantages offset by drawbacks. Increasing difficulties must be overcome in the effort to achieve more and more advanced cost-effective miniaturizations and results that can be judged as added quality. The same observations made above a propos of gigantism apply to this area as well.
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Like the longer/shorter-lifetime trends considered in the previous section and similar examples that we can imagine and discover, these twin trends with opposite goals may coexist in time, but in general they appear in different sectors, according to their specific applicability. In some extreme cases they even appear in the same sector, as expressions of two opposite orientations. One obvious example is in data processing, where the advent of large parallel-processing computers has been mirrored by that of ever smaller logic units. In such cases, it takes more sophisticated analysis to identify the trend; merely gathering and comparing data that argue in opposite directions cannot lead to any definitive conclusion. What we can do is see whether the results pointing in one or the other direction have gathered more steam than before. We might even find, as a general conclusion inferrable from our theoretical scheme, that an element common to all technological trajectories is the progressive radicalization of differences in all the directions we can imagine. This general trend of technology towards differentiation is an anti-entropic feature which well reflects its intrinsic nature: in effect, the role of technology is to modify the entropic and casual trend of nature towards shapeless homogeneity.
Possibilities and limits of technology The picture l
l
l
we have drawn
forecasting
so far shows three
determining
factors:
man’s propensity for attributing quality to certain results, ie appreciating certain performances, and for seeking greater quality; nature’s tendency to allow, for any one problem, various solutions whose quality we believe increases in given directions; man’s ability to jump from a traditional to an innovative process, overcoming technical and commercial difficulties which increase with the gap between the two.
This situation is similar to what a mariner would meet in exploring an archipelago of variously distributed ‘valid’ islands (so judged by the explorer). The difficulty of navigation increases exponentially with the distance to be travelled in the open sea. Exploration is possible precisely because the subject is an archipelago, where overall distances are broken up by the islands. The explorer does not know what type or number of islands he/she will encounter, only that if none has been discovered far from base, it is highly unlikely that any will be found nearby, or in the tract of sea between two known islands. Our propensity for innovation grows out of our desire to satisfy our needs, and is thus determined by our identification of unsatisfied needs. The latter may appear in the form of discrete thresholds (in space exploration, for instance, where success appears only after the difficulties involved in reaching a specific planet have been overcome) or an unbroken series of targets (such as speed levels in transportation). Success is more likely in cases of the second type, where any result that tops the earlier record will be considered valid. However, these cases are affected by the law of
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diminishing returns, according to which appreciation of increases in performance progressively declines. Depending on the degree to which it operates in any specific case, the likelihood of success will be greater or lesser. In at least two areas, the reduction of physical labour (costs) and better healthcare, our appreciation of quality is continuous, and the law of diminishing returns may not apply at all: any progress in these areas, small though it may be, is always appreciated. As innovation is most likely in these areas, this is where it is most frequent. The frequency of innovation in the past has little bearing on forecasts; it simply indicates one characteristic of technological development in a certain area. (In our metaphorical archipelago, this is represented by the frequency of islands in the last area explored, which cannot be thought applicable a priori to a subsequent area.) What is an important parameter is the amount of time elapsing since the last innovation along a particular trajectory. If long, it means that no easy solution exists, and difficult ones are hard to find. The likelihood of innovation in any paradigm thus decreases as the time gap increases. In other words, in any sector where innovation stagnates, more stagnation is likely to follow. Another important factor is whether or not an innovation is revolutionary. This characteristic is generally associated with a considerable buildup of scientific and technological knowledge in a particular area, which drives the research that develops around a radical innovation. The likeliness of incremental innovations thereafter may be particularly high (as in the concept of Schumpeter’s ‘swarms’). Stability of technological
trends
It may be worthwhile to see whether the trajectories we have discussed are valid only for modern technological development since the Industrial Revolution, or if they apply to technology in general. It is also important to check how far projections depend on the general prohibitive-permissive rule. We derived that rule from still more general hypotheses, but its contents imply the general stability of all trends characterized by variations in quality parameters (capital cost, lifetime and so forth). For instance: (a) The stability of the trend towards reduction of total cost is assured by the intervention of human will, as we select innovations according to how we judge their cost-effectiveness. (b) The general rule makes unlikely a reversal in the trend towards an increasing number of market segments (equal to the number of competing processes at any given time). In fact, since the most recent better-quality process will probably be more costly, at least initially, than it is unlikely to be more cost-efficient than older its predecessors, processes whose learning curves have been exploited for longer periods of time. Lastly, we may note that while the various technological appeared in the course of history may have followed
paradigms that have one trajectory more
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Technological
Human
goals
-
Utilitarian Censorship
591
Trajectories
nature
acceptance
trajectories
in the of
innovation
r
I Cost *
labour
*
energy
*
materials
*
time
*
space
Meeting *
*
I Cost reduction Greater incidence Longer lifetime (from therapy to
minimization
Scale
of
capital
cost
prevention)
economies
Market
segmentation
Faster
services
-i Goods
needs E
customization optimum
I’
for
services
substitution
Dematerialization
performances
v
Figure 1. Mechanisms
closely than another, described above.
involved in the formation of technological
they
have
all
kept
within
the
trajectories
general
framework
Conclusions We began by setting out several hypotheses from which to derive a general Its limited predictive potential makes this a rule of technological evolution. prohibitive-permissive type of rule rather than a prescriptive one. It generates ‘natural trajectories’ that coincide with what we find in the reality of technological development. This approach enables us to logically attribute the characteristic of intrinsic stability to the trajectories discerned so far, and points to a way of identifying others that known facts may not yet corroborate. Figure1 shows the relationships between these trajectories and some fundamental human goals-minimization of labour cost and resources use materials), product customization, optimization of (time, space, energy, performances. Man’s judgments in these matters determine the trajectories through utilitarian choices and the censorship exercised in accepting or rejecting innovations. Technological evolution as it appears in this scheme has the nature of an ordered progression of differentiation in process performances. This for it fits technology’s actual role and purpose of trend is significant, countering nature’s own trend towards disorder (which in this context is synonymous with uniformity). We are sceptical about the possibility of formulating hypotheses from which to derive prescriptive laws and deterministic predictions. In our opinion, the minimum requisite for even the most modest predictions is the identification of a law that would rule out, by reason of the most recent innovation discovered, any new innovation in the same category and with similar characteristics. The wider the area of interdiction, the greater will be the predictive power associated with such a law.
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Notes and references 1. R. Nelson and S. Winter, ‘In search of a useful theory of innovation’, Research Policy, I(6), 1977, pages 66-76. 2. C. Dosi, ‘Technological paradigms and technological trajectories’, Research Policy, 11(3) 1982, pages 147-163. 3. Boston Consulting Group, Perspective on Experience (Boston, MA, BCG, 1970). 4. C. Perez, ‘Structural change and the assimilation of new technologies in the economy and social system’, Futures, V(4), October 1983, pages 357-375. 5. 0. Bernardini, ‘The urban determinants of economic growth and energy demand’, Economia de//e fonti di energia, 13, 1981, page 119. 6. J. F. Rada, ‘Tecnologie dell’informazione e servizi’, L’lmpresa, 29(4), 1987, pages 19-23. 7. UNCTAD, Impact of New and Emerging Technologies on Trade and Development, TD/B/C.6/136 (Geneva 1986); R. Galli, ‘La rivoluzione annunciata delle biotecnologie’, L’lmpresa, 30(3), 1988, pages 87-95. 8. Ibid; and OECD Biotechnology: Economic and Wider impacts (Paris, OECD, 1989), pages 52-53.
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