Blade Runner Economics.

Will Innovation lead the Economic Recovery?1

Daniele Archibugi

Italian National Research Council, IRPPS, Via Palestro, 32- 00185 Rome, Italy,
Tel. +39-06 492724241, Email: daniele.archibugi@cnr.it ; and
Birkbeck College, University of London
Malet Street, Bloomsbury, London WC1E 7HX,
Tel. +44 (0)20 7631 6741, Email: d.archibugi@bbk.ac.uk

Fifth Revision 05.01.2016

Forthcoming in Research Policy

ABSTRACT

According to Schumpeterian theories, economic expansions are associated to the introduction

of successful new products, processes and services while depressions to stagnant periods with
few innovations. Can the economic crisis started in 2008 be explained by the incapacity to
upgrade production? And, conversely, will an economic recovery require a new stream of
innovations? On the grounds of the debate developed after the 1970s crisis, this paper tries to
assess if it is likely that the next long-term expansion will be linked to a new stream of
innovations. While most evidence suggests that ICTs continue to be the back-bone of
economic activities, there is the prospect that Biotech will eventually start to fulfil the
promises already envisaged in Blade Runner.

1
Previous versions of this paper have been presented at the Association of the European Schools of Planning
(AESOP) Annual Congress 2014, Utrecht, July 2014, at the International Seminar convened by the Institute of
Research on Innovation on “The New Agendas for Innovation Studies and Policy Implications, Madrid, March
2014, at the Science Policy Research Unit, University of Sussex, October 2014, and at Workshop Explaining
Economic Change, Sapienza University of Rome, November 2014. I wish to thank the participants and Cristiano
Antonelli, Luuk Boelens, Rosaria Conte, Andrea Filippetti, Marion Frenz, José Molero, Paul Nightingale, Luigi
Orsenigo, Pari Patel, Maria Savona, Ed Steinmueller and two referees for their comments on previous versions.
A special thanks to Alice Pease for editing my English. A grant from the School of Business, Economics and
Informatics of Birkbeck College is gratefully acknowledged.

1
 Artificial Life in Venice

I was just a boy when in 1982, the fortunes of life led me to watch Blade Runner at the
Venice Film Festival. Ridley Scott and Harrison Ford were there, but I was much more
impressed and fascinated by the fantasy of new technologies than by the celebrities in the
cinema. I was not the only one: the film and its seven different versions have become a “cult
movie” and have been investigated not only for their artistic meaning but also for their social,
political and economic implications (see, for example, the variety of perspectives presented in
Kerman, 1997).
I would like here to explore the film as an experiment in technological forecasting.
Many prospective technologies presented in the film, such as flying vehicles, were already
predicted by previous science fictions novels, films and cartoons. But some devices struck
my imagination:
Electronics. Battery-operated electronic tills present everywhere, even in street kiosks.
Voice-operated televisions. Gigantic electronic screens. Scanners (I do not think that the
word already existed in 1982) that could in an instant enlarge photos several times over.
Biological artefacts. Artificial animals (snakes, owls). Artificial body parts (human
eyes). Living toys (dolls, puppets and tin soldiers). And, of course, the very hero of the film,
the Replicant, an artificial human who could be distinguished from a real human only after
undergoing a rather complex psychological / oculist test.
Experts in science fiction will no doubt find that any one of these innovations was
already predicted in previous science fiction works.2 Nevertheless, the narrative of Blade
Runner makes these manufactured biological artefacts realistic and impressive for their
pervasive social diffusion, perhaps because it portrays a vision of an entire industry based on
what we can label today as a general purpose technology (for a discussion of the latter
concept, see David, 1990; Bresnahan and Trajtenberg, 1995), namely artificial life.
A distinctive aspect of Blade Runner should be underlined. It did not present a totally
new society: many things were almost identical to the civilization of the 1980s. The structure
of social classes depicted in Blade Runner is rather similar to what existed at the time of the
film’s release, and this is by itself an accomplished prediction since income inequality has
become even greater in the last thirty years. Already Fritz Lange’s Metropolis (1927)

2
Thanks to a very knowledgeable reviewer, I have learnt that “bio-engineered” animals could be found in Olaf
Stapledon’s Sirius, (1944)and that a mixture of humans and animals are also to be found in Cordwainer Smith’s
The dead lady of Clown Town (1964).

2
depicted a social stratification in which lower classes re-entered a state of slavery and Blade
Runner shows that the new lumpen-proletariat of Marxist remembrance has a new
competitor: the non-human class of the androids. Like Metropolis, the film represents a
peculiar urban stratification of social classes: it is not horizontal, as when you have different
neighbourhoods, but rather vertical: lower classes are low also because they live on the
ground floor, while the upper classes show their highflying nature also literally, occupying
the top floors of skyscrapers.
The dominant technologies are not identified by single innovations only, but by clusters
of interrelated innovations. Surprisingly, however, the film fails to connect systematically the
two clusters in Electronics and Biological artefacts. With retrospective wisdom, we can today
identify these technologies as belonging to two main clusters: “Information and
Communication Technologies” (ICTs) and “Biotechnologies”. In the eyes of the early 1980s,
both ICTs and Biotech had a potential that was still unexplored and that appeared equally
revolutionary and promising.
After thirty years, I watched the film again in very privileged company, that of my
children. Like me, my kids found the film imaginative and exciting, but with some basic
differences. On the one hand, all the innovations in the field of ICTs have become trivial for
them: the mobiles in their pockets (and that I paid for) contain scanners, audio-visuals, photo
enlargers and GPS navigators more powerful and much smaller than in the film. In the middle
of the adventure, one of my kids wondered: “why does he not send an email with an
attachment?”, and the question was not that silly. If we accept the intriguing idea that science
fiction could influence innovation as much as innovation influences science fiction (Bassett et
al., 2013), we can now say that this influence has been much stronger for ICTs than for
Biotechnologies. Blade Runner underestimated the pace of change in ICTs, to the point that it
does not forecast what has become the most significant innovation of the last decades,
namely the web. TV screens, GPS navigators, video-telephones pictured in the film are, by
contemporary standards, big and clumpy.
On the other hand, none of the innovations in Biotechnology has to the same extent
changed our lives. ICTs have created new companies and millions of jobs, and they have
transformed the operation of traditional industries such as retailing. Biotechnologies, in spite
of the massive investment in R&D, have not (yet?) produced the same effect. Biotechnology
has still to produce the general purpose technology equivalent to the microprocessor and it is
confined to a very narrow, niche collection.

3
 Schumpeterian insights

The idea that clusters of innovations generate phases of economic development is older
than Blade Runner. Marxist the Schumpeterian economists have for more than a century tried
to relate stages of development to the emergence and decline of different technologies.
According to this view, each historical period is dominated by the intensive and extensive use
of specific production technologies. These technologies may be fostered or hampered by
institutions and social beliefs, which often explain why they develop and are disseminated in
some parts of the world rather than in others.
Crucial to the Schumpeterian insight is that innovations do not have an economic
impact in isolation: they become dominant because they are applied in different contexts
shaping and transforming original ideas. Innovations could occur in different economic areas
(e.g. steam engine and textile machinery), but they are mixed and recombined in the
economic and social fabric (e.g. the steam engine provides power for textile mills). When the
new knowledge associated to a few emerging technologies starts to be diffused in economic
life, then it will generate a phase of economic expansion. New technological opportunities
manage to engender new industries that did not exist before, leading to job creation and
structural change. When the opportunities start to dry out, it is likely that there will be a lower
rate of economic growth or even an economic crisis.
Regular patterns are always difficult to be recognized, but Schumpeterian economists
have made an attempt to identify five phases of capitalist development, each associated to a
cluster of dominant technologies (Schumpeter, 1939; Freeman, 1984b; Mandel, 1995;
Freeman and Louçã, 2001). Chris Freeman (1992) and Carlota Perez (2002) have called these
major phases “techno-economic paradigms” by identifying their key characteristics in terms
of: i) core industries, ii) industrial organization, iii) modality to introduce innovations. Table
1 sketches the key characteristic of each techno-economic paradigm.
Why do we need these categorizations? The main purpose is to understand the
distinctive technological areas of a specific epoch and to trace their evolution. Archaeologists
have found it useful to classify ancient societies in Stone, Bronze and Iron Ages since the
techniques associated to each of these periods can explain quite a lot about their economic,
social and even cultural and political life.3 These ages do not necessarily occur
simultaneously: for example, anthropologists consider that aboriginal communities in

3
This periodization was originally suggested by the Danish archaeologist Christian Jürgensen Thomsen in the
1840s and since then it has been widely applied.

4
Australia lived in the Stone Age until the advent of the European colonization. It is
sometimes said that “uncontacted peoples” in remote parts of South America, Asia or
Oceania continue to this today to live in the Stone Age.
The French historian Bernard Gille (1978) has further developed the archaeological
approach by tracing the core “technical system” of each society. A technical system can be
identified on the grounds of the core technologies used in a society and, above all, on the
interconnections among various devices. This requires the development of human skills to
use the available techniques profitably, which in turn generates substantial changes in the
distribution of employment across the various sectors of production. Mutual interdependence
guarantees the coherence and the success of the overall economic and social system.
One of the core characteristics of development is that only a few previous technologies
become totally obsolete. The innovations introduced in the first industrial revolution continue
to be with us and it is difficult to imagine our life without simple technological artefacts such
as the myriad of mechanical devices that came to the fore during the Enlightenment. Of
course, several products and services were replaced by alternatives that have become more
popular: steam power has been substituted by the combustion engine and the combustion
engine will hopefully be replaced by solar power. The rate of change has been even faster in
communications: pigeon-post has been substituted by telegrams and telegrams by email.
There is no implication, of course, that the last method is superior to the previous one and
some very progressive societies have occasionally returned to techniques considered
obsolete. Cities like Amsterdam and Copenhagen, for example, are fighting to bring back
bicycles and trams in order to get rid of automobiles. But by looking at the techniques used, it
is possible to recognize each epoch and to distinguish the areas driving change.
The capitalist system in the last three centuries has made such development faster and
geographically comprehensive. Each phase can also be associated to the birth of firms with
rather distinctive typologies. These companies are likely to exploit the new technological
opportunities and organizational structures and become the distinctive institutions of the new
phase (see last column of Table 1). When Keith Pavitt (1984) suggested a taxonomy of
innovating companies destined to become very successful, one of his motivations was to
show Freeman and his followers that innovative companies, with their expertise and

5
competences, also need continuity. And, more importantly, that it was crucial to understand
the differences across firms in the way they introduced innovations.4
Even if originally designed to stress the importance of knowledge accumulation in
companies, institutions and nations, in one aspect the taxonomy of Pavitt contributed, perhaps
involuntarily, to the long wave theory: each category of companies he identified was born in
a specific stage. In a relatively short period of time, the emerging category became the
attractive form of economic organization. The first industrial revolution is associated to the
separation between traditional companies and producers of equipment, machinery and
instruments. The second industrial revolution saw specialized suppliers becoming the front-
runners of change. At the turn between the 19th and 20th centuries, a new typology of firm
emerged, based on a systematic exploration and exploitation of scientific opportunities in
industries as diverse as chemicals, electrical machinery and engineering. We are familiar with
the large companies based on Taylorism and Fordism that dominated most of the 20th
century. And, of course, we have seen in the last thirty years how information-intensive
companies, ranging from software producers to extensive users in banking and retailing, have
shaped our lives. Pavitt himself had to face the problem of how quickly change could occur:
information intensive firms rose to the limelight in just a few years. The category was absent
in the first formulation of the taxonomy and it had to be introduced later (compare Pavitt,
1984 and 1990).
Since Blade Runner was released, a few of these companies have become part of our
daily life: Microsoft (US$87 bn sales in 2014), Apple (US$42 bn), Google (US$66 bn),
Amazon (US$89 billion), Oracle (US$ 37 bn) and Facebook (US$12 bn) were all anticipated
by the imaginary Tyrell Corporation, perhaps also because, as predicted by Ridley Scott, they
continue to be associated to the vision of successful entrepreneurs. These relatively new and
fast-growing corporations do co-exist with established companies that have opened business
lines to exploit new opportunities such as HP (US$ 111 before the 2015 subdivision in two
corporations) or Sony (US$ 65). One of the most significant cases of transformation of an old
corporation is IBM, a company that has been in business for more than a century and that has
managed to remain big and leading-edge by progressively abandoning its hardware
component to embrace the emerging software services (Gerstner, 2002). This indicates that a
new and growing industry can be populated both by brand new companies and by companies

4
Pavitt drew on a variety of sources to build his taxonomy, including the organizational theory of Woodward et
al., 1965.

6
that have the resources and the competences to enter into the new field by reusing their
accumulated competences.
The new techno-economic paradigm is not just shaped by large firms. All the companies
mentioned, in spite of the invaluable contribution they have provided to the coming of the
information society, are not sufficient to shape our economic life: without a myriad of smaller
and often unknown firms, we would not be in a society that makes such an intensive use of
information. The fact that there is virtually no industry that does not benefit from ICTs shows
the degree of pervasiveness and integration today reached in the information society (what
David, 1990, and Bresnahan and Trajtenberg, 1995, and others have labelled general purpose
technologies).

Creative destruction or technological accumulation?

To move from one techno-economic paradigm to another one is often a traumatic

experience. Blade Runner describes a given society, but how smooth or traumatic is the
change towards that particular society? Economists have for a long time debated the relative
importance of the cumulative development of expertise on the one hand and the disruptive
nature of change on the other hand. Karl Marx compared capitalism to the ancient Greek
myth of the giant Antaeus, who was able to obtain new energy every time he fell down and
touched the earth (modern wrestlers have perhaps contributed to a better understanding of
Antaeus’ fighting skills). Marx underlined that capitalism needs economic crises to
reorganize its production, to demobilize capital from the industries with lower profit margins
and to reinvest it in the growing industries.
Schumpeter, an economist who was a fierce opponent of Marx but also among his
devoted readers,5 also stressed the importance of disruptive change, noting that it too was
associated to technological transformations. In one of his most quoted sentences – “Add
successively as many mail coaches as you please, you will never get a railway thereby”
(Schumpeter, 1934, p. 64) – he made it clear that radically new products and processes could
not be obtained by incremental changes only. Discontinuities were therefore needed to allow
the introduction of new technologies and these were also likely to produce crises in the

5
Schumpeter called his mentor Eugen von Böhm-Bawerk “the Marx of the bourgeoisie”. But, as noted by his
pupil Paolo Sylos-Labini, 1970, he would have been pleased to get such a nick-name for himself. On the
influence of Marx’s thinking on Schumpeter, see Elliott, 1980; Rosenberg, 2011.

7
economic space. Some could be confined to selected firms, industries, cities, regions or
nations; others were likely to have a broader impact.
Schumpeter also stressed that there was not only a process of reorganization of capital,
but that such a process was associated to individual agency. Schumpeter, an admirer of
Nietzsche as much as of Marx (on Nietzsche’s influence on Schumpeter, see Santarelli and
Pesciarelli, 1990; Reinert and Reinert, 2006), understood that changes occur not only because
there is an unanimated capital willing to grow, but because there are entrepreneurs, a sort of
Nietzschean overman in the economic sphere, that search and exploit new opportunities. It is
out of these animal spirits, as Keynes (1936, pp. 161-162) labelled them, that inventions are
transformed into innovations and eventually diffused up to the point that they shape
economic and social life.
The problem is therefore to understand which players will be able to grasp these
opportunities. On some occasions they are associated to new, successful entrepreneurs: the
automobile industry was shaped by Henry Ford and the electricity business by Thomas
Edison. It would be difficult for us to imagine an information-based society without thinking
of the rise of companies such as Microsoft, Apple, Oracle, Google, Amazon and Facebook
and we associate them with entrepreneurs such as Bill Gates, Steve Jobs, Larry Ellison, Larry
Page, Sergey Brin, Jeff Bezos and Mark Zuckerberg. These entrepreneurs understood earlier
and better than others that the supply of information could become much larger than
conceived in the past and that, in spite of the fact that its cost per unit would drop by orders
of magnitude (compare the cost of a telegram to the cost of an email), new technological
opportunities were so huge that the overall market would grow.
On other occasions established firms, which have already accumulated organizational
resources, labour and capital, are the first to understand that winds are changing and to adjust
to the new paradigm. If they do not manage to do that, they are likely to be locked into their
own existing market and to decline with it. If, on the other hand, they manage to use their
skills and competences to explore new opportunities, they may jump into a new profitable
business. Take the case of Eastman Kodak and Fujifilm, two companies competing on the
same core market, photographic film (The Economist, 2012; Gebremeskel, Tesfaye and
Nguyen, 2012, Nonaka et al., 2014). The former has not managed to adjust to the digital
revolution in photography; the latter has done so and, exploiting its knowledge of consumers
and markets, has successfully managed to jump into a new technological paradigm, becoming
a leader in digital technology.

8
 Change is therefore driven not only by disruption but also by continuity. Disruption
does not necessarily lead to progress or to greater economic efficiency, and if it is not
properly managed it can lead not only to company losses, but to societal damages as well.6
Competences and skills are needed to upgrade production, and they are often accumulated by
individuals and organizations in years and years of experiments. The potential of creative
destruction should be compared to that of creative accumulation, which assumes that
individuals and organizations with an appropriate stock of competences are better positioned
to introduce successful changes.7
Nelson and Winter (1982) and Malerba and Orsenigo (1995) have already taught us that
there is no reason to assume that either creative destruction or creative accumulation can
explain the process of change in all industries. Table 2 compares the characteristics of the
models of creative accumulation and creative destruction to show that there are cases in
which each of the strategy may allow companies to prosper. In the creative accumulation
model, large firms systematically exploit new technological opportunities as a method to
maintain their market shares and to keep outsiders out of business. In the creative destruction
model, major innovations are introduced by small companies that become big precisely
because they have won the bet on the potential of their new products and processes. It is not
difficult to find examples in business history where successful companies prospered
according to each of the two models. But are these models equally suited to identifying the
companies that will, hopefully, lead the economic recovery?

Who is investing in innovation after the 2008 economic crisis?

Much has been written about the origins of the economic crisis and there is not yet a
consensus on either its causes or its consequences. In less than a decade, we have witnessed
both the 2001 financial bubble mostly associated to the difficulty of ICTs to keep up with
speculative expectations, and the 2008 economic crisis originated in a traditional sector, such
as housing. Besides the fuse that has generated the crisis, is it possible to identify underlying
structural causes? We have learnt from Keynesian economics (see Kindleberger, 1978, and
Minsky, 1986) that the detonator of major economic crisis is often the financial market. The
speculative tendencies of the financial markets could be tamed by good regulations. Finally a

6
The disruptive effects of innovation, praised by Christensen (1997), have been critically addressed by Lepore
(2014).
7
One way to assess the relative importance of accumulation and destruction is to look at companies’ case-
studies. See, among others, Tripsas (1997) on the typesetter industry.

9
lender of last resort helps to avoid the deepening and the dissemination of adverse
consequences.
The Kindleberger-Minsky model is also able to explain the 2008 events (see Shiller,
2008): speculative trends in the financial markets were not contrasted by regulation (at least,
not in the United States), but the willingness of governments and central banks to act as
lenders of last resort has helped to prevent a deepening of the crisis. But can the crisis, or at
least the difficulty to get an effective and timely economic recovery, also be associated to the
drying out of technological opportunities and, therefore, to the difficulty to sustain the
expectations of a high and steady growth rate? In other words, is there a real economic
explanation in the rate of innovation that could integrate the sole financial analysis of the
crisis?
According to a pessimistic view, it is difficult to foresee technological opportunities
comparable to those that the world economy experienced in the 1950s and 1960s. The rate of
economic growth of these decades (what Angus Maddison, 1992, labelled the golden age) is
likely to be unique in history. Gordon (2012) maintained that “the rapid progress made over
the past 250 years could well turn out to be a unique episode in human history”. More
optimistic views claim that technological opportunities are still there, and they can guarantee
new jobs and new prospects, provided the economic and social systems allow for their
introduction and diffusion (Perez, 2013; Mokyr, 2013).
Eight years on from the beginning of the economic crisis, and when a few signs of
economic recovery are emerging, the core question is: in which direction will the world
economy grow? Which industries and technologies will take the lead? These are the core
issues discussed by policy makers, business leaders and public opinion. Perhaps economists
of innovation should also provide some insights.
The first way to explore this is to check the willingness of economic players to bear the
costs and risks of innovation. Since investment in innovation is a bet on the future, firms
invest in new and improved products, processes and services when they expect that they will
be able to repay the costs thorough successful market reception. We already know that
innovation, more than other forms of investment, is an uncertain activity. Some projects may
manage to introduce successful innovations that will repay several times over the initial costs,
while others may not succeed in generating commercially successful innovations at all. In
spite of this, businessmen’s willingness to invest in innovation indicates a propensity not only
to bear risks, but also to play the game. And, without playing, there will never be winners.

10
 The research that Andrea Filippetti, Marion Frenz and I have carried out has tried to
identify businesses’ reaction in terms of innovation investment as a consequence of the 2008
financial crisis (Archibugi et al., 2013a; 2013b). Using Eurobarometer data, we have
identified three groups of enterprises according to decisions to decrease, maintain or increase
innovation investment from 2006 to 2009. The number of enterprises that decreased their
innovation investment moved from less than 10 per cent in the pre-crisis to 27 per cent after
the crisis. This is hardly a surprising result: in the middle of the credit crunch and with
gloomy business opportunities, companies may be tempted to reduce all costs, including
investment or be forced to do so to preserve some earning and hence share prices. The
behaviour of these enterprises may lead to the deepening of the recession: Keynesian
economics has shown that a reduction of investment depresses aggregate demand, and
Schumpeterian economics has indicated that a reduction in the rate of innovation may lead to
stagnation.
Those that are confident in the virtues of technological accumulation would be
reassured to discover that as many as 60 per cent of enterprises kept their innovative
investment unchanged: there is an innovative routine that it is not affected, not even by major
events such as the 2008 financial crisis (before the crisis, about half of the enterprises
reported steady innovation investment). For most economic organizations, steady knowledge
accumulation is vital to their survival. The number of enterprises that behaved anti-cyclically,
i.e. that increased innovation investment after the crisis, is comparatively small: 9 per cent
only. If we compare it to the fact that before the crisis as many as 40 per cent of enterprises
were increasing their innovation investment, we can really appreciate how the decision to
expand innovation may be affected by adverse events. Could such a small number of daring
enterprises have a “detonator” effect on the whole economy?
Here lies a fundamental difference between investment in general and investment for
innovation in particular, a difference that is implicit in the Schumpeterian tradition and never
properly assimilated by Keynesian economics. While investment in general is a steady
proportion of aggregate demand, investment in innovation has unpredictable economic
effects. A few successful innovative projects may have the Schumpeterian band-wagon
effect, generating jobs, profits and structural change that could potentially revitalize the
whole economy. The innovation multiplier can be much larger than the investment multiplier.
The effect of the innovation multiplier is not equally distributed across the economic space,
and we see that there are exceptional agglomerations in selected cities, regions and nations. It

11
is no surprise that the areas with the most sustained economic growth rates are also those
which have first entered into the innovative driving sectors.
In some European countries, the number of companies that have maintained or even
increased innovative investment is greater than the number of companies that have reduced it.
Within Europe, the most innovative nations, such as Sweden, Switzerland, Finland and
Germany, were the least affected by the crisis. This might also be the result of other
institutional factors such as their rather conservative banking regulation compared to that of
liberal market economies. Nevertheless, these countries cannot avoid continuing investing
since they are highly specialized in areas where you innovate or perish. If they stop
innovating, they may be forced out of business.8
It would be important to compare Europe with other continents. In a large national
innovative system such as the USA, knowledge-intensive states such as California have also
increased their R&D expenditure after the economic crisis, while other and less innovation-
intensive states have reduced it. In emerging economies, including China and India, the
growth of innovation-related activities has been so phenomenal that the presence of an
economic crisis from time-series statistics on R&D or patents can hardly be noted. One of the
consequences of an economic crisis is also to accelerate change across areas, and we are
aware that, at the end of the economic crisis, the OECD member countries will have to
compete withmore assertive and more capable emerging areas.
The profile of the innovators becomes fundamental to predict what the overall
economic impact of the investment will be. Who is likely to generate new ideas and introduce
innovations? In other words, who will “swim against the stream”? Our data associate these
enterprises to the following traits:

 They tend to be of small size.

 They had an R&D department before the crisis.
 There are a high proportion of young enterprises (created after 2001).
 They combine innovation with the exploration of new market opportunities.
 Their competitive strategy is more likely to be based on products than on costs.9

8
These findings are consistent with Amore (2015), who has shown that companies manage to capitalize their
innovative routine also in bad times.
9
Our data only accounts for surviving enterprises and therefore not able to detect those that may fail after a
short period. But other evidence corroborates the intuition that small innovative companies have a lower
survival expectancy. See Buddelmeyer, et al., 2009; Dosi et al., 2008.

12
 Eurobarometer data is not particularly robust since we have an indication of the trend
but no real data on how much is being spent on innovation. However, data based on the
Community Innovation Survey for the UK seems to confirm this picture (Archibugi et al.,
2013b), in particular in terms of a greater concentration of innovative resources in fewer
companies. In other words, there are signs that suggest that recovery will be led by creative
new enterprises rather than by incumbent ones. This will confirm the idea that during crises
radical new opportunities are less likely to be exploited by the incumbents, while newcomers
may find the energy and the willingness to challenge the current steady state (Dosi et al.,
2008). We have detailed an identikit of the innovators: but where they will innovate?

Where are emerging technological opportunities?

Already in The coming of post-industrial society, Daniel Bell (1973) predicted that
information would replace goods as the leading product and that service industries would
replace manufacturing as the major employer. In the same vein, Toffler (1980) tried to
identify the set of technologies that would serve a post-industrial society. Both the predictions
were fulfilled but this, in turn, required some tools able to assess the economic and social
impact of emerging technologies.
Dosi (1982) and Freeman (1992) made an attempt to classify technologies that could
determine a genuine revolution. In the early 1980s, Freeman (1984a) identified five criteria to
identify the emerging technologies of greatest impact. The criteria he used were the
following:
1) Drastic reduction in the costs of many products and services.
2) Dramatic improvement in the technical characteristics of many products and
processes.
3) Social and political acceptability.
4) Environmental acceptability.
5) Pervasive effects throughout the economic system, i.e. the potential to become what
was later labelled as general purpose technologies.
Using these criteria, it was rather easy for him to predict that micro-electronics were
going to become the back-bone of the coming techno-economic paradigm, while the
economic and social impact of nuclear technology, considered by some commentators the
would-be leading innovation, was grossly exaggerated.
13
 Business analysts invest much time in exploring market and technological
opportunities.10 A recent and very detailed attempt to identify and explore new technological
opportunities was released by the McKinsey Global Institute (Manyika et al., 2013). They
have tried to identify the core technologies that are expected to have a major impact by 2025.
The four criteria they used are:

1. Technology is rapidly advancing or experiencing breakthroughs.

2. The potential scope of impact is broad.
3. Significant economic value could be affected.
4. Economic impact is potentially disruptive.

As it can be seen, after thirty years McKinsey follows very closely the Schumpeterian
tradition as exposed by Freeman (1984a), Perez (2002) and Dosi (1982).
The top technologies identified by the McKinsey foresight for substantial growth are all
in the ICT area (see Table 3). The top four, Mobile Internet, Automation of knowledge work,
Internet of Things and Cloud technology all belong directly to the ICT cluster. The next two,
Advanced robotics and Autonomous vehicles, only seemingly belong to the Machinery and
Transport industries since the core innovative component is software. The next six emerging
technologies are predicted to have a lower economic impact, but are also associated to a
broader knowledge base. Amongst these we find, for example, Next-generation genomics, the
fundamental component to implement the Blade Runner’s Replicant, Advanced materials and
issues associated to energy production and distribution such as Energy storage, Renewable
energy and Advanced oil and gas exploration. 3D printing, so heavily based on software,
seems to be another important extension of the information society.
Science and technology indicators provide a rather similar picture. If we concentrate on
the two clusters of ICTs and Biotech, we find that patent applications in 1981, at the very
early stage of both technologies, were 1,000 in ICTs and 119 in Biotech. Both fields have
grown exponentially, and in 2012 there were as many as 60,000 in ICTs, while they were less
than 10,000 in Biotech (see Figure 1). These numbers confirm the impression that while ICTs
have become a general purpose technology, developed by companies belonging to a variety
of different product industries and used in an even larger number of applications, Biotech are
still confined to specific products and areas, notably human health and food. The profit-

10
For a recent scholarly attempt of what is meant by “emergent technology”, see Rotolo et al., 2015. Most of the
attempts here considered were based on intuition more than on rigorous analysis.

14
seeking community, as represented by the patents taken out, has clearly absorbed greater
investment and is still generating more optimistic expectations in ICTs than in Biotech. The
problem with technology indicators, however, is that they may report what is already in the
pipe-line rather than the innovations that will powerfully impose their potential in the future.
Data from scientific publications, which are more likely to reflect the activities promoted by
the academic community and the public sector, shows a different picture: the Web of Science
reports more than six million publications with the word DNA and just over one and a half
million with the word semiconductor. Is this evidence enough to infer that academic research
has already moved in another direction?
If the trends of technology indicators and the prediction of McKinsey prove to be
accurate, the next decade will continue to be dominated by the ICT techno-economic
paradigm while the Biotech cluster will account for 5-10 per cent of the expected economic
potential of new technologies. We could expect a consolidation and a deepening of the
current paradigm rather than the emergence of radically new technologies. Biotech,
anticipated as an emerging industry, and not only by Ridley Scott (see Orsenigo, 1989) may
still have to wait its turn since, so far, it has not fulfilled the optimistic expectations.
Economists of innovation soon recognized the very peculiar characteristic of the Biotech
industry and four factors were singled out (see Pisano, 2006). First of all, the major
breakthroughs were generated in universities and in publicly funded research centres. Second,
the business sector, often a direct filiation of academic staff, was very fast in exploring its
commercial potential. Third, the industry found new forms of financing based on the
expectations that research could bring new and successful drugs to the market (Orsenigo,
1989). Fourth, the lag between R&D to product innovation has proven to be longer than what
was originally expected. The fundamental scientific advances which occurred several years
ago have not yet been capitalised on in terms of sales, profits or job creation and have not led
to a distinctive typology of companies.
What has happened to the pioneering companies in the area seems to confirm this
impression: most of the ground-breaking companies in Biotech have been acquired by other
and larger companies: Genentech was eventually fully acquired by Hoffmann-La Roche in
2009, Genzyme by Sanofi in 2011, indicating that the main output, so far, has been
knowledge rather than products. The leading companies in the industry have not grown in
terms of new products in the market, but rather have been acquired by already very large
firms because of their competences. The business leaders in ICTs, such as Microsoft, Google
and Facebook, have followed an opposite pattern: they started as small companies and have
15
grown to their current size, up to the point that they had the resources to acquire fast-growing
companies based on new ideas and technologies such as Skype, Android and WhatsApp. The
creative destruction of the ICT industry, which dominated for nearly three decades, has
turned into creative accumulation, with the grown-up companies able to scan and exploit new
opportunities, including through the acquisition of small and emerging companies. This
suggests that the dominant techno-economic paradigm is now being consolidated through
adoption, development and diffusion.

Questioning the Coming Paradigm

One of the key characteristics of disruptive technologies is that they do not knock at the
door: they enter social and economic life unexpectedly. To look at R&D expenditure by
considering patents taken out and scientific publications alone could be misleading since they
point to a Schumpeterian swarming that is already at an advanced stage. Business reports
show that in 2014 the Biotech industry reached all records compared to its past performance
in terms of R&D expenditure and net income (see Ernst and Young, 2015). Even if their
overall economic impact is not yet comparable to ICTs, these new opportunities could play
an unexpected role, especially if properly combined with ICTs. In the past we have seen how
steam power and mechanical engineering, synthetic materials and electrical machinery
evolved simultaneously. Should we expect a new alliance between ICTs and Biotech?
Theodor Adorno warned us that “life does not live”. Paraphrasing him, technological
opportunities do not enter into economic and social life without deliberate efforts and
choices. We should be able to envisage new forms of organization that could be associated to
emerging technology. ICTs have already changed our lifestyle even more than our economic
life: they have generated jobs and profits, but above all they have transformed the way we use
our time and interact with the world. Biotech could have even greater radical social
transformations at the core of our life. Why have these not yet been delivered? What can be
done to unleash their potential? There are a few basic questions that need to be addressed.

 Investment in Biotech has mostly been carried out by business corporations. Universities
and public laboratories, in spite of the fact that they originated scientific advance, are
today second in line. As noted by Pisano (2006), a science-based industry with a very long
gestation period before the new discoveries are transformed into products may encounter
major problems if it is driven by profit-seekers. Many of the new openings in Biotech are
16
 either kept confidential or patrolled by intellectual property rights and this may delay the
diffusion of knowledge. In an area where most advances are interrelated, public sharing
could be crucial to avoid dead-ends. Is profit-driven research today obstructing the
industry’s potential?

 If more active public and non-profit research is needed, how should it be integrated with
market-oriented research? A revision of the current division of labour between public and
private players may be needed. The triple-helix model (Etzkowitz and Leydesdorff, 2000)
has somehow blessed the idea that the leading dancer in innovation should be the business
sector. Should we give universities and public research centres greater responsibility in the
effort to disseminate and distribute the knowledge to final users?

 To what extent could the full potential of Biotech emerge if properly integrated with the
dominant general purpose infrastructure, i.e. ICTs? Is there the possibility that Biotech
will manage to reinvigorate what has already been delivered by ICTs? In the past, cross-
fertilization has multiplied the benefits of new technological opportunities. Can we
forecast a successful alliance between ICTs and Biotech?

 And finally, there is also the problem of identifying the impact of new technological
opportunities. Do we have appropriate indicators to measure their economic impact in a
changing context? So far, we have mostly concentrated on economic indicators, such as
employment, sales and profits. These indicators are certainly crucial for business
performance, but they need to be integrated with others able to account for their social
benefits. The rise of Biotech may be one of the cases that force us to assess the potential of
radically new innovations also through social indicators, such as life expectancy or quality
of life. If we do, perhaps we may be forced to re-evaluate the relative impact of Biotech
and ICTs.

Back to cinema?

As usual, cinema has been quick to forecast some of these opportunities:

Transcendence by Wally Pfister already describes the perfect integration of Biotech, ICTs
and another emerging technology of the 21st century, nano-technology. This science fiction

17
film has taken into account the reality of geometrical expansion of nano-technologies and its
capacity to be as pervasive as ICTs have been in the last thirty years. Location should be
noticed: like Blade Runner, the film takes place in California, although the final parts, those
devoted to the birth of revolutionary innovations, have been set in New Mexico, an area
envisaged to become the leader from scratch. A suggestion that seems peculiar if the size and
the absolute amount of R&D expenditure is taken into account, but that might seem less
extravagant considering that New Mexico has the highest R&D to GDP ratio in the USA (as
high as 8 per cent, see National Science Foundation, 2014, chapter 8, table 8-40).
Transcendence is suggesting that the integration of various domains of knowledge
could be crucial and this will perhaps be another case where science fiction is able to provide
inspiration to captains of industry, scientists, bankers and politicians; sometimes science
fiction may be pioneering and act as the source for suggestions to be implemented in the real
word (see the challenging review on the interactive relation between science fiction and
innovation by Bassett et al., 2013). The film shows that quality of human life could change
substantially and the next major advances to shape our lives will not be associated to our
ability to connect everywhere and with everybody, but to better understand how our bodies
work and how to use this information to increase our well-being. Portable devices that tell us
instantaneously when it rain this afternoon are already installed in the mobiles that we have in
our pockets, and there are apps teaching us how to prevent diseases in different environments.
Soon new devices will be able, on the ground of our genome, to inform us on the effects of
every single event in our organism and possibly even to fix it. Through the exploitation of big
data, new challenges such as growing urbanization, ageing population and environmental
risks could also be addressed through more advanced instruments.
If I watch Blade Runner again with my grand-children, my forecast is that they will be
totally unimpressed by the innovations in both ICTs and Biotech, as an artificial cat tries to
jump over their lap. I bet that my grand-children will note with wiseacre attitude that the film
underestimated progress by all accounts since the real advances will be occurring in nano-
technologies or in areas for which I will have no understanding. When they pet me as the
thick and dumb grandfather, I will shield myself with an evergreen lesson: economists,
futurologists and business analysts often get it wrong. But artists, real artists, always get it
right.

18
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Table 1 - Phases of Capitalist Development and Pavitt's Categories of Firms

Period Successive Industrial organisation Typical industries Rise of Pavitt's

Techno-Economic Paradigms category of firms

1770- Growing importance of Textiles, Potteries, Supplier

1830 Early Mechanisation small Machinery dominated
manufacturing firms

1840- Separation been producers Specialized

1880 Steam power and railway of Mechanical engineering, suppliers
capital and consumption
goods Steel and Coal

1890- Opportunities associated to

1930 scientific discoveries Emergence of large firms Chemicals, Electrical Science based
machinery, Engineering

1940- Fordist and Taylorist Oligopolistic competition Automobiles, Synthetic

1980 revolutions for products, Scale intensive
mass consumption Consumer durables

Information and Information

1980- communicaiton Networks of firms, strong Microelectronics, Telecoms, intensive
2010 user-producer interactions Software

Source: Author's Elaborations on Freeman (1987), Table 15. Last column derived from Pavitt
(1984; 1990).

23
Table 2 - Innovative firms’ characteristics under the creative accumulation and creative destruction models

Categories Creative accumulation Creative destruction

Characteristics of the Innovations are driven by large, incumbent firms that Small firms, new entrants are the key drivers in the
innovating firms seek new solutions through formal research exploiting innovation process. They use innovation and
their pre-existing capabilities. economic turbulence to acquire market share from
incumbent firms.
Type of knowledge High relevance of past innovations and accumulated Greater relevance of collaborative arrangements
sources knowledge. Importance of formal R&D, in-house but also leaning towards the applied knowledge base (other
jointly performed or externally acquired. firms). Exploration of new markets and technological
opportunities.
Type of innovations The innovation process is dominated by a large number of The emphasis is on path-breaking innovations often
incremental innovations. able to create new industries.
Organizational routines dominate the generation of New organizational forms contribute to generating
innovations. innovations.
Characteristics of the Barriers to entry are high due to relative importance of Low barriers to entry into the new industries. A high
market appropriation and accumulation of knowledge and high rate of entry and exit leads to low levels of
costs of innovation. Dominance of oligopolistic markets. concentration and high competition. Discontinuous
Technological advancement based on path dependent and technologies are available that generate growing
cumulative technological trajectories. markets and new opportunities.

Source: Archibugi and Filippetti (2011) on the ground of insights of Freeman (1984a; 1992), Dosi (1982); Pavitt (1984; 1990), Malerba and
Orsenigo (1995).

24
Table 3 – Estimated potential economic impact of technologies from sized applications in 2025,
including consumer surplus $ trillion, annual to 2025

Technologies Estimated impact

Min Max
1 Mobile Internet 3.7 10.8
2 Automation of Knowledge work 5.2 6.7
3 Internet of things 2.7 6.2
4 Cloud technology 1.7 6.2
5 Advanced robotics 1.7 4.5
6 Autonomous vehicles 0.2 1.9
7 Next generation genomics 0.7 1.6
8 Energy storage 0.1 0.6
9 3D printing 0.2 0.6
10 Advanced materials 0.2 0.5
11 Advanced oil and gas exploration 0.1 0.5
12 Renewable energy 0.2 0.3
TOTAL 16.7 40.4

Source: McKinsey Global Institute (2013)

25
Figure 1 – Patents in ICTs and Biotech, 1980 - 2012

Source: OECD database, elaboration on Patent Cooperation Treaty by year of application,

26