Bio to Nano: What Can We Learn From 20 Years Experience of Biotechnologies?
A Triple Helix 5 Workshop proposed by:
Nanotechnology will soon become
a household word. It is a leading-edge technology that will revolutionize
many sectors of manufacturing over the long-term. Nano S&T
combines two complementary processes: miniaturization of components,
based on nano materials and nano electronics and construction
of nano devices based on the manipulation at the atomic level.
Both processes involve understanding and control of matter and
processes at the atomic and molecular level – building atom
by atom. Nano S&T refers to science and technology which are
able to assemble, manipulate, observe and control matter on length
from one nanometre up to 100 nanometres or so. Nano S&T is
the construction and the use of functional structures designed
from atomic or molecular scale with at least one characteristic
dimension measured in nanometre.
Nanotechnology could affect the production of virtually every
human-made object – from automobiles and electronics to
advanced diagnostics, surgery, advanced medicines, and tissues
and bone replacements. To build electronic devices using atom-by-atom
engineering, for example, it is necessary to understand the interaction
among atoms and molecules, how to manipulate them, how to keep
them stable, how to communicate signals among them and how to
face them with the real world. Thus, nanoscale science and nanotechnology
not only lead to a renewal of various industry, they also lead
to another breakthrough invention of a method of inventing with
the potential to drive technological progress which affect leading
high tech sectors like biotechnology, micro-electronics and NTICs.
The present situation is somewhat analogous to that of biotechnology
and genetic engineering—a field that, 15 or 20 years ago.
Few people could define what biotechnology was, even fewer could
envision how the biotechnology industry would fundamentally change
the development of drugs and diagnostics. Nano S&T is 15-20
years younger than biotechnology but so far following a similar
growth trajectory. Just as in biotechnology in its infancy, in
nano S&T investments are based on anticipations and promises
from both public authorities and private investors. According
to H.P. Buff , total public investment for nanotechnology for
2002 is estimated over than $2.3 billion, mostly by Japan, US
and EU. Firms from different sectors are involved in nanotechnogy
R&D. Large incumbents in micro-electronics (Philips, STM,
Motorolla, etc.), in informatics (IBM, HP, etc.), in materials
or biotechnologies are investing as well as science based dedicated
start-ups. The Industry organisation of the emerging sector is
still unsettled. And, actors are event more diverse than in biotech
as nano S&T assemble different scientific fields i.e. chemistry,
physics, engineering sciences, biotechnologies and life sciences
and various technological competencies such as materials, software,
tools, devices and nanobiotech.
The session focuses on strategic management of emerging activities,
by private firms, stakeholders and public authorities. It aims
at exploring the lessons which can be derived from the biotech
experience. This session presents contributions communications
dealing with the emergence of new industries:
a remake of the US domination in the near future? Ph. Laredo
US has been leading the biotech industry since the very begin as
the academic sector was successful in producing and transferring
breakthrough innovation. What will happen with the new grilichian
||1. Development of high tech and project based organising,
S. Blanco, B. Deschamps, C. Genet and V. Mangematin
The integration and the economic
valorisation of knowledge represent one of the key challenges
in the knowledge society. It is particularly true for science-based
industries like biotechnology. Knowledge integration has always
been important at the firm level (Grant, 1996). In the resource
base perspective, the integration of knowledge, whatever is scientific
or managerial is linked to the performances of the firm that gains
competitive advantages if the resources can be integrated into
a set of mutually supportive resource bundles (Teece et al., 1994).
There is an explicit tension between project-based organisation
and the traditional organisational form of the firm. The integration
of knowledge supposes a stable community of people who are sharing
space and routines while project based organisations are labile
by definition. Powell et al. (Powell et al., 1996) note that learning
occurs across firms and within networks. They underline that the
specificity of the biotech sector because of the tension between
formal and informal and between levels and types of knowledge
integration. However, knowledge integration capacities remain
in formal organisations. To understand the dynamics of development
of the biotech sector, and the challenges that biotech firms are
facing, it is necessary to analyse the different pathways or business
models (Mangematin et al., 2003) that firms can follow and their
implication in term of knowledge integration: knowledge integration
in high growth firm model; knowledge integration by other actors
when firms fail, and knowledge integration in firms which are
bought out. The sustainability of new forms of organisation depends
on their capacity to integrate knowledge and to exploit it commercially.
Although knowledge has been an important research avenue for almost
15 years, little detailed work has been performed on knowledge
integration. New organisational forms, in particular project-based
organising, and their evolution linked to the maturation of the
biotech industry are important to analyse so as to understand
the existing integration capabilities and the creation of new
ones. Based on comparative case studies, this paper analyses the
conditions under which project-based organising can be a sustainable
organisation in high tech sectors.
|2. Leadership and emergence of Science districts: Comparison
between Minatec and Imec, Aurélie Delemarle, LATTS, ENPC
To understand the mechanisms
of location and the aggregation process of firms and academic
(public or national) labs or research teams, it is necessary to
better know what are the forces at stakes within a Science District
(SD) at different stages of development, in different contexts.
The history of a specific geographic area, of its universities
and its scientific involvement in microelectronics, biotechnology,
informatics or instrumentation may explain the initial location.
However, similar initial configurations (leading scientists, presence
of firms, entrepreneurial culture, etc.) may generate different
trajectories in which the process is self-reinforced or not. Rip
(Rip, 2002) emphasises the main dynamics of the constitution of
geographic agglomeration: national and regional top-down policies
to encourage the emergence of specific clusters on the one side
and local bottom-up dynamics based on localised knowledge spillovers
on the other. In these approaches, the strategies of large firms
to localise their research are often underestimated as well as
the dynamics of evolution of the ‘clusters’.
What are the advantages for large firms in locating R&D and
innovation (RD&I) activities in a SD? Is it an initial source
of growth for newly created firms? What role does the convergence
of anticipations amongst actors play? They also suggest that the
weight of geographic proximity changes as the industry matures.
To what extent then is the sustainability of firms linked to “local”
networking? To what extent does being in a science district lead
to a rapid evolution of organisation in SMEs? What are the very
advantages of the proximity and how do they differ for large and
small and medium enterprises?
Different actors play a role in the constitution and consolidation
of science districts. Comparison between two emerging science
districts in nanotechnologies allows us to identify different
configurations of actors in which the leadership can be either
public or private, local or national.
|3. Tracking the emergence of nanotechnologies: Knowledge
creation, knowledge circulation and technological trajectories,
Thomas Grid, M. Zitt
This paper presents new methods
and indicators to track the emergence of new fields and new related
sectors. It develops a method for tracking and analysing the emergence
of a new field and tests the hypothesis of agglomeration dynamics
in new fast growing fields in the case of nanotechnology.
Bonaccorsi (2003) proposed three main features of field evolution
to characterise "search regimes" in a synthetic way.
This renews the classic Price’s analysis of science dynamics.
The paper tests the three main characteristic of search regimes
i.e. growth rate, divergence/convergence and complementarity through
bibliometric analyses (patent and publication analysis). It delineates
the domains and sub-domains, relative rates of growth (with reference
to part of, or all SCI-covered science) and divergence and complementarity
of science in technology with nanotechnologies.
|4. Start-ups, firm growth and consolidation of the industry,
A. Lunakova, E. Avenel, F. Corolleur and C. Gauthier
This paper analyses the interplay
between firm creation, firm growth and the consolidation of an
emerging industries. Based on the European biotech example which
demonstrates significant economic activity derived from spin-off
and start-up firms, the aim of this paper is twofold: to develop
and test a methodology to modelise the interplay between firm
creation, firm growth and the consolidation of the industry on
the one hand and to identify the determinants (proximity to the
centres of excellence, proximity to the demand, diversity of the
existing knowledge based, diversity of the partnership, etc.)
of the SME growth on the other hand.
In high tech sectors like in biotech or nanotech, what are the
determinants of SME growth and survival as compared to the determinants
of growth and survival in other, more traditional sectors? Is
there a specificity of the life cycle for firms operating in emergent
sectors? If so, what are these specificities?
Four longitudinal databases are combined : economic database of
the life science sector, firm location, firm size, etc; database
on biotech firms, from their creation up to now displaying a large
set of data, including financial data, publication and patent
data; mapping of the density and diversity of knowledge production
within regions, and economic data for a control sample of firms.
This paper presents quantitative analysis mapping.
|5. Networks of start-ups, networks of incumbents: from
bio to nano, B. Kahane, V. Mangematin and S. Jensen
In knowledge intensive industries, the access of external knowledge
has been critical. Firms benefited from knowledge leakages and
flows and they have developed dense networks of collaborations,
mixing a large variety of partners such as universities, research
centres, small and large firms along several activities i.e.
research, development, production activities or marketing. The
increasing number of alliances has inspired significant academic
work on why firms enter into alliances: to monitor the market
- to overcome market failures or to increase market power, to
learn from other organisations, to have access to complementary
assets or technologies. Alliances are also seen as a mean to
enhance new capabilities : creating legitimacy, building new
competencies, entering new markets or new technologies. Finally,
alliances are a way to share risks and costs in uncertain environment.
In addition to the question of why allying, lies the question
of who is allying with whom.
Technology Life Cycle theories exhibit two major phases in industry
development. The first phase is characterised by radical and
rapid technical change (emergence) and the second phase (consolidation)
reveals some sort of technological consolidation and stabilisation
around a dominant design. During the first phase, scientific
and technological hypotheses have to be explored. In science
based sectors, the emergence period is characterised by the
scientific exploration of different scientific and technological
results and trajectories. Research and development agreements
with universities and with dedicated biotech SMEs are designed
to have access to a large diversity of knowledge bodies, to
explore a wide variety of hypotheses and to design innovative
products and processes based on radical innovation.
Technology and firm life cycles are intimately intertwined and
they influence the industry life cycle. At the early stage of
the industry, the emergence of the industry is based on the
entry of a large number of new firms. Indeed, during the emergence
phase, new ventures are devoted to the exploration of new scientific
and technological opportunities and a new organisation of the
industry emerges based on a fluid and evolving community. As
the technological conditions change and as the industry consolidates,
technological trajectories appear and firms innovate within
given trajectories. The degree of novelty is reduced compared
to its former level. Firms develop incremental innovation combining
existing technologies that they acquire through networking in
a recent past. The rhythm of creation of new ventures is reducing
and the consolidation of the industry leads to firm failures,
mergers and acquisitions.
This co-evolution of technologies, firms and networks was true
in biotechnology where development of new processes and products
were science based. In nanotechnologies, most of developments
require large research facilities, like large clean rooms, synchrotron
or large scale equipments.
Based on case studies, this paper explores the patterns of networks
in nanotechnologies and the extent to which science and technology
networks works in the same ways.
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