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From Bio to Nano: What Can We Learn From 20 Years Experience of Biotechnologies?

A Triple Helix 5 Workshop proposed by:

Vincent Mangematin,


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:


Introduction: Nanotechnologies, 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 revolution?

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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Grant RB. 1996. Prospering in Dynamically-competitive Environments: Organizational capability as Knowledge Integration. Organization Science 7(4): 375-387

Mangematin V, Lemarie S, Boissin JP, Catherine D, Corolleur F, Coronini R, Trommetter M. 2003. Sectoral system of innovation, SMEs development and heterogeneity of trajectories. Research Policy 32(4): 621-638

Powell WW, Koput KW, Smith-Doerr L. 1996. Interorganisational collaboration and the locus of innovation : networks of learning in biotechnology. Administrative Science Quarterly 41: 116-145
Rip A. 2002. Regional Innovation Systems and the Advent of Strategic Science. Journal of Technology Transfer 27: 123-131

Teece DJ, Rumelt R, Dosi G, Winter SG. 1994. Understanding Corporate Coherence : Theory and Evidence. Journal of Economic Behavior and Organisation 23(1): 1-30






Triple Helix Conference I Amsterdam, 1996 II New York, 1998 III Rio de Janeiro, 2000 IV Copenhagen, 2002 V Turin, 2005 VI Singapore, 2007 VII Glasgow, 2009 VIII Madrid, 2010 IX Stanford, 2011 X Indonesia, 2012 XI London, 2013
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