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Between Technology and Science:

Exploring an Emerging Field: Knowledge Flows and Networking on the Nano-scale

by

Martin S. Meyer

ISBN: 1-58112-253-5

DISSERTATION.COM

Boca Raton, Florida USA • 2005

Between Technology and Science: Exploring an Emerging Field: Knowledge Flows and Networking on the Nano-scale

Copyright © 2003 Martin S. Meyer All rights reserved.

Dissertation.com

Boca Raton, Florida USA • 2005

ISBN: 1-58112-253-5

MARTIN STEPHAN MEYER

BETWEEN TECHNOLOGY AND SCIENCE EXPLORING AN EMERGING FIELD

KNOWLEDGE FLOWS AND NETWORKING ON THE NANO-SCALE

D.Phil. Thesis

SPRU – Science and Technology Policy Research

University of Sussex

September 2001

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Abstract

This dissertation addresses emerging developer communities in a new field of science and technology as well as methods to capture exchange processes between them. It contributes to the discussion about a new mode of knowledge production and a changing division of labour between public research, industry, and government by investigating 'nanotechnology' – an emerging area between science and technology. To explore exchange processes in this field, the study applies various methods. In particular, it uses patent citation analysis.

The methodological contribution is a new interpretation of this indicator, which sees patent citations as information flows that point to reciprocal exchange processes and potential overlaps between science and technology. This is in contrast to the received interpretation, which suffers from the application of a framework that was developed in the context of scholarly citation and does not fully appreciate that a patent citation is established by the patent examiner – a party external to the inventive process.

Various formats of patent citation analysis describe 'nanotechnology' as a set of instrument-driven scientific fields on their way towards science-related technologies. Even though nanotechnology patents contain more patent citations to the scientific literature than other technical fields, the science and technology systems are relatively autonomous. What links them in the case of nano-science and technology is a common interest in improving techniques of nano-scale measurement and manipulation.

Another finding is that both countries and firms exhibit relatively strong path-dependencies. While nanotechnology comprises a key set of technological areas – instrumentation, electronics, and pharmaceuticals/chemicals – nano-scale activities vary considerably from country to country. Also knowledge-building activities of firms follow a strong technological path-dependency. As a result, 'social capital' seems to be confined to chiefly technological or scientific trajectories. Hence, 'social capital' appears not to be very useful in explaining how knowledge is accumulated and integrated at the nano-scale.

Given the central role of instrumentation and the mediated nature of exchange between science and technology at the nano-scale, public policies should be directed towards supporting education and infrastructure in the area rather than more 'direct' transfer mechanisms.

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Table of Contents 1 INTRODUCTION.......................................................................................................... 8

1.1 Objectives and Background.................................................................................. 9 1.2 Relevance.......................................................................................................... 12 1.3 Fundamental Assumptions ................................................................................. 17

1.3.1 Developer Communities......................................................................... 18 1.3.2 Developers in Science and Technology.................................................. 18 1.3.3 Novelty in Science and Technology........................................................ 19 1.3.4 Developer Communities as Complex Systems ....................................... 20

1.4 Contributions...................................................................................................... 22 1.5 Research design ................................................................................................ 23

1.5.1 Foundation and Analytical Framework.................................................... 25 1.5.2 Method Development............................................................................. 28 1.5.3 Field Exploration.................................................................................... 29 1.5.4 Triangulation and Conclusion................................................................. 32

2 THE EMPRICAL PROBLEM ...................................................................................... 34 2.1 Introduction ........................................................................................................ 35 2.2 Course of Proceeding......................................................................................... 36 2.3 Definitions .......................................................................................................... 37 2.4 Factual Data....................................................................................................... 41

2.4.1 Nano-Publications.................................................................................. 41 2.4.2 Nano-Patents......................................................................................... 46

2.5 Speculative Data ................................................................................................ 52 2.5.1 Technology Reports and Market Studies................................................ 52 2.5.2 Technology Foresight ............................................................................ 56

2.6 Issues for further investigation ............................................................................ 63 3 ANALYTICAL FRAMEWORK .................................................................................... 66

3.1 Introduction ........................................................................................................ 67 3.2 Science/Technology Literature ........................................................................... 69

3.2.1 Science and Technology........................................................................ 69 3.2.2 The relationship of science and technology ............................................ 73

3.3 Systems approaches.......................................................................................... 79 3.3.1 National Systems of Innovation.............................................................. 79 3.3.2 Technological Systems .......................................................................... 82

3.4 Knowledge, Path Dependency and Learning-focused Approaches...................... 86 3.4.1 Knowledge and Information.................................................................... 86 3.4.2 Knowledge Management and Path Dependency .................................... 90 3.4.3 Learning in Organisations ...................................................................... 96

3.5 Social Capital and Network Approaches ........................................................... 100 3.5.1 Network Approaches............................................................................ 100 3.5.2 The Notion of Social Capital................................................................. 107

3.6 Synthesis ......................................................................................................... 111 4 DIFFERENCES BETWEEN SCIENTIFIC AND PATENT CITATIONS....................... 116

4.1 Introduction ...................................................................................................... 117 4.2 Motivation......................................................................................................... 118 4.3 Potential Parallels............................................................................................. 120 4.4 Differences between Patents and Papers ......................................................... 124

4.4.1 Patent Documents ............................................................................... 124 4.4.2 Patenting and its social and legal contexts ........................................... 130

4.5 Pattern-Matching.............................................................................................. 143 4.6 Conclusion ....................................................................................................... 146

5 INTERPRETING THE PATENT CITATION LINK...................................................... 150 5.1 Introduction ...................................................................................................... 151 5.2 Different Interpretations of Patent Citations....................................................... 153

5.2.1 Patent Citations and Definitions of Science and Technology................. 153 5.2.2 Linear and Two-branched Perspectives ............................................... 154

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5.3 The Role of Citations in Patents........................................................................ 157 5.3.1 Patents as Legal Documents: Applicants' and Examiners' Tasks.......... 158 5.3.2 Motives behind NPRs .......................................................................... 160 5.3.3 Research Issues .................................................................................. 161

5.4 Method............................................................................................................. 163 5.4.1 Case Selection..................................................................................... 163 5.4.2 Data Collection .................................................................................... 170

5.5 The Cases........................................................................................................ 172 5.5.1 Science Links ...................................................................................... 172 5.5.2 Direction of the Knowledge Flow .......................................................... 175 5.5.3 National Differences in Examining and Patenting Practices .................. 178

5.6 Discussion........................................................................................................ 180 5.7 Conclusions ..................................................................................................... 183

6 COGNITIVE WEBS BETWEEN NANO-SCIENCE AND TECHNOLOGY .................. 186 6.1 Introduction ...................................................................................................... 187 6.2 Methodology .................................................................................................... 188

6.2.1 Publication Database ........................................................................... 188 6.2.2 The publication database ..................................................................... 189 6.2.3 Limitations ........................................................................................... 190

6.3 Patent Citation Analysis.................................................................................... 192 6.3.1 Patent citations as linkage indicators.................................................... 192 6.3.2 Patent citations by scientific and technological fields ............................ 195 6.3.3 Patent citations by organisational categories........................................ 199 6.3.4 Patent citations by scientific/technological fields and subclasses .......... 201 6.3.5 Patent citations by organisational and locality categories...................... 204 6.3.6 Co-activity of potential key actors......................................................... 205

6.4 Title word analysis............................................................................................ 208 6.4.1 Instrumentalities................................................................................... 209 6.4.2 Industrial science................................................................................. 211 6.4.3 Different Objectives.............................................................................. 212 6.4.4 Relation without Connection................................................................. 213

6.5 Conclusions ..................................................................................................... 214 7 COUNTRY COMPARISON....................................................................................... 218

7.1 Introduction ...................................................................................................... 219 7.2 Methodology .................................................................................................... 219

7.2.1 Case Selection and Limitations ............................................................ 219 7.2.2 Further Proceeding .............................................................................. 221

7.3 Patents and Publications .................................................................................. 223 7.3.1 Expected Patterns of National Specialisation........................................ 223 7.3.2 Benchmarks......................................................................................... 226 7.3.3 United States ....................................................................................... 228 7.3.4 Germany.............................................................................................. 232 7.3.5 United Kingdom ................................................................................... 235 7.3.6 Finland ................................................................................................ 237 7.3.7 Sweden ............................................................................................... 240 7.3.8 Country comparison............................................................................. 242

7.4 Institutional Setting and Networks..................................................................... 244 7.4.1 United States ....................................................................................... 244 7.4.2 Germany.............................................................................................. 249 7.4.3 United Kingdom ................................................................................... 254 7.4.4 Finland ................................................................................................ 256 7.4.5 Sweden ............................................................................................... 260

7.5 Synthesis ......................................................................................................... 263 8 MICRO-LEVEL CASE STUDIES .............................................................................. 266

8.1 Introduction ...................................................................................................... 267 8.2 Methodology .................................................................................................... 268

8.2.1 Selection of Cases............................................................................... 268 8.2.2 Data Collection .................................................................................... 272 8.2.3 Presentation of the Evidence ............................................................... 273

8.3 Findings In Relation To Central Hypotheses ..................................................... 273

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8.3.1 Method Building................................................................................... 275 8.3.2 Field Exploration.................................................................................. 278

8.4 Conclusions ..................................................................................................... 311 9 CONCLUSION ......................................................................................................... 314

9.1 Introduction ...................................................................................................... 315 9.2 Findings ........................................................................................................... 316

9.2.1 Emergence of Communities ................................................................. 316 9.2.2 Metrics of Community Emergence........................................................ 329 9.2.3 Generalised Findings ........................................................................... 332

9.3 Implications ...................................................................................................... 334 9.3.1 Theoretical Implications ....................................................................... 334 9.3.2 Methodological Implications ................................................................. 336 9.3.3 Policy Implications ............................................................................... 336 9.3.4 Managerial Implications ....................................................................... 339

9.4 Outlook ............................................................................................................ 341 10 REFERENCES......................................................................................................... 344 11 APPENDICES .......................................................................................................... 362

A. Case Summaries Patent Citations ........................................................................ 363 B. Nano-Patents ....................................................................................................... 372 C. Other Countries: Japan......................................................................................... 394 D. Other Countries: France ....................................................................................... 398

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Table of Exhibits Exhibit 1-1. Trajectory of learning in a community of practice............................................... 16 Exhibit 1-2. Research design............................................................................................... 24 Exhibit 2-1. Comparison of nano-publication counts (Meyer/Persson vs. Braun et al.).......... 42 Exhibit 2-2. Distribution of papers by major field by SPRU-classification .............................. 43 Exhibit 2-3. The sub-field distribution of nano-papers by SPRU-classification....................... 44 Exhibit 2-4. Development of nano-patenting over time. ........................................................ 47 Exhibit 2-5. Nano-patents in relation to nano-publications over time..................................... 48 Exhibit 2-6. Patenting activities in relation to publications by country.................................... 50 Exhibit 2-7. Nanotechnology and its industrial applications - the nano-bonsai. ..................... 54 Exhibit 2-8. Nanotechnology Topics in the German 1995 Mini-Delphi Study......................... 57 Exhibit 3-1. Differences between basic research and technological development (after Pavitt).

................................................................................................................................... 72 Exhibit 3-2. Nonaka-Takeuchi learning cycle. ...................................................................... 93 Exhibit 3-3. Håkansson's network model. .......................................................................... 101 Exhibit 4-1. Comparison of examiner and applicant citations in a set of patents. ................ 128 Exhibit 4-2. Structure of a US Specification ....................................................................... 130 Exhibit 4-3. Substantive requirements. .............................................................................. 134 Exhibit 4-4. Differences between the European and the US examination practices. ........... 143 Exhibit 5-1. Different Interpretations of patent citations. ..................................................... 156 Exhibit 5-2. Motives for citing non-patent literature............................................................. 160 Exhibit 5-3. Patent cases selected..................................................................................... 169 Exhibit 5-4. Non-patent references and Citations to Patents in Cases Selected ................. 171 Exhibit 5-5. Findings from the cases: Science links............................................................ 173 Exhibit 5-6. Findings from the cases: Examples of science-technology interactions. .......... 176 Exhibit 6-1. Patent citations and their context. ................................................................... 191 Exhibit 6-2. Citation indicators for nano-publications and patents. ...................................... 193 Exhibit 6-3. The overlap of the data sets............................................................................ 195 Exhibit 6-4. Disciplinary origin of nano-patent citations in comparison to nano-SCI papers. 196 Exhibit 6-5. Patent citations after industrial classes and Spru sub-classes. ........................ 198 Exhibit 6-6. Patent citations after organisational categories................................................ 201 Exhibit 6-7. Other machinery ............................................................................................. 203 Exhibit 6-8. Metal products, ex. Machines.......................................................................... 203 Exhibit 6-9. Electronics...................................................................................................... 203 Exhibit 6-10. Instruments................................................................................................... 203 Exhibit 6-11. Inventor/author pairs by locality..................................................................... 204 Exhibit 6-12. CO1B group of nano-patents and the nano-publications they cite.................. 207 Exhibit 6-13. Title word co-occurrences in patents, SCI and Inspec publications ................ 210 Exhibit 7-1. Relative specialisation of countries in nano-related fields. ............................... 224 Exhibit 7-2. Distribution of nano-patents. ........................................................................... 227 Exhibit 7-3. Nano-publications by SPRU main and sub-fields............................................. 227 Exhibit 7-4. Distribution of US patents. .............................................................................. 229 Exhibit 7-5. Distribution of US scientific publications. ......................................................... 232 Exhibit 7-6. Distribution of German patents........................................................................ 234 Exhibit 7-7. Distribution of German scientific publications. ................................................. 235 Exhibit 7-8. Distribution of UK patents. .............................................................................. 236 Exhibit 7-9. Distribution of UK scientific publications. ......................................................... 237 Exhibit 7-10. Potential actors in nanotechnology in Finland (after patent clusters). ............. 239 Exhibit 7-11. Distribution of Finnish scientific publications. ................................................. 240 Exhibit 7-12. Swedish nano-publication activities............................................................... 241 Exhibit 7-13. Country comparison of nano-patenting.......................................................... 243 Exhibit 7-14. Planned Expenditure of the National Nanotechnology Initiative (NNI). ........... 248 Exhibit 7-15. Federal funding for nanotechnology-related research. ................................... 251 Exhibit 7-16. German nano-networks and their overlap...................................................... 253 Exhibit 7-17. Challenges for university/industry collaboration. ............................................ 259 Exhibit 8-1. Overview of the case studies .......................................................................... 271 Exhibit 8-2. Illustrative Cases: National Innovation Systems & Firms. ................................ 284 Exhibit 8-3. Selected companies and their relationship to nanotechnology. ........................ 288

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Exhibit 8-4. Relationships and overlaps between fields in nanotechnology......................... 292 Exhibit 8-5. Industry Networks of Exploration..................................................................... 294 Exhibit 8-6. Illustrative cases: Chemicals. .......................................................................... 298 Exhibit 8-7. Illustrative cases: Electronics & Telecommunications. ..................................... 299 Exhibit 8-8. Illustrative case: Automobiles.......................................................................... 300 Exhibit 8-9. Established SMEs & Path-dependency. .......................................................... 303 Exhibit 8-10. Illustrative Cases. Path-dependency & research-based start-ups. ................. 304 Exhibit 8-11. Illustrative Cases: Large firms & Social Capital.............................................. 306 Exhibit 8-12. Illustrative cases. SMEs & Social Capital. ..................................................... 307 Exhibit 8-13. Illustrative Cases. Individuals and their Organisation. .................................... 310 Exhibit 9-1. Triangulation of evidence in relation to hypotheses. ........................................ 317 Exhibit 9-2. The Model of Mediated Science/Technology Interaction.................................. 328 Exhibit 11-1. North-American nano-patenting ................................................................... 372 Exhibit 11-2. US nano-patenting over time (organizations with more than 5 nano-patents

only). ........................................................................................................................ 376 Exhibit 11-3. German nano-patenting (complete listing, classified after IPC technical units)378 Exhibit 11-4. Distribution of UK nano-patents after firms and IPC Technical Units. ............. 380 Exhibit 11-5. Details of Nordic nano-patents identified. ...................................................... 382 Exhibit 11-6. Distribution of nano-patents in California after place and IPC Technical Unit. 384 Exhibit 11-7. Distribution of nano-patents in Massachusetts, after place and IPC Technical

Unit........................................................................................................................... 386 Exhibit 11-8. Distribution of nano-patents in New York State after place and IPC Technical

Unit........................................................................................................................... 387 Exhibit 11-9. Distribution of nano-patents in New Jersey, after place and IPC Technical Unit.

................................................................................................................................. 389 Exhibit 11-10. Distribution of nano-patents in Pennsylvania, after place and IPC Technical

Unit........................................................................................................................... 391 Exhibit 11-11. Distribution of nano-patents in Illinois, after place and IPC Technical Unit.... 392 Exhibit 11-12. Distribution of nano-patents in Texas, after place and IPC Technical Unit.... 393 Exhibit 11-13. Japanese nano-patents after firms and IPC Technical Units. ...................... 395 Exhibit 11-14. Distribution of French nano-patents after firms and IPC Technical Units. ..... 399

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PART I:

FOUNDATION AND FRAMEWORK FOR ANALYSIS

Chapter 1 - INTRODUCTION

1 INTRODUCTION

M. MEYER, BETWEEN TECHNOLOGY AND SCIENCE: EXPLORING AN EMERGING FIELD. CHAPTER 1 - INTRODUCTION

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1.1 Objectives and Background

The subject of this thesis is technologies emerging in the context of

science-based innovation. This study investigates the relationships between

particular factors that determine how actors enter and explore new science

and technology. It contributes to the body of knowledge addressing issues,

such as: How do new fields between science and technology emerge? What

impact do path-dependencies and networks of organisations have on their

emergence? How do nation states influence 'technological choice' under

uncertainty? How can one track the evolution of developer communities?

In particular, the thesis addresses the question: How do actors access and

integrate new knowledge in emerging and science-related fields? In new

technologies, actors face a high level of uncertainty. Often the borderlines of

the new paradigm are not drawn yet. Networks are either not formed or are

still being formed. A process of trial-and-error search goes on, at the same

time that investing in commercial products has begun. Due to the paradox that

while uncertainty makes ventures risky, high risk is often associated with high

rewards,1 corporations face appraisal dilemmas in new technological fields.2

Nanotechnology was chosen as the subject of this study because it is a

field where actors may experience difficulty in evaluating technological options

for the reasons mentioned above. Many companies have begun to explore the

1 Brealey, R.A.; Myers, S.C. (1996). Principles of corporate finance. New York: McGraw-Hill;

part 6. 2 This is indicated by the growing management literature on options evaluation. See in

particular the works by Mitchell and Hamilton, for instance, Hamilton, W.F. (1990). The dynamics of technology and strategy. European Journal of Operations Research, 47, 141-152. Mitchell, G.R. (1990). Alternative frameworks for technology strategy. European Journal of Operational Research, 47, 153-161. Mitchell, G.R.; Hamilton, W.F. (1988). Managing R&D as a strategic option. Research-Technology Management, 31 (3), 15-22. Also, see Myers, S.C. (1984). Finance theory and financial strategy. Interfaces, 14, 126-137.


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underlying scientific aspects of nanotechnology; some firms have even

invested in certain nano-scale techniques and processes. However,

nanotechnology is at the early stage of its development. Therefore, there is no

generally accepted definition.

For the purposes of this thesis, nanotechnology is defined as a cluster of

scientific and technological activities where functional structures with

dimensions or tolerances in the nanometre (0.1 to 100 nm) level play a critical

role. Nanotechnology comprises those fields of technology that help to study,

observe or manipulate structures at the nano-scale3 as well as objects or

projects whose novel properties derive from their nanometre-scale.4

Electronics, materials and instrumentation are potential fields of application for

nanotechnology. Companies in these fields are currently exploring nano-scale

technologies. Foresight studies predict, moreover, that developments in

nanotechnology will affect large parts of the manufacturing economy.

Traditionally, there has been an institutionalised division of labour between

publicly funded scientific research in the university sector and privately funded

technological development in industry. However, this division of labour is

undergoing a dramatic change – in particular, because universities are

increasingly assuming a role in developing and commercialising new

technologies. Science policy analysts, most notably Gibbons and his

colleagues, believe they are witnessing a shift towards a new mode of

knowledge production, which they call 'Mode 2' for lack of a better term. In

3 This includes in particular advanced instrumentation, such as the Scanning Tunneling

Microscope (STM) and the Atomic Force Microscope (AFM) as well as a number of advanced thin-film growing techniques.

4 A growing number of nanostructured powders and pigments are being commercialized especially in the US. Materials for semiconductors and molecular electronics are said to be


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particular, this mode is characterised by 'transdisciplinary' collaboration in

transient organisations of both industrial and academic actors.5 Gibbons et al.

suggest that this new approach of knowledge production ('Mode 2') is

replacing the traditional type of knowledge generation ('Mode 1'). While Mode

1 is described as disciplinary, located in well-established sites and far away

from an application context, Mode 2 is depicted as

"distinctly applied in character, transdisciplinary in its fundamental

research orientations, pursued by heterogeneous and transient

research collective[s] and both socially accountable and inherently

reflexive in its contents and research methods. The new mode of

knowledge production is typically observed in innovative research fields

such as new materials, biogenetics and information technology."6

Because of the lack of comprehensive empirical studies of knowledge

production phenomena, Modes 1 and 2 appear in this context to be the only

alternatives as to how knowledge production can be organised. An 'either/or'

seems to dominate the discussion. This raises the question how useful the

ideas related to Mode 2, or a new mode of knowledge production, really are.

However, instead of rejecting the model entirely, it might be useful to

investigate the world that lies between the two modes.

In the study of university-industry-government interrelationships, these

new developments are often referred to as the 'triple helix'.7 To develop new

technologies, universities, industry, and government- formerly the occupants

of particular importance.

5 Gibbons, M.; et al. (1994). The new production of knowledge. London: Sage. 6 Wilts, A. (2000). Forms of research organisation and their responsiveness to external goal

setting. Research Policy, 29, 767-781, here 768. 7 Etzkowitz, H.; Leydesdorff, L. (eds) (1997). Universities and the global knowledge economy:


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of relatively separate and distinct institutional spheres- are now assuming

tasks in the development that were originally in each other's domains.8 This is

the case especially in the field of so-called science-based technologies, an

area of growing economic importance where industrial technology relies

heavily on scientific results from universities and other research

organisations.9 This research investigates the specific forms of the new

division of labour in a novel area that is about to become a science-related

field of technology.

The following section of this chapter will first outline the relevance of this

study before the backdrop of previous work on emerging technologies and

community evolution. Then fundamental assumptions about the nature of

developer communities and their members are clarified and the term novelty

is defined. This section also specifies the contributions to knowledge that this

thesis makes. Finally, the general research design and structure of the study

are presented.

1.2 Relevance

This section illustrates why it is relevant to study how new fields and

communities of scientists and technologists evolve. Surprisingly, there is little

literature on the underlying factors that shape the emergence of a developer

community. Most of the models presented appear to be essentially sequential

and descriptive, or they focus on the evolution of existing networks, not on

emerging communities and fields. Yet these models do not elucidate the

a triple helix of university-industry-government. London: Pinter.

8 Ibid. 9 Narin, F.; et al. (1997). The increasing linkage between U.S. technology and public science.

Research Policy, 26 (3) 317-330, and literature therein.


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driving factors that determine the way in which actors explore new science

and technology. Nor do they explain how this type of knowledge building is

related to the development of networks and the emergence of a new scientific

and technological community. Two examples may illustrate this.

For instance, Debackere and Rappa discuss community networks

evolving in relation to the emergence of a new technological paradigm. These

authors characterise the typical early stages of a successful new paradigm as

'bootlegging' and 'bandwagon'. During the bootlegging period, which may last

for a long time, a handful of researchers dedicate themselves to furthering the

field, even though their enthusiasm may not be shared by their peers but

severely criticised. Typically, they have difficulties in securing adequate

funding; hence, the term 'bootlegging'. Characteristically, a few isolated

individuals start working on similar problems with roughly similar ideas.10

Researchers dedicated to a new and unorthodox field of inquiry are

confronted with a difficult dilemma. On one hand, before receiving resources,

they need proof that their work will yield results. On the other hand, without

resources, they are unable to do that. 'Bootlegging' enables fledging research

to proceed without being scrutinised by managers and other researchers, up

to a point at which the idea starts to look promising. During this phase, then,

the community consists of only a few organisations, and only a fairly modest

number of researchers join its ranks every year.11

As the number of individuals working on the same problem area

increases, a communication network emerges with ties that are much stronger

10 Debackere, K.; Rappa, M. (1994). Science and industry: network theory and paradigms.

Technology Analysis and Strategic Management, 6 (1) 21-37, here 27-28


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than the ties binding the individuals to the organisations they formally belong

to. In the course of this so-called bandwagon phase the number of

researchers belonging to the community increases rapidly. As the community

grows, a new paradigm comes into being, which is seen by the higher-level

network of the (sub-) discipline as competing with older paradigms. The

community tries to organise congresses and start journals in order to steer the

selection process. The R&D community is typically distributed across

organisations, sectors, and countries. If the work of a new community seems

interesting from a commercial point of view, some scientists are recruited by

enterprises, while those who already work within industry are allowed to

devote their efforts openly to the new field. Also, some scientists may decide

to become entrepreneurs themselves.

While this model gives an accurate account of how a developer

community emerges at the interface between science and technology, it says

very little about the underlying factors that shape an emerging field. It does

not provide answers to the crucial 'who', 'what' and 'why' questions related to

a specific field of science or technology.

Unfortunately, social-constructivist approaches are not much more

instructive. They often focus on learning or knowledge acquisition in an

established context of existing communities. An example of this is Tuomi's

notion of learning trajectories. He focuses on how a 'novice' enters a

community and becomes a legitimate member following a 'trajectory of

learning'. According to Tuomi, the beginner gradually adopts knowledge and

practices of a given community up to the point where s/he will have reached

11 Ibid.


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the position of an expert. This development is related to a process of learning.

In the beginning, the newcomer is tolerated by the other members of the

community as a 'peripheral participant', "who can barely make sense of the

discourse within the community."12 As the novice familiarises him/herself with

the 'conceptual systems' of the community and subscribes to certain positions

and commits to specific interpretations, he/she begins to take part in the

activities and exchanges of the community. As a result, his or her

understanding of the field develops further. As a community member, he or

she can understand the positions of their peers and is knowledgeable enough

to argue points of view. This leads to yet another, higher level of cognitive

ability since a member of the community needs to manage both internal and

external points of view simultaneously. Eventually, the new member of the

community reaches the cognitive level of an expert who, in Tuomi's words,

can "not only understand […] the various points of view within a community,

but also grasps the ability of the owners of these views to develop them."

However, in the context of this study, it is important to be aware of the

assumption that underlies this model of learning. Tuomi implicitly assumes

that there is a community of practice that a 'novice' can 'enter'. What one can

find tracing the emergence of a novel field of technology is not a community of

practice where novices can 'join the club' of experts and 'old-timers', but a

multiplicity of communities of practice. Some members (including the senior

12 Tuomi, I. (1999). Inside innovation clusters: collective knowledge creation in networks and

communities. In Schienstock, G.; Kuusi, O. (eds). Transformation towards a learning economy. Helsinki: Sitra, 143-157. Cited after draft, 8-9.


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ones) are pursuing activities directed at creating a 'new zone of legitimate

(peripheral) participation', i.e., a community in which they are all novices.13

Exhibit 1-1. Trajectory of learning in a community of practice.

novices

experts

"old-timers"

the zone of legitimateperipheral

participation

The concepts discussed above are useful in describing how existing

communities adopt new members (as in the Tuomi model) or in a general way

depicting how communities evolve (as in the case of Debackere and Rappa).

However, neither of these concepts explains the factors that shape the co-

evolution of networks and technologies in their early stages. Other studies

have focused more explicitly on how technology and network develop in

relation to each other. However, this has usually been done within the context

of an established industry.14

13 To illustrate this situation, one would need to multiply the zone depicted in Exhibit 1-1. The

trajectories of learning, which are illustrated by an arrow leading into the center of the community of practice in the exhibit, would now be directed leading away from the familiar center towards a fictive, not yet existing one. This center is the focal point of a new community of practice that has not fully come into being yet. Even though Tuomi's model does not directly apply to this context, it helps us understand why the formation of new technologies and communities of practice is a long and laborious process. It links the idea of a technological or industrial path of development with existing networks of personal and organisational contacts that are influential when novel fields are to be explored.

14 Rosenkopf, L.; Tushman, M.L. (1998). The coevolution of community networks and technology: Lessons from the flight simulation industry. Industrial and Corporate Change, 7 (2), 311-346.


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So far these phenomena have not been studied from the point of view of

the emerging field itself. Such a view is important if one deals with cross-

sectoral technologies that have a strong relation to novel sciences.

Practitioners in S&T policy often try to plan and administrate technology-

centred programs, but need to rely on industry-level information only. For

these reasons, it is important to study the factors that either facilitate or

obstruct a new area's transition from the bootlegging to the bandwagon stage,

and to do so by adopting the perspective of the novel field itself.

1.3 Fundamental Assumptions

This thesis deals with factors that have an impact on the 'division of

labour' in a new field of science and technology. Even though this research is

context-driven, it is built upon a number of fundamental assumptions. It is not

entirely free of any preconceptions about developer communities, their

members and how they interact in a systems environment. In particular,

developers are viewed as heterogeneous15, resource-dependent and capable

of learning. This research also assumes at the outset that developer

communities are components of complex socio-technical systems.

Furthermore, since this research discusses the emergence of new fields of

science and technology, novelty needs to be defined in the context of this

study. Finally, the notion of developer communities is defined and related to

the broader discussion on the topic. This section clarifies in more detail the

basic ideas that this thesis takes as its points of departure.

15 The term 'heterogeneous' in this context means differing in structure, quality, etc.;

dissimilar' (Webster's New World Dictionary).


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1.3.1 Developer Communities The emergence of a new technology, or even more generally speaking, a

new paradigm, presupposes an increasing number of individuals working on a

certain subject matter, a certain phenomenon, or some form of artefact. This

work can be purely scientific in nature, it can be essentially technological, or it

may encompass aspects of both. Whatever the nature of such a project may

be, it must, in order to be noticed, gain 'critical mass'. It must transcend the

scale and scope of scattered and individual efforts. Something must arise that

connects individual efforts and actors. Some authors refer to this as a 'leitbild',

a 'guiding image' that - by providing a shared goal - functions as a stabiliser

for actors from different professions and disciplines.16 People working towards

this 'leitbild' constitute a collective; in this study the collectives are called

'developer communities'.17

1.3.2 Developers in Science and Technology

Firstly, developers in science and technology are seen as heterogeneous,

resource-dependent and capability-building actors. This notion is in line with

the resource-based approach, which assumes heterogeneity and emphasises

internal resources as the basis for obtaining competitive advantages.18 It views

organisations as channels for material and immaterial resources. The position

16 See also Marz, L.; Dierkes, M. (1994). Leitbildprägung und Leitbildgestaltung. In

Bechmann, G.; Petermann, T. (eds). Interdisziplinäre Technikforschung: Genese, Folgen, Diskurs. Frankfurt/Main, New York: Campus, 35-72.

17 In the context of this study, the term 'developer community' is used to denote social entities that unite individuals who advance scientific and/or technological knowledge in a certain direction. These communities can be characterised by similar instrumentation, or their use of a certain subject-matter. Analysts find it increasingly difficult to distinguish between 'science' and 'technology' and, instead, prefer to investigate the dichotomy of 'academe' and 'industry' and efforts to overcome it. In order to avoid the terminological confusion, the term 'developer community' is used.

18 Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5, 171-180. See also Rumelt, R.P. (1984). Toward a strategic theory of the firm. In Lamb, R.B.


19

of an organisation today is the result of decisions and actions made in the

past. Different historical developments lead to uniqueness, or heterogeneity,

of the resource endowment.

This study assumes that the actors who form developer communities are

organisations or individuals that are capable of learning. Moreover, a specific

knowledge base is regarded as critical for an organisation to secure the

competitive advantage. However, this knowledge base is subject to

continuous change and ongoing learning (knowledge accumulation

processes).19 Dynamic capabilities emerge from deliberate and continuous

investments in learning and improvement.20, 21

1.3.3 Novelty in Science and Technology

There are several ways of denoting novelty. One could use a strictly

chronological definition. Then all those events, occurrences, and other

incidents that happen within a defined timeframe might be viewed as novel.

However, studies that present the innovation process in a sequential pattern

remind us that novelty is a context-dependent phenomenon. For instance,

market novelty is different from scientific or technological novelty.

A novel technological field can be defined as a field that has essentially

evolved within the past 20 years. Mahdi and Pavitt have suggested an

analogous concept for 'new science'.22 They define new science as something

(ed.). Competitive strategic management. Englewood Cliffs, NJ: Prentice Hall.

19 Teece, D.J.; Pisano, G.; Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18 (7) 509–534.

20 Hodgson, G.M. (1998). Evolutionary and competence-based theories of the firm. Journal of Economic Studies, 25 (1) 25-56.

21 Teece, D.; Pisano, G. (1994). The dynamic capabilities of the firm. Industrial and Corporate Change, 3 (3).

22 Mahdi, S.; Pavitt, K (1997). Key national factors in the emergence of computational chemistry firms. International Journal of Innovation Management, 1 (4) 355-386.


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"that has emerged since 1970 and is characterised by its separation from the

parent sciences in literature headings. This separation may take the form of

the creation of a new journal, a new keyword or research front in on-line

databases, or a new heading in scientific indexes."23 The authors admit that

their definition is not necessarily accurate since developments may have

begun several years before the quoted examples, such as the third generation

biotechnology and computational chemistry. Also, the definition may not

reflect the date of economic impact of the novel field, which could have been

felt several years earlier during the incubation phase.24 Even though the

definition presented here does not distinguish between science and

technology,25 it is still useful in describing 'novelty'.

1.3.4 Developer Communities as Complex Systems

Garnsey argues that theories of enterprise and innovation exclude the

individuality of the actor,26 whereas theory dealing with complex systems

views individuals and local events as a critical source of diversity and

change.27 This thesis follows Kline, Kash and Rycroft, who suggest that co-

evolving technologies and networks are appropriately seen as socio-technical

systems that continuously access, create and synthesise tacit and explicit

knowledge in the process of innovation.28 Kline views developer communities

23 Mahdi/Pavitt, op.cit., 356. 24 For instance, the first biotech company, Genentech, was established in 1977, while

biotechnology appeared for the first time in 1986 as a 'recognised independent science'. 25 See Chapter 3. 26 Garnsey, E. (1998). A theory of the early growth of the firm. Industrial and Corporate

Change, 7 (3) 523-556. 27 See also Allen, P. (1997). Cities and regions as self-organizing systems: models of

complexity, Gorden and Breach: London, 2. 28 Kash, D.E.; Rycroft, R. (1998). Technology policy in the 21st century: how will we adapt to

complexity? Science and Public Policy, 25 (3) 70-86. See also Kline, S. (1995). Conceptual foundations for multidisciplinary thinking. Stanford UP. Stanford, CA, 49-97.


21

as a component of socio-technical systems.29 He defines socio-technical

systems as "complete systems of coupled social and technical parts which

humans erect and operate primarily to control our environment and perform

tasks we cannot do without such systems."30 Socio-technical systems are the

most complex systems since they include all the other classes of systems and

depend on interactions amongst them.31 A socio-technical system derives its

complexity from a multitude of interrelated connections between its elements.

Complexity in turn gives the system its character as unity of a plurality.32

The system as a unity is complex insofar as it has several elements which it

connects through several relations. The number of possible relations between

elements grows in geometric progression. However, interconnectivity is

drastically limited in reality. Hence, this mathematical law just allows for

selectively interconnecting elements. Thus, complex systems are different

from simple systems because only in simple systems is it possible to relate

each element to another in any possible way at any time. In complex systems,

relations between elements are the result of a selection process. Selection

leads to contingent situations.33 The purpose of this dissertation is to help

identify factors that shape particular situations arising when a novel

community unfolds at the interface between science and technology.

29 Kline also distinguishes four distinct socio-technical systems, namely manufacturing

systems, systems of use, systems of distribution, and systems of research and development for creating new or modified socio-technical systems.

30 Kline, op. cit., 62. 31 Ibid. 32 Luhmann, N. (1998). Die Gesellschaft der Gesellschaft. Teilband 1. Frankfurt: Suhrkamp,

135. 33 Situations that could possibly be different.


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1.4 Contributions

The objective of this study is to shed some light on the forces that shape

communities in an emerging field at the interface between science and

technology. An understanding of these underlying factors (and how to

measure them) furthers a better comprehension of the innovative process as

such, and also helps to explain why certain technologies do not 'take off'.

Insights derived from this study provide a basis for an informed review of

technology-focused policies in the area of science-based innovation. So, this

thesis contributes to research in the field in the following ways:

First, it suggests a revised interpretation of patent citations as flows of

information that point to potential and reciprocal exchange between

science and technology. This study challenges the received

interpretation of patent citations of the non-patent literature as a

measure for the science-dependence of technology. It does so by

characterising these patent citations as a mediated link established by

a party that is external to the inventive process, i.e. the patent

examiner.

Second, the thesis employs various formats of patent citation analysis

to show that nanotechnology patents contain more patent citations of

scientific literature than other technical fields. Yet the data also

indicates that science and technology remain autonomous systems.

Instead of a single, boundary-crossing developer community, there are

several scientific and technological communities that approach the

nano-scale.


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Third, the thesis identifies the interest in improving techniques of nano-

scale measurement and manipulation as the commonality that links the

heterogeneous communities in the case of nano-science and

technology. Both patent bibliometric data as well as narrative accounts

confirm Rosenberg's conceptualisation of instrument-driven

technological development and are also in line with Price's idea of

instrumentalities as a chief mediator between science and technology.

Finally, the thesis points to the relatively persistent path-dependencies

which both countries and firms exhibit in the field of nanotechnology.

These path-dependencies severely limit managerial approaches. In

particular, the strong technological path-dependency in firms appears

to determine the network context in which they explore

nanotechnology. In other words, the 'social capital' of firms seems to

co-evolve with technological or scientific trajectories.

These findings point to the central role of instrumentation and the

mediated nature of exchange between nano-science and technology. The

thesis therefore concludes that policy measures should be directed towards

supporting education and infrastructure in the area, instead of favouring

'direct' venturing approaches.

1.5 Research design

This dissertation addresses essentially two issues: first, the emergence of

a novel field at the interface between science and technology and ways to

measure this; second, the interplay between scientific and technological

aspects. In fact, as will be elaborated later in more detail, a key method for