A Network Perspec.ve of Nanotechnology Innova.on: A Comparison of Quebec, Canada and the United States The Responsible Development of Nanotechnology: Challenges and Perspec.ves Ne3LS Network Interna.onal Conference November 12, 2012, Montreal, Canada Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Beaudry, Schiffauerova & Moazami_The scientific and technological nanotechnology networks the comparison between canada, quebec and the united states
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A Network Perspec.ve of Nanotechnology Innova.on: A Comparison of Quebec, Canada and the United States
The Responsible Development of Nanotechnology: Challenges and Perspec.ves Ne3LS Network Interna.onal Conference November 1-‐2, 2012, Montreal, Canada
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Outline
• Introduc)on • Literature review • Hypotheses • Data and methodology • Results • Policy Implica)ons • Limita)ons and future works
2 Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Introduction
• Nanotechnology – a general-‐purpose technology – a concern for many countries, including Canada
• Innova)on – where is it created? – how is it transferred?
• Networks analysis – studying the structure of rela)onships between actors
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
3 Catherine Beaudry Andrea Schiffauerova Afshin Moazami
National Innovation System (NIS)
• A network of ins)tu)ons which contribute to the development and diffusion of new technologies in a country (Freeman 1987, Lundval 1992)
• Three main sectors of NIS and their oJen focus 1. universi)es: fundamental research 2. governmental labs: applied research 3. industrial sectors: applied research (Niosi 2000)
4
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
NIS in Quebec, Canada, and the US
• More important role of interna)onal linkages in Canada compared to the US (OECD 1999)
• The US is leading in nanotechnology publica)ons and patents
• Quebec policies (QPSI 2002) – independent ac)vi)es – financial resources – infrastructure
5
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Network Structural Properties • Vertex centrality
– betweenness centrality (Brandes 2001) • number of shortest paths that pass through one vertex over the total number of shortest paths
– degree centrality (Arenas et al. 2008) • number of edges connected to one vertex
• Fragmenta)on (Beaudry and Schiffauerova 2010) – size of the largest component – average size of components – number of isolated ver)ces
6
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Hypotheses (I / III)
• Regional characteris)cs of the networks – H1 (Reg-‐CA/Intl): Interna)onal collabora)on form a significant part of the overall Canadian collabora)on pa\ern
– H2 (Reg-‐QC): Quebec-‐based researchers are involved in more internal research rela)onships within Quebec
7
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Hypotheses (II / III)
• Academia and industry – H3 (Aff-‐metrics): Academics are more clustered, more centralized and have a higher number of direct )es than non-‐academics
– H4 (Aff-‐AC/NA pos): Academics, who co-‐author ar)cles with industrial scien)sts, occupy (a) more cliquish and (b) more central posi)ons compared with academics who do not collaborate with industrial scien)sts
8
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Hypotheses (III / III)
• Regional differences in academia and industry – H5 (RegAff-‐AC): American academics (a) collaborate more with non-‐academic scien)sts, and occupy (b) more central and (b) more cliquish network posi)ons compared to their Canadian counterparts.
– H6 (RegAff-‐NA): The US non-‐academic network is (a) more centralized and clustered, and (b) accounts for a greater propor)on of the researchers than Canada
9
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Methodology Steps
10
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Methodology Steps
11
Database of articles articles: 748,251 authors: 1,050,676 collaborations: 3,160,795
Database of patents patents: 240,436 inventors: 236,784 collaborations: 688,052
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Network Building
• Time events networks – 3-‐year intervals – patents (1994-‐2002), ar)cles (1994-‐2008)
• Regional Networks – patents: based on city of residency – ar)cles: based on affilia)ons
• Affilia)on Networks – only for ar)cles and based on the
affilia)ons of scien)sts – high share of industry in non-‐academics
12
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Canada vs. the US
• Interna)onal collabora)ons (H1 Reg-‐Ca/Intl)
13
Canada 30%
The US 27%
World 43%
Canada Canada 2%
The US 55%
World 44%
The US
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Quebec vs. Rest of Canada
• The tendency to internal collabora)on is increasing in Quebec (H2 Reg-‐QC)
14
0
0.5
1
1.5
2
2.5
3
Average Num
ber o
f Collabo
rators per
Authors for Q
uebe
c-‐ba
sed researchers
Quebec Rest of Canada
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics vs. Industry
15
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average De
gree Cen
trality
Degree Centrality (Academia vs. Industry)
Academic researchers Non-‐academic researchers
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics vs. Industry
16
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0
5
10
15
20
25
30
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average Be
tweenn
ess C
entrality
(x10^6)
Betweenness Centrality (Academia vs. Industry)
Academic researchers Non-‐academic researchers
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics vs. Industry
17
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.8
0.81
0.82
0.83
0.84
0.85
0.86
0.87
0.88
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average Clusterin
g Co
efficien
t
Cliquishness (Academia vs. Industry)
Academic researchers Non-‐academic researchers
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics vs. Industry
• Nanotechnology researchers from industry are a) more clustered b) more central in terms of degree
centrality c) slightly less central in terms of
betweenness centrality than academics (H3 Aff-‐metrics)
18
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Links of Academia and Industry
19
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
2
3
4
5
6
7
8
9
10
11
12
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average De
gree Cen
trality
Academics with only academic collabora)on (AC-‐AC)
Academics with at least one non-‐academic collabora)on (AC-‐NA)
Non-‐Academics with only Non-‐academic collabora)on (NA-‐NA)
Non-‐ Academics with at least one academic collabora)on (NA-‐AC)
Degree Centrality
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Links of Academia and Industry
20
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0
5
10
15
20
25
30
35
40
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average Be
tweenn
ess C
entrality
(x10^6)
Academics with only academic collabora)on (AC-‐AC)
Academics with at least one non-‐academic collabora)on (AC-‐NA)
Non-‐Academics with only Non-‐academic collabora)on (NA-‐NA)
Non-‐ Academics with at least one academic collabora)on (NA-‐AC)
Betweenness Centrality
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Links of Academia and Industry
21
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.7
0.75
0.8
0.85
0.9
0.95
1
94-‐96 95-‐97 96-‐98 97-‐99 98-‐00 99-‐01 00-‐02 01-‐03 02-‐04 03-‐05 04-‐06 05-‐07 06-‐08
Average Clusterin
g Co
efficien
t Academics with only academic collabora)on (AC-‐AC)
Academics with at least one non-‐academic collabora)on (AC-‐NA)
Non-‐Academics with only Non-‐academic collabora)on (NA-‐NA)
Non-‐ Academics with at least one academic collabora)on (NA-‐AC)
Cliquishness
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Links of Academia and Industry
• Researchers who links academic and industry – academics who have collaborators from industry and vise versa – are: a) more central b) less cliquish than the ones who create collabora)ve partnerships only within their own subgroup (H4 Aff-‐AC/NA pos)
22
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics: Canada vs. the US
23
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00% Pe
rcen
tage of C
ollabo
ra.o
ns
Academia / Non-‐Academia (Canada vs. the US)
Canada The US
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics: Canada vs. the US
24
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0
10
20
30
40
50
60 Av
erage Be
tweenn
ess C
entrality
(x 106)
Betweenness Centrality of Academics (Canada vs. the US)
Canada Academics The US Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics: Canada vs. the US
25
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
4
5
6
7
8
9
10
Average De
gree Cen
trality
Degree Centrality of Academics (Canada vs. the US)
Canada Academics The US Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics: Canada vs. the US
26
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.75
0.77
0.79
0.81
0.83
0.85
0.87
0.89 Av
erage Clusterin
g Co
efficien
t
Cliquishness of Academics (Canada vs. the US)
Canada Academics The US Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Academics: Canada vs. the US
• American academic nanotechnology scien)sts a) collaborate more with non-‐academic
scien)sts b) occupy more central network
posi)ons c) occupy less cliquish network
posi)ons than the Canadian ones (H5 RegAff-‐AC)
27
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Non-academics: Canada vs. the US
28
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00% Pe
rcen
tage of N
on-‐Acade
mics
Propor.on of Non-‐academics (Canada vs. the US)
Canada The US
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Non-academics: Canada vs. the US
29
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
4
5
6
7
8
9
10 Av
erage De
gree Cen
trality
Degree Centrality of Non-‐academics (Canada vs. the US)
Canada Non-‐Academics The US Non-‐Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Non-academics: Canada vs. the US
30
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0
10
20
30
40
50
60 Av
erage Be
tweenn
ess C
entrality
(x 106)
Betweenness Centrality of Non-‐academics (Canada vs. the US)
Canada Non-‐Academics The US Non-‐Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Non-academics: Canada vs. the US
31
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
0.75
0.77
0.79
0.81
0.83
0.85
0.87
0.89 Av
erage Clusterin
g Co
efficien
t
Cliquishness of Non-‐academics (Canada vs. the US)
Canada Non-‐Academics The US Non-‐Academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Non-academics: Canada vs. the US
• American non-‐academic nanotechnology network a) accounts for a greater propor)on of
the researchers b) does not occupy more central and
cliquish posi)ons than the Canadian ones (H6 RegAff-‐NA)
32
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Policy Implications (Canada)
• Government of Canada should – encourage industrial research through
suppor)ng small nanotechnology companies
– facilitate industry-‐academia collabora)on by providing more programs, grants and funding opportuni)es
33
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Policy Implications (Quebec)
• Government of Quebec should – support na)onal and interna)onal
connec)ons by inves)ng on joint programs and alloca)ng financial supports
– s)mulate collabora)on of Quebec-‐based academic researchers with non-‐academia by providing more funding for academia-‐industry collabora)ons
34
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Thank you
35
Quebec nanotechnology network of researchers (articles) in 2006-2008; academics and non-academics
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
Limita.on
• Quan)ty instead of quality; equal weight for every collabora)on
• The informal rela)onships are ignored
Future Work • Indicators for
quality of collabora)on; e.g. number of cita)ons
• Study of other professional networks like LinkedIn
36
Limitations and Future Work
Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works
Catherine Beaudry Andrea Schiffauerova Afshin Moazami
References (I / II)
• C. Freeman, Technology and Economic Performance: Lessons from Japan, London: Pinter, 1987.
• B. A. Lundvall, Na)onal Innova)on Systems: Towards a Theory of Innova)on and Interac)ve Learning, London: Pinter, 1992.
• J. Niosi, Canada's na)onal system of innova)on, Montreal: McGill-‐Queen’s University, 2000.
• OCED, Managing Na)onal Innova)on Systems, Paris: Organiza)on for Economic Coopera)on and Development, 1999.
• "Québec Policy on science, technology and innova)on," Conseil de la science et de la technologie du Québec, Québec, 2002.
• U. Brandes, "A Faster Algorithm for Betweenness Centrality," Journal of MathemaWcal Sociology, vol. 25, p. 163–177, 2001.
37 Catherine Beaudry Andrea Schiffauerova Afshin Moazami
References (II / II)
• A. Arenas, A. Diaz-‐Guilera, J. Kurths, Y. Moreno and C. Zhou, "Synchroniza)on in complex networks," Physics Reports, vol. 469, pp. 93-‐-‐153, 2008.
• C. Beaudry and A. Schiffauerova, "Biotechnology and Nanotechnology Innova)on Networks in Canadian Clusters," in InnovaWon Networks and Clusters, Brussels, P.I.E Peter Lang, 2010, pp. 159-‐197.
38 Catherine Beaudry Andrea Schiffauerova Afshin Moazami
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