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Semelhante a Beaudry, Schiffauerova & Moazami_The scientific and technological nanotechnology networks the comparison between canada, quebec and the united states
Semelhante a Beaudry, Schiffauerova & Moazami_The scientific and technological nanotechnology networks the comparison between canada, quebec and the united states (20)
Mais de Ne3LS_Network
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Beaudry, Schiffauerova & Moazami_The scientific and technological nanotechnology networks the comparison between canada, quebec and the united states
- 1. 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
- 2. Outline • Introduc)on • Literature review • Hypotheses • Data and methodology • Results • Policy Implica)ons • Limita)ons and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 2
- 3. Introduction • Nanotechnology – a general-‐purpose technology – a concern for many countries, including Canada • Innova)on – where is it created? – how is it transferred? Introduction Literature review Hypotheses • Networks analysis Data and methodology Results – studying the structure of rela)onships Policy Implications between actors Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 3
- 4. 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 Introduction Literature review 2. governmental labs: applied research Hypotheses Data and methodology 3. industrial sectors: applied research Results Policy Implications (Niosi 2000) Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 4
- 5. 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 Introduction Literature review – financial resources Hypotheses Data and methodology – infrastructure Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 5
- 6. 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) Introduction – size of the largest component Literature review Hypotheses – average size of components Data and methodology Results – number of isolated ver)ces Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 6
- 7. 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 paern – H2 (Reg-‐QC): Quebec-‐based researchers are involved in more internal research rela)onships within Quebec Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 7
- 8. 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 Introduction Literature review central posi)ons compared with academics Hypotheses Data and methodology who do not collaborate with industrial Results Policy Implications scien)sts Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 8
- 9. 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. Introduction – H6 (RegAff-‐NA): The US non-‐academic Literature review network is (a) more centralized and Hypotheses Data and methodology clustered, and (b) accounts for a greater propor)on of the researchers than Canada Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 9
- 10. Introduction Literature review Hypotheses Data and methodology Results Policy Implications Methodology Steps Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 10
- 11. Introduction Literature review Hypotheses Data and methodology Results Policy Implications Methodology Steps Limitations and future works Database of patents patents: 240,436 Database of articles inventors: 236,784 articles: 748,251 collaborations: 688,052 authors: 1,050,676 collaborations: 3,160,795 Catherine Beaudry Andrea Schiffauerova Afshin Moazami 11
- 12. 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 Introduction • Affilia)on Networks Literature review Hypotheses – only for ar)cles and based on the Data and methodology Results affilia)ons of scien)sts Policy Implications Limitations and future works – high share of industry in non-‐academics Catherine Beaudry Andrea Schiffauerova Afshin Moazami 12
- 13. Canada vs. the US • Interna)onal collabora)ons (H1 Reg-‐Ca/Intl) Canada The US Canada Canada 30% 2% World World 43% 44% The US Introduction 55% Literature review The US Hypotheses 27% Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 13
- 14. Quebec vs. Rest of Canada • The tendency to internal collabora)on is increasing in Quebec (H2 Reg-‐QC) 3 Authors for Quebec-‐based researchers Average Number of Collaborators per 2.5 2 1.5 1 Introduction Literature review 0.5 Hypotheses Data and methodology 0 Results Policy Implications Limitations and future works Quebec Rest of Canada Catherine Beaudry Andrea Schiffauerova Afshin Moazami 14
- 15. Academics vs. Industry Degree Centrality (Academia vs. Industry) 9.5 9 8.5 Average Degree Centrality 8 7.5 7 6.5 6 Introduction Literature review 5.5 Hypotheses Data and methodology 5 Results 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 Policy Implications Academic researchers Non-‐academic researchers Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 15
- 16. Academics vs. Industry Betweenness Centrality (Academia vs. Industry) 30 Average Betweenness Centrality (x10^6) 25 20 15 10 Introduction 5 Literature review Hypotheses 0 Data and methodology 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 Results Policy Implications Academic researchers Non-‐academic researchers Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 16
- 17. Academics vs. Industry Cliquishness (Academia vs. Industry) 0.88 0.87 Average Clustering Coefficient 0.86 0.85 0.84 0.83 0.82 Introduction 0.81 Literature review Hypotheses 0.8 Data and methodology 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 Results Policy Implications Academic researchers Non-‐academic researchers Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 17
- 18. 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 Introduction betweenness centrality than academics Literature review Hypotheses Data and methodology Results (H3 Aff-‐metrics) Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 18
- 19. Links of Academia and Industry Degree Centrality 12 11 Academics with only academic collabora)on 10 (AC-‐AC) Average Degree Centrality 9 Academics with at least 8 one non-‐academic collabora)on (AC-‐NA) 7 6 Non-‐Academics with only Non-‐academic 5 collabora)on (NA-‐NA) 4 Introduction Non-‐ Academics with at 3 least one academic Literature review collabora)on (NA-‐AC) Hypotheses 2 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 Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 19
- 20. Links of Academia and Industry Betweenness Centrality 40 Average Betweenness Centrality (x10^6) 35 Academics with only academic collabora)on 30 (AC-‐AC) 25 Academics with at least one non-‐academic 20 collabora)on (AC-‐NA) 15 Non-‐Academics with only Non-‐academic 10 collabora)on (NA-‐NA) Introduction 5 Non-‐ Academics with at Literature review least one academic Hypotheses collabora)on (NA-‐AC) 0 Data and methodology 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 Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 20
- 21. Links of Academia and Industry Cliquishness 1 0.95 Academics with only academic collabora)on Average Clustering Coefficient (AC-‐AC) 0.9 Academics with at least one non-‐academic 0.85 collabora)on (AC-‐NA) Non-‐Academics with 0.8 only Non-‐academic collabora)on (NA-‐NA) Introduction 0.75 Literature review Non-‐ Academics with at least one academic Hypotheses collabora)on (NA-‐AC) Data and methodology 0.7 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 Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 21
- 22. 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 Introduction than the ones who create collabora)ve partnerships only within their own Literature review Hypotheses Data and methodology Results Policy Implications subgroup (H4 Aff-‐AC/NA pos) Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 22
- 23. Academics: Canada vs. the US Academia / Non-‐Academia (Canada vs. the US) 70.00% 60.00% Percentage of Collabora.ons 50.00% 40.00% 30.00% 20.00% 10.00% Introduction Literature review 0.00% Hypotheses Data and methodology Results Canada The US Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 23
- 24. Academics: Canada vs. the US Betweenness Centrality of Academics (Canada vs. the US) 60 Average Betweenness Centrality 50 40 (x 106) 30 20 10 Introduction 0 Literature review Hypotheses Data and methodology Canada Academics The US Academics Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 24
- 25. Academics: Canada vs. the US Degree Centrality of Academics (Canada vs. the US) 10 9 Average Degree Centrality 8 7 6 5 Introduction 4 Literature review Hypotheses Data and methodology Canada Academics The US Academics Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 25
- 26. Academics: Canada vs. the US Cliquishness of Academics (Canada vs. the US) 0.89 0.87 Average Clustering Coefficient 0.85 0.83 0.81 0.79 0.77 Introduction 0.75 Literature review Hypotheses Data and methodology Canada Academics The US Academics Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 26
- 27. 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 Introduction c) occupy less cliquish network Literature review Hypotheses posi)ons than the Canadian ones (H5 RegAff-‐AC) Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 27
- 28. Non-academics: Canada vs. the US Propor.on of Non-‐academics (Canada vs. the US) 50.00% 45.00% Percentage of Non-‐Academics 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Introduction Literature review Hypotheses Canada The US Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 28
- 29. Non-academics: Canada vs. the US Degree Centrality of Non-‐academics (Canada vs. the US) 10 9 Average Degree Centrality 8 7 6 5 4 Introduction Literature review Hypotheses Canada Non-‐Academics The US Non-‐Academics Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 29
- 30. Non-academics: Canada vs. the US Betweenness Centrality of Non-‐academics (Canada vs. the US) 60 Average Betweenness Centrality 50 40 (x 106) 30 20 10 0 Introduction Literature review Hypotheses Canada Non-‐Academics The US Non-‐Academics Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 30
- 31. Non-academics: Canada vs. the US Cliquishness of Non-‐academics (Canada vs. the US) Average Clustering Coefficient 0.89 0.87 0.85 0.83 0.81 0.79 0.77 Introduction 0.75 Literature review Hypotheses Canada Non-‐Academics The US Non-‐Academics Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 31
- 32. 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 Introduction than the Canadian ones (H6 RegAff-‐NA) Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 32
- 33. 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 Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 33
- 34. 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 Introduction Literature review Hypotheses Data and methodology Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 34
- 35. Thank you Quebec nanotechnology network of researchers (articles) in 2006-2008; academics and non-academics Catherine Beaudry Andrea Schiffauerova Afshin Moazami 35
- 36. Limitations and Future Work Limita.on Future Work • Quan)ty instead of • Indicators for quality; equal weight quality of for every collabora)on; e.g. collabora)on number of cita)ons • The informal • Study of other Introduction rela)onships are professional Literature review Hypotheses ignored networks like Data and methodology LinkedIn Results Policy Implications Limitations and future works Catherine Beaudry Andrea Schiffauerova Afshin Moazami 36
- 37. 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. Catherine Beaudry Andrea Schiffauerova Afshin Moazami 37
- 38. 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. Catherine Beaudry Andrea Schiffauerova Afshin Moazami 38