From Clusters to Ecologies An exploration of Australia's research environment

1. [ ] From Clusters to EcologiesAn exploration of Australia's research environment Marco Fahmi Queensland University of Technology

2. Australia’s Research Strategy The objectives of research funding policies • Increase the global competitiveness of Australian research • Increase the relevance of Australian research to the community at large However, • Australian research is ranked 15th in the world • The role of research is increasingly changing

3. The Problem • Lack of Clarity • Hard to identify problems early • Hard to determine the extent of problems • Lack of Reliable Solutions • Unclear what impact solutions have • No investigation of root causes (if any) • An Alternative Approach • Need for a clinical approach (better diagnosis) • Need for stewardship (longterm management)

4. A 4-Layer Stewardship Model } Policy Evidence-based Stewardship Strategy Conceptual Framework Analysis Data

5. A 4-Layer Stewardship Model Policy Tools Data streams Process Collection and classification of data Output Data repository Conceptual Framework Analysis ← Data

6. A 4-Layer Stewardship Model Policy Tools Statistical analytics Process Mining available data sources Output Statistics and profiles Conceptual Framework ← Analysis Data

7. A 4-Layer Stewardship Model Policy Tools Conceptual framework Process An interpretation of patterns and motifs Output A status report on the environment ← Conceptual Framework Analysis Data

8. A 4-Layer Stewardship Model ← Policy Tools Rules and rewards Process Extrapolation of future scenarios and outcomes Output A stewardship policy Conceptual Framework Analysis Data

9. A Triad of Resources Research priorities Acquiring contracts and funding (Nieminen& Kaukonen, 2001; Harman, 2001) Enhances scientists’ productivity (e.g. Lee & Bozeman, 2005; Landry et al., 1996; Harman, 1999) Policy

10. A Clinical Approach I A fundamental change in the way diseases were dealt with in the 18th century is indicated “… by the minute but decisive change, whereby the question: What is the matter with you?, with which the eighteenth-century dialogue between doctor and patient began … was replaced by that other question: Where does it hurt?” Foucault, The birth of the clinic p. xviii Policy

11. A Clinical Approach II Diagnosis becomes “perceptible and stable... a welding of the disease onto the organism”: “a new distribution of the discrete elements of corporal space” “a reorganization of the elements that made up the pathological phenomenon” “a definition of the linear series of morbid events” Foucault, The birth of the clinic p. xviii Topology Patterns Evolution Policy

12. The Ecosystem Paradigm • Socio-technical environment • Sustainable competition and the resource-based view • A Research Ecosystem • Holistic System Approach Conceptual Framework

13. What is an ecosystem? • Interactions between agents are restricted to their local vicinity. But give rise to system-wide "emergent" properties • The system lacks strong top-down control. Top-down control is often weakened by bottom-up forces • The ecosystem is organised as a heterogeneous network structure • The various elements of the ecosystem are able to adapt to the changing conditions of their environment • The elements of the ecosystem possess mechanisms that evolve new properties and functions under the influence of environmental forces Conceptual Framework

14. Analytical Tools • Research • Statistics • Bibliometrics • Funding • Competitive grants/projects • Research Centres • Interactions • Social Networking Analysis Analysis

15. Caveats • The validity of bibliometric studies rests on the crucial assumption that co-authors are identical to co-operators. • Empirical research has shown that this is not always the case (Laudel 2002) and (Martin, 1997) Analysis

16. Data Sources • Coarse-grained Statistics • ABS & University rankings • Research • Publication Repositories • Interactions • University HR Data • Funding • Grants/Projects Databases Data

17. Stewardship: How to Impact the System Oversight Insight Foresight Macro Feedback loops Constraints Paradigm rules Meso Buffers Flows Patterns Micro Parameters Delays Self-organisation Adapted from (Meadows 1997)

18. Research Oversight Oversight Macro Feedback loops Meso Buffers Micro Parameters

19. Parameters: Financial • Budget of universities is balanced by income generated from attracting international students • We maximize the revenues from international education • Minimize its impact on our system (Marginson 2009) Oversight Micro Parameters

21. Buffers: Financial • “It is inescapable that the present incentive for hyper-growth of international students will continue to skew the whole system in favour of exports at the expense of domestic capacity…” Oversight Meso Buffers

22. Feedback Loops • Research: Move away from basic research and towards applied research • Financial: Reticence to change the structure: “The fear is that if the incentive structure changes export growth will level off or trend downwards.” (Marginson 2009) Oversight Macro Feedback loops

24. Stewardship:How to Impact the System Insight Macro Constraints Meso Flows Micro Delays

25. Delays: Research • Commercialisation of research is counterproductive on the long term • If universities lock breakthrough discoveries in long patent chains it slows the rate of innovation overall. • Commercial R&D and knowledge intensive industries should be developing IP, not universities. (Marginson 2009) Insight Micro Delays

26. Flows: Financial • More financial resources need to be allocated to research • Extra funding for identifiable areas of research strength, plus the most promising new ideas. • It would be much better to provide extra research funding on the basis of research groupings rather than institutions. Insight Meso Flows

27. Word map of Australian research

28. Flows: Interactions • Research networks are instrumental in the diffusion and creation of new knowledge • Interactions/collaborations happen at all levels of granularity in the HE environment • Interactions also take place with the public/private sector Insight Meso Flows

29. Reasons for Collaboration Research Cross fertilisation across disciplines Increasing specialization of science Technical Access to expertise Pooling knowledge for tackling large and complex problems Enhancing productivity Pedagogical Educating a student Learning tacit knowledge about a technique Social Improving access to funds Obtaining prestige or visibility For fun and pleasure From (van Rijnsoever, et al. 2008)

30. Research collaboration between universities in QLD and Northern NSW (10+)

31. Types of Collaborations with the Private Sector Research the relation can involve collaborative research Applied research the company can be an object of a case study Consulting researcher can be a supplier of knowledge Financial the company can fund the chair of the researcher Entrepreneurial the company can be a spin-off of the university Technical a researcher can be a customer for materials From (Carayol 2003)

32. CRC collaborations between universities and the public/private sector ($80M+)

33. Constraints: Financial • Financial incentives reward applications • ARC science/technology research • NHMRC health/biology research • CRC problem-solving/technical • Research is under-funded • Under-funding drives exports, this is why Australian governments are chronically unable to re-invest in universities. Insight Macro Constraints

34. ARC funding map by RFCD ($10M+)

35. CRC funding map ($1B+)

37. Constrains: Research • Academic Rewards • Abundance of journals • High rankings journals Insight Macro Constraints

38. ERA Journal map (Physical, chemical, earth sciences)

39. ERA Journal map (Humanities and creative arts)

40. Constraints: Interactions • The topology of the Network • Network Hubs (determinants of growth) • Network Brokers (determinants of survival) Insight Macro Constraints

41. 2007 research collaborations within QUT (4+)

42. Stewardship:How to Impact the System Foresight Macro Paradigm rules Meso Patterns Micro Self-organisation

43. Self-organisation Natural tendency to collaborate (although it varies) • Motivations for collaborations • Research output • Career advancement • Deterrents for collaborations • Overhead • Opportunity cost Foresight Micro Self-organisation

44. Patterns • Some networks are more important than others for innovation • “Strategic information” networks are most important • Advice networks are less so • Centrality in strategic information networks is a good predictor of recognition for innovation (Considine & Lewis 2007) Foresight Meso Patterns

45. Innovation in Academic Collaboration Networks Research Pedagogy Technical Social Most strategic Least strategic

46. Patterns • Collaboration and career advancement are strongly correlated • Collaboration with academic institutions is most beneficial • Collaboration with the public/private sector is least beneficial (van Rijnsoever et al. 2008) Foresight Meso Patterns

47. Innovation in Collaborations with the Private Sector Research Applied research Consulting Financial Entrepreneurial Technical Most innovation Least innovation

48. Solution: maximise academic collaboration by leveraging funding from industry

49. Paradigm Rules • Financial: Research geared towards economic output • Research: Basic research capacity is more vital in the k-economy: the OECD has shifted its main priority for university research from the nurturing of intellectual property by universities, to the creation and dissemination of ‘open science’. (OECD 2008) Foresight Macro Paradigm rules

50. Paradigm Rules • Interactions: The government policy did not create competition but conformity and loss of diversity • There is a lack of differentiation at the university level (Marginson & Considine 2000) Foresight Macro Paradigm rules