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

From Clusters to EcologiesAn exploration of Australia's

research environment

Marco FahmiQueensland University of Technology

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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

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)

A 4-Layer Stewardship Model

Data

Policy

Conceptual Framework

Analysis } Evidence-basedStewardship

Strategy

A 4-Layer Stewardship Model

Data

Policy

Conceptual Framework

Analysis

←

ToolsData streams

ProcessCollection and classification of data

OutputData repository

A 4-Layer Stewardship Model

Data

Policy

Conceptual Framework

Analysis ←

ToolsStatistical analytics

ProcessMining available data sources

OutputStatistics and profiles

A 4-Layer Stewardship Model

Data

Policy

Conceptual Framework

Analysis

←ToolsConceptual framework

ProcessAn interpretation of patterns and motifs

OutputA status report on the environment

A 4-Layer Stewardship Model

Data

Policy

Conceptual Framework

Analysis

← ToolsRules and rewards

ProcessExtrapolation of future scenarios and outcomes

OutputA stewardship policy

A Triad of Resources

Research

Interactions

Funding

Enhances scientists’ productivity(e.g. Lee & Bozeman, 2005; Landry et al., 1996; Harman, 1999)

Acquiring contracts and funding(Nieminen& Kaukonen, 2001; Harman, 2001)

Policy

Research priorities

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

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

The Ecosystem Paradigm

• Socio-technical environment

• Sustainable competition and the resource-based view

• A Research Ecosystem

• Holistic System Approach

Conceptual Framework

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

Analytical Tools

• Research– Statistics– Bibliometrics

• Funding– Competitive grants/projects– Research Centres

• Interactions– Social Networking Analysis

Analysis

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

Data Sources

• Coarse-grained Statistics– ABS & University rankings

• Research– Publication Repositories

• Interactions– University HR Data

• Funding– Grants/Projects Databases

Data

Stewardship: How to Impact the System

Micro

Macro

Meso

ForesightOversight Insight

Feedback loops Paradigm rulesConstraints

Buffers PatternsFlows

Parameters Self-organisationDelays

Adapted from (Meadows 1997)

Research Oversight

Micro

Macro

Meso

Oversight

Feedback loops

Buffers

Parameters

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)

Micro

Oversight

Parameters

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…”

Meso

Oversight

Buffers

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)

Macro

Oversight

Feedback loops

Stewardship:How to Impact the System

Micro

Macro

Meso

Insight

Constraints

Flows

Delays

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)

Micro

Insight

Delays

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.

Meso

Insight

Flows

Word map of Australian research

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

Meso

Insight

Flows

Reasons for Collaboration

Research Cross fertilisation across disciplinesIncreasing specialization of science

Technical Access to expertisePooling knowledge for tackling large and complex problemsEnhancing productivity

Pedagogical Educating a studentLearning tacit knowledge about a technique

Social Improving access to fundsObtaining prestige or visibilityFor fun and pleasure

From (van Rijnsoever, et al. 2008)

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

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)

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

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.

Macro

Insight

Constraints

ARC funding map by RFCD ($10M+)

CRC funding map ($1B+)

Constrains: Research

• Academic Rewards– Abundance of journals– High rankings journals

Macro

Insight

Constraints

ERA Journal map (Physical, chemical, earth sciences)

ERA Journal map (Humanities and creative arts)

Constraints: Interactions

• The topology of the Network– Network Hubs (determinants of growth)– Network Brokers (determinants of survival)

Macro

Insight

Constraints

2007 research collaborations within QUT (4+)

Stewardship:How to Impact the System

Micro

Macro

Meso

Foresight

Paradigm rules

Patterns

Self-organisation

Self-organisation

Natural tendency to collaborate (although it varies)

• Motivations for collaborations– Research output– Career advancement

• Deterrents for collaborations– Overhead– Opportunity cost

Micro

Foresight

Self-organisation

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)

Meso

Foresight

Patterns

Innovation in Academic Collaboration Networks

Research

Pedagogy

Technical

Social

Most strategic

Least strategic

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)

Meso

Foresight

Patterns

Innovation in Collaborations with the Private Sector

Research

Applied research

Consulting

Financial

Entrepreneurial

Technical

Most innovation

Least innovation

Solution: maximise academic collaboration by leveraging funding from industry

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)

Macro

Foresight

Paradigm rules

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)

Macro

Foresight

Paradigm rules

Solutions: Financial

Three issues need to be tackled by the government’s funding policy– indexation– the unit level of public funding– full cost research funding

Solutions: Research

• Universities should give their main attention to what they are best at, which is curiosity-driven basic research, its dissemination, and research training.

• This leaves Australia at something of a disadvantage because our policy settings have focused on shifting university research out of basic research and into commercializable activity. As if basic research and industry innovation are ‘either/or’, instead of ‘both and more’.

Solutions: Interactions

• Ensure the sustainability of the research environment because:– Address short-term problems as part of the

long-term survival of the environment– It plays an increasing role in Australian

economy (as an attractor to international students)

– It faces increasing competition from external HE research environments

A Research Ecosystem

• A holistic system approach– Identifying distinctive research features of

universities/groupings– Developing ways to maintain the diversity of

the system– Promote a paradigmatic shift to make the

research and financial solutions possible

Challenges

Technical Access to dataData evaluation

Analytics Bibliometric normalisationConcept Mining

Conceptual What is sustainability?What is diversity?

Policy Policy implementationParadigmatic shifts