NEXT STEPS IN NETWORK ANALYSIS

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NEXT STEPS IN NETWORK ANALYSIS Franco Malerba
and Nicholas Vonortas CESPRI and
GWU Workshop Network Analysis An essential
Research Evaluative Tool Brussels 22 April 2005
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Indicators for Evaluation

• Important recent advancements in understanding
  the process of technological advance and
  innovation, and their role in the socio-economic
  environments of modern societies, have resulted
  in significant improvements in the availability,
  breadth, and usefulness of indicators for the
  evaluation on RTD programmes.
• Extensive experimentation in advanced countries
  has culminated in an ever richer set of
  statistical data and related theoretical concepts
  that allow analysts a more realistic chance to
  peer into the black box of innovation. (e.g.,
  ASIF, EPUB, STI-NET, KNOW, STEP-TO-RJVs)

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RTD Indicators

• Indicators for RTD programme evaluation can be
  grouped into four sets
• Input indicators
• Output indicators
• Innovation indicators
• Process indicators

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ST Input Indicators

• Science and technology input indicators were
  developed first
• - They are the easiest to collect.
• - They also accommodated sufficiently well the
  prevalent conceptualization of innovation as a
  linear process.
• Science and technology input indicators include
  indicators such as
• RD expenditure
• Research personnel
• University graduates
• Technological intensity

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ST Output Indicators

• Science and technology output indicators
  complemented input indicators by accounting for
  the results of ST activities.
• Typical examples of ST output indicators are
• Patents
• Scientific publications
• Technology balance of payments
• New products, processes
• High-tech trade
• Output indicators are used in appraising
  longer-term socio-economic outcomes (e.g.
  competitiveness, innovation).

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Innovation Indicators

• Innovation indicators are about a decade old
  (e.g., CIS). They have been developed on the
  basis of the Oslo Manuals. Their advantages
  include
• The collection of unique data of innovation
  inputs, outputs and agent behaviour
• The collection of subject-based data that can
  potentially be combined with other publicly
  available information on the performance of the
  organizations in question (e.g., firms) for a
  richer set.
• Remaining difficulties include the satisfactory
  incorporation of service innovation into the
  surveys and the inability of surveys to capture
  societal effects.

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Process Indicators

• Economists would argue that all these indicators
  could fit well to the classic mold of a
  production function, Y f(X), where X is a set
  of ST input indicators and the Y stands for the
  ST output indicators and innovation indicators.
• We are only now starting to open the middle, the
  black box, the transformation of one into the
  other (function f).
• Some of the information collected through the
  innovation surveys is heading that way by pulling
  in qualitative information on agent behavior.
  Still, nobody can claim we are there yet.

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Network Indicators

• This is exactly where innovation network
  indicators fit in.
• Innovation network indicators account for the
  complex formal and informal relationships among
  economic agents involved in innovation, including
  companies, universities, and government agencies.
• In the past few years several international
  research projects have built extensive
  longitudinal innovation network data on a
  subject-based approach. This allows their
  complement with other publicly available
  time-series information on the performance of
  individual organizations.

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• CESPRI
• BOCCONI UNIVERSITY
• _________
• Evaluation of progress towards a European
  Research Area for
• Information Society Technologies
• Franco Malerba
• Nicholas Vonortas
• Stefano Breschi
• Lorenzo Cassi
• _________

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Aims

• Develop and test a methodological framework for
  the assessment of the characteristics and
  performance of networks supported by IST RTD in
  Framework Programmes
• Establish and prove the basic concepts of a
  mechanism to enhance IST programme monitoring and
  evaluation

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Focus

• Elaboration of mechanisms to collect the
  necessary information and data from various
  sources and compile it appropriately in databases
  specifically constructed to facilitate network
  analysis.
• Analysis of knowledge and partnership networks
  for selected IST domains to study their nature,
  topology and effectiveness in empowering member
  organizations.
• Interpretation of the results with emphasis on
  the utility of network analysis in assessing an
  effective allocation of RTD resources.
• Analysis of networks of inventors and of their
  mobility within the organisations of the sample.

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Network analysis

• Partnership network topology
• Knowledge network topology
• Clustering and Small Worlds
• Agent Positioning Technology and Market
  Leadership

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The Evaluation questions

• How do the characteristics of the IST-RTD
  partnership and knowledge networks compare with
  the characteristics of the global partnership and
  knowledge networks of IST-RTD companies and with
  the characteristics of the related global
  networks?
• How effective are IST-RTD networks as mechanisms
  for transmitting knowledge?

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• How well are the companies participating in
  IST-RTD programmes positioned in the global
  partnership and knowledge networks?
• Are European organisations world leaders in the
  examined IST domains?
• Are the IPs and NoEs creating leading knowledge
  hubs?

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• What makes these knowledge hubs effective?
• What further actions could facilitate the
  development of new world-leading knowledge hubs
  in Europe and to optimise their role in
  industrial competitiveness?

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• To what extent does the prominent network status
  of certain IST-RTD companies or clusters match EU
  technological leadership in certain areas?
• Are the global networks of selected hub
  companies with extensive ICT supply chains
  represented in FP6 IST RTD?
• Are the perceived national IST knowledge hubs
  well integrated into the FP6 network?

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