Regional Innovation Networks
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Understanding how a regional innovation value network is
activated in different stages of innovation
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Traditional approaches to regional innovation focus primarily on the material inputs into a region, such as finance - and material outputs of the region, an example being the number of patents generated. But innovation within a region is not a mechanistic process - it is a network activity.
From a value network perspective an innovation system can be defined as the system of organizations, individuals, and rules and regulations within which the creation, dissemination, and innovative exploitation of technology and other branches of knowledge take place. When the interaction between the different players works well, then new, valuable knowledge is generated which is quickly put to practical use by commercialization or other implementation. This creates the foundation for innovations and attracts investments.
Expanding the Value Network Analysis (VNA) (Allee 2008) method to assess large-scale networks and Intellectual Capital formation at the level of networks and regions requires finding good sources of data and determining intangible asset indicators that can reasonably be linked to value network patterns. Several developmental projects helped to lay the foundation for large-scale VNA, such as:
- The EU CESPRI (CESPRI 2006), RAND (RAND 2006), EU ICT-RTD (Allee et al 2007)
- Skane Regional Innovation evaluation studies (Daal et al, 2009, Skane 2009, Eriksson 2010)
- An industry analysis of the Global Finance industry (Waddell 2010) and
- Multiple commercial research studies with global players such as SAP
- Mobile Workers (Venezia, Allee and Schwabe 2008)
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Overall objectives of a value network approach
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The basic goal
of this approach is to better understand how a regional innovation value
network is "activated" in different stages of innovation. Some organizations
may be involved in multiple roles, and even though they may be active in more
than one stage their roles may be different in different stages. Evaluating
regional innovation with a value network perspective:
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Provides an expanded foundation for assessing regional innovation capacity and
the effectiveness of the regional innovation system.
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Develops value network indicators to assess the health and vitality of regional
innovation systems and to link innovation system behaviors to regional economic
and Intellectual Capital (IC) indicators.
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Provides a powerful visual language for engaging critical stakeholders,
fostering connective tissue, and improving innovation capacity at the regional
level.
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Defines the requirements for continuous monitoring and evaluation of regional innovation
value networks. Value Network
Analysis is part of a self evaluation of the innovation strength of a given region.
Therefore VNA works best in combination with a systemic meeting approach to
engage in collective sense making and strategy development with the regional
stakeholders and participants in the relevant value networks. Such an approach
has been employed with great success in the Skane Region in Sweden where a
series of systemic meetings are part of the self evaluation effort and are also
part of developing an innovation governance function. (Skane 2009, Daal et al
2009)
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The applied
method includes several different elements, including VNA. Information about
participating organizations is gathered using web surveys, interviews, and
online research. All gathered information about the organizations and the
networks they operate in are consolidated into a single database structured in
accordance with a value network data model. The data is then subjected to data
mining methods in order to discover stable patterns of value conversion that
represent the way work is done in the relevant context.
Involved organizations
are then categorized based on maturity and supportability in respect to value
conversion capability. This step then allows for comparing individual
organizations and their own specific networks among each other in order to
identify best practice approaches, while at the same time leading to specific
interventions necessary on a tactical level to nurture individual networks
towards higher performance.
Three key levels of analysis
The
methodology addresses three key levels:
1.
The conditions or environment of the regional innovation system
2.
The roles, products, and services provided in the supporting value network(s)
3.
The innovation value networks themselves by technology, products, services, or
industry
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An integrated methodology approach using
regional economic and Intellectual Capital Indicators, webcrawls and SNA, VNA,
surveys, and data mining of survey results. Other frameworks can be integrated
that may be in use within a specific region or country.
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Framework for an integrated methodology approach.
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The method is
based on identifying four perspectives:
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Web connectivity - how are websites linked technically?
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Web messaging - what message and business model is communicated by a website?
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Web survey - what view of the network do its individual participants have?
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Interviews - can the emerging network patterns be verified as correct by its
members?
The figure below offers a
process view of the method, once the project scope and boundaries have been
defined.
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A process view of the method.
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A typical webcrawl begins with identification of an initial set of 50-75 URLs of organizations of interest. The analysis team then conducts a qualitative analysis to extract a first standardization of roles and deliverables and first insights of the network, turning each website into a value network. More on this is described in Website Analysis.
All value networks generated during the website analysis are then aggregated into a legible single value network. The deliverables are evaluated to create value creation thumbprints (an overview of what asset types are created by a role), and a value conversion profile (a comparison of the number of deliverables received by a role versus the number of deliverables created by a role), for each network and the whole network. Indicators are also generated such as resilience, stability, risk, agility, maturity, and reciprocity.
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An example: Linking value network patterns to Intellectual Capital formation in regions
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In
2007 an evaluative study "Effectiveness
of ICT RTD Impacts on the EU Innovation System," was conducted for the European Commission, DG INFSO
Evaluation and Monitoring Unit, by ALTEC SA and Edna Pasher PhD &
Associates (Allee et al 2007a and 2007b) under the direction of Peter Johnston,
Head of Unit, and Frank Cunningham, Evaluation Specialist. The aim was to
assess how effectively EU ICT-RTD and deployment initiatives are being
exploited in European systems of innovation at member, state, and regional
levels.
There were three primary goals for the evaluation:
1. To understand the effectiveness of networks of collaboration in
facilitating knowledge transfer across regions and sectors.
2. To identify where and how the links between ICT-RTD, technology
diffusion, and systems of innovation could be strengthened at the EU, Member,
State, and Regional levels
3. To target where and how to strengthen the impact of EU ICT-RTD and
deployment initiatives by leveraging Structural Funds programmes, co-ordinated
public procurement, and Information Society deployment initiatives.
Intellectual Capital assessment
For
this evaluation a base set of Intellectual Capital indicators were identified
and applied at both the regional and national levels, drawing from established
practices in Intellectual Capital and the Skandia Navigator model (Edvinsson
and Malone 1997). The Intellectual Capital (IC) framework provided a set of
indicators based on five focal areas: 1) financial capital, 2) market capital,
3) process capital, 4) human capital and 5) renewal and development capital.
Table: Regional indicators of Intellectual Capital
used in the study.
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Indicator
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Category
Intellectual Capital
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Human
resources in science and technology
(% of population)
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human capital
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Participation
in life-long learning
(per 100 population aged 25-64)
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process capital
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EPO patents
per million population
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process capital
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Employment
in medium-high and high-tech
manufacturing (% of total workforce)
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market capital
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Employment
in high-tech services
(% of total workforce)
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market capital
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Public
R&D expenditures (% of GDP)
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renewal
and development
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Business
R&D expenditures (% of GDP)
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renewal
and development
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Unemployment
(% of total population)
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financial
capital
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GDP per capita
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financial
capital
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Assessing Intellectual Capital formation
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An analysis of FP6 data revealed network patterns
of typical roles and interactions occurring across FP6 projects. From these
basic patterns four specific types of purposeful value networks were identified
and categorized as noted below. These categories were not predetermined or
driven by instrument, but were a result of a direct analysis of project
deliverables as described in project documentation. Analysis of the actual
described deliverables made it possible to assign an intended purpose for each
project that corresponds to one of the four archetypes.
The value network archetypes are important for two
reasons: 1) Each archetype generates a Value Network Intellectual Capital
Profile based on its typical deliverables and beneficiaries; and 2) Each
archetype supports a particular stage of innovation from conception to
implementation in the form of commercialization or production.
It can be assumed that in regions where
participation in any particular value network archetype is high then there
would be a corresponding high performance in generation of Intellectual Capital,
at both the organizational and the regional levels corresponding with the
project deliverables supported by that type of network. Thus regional Intellectual
Capital creation can be linked directly with value network archetypes that are
the intended outcomes of FP6 programs.
Since the ICT-RTD programs are not designed to
generate direct Financial Capital either for the participating organizations or
the beneficiaries of specific projects, assessing financial impact requires
indirect evaluation, consideration of value deliverables generated, and
comparison of macro-economic data with archetype distribution.
The following descriptions and visuals have been
greatly simplified in order to demonstrate the basic patterns of roles and
interactions. Each value network archetype or pattern is shown with a "thumbprint"
graph of its anticipated IC formation for the 10 regions. Anticipated IC
generation provides a foundation for comparative analysis with the actual IC
indicators generated at the organizational and regional level. Analysis of
these patterns over time potentially can surface the critical causal relationships
between value network patterns and IC formation.
Research value network archetype
Most FP6 projects include descriptions of research activity or
innovation exploration. The category of Research was chosen where the primary
aim is to produce research results or an innovative product. The Research value
network consists of tangible and intangible exchanges between the project team
(central node with sub-nodes), intended beneficiaries, and the research community.
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Research value network archetype and anticipated IC creation for 20 regions.
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Community Building value network archetype
The category Community Building was chosen when the aim of the project
is primarily coordinated action or building a network or a community of people
sharing a common interest or common task. The Community Building value network
logically builds on the efforts of a Research archetype, although it also could
be a precursor to launching a research project. This network type consists of
tangible and intangible exchanges between the project team (central node with
sub-nodes), intended beneficiaries, research community, and the practitioner
community.
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Community Building value network archetype and anticipated IC creation for 10 regions.
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Market Validation value network archetype
The Market Validation category was chosen when the product or the result
is well defined, and the project goal is to test and validate market or
beneficiary readiness. The Market Validation value network logically builds on
the efforts of a previous Community Building value network. This network
consists of tangible and intangible exchanges between the project team (central
node with sub-nodes), intended beneficiaries, research community, practitioner
community, and the product packager.
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Market Validation value network archetype and anticipated IC creation for 10 regions.
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Commercialization value network archetype
(visualization)
Commercialization involves actually bringing the product or result to
the market or implementation through production and distribution. The
Commercialization value network logically builds on efforts of a previous
Market Validation value network. This network consists of tangible and
intangible exchanges between the project team (central node with sub-nodes),
intended beneficiaries, research community, practitioner community, product
packager, and the commercializer. It then "closes the circle" through exchanges
between the commercializer and the beneficiary. None of the 10 regions in the
sampling had this archetype represented in their roles and deliverables.
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Commercialization value network archetype and anticipated IC creation for 10 regions.
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Data mining and project interviews confirmed that
not only are there very few cases of organizations being active in both RTD and
deployment networks, but there is also little evidence of ICT results having
followed the entire value network pathway from invention to development, and
from research to deployment/innovation. In-depth analysis shows the great
potential for these value networks to increase innovation capacity, diffuse
innovation, and contribute to Intellectual Capital formation at the regional level.
This 2007 EU evaluation demonstrates that research
program interactions can be fruitfully represented as value networks, operating
both at European and national/regional levels. Regional performance, in terms of value created from FP6 project
participations, depends on the projects being used to improve value network
patterns of knowledge sharing, cooperation, and connectivity within a region,
in addition to benefitting organizations taking part in the project. Value network patterns link to
specific value conversion activities and Intellectual Capital formation for
project partners as well as to the innovation capacity of the region as a
whole.
The practical implication of this work is that Value
Network Analysis provides a possible solution to one of the most challenging
business issues in the intangibles economy: describing and monitoring the role
of intangibles in value creation. VNA offers a scalable method for
understanding the dynamics of intangibles and value creation at virtually every
level of complexity from shop floor and business networks to regions and global
networks.
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Allee, V., Innocenti, A., Koumpis, A., Mavridis, A., Molinari, F., Pasher, E., Shachar, S., Schwabe, O., Tektonidis, D., Tresman, M. and Vontas, A. (2007) "Effectiveness of ICT RTD Impacts on the EU Innovation System: Final Report. Evaluation Study for the European Commission, DG Information Society and Media Directorate C," Lisbon Strategy and Policies for the Information Society, Unit C3 - Evaluation and Monitoring, December 11, 2007. [PDF]
Allee, V., Innocenti, A., Koumpis, A., Mavridis, A., Molinari, F., Pasher, E., Shachar, S., Schwabe, O., Tektonidis, D., Tresman, M. and Vontas, A. (2007) "Annex to the Final Report. Evaluation Study for the European Commission, DG Information Society and Media Directorate C," Lisbon Strategy and Policies for the Information Society, Unit C3 - Evaluation and Monitoring, December 11, 2007. [PDF]
Allee, V. (2008) "Value Network Analysis and Value Conversion of Tangible and Intangible Assets," Journal of Intellectual Capital, Vol 9, Issue 1, pp 5-24. [PDF]
Allee, V., and Schwabe, O. (2009), "Measuring the Impact of Research Networks in the EU: Value Networks and Intellectual Capital Formation," Conference Proceedings, European Conference on Intellectual Capital, Haarlem, The Netherlands, April 28-29, 2009. [PDF]
CESPRI (2006:1) "Evaluation of progress towards a European Research Area for Information Society Technologies," Final Report submitted to the European Commission, Directorate-General Information Society and Media, Unit 3C - June 2006.
CESPRI (2006:2) "Networks of Innovation in Information Society: Development and Deployment in Europe," Interim Report submitted to the European Commission, Directorate-General Information Society and Media, Unit 3C - January 2006.
Daal, C., et al, (2009). The Skane Regional Innovation System A value network perspective: Summary of research results Final Report, December 2009 [PDF]
Edvinsson, L. and Malone, M.S. (1997) Intellectual Capital: Realizing Your Company's True Value by Finding its Hidden Brainpower, Harper Business, New York, NY.
Eriksson, A., ed, (2010) The Matrix: Post Cluster Innovation Policy, VINNOVA, Stockholm. www.vinnova.se/en/Publications/Products/The-Matrix/
Rand Europe (2005), "ERAnets - Evaluation of Networks of Collaboration among Participants in IST Research and their Evolution to Collaborations in the European Research Area (ERA)," Report prepared for the European Commission Directorate-General Information Society - March 2005.
Skane's Innovation Capacity: A Situation Analysis, Region Skane, December 2009. [PDF]
Venezia, C., Allee, V. and Schwabe, O. (2008) "Designing Productive Workspaces for Mobile Workers: Role Insights from Network Analysis," Information-Knowledge-Systems Management: Special Issue: Enterprise Mobility: Applications, Technologies and Strategies, Vol 7, No 1-2, pp 61-75. [PDF]
Waddell, S. (2011) Global Action Networks Creating our Future Together, Bocconi University Press. http://networkingaction.net/
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