By Scott Dempwolf, presented at the 17th TCI Global Conference, Monterrey 2014.

1. Evolving the Regional Innovation Cluster Paradigm
for an Innovation Driven Economy
Scott Dempwolf
Academic 3: The Evolution of Cluster: from the Competitive Advantage
of Nations to the Cluster Initiatives Greenbook 2.0
12 November 2014

2. Network Models of Regional
Innovation Clusters and their
Influence on Economic Growth
Evolving the Regional Innovation Cluster Paradigm
for an Innovation Driven Economy
17th TCI Global Conference
Monterrey Mexico
November 12, 2014
C. Scott Dempwolf, PhD
Assistant Research Professor
& Director
UMD – Morgan State Joint
Center for Economic Development

3. Regional Innovation Clusters (RIC)
“A geographically-bounded, active network of similar, synergistic or complementary
organizations in a sector or industry that leverages the region’s unique competitive
strengths to create jobs and broaden prosperity.” (EDA, 2011)
This research…
• Validates current cluster
theory and policies
• Exposes their limitation
• Offers useful extensions
We have an opportunity to take
Regional Innovation Clusters to
the next level – to respond to
innovation-driven growth
Limits of Cluster Analysis
1. Active networks are not geographically
bounded
2. presence of networks is assumed but
not measured
3. NAICS-based clusters not sensitive to
emergence
4. based on employment data; does not
connect economic growth to innovation
5. Backward-looking

4. Innovation Driven Growth
a simple stylized model
Invention
Basic Research
Production
Development
Product Improvement
Research Parks
Incubators
Production Employment
Business Attraction
Business Expansion
Business Retention
Innovation
based
Production
TBED
Response
years

5. Innovation Driven Growth
how do we measure it now?
Invention
Basic Research
Production
Development
Product Improvement
Research Parks
Incubators
Production Employment
First Employment Data Available
Clusters defined by established
Industries, not emerging technologies
Business Attraction
Business Expansion
Business Retention
~ 5 years +/-
Innovation
based
Production
Regional
Cluster
Analysis
years
Bottom Line
Industry clusters -by whatever name- reflect
the state of innovation about five years ago

6. Innovation Driven Growth
gaining early actionable intelligence
Invention
Basic Research
Production
Development
Product Improvement
Production Employment
First Employment Data Available
This approach can shorten
the lag between real-time
innovation and actionable
economic development
intelligence by several years
while also revealing rich
talent pools, emerging
technology trends, and
specific E.D. targets
Clusters defined by established
Industries, not emerging technologies
Research Parks
Patents
SBIR Awards
NIH Awards
NSF Awards
NASA Awards
~ 5 years +/-
Innovation
based
Production
A New
Approach
Available Data Sets
Innovation
Network Analysis
years
~ 4 years +/-
State Investment Data
Incubators
Business Attraction
Business Expansion
Business Retention

7. Networks & Network Models
Georgia Innovation Network 2008 – 2010
Locations of selected actors
Networks made up of nodes (vertices)
and links (ties, edges)
Nodes are actors, agents or objects
People, Organizations, Agencies,
Documents, Places *
Links are the relationships that
connect the nodes
Regional innovation clusters are
geographically concentrated but also
have important ties to distant actors

8. Analyzing Regional Innovation Networks
Extract relationships from patent and
research grant data - about 7M records
Use social network analysis (SNA) to
analyze and visualize network structure
Theoretical grounding in sociology
and science of complexity
Behavior of the core network guides
behavior of whole network
Clustering based on intensity of
relationships
This reveals emerging technologies - what
people and firms are working on – and
specialized talent pools
Battelle Innovation Network 2005 – 2010
Created with NodeXL

9. 1. Innovation is more global and more
interconnected than previously
thought
2. Network structure influences
manufacturing employment growth
within about 3 years of patent
application (more for med &
pharma)
3. Economic development strategies
that enhance innovation networks
may be a cost-effective alternative
to current capital intensive
strategies.
4. Innovation networks are (or could be)
drivers of economic development in
tier 2 manufacturing regions.
PA Innovation Clusters
Westinghouse
Westinghouse cluster, Pittsburgh PA Dissertation Conclusions
Network graphics created with NodeXL
Allegheny County
Westmoreland County
Core
2nd tier
3rd tier

10. Regional Innovation Clusters
are Complex, Emergent Systems
Networks are Ideal for Modeling Complex Systems:
• involve many interconnected or interacting parts
• exhibit emergence - behaviors that cannot be understood or
predicted by looking at the components of the system alone
• Emergence is characteristic
of self-organizing networks
• The behavior of the whole
network is driven by the
behavior of the core
• Thus we can focus on the
core and filter out the noise
Pennsylvania Innovation Networks 1990 - 2007 in the periphery

11. Applications
1. Illinois Battery Cluster (2014)
 Identifying emerging opportunities
 Combining cluster and network analysis to develop targeted strategies
2. Great Lakes Patent network (2011)
 Finding current opportunity for growth in large active clusters
 Identifying talent pools
3. Georgia Tech Research Network (2013)
 Visualizing & managing the research portfolio
 Identifying University collaborations
4. Maryland Innovation Network (2011)
 Biotech & Pharma – differentiating comingled clusters
 Zooming in to look at Baltimore’s Clusters
5. Startups, Venture Capital & Accelerators (2014)
 The CrunchBase network for Maryland
 The CrunchBase network for Illinois
6. New Jersey Solar –PV Research & Manufacturing network (2012)
 Visualizing the university – industry gap
 Developing a targeted strategy

12. Illinois Battery Cluster
The Illinois Battery Cluster
illustrates how network analysis
can augment industry cluster
analysis by identifying emerging
technologies and opportunities
for innovation – led growth.
Using network and cluster
analysis together economic
developers can rapidly develop
detailed strategies, identifying
the specific firms, institutions
and agencies involved and how
they need to connect to achieve
economic growth.

13. Illinois Battery Cluster
Cluster Analysis
• Battery manufacturing split
between two clusters
• Communications (335912: 1
est; empl N/A for 2012)
• Lighting (335911: 11 est; empl
N/A for 2012)
• NAICS 33591 Battery manufacturing
2013 (BLS)
– 2013 Location Quotient = .34
– 18 establishments
– 565 employees
Communications Cluster
Communications Equipment Components sub-cluster
Lighting Cluster
Storage Batteries sub-cluster
Conclusion: Limited opportunity

14. Illinois Battery Cluster

15. Illinois Battery Cluster

16. Illinois Battery Cluster
Network Analysis
• 2012 - $120M JCESR created at Argonne
• ‘5-5-5’ goal  significant industry growth ~
2017
• Network identifies specific firms + real &
potential research ties in specific
technologies
Conclusion: The combination of limited
production capacity (from cluster analysis),
strong research capacity & research investment
suggest specific economic development
strategies to capture future job growth.
• Build industry partnerships around existing
firms & supply chains to facilitate growth
• Target specific firms for attraction to grow
cluster rapidly

17. Great Lakes Regional Innovation &
Manufacturing Clusters (core)

18. Great Lakes Innovation Clusters Impact
on Planning Practice

19. Potential University Applications
Well suited for integrating and
managing research across
multiple institutions via open
networks rather than institutional
structure
Visualizing a Research Portfolio
Offers both a big picture and
details of technology
commercialization areas and
opportunities Georgia Tech Innovation Network 2008 - 2010 (2 steps)
Created with NodeXL

20. Maryland Innovation Clusters 2008 - 2010
This analysis showed that the
clustering algorithm is sensitive
enough to distinguish between
pharma and biotech.
Maryland Innovation Network 2008 – 2010
Created with NodeXL
Baltimore Innovation Network 2008 – 2010
Created with NodeXL

21. CrunchBase startup networks 2005-2014
Illinois Startup Network
Although similar in size the Illinois
network exhibits more robust
structure
Little discernable structure; clustering
appears weak
Maryland Startup Network
Some structure and beginnings of
clusters apparent

22. Maryland
Startup Network (CrunchBase 2005 - 2014)
When clustered, spatial agglomeration is the main organizing factor both
locally and for distant capital sources; DBED & TEDCO feature
prominently, followed by a few investment firms.

23. Maryland
Startup Network (CrunchBase 2005 - 2014)
Removing New York, Boston and San Francisco nodes diminishes
spatial influence as an organizing influence, allowing technology clusters
to emerge. (between-cluster ties hidden in this graph)

24. Illinois
Startup Network (CrunchBase 2005 - 2014)
Spatial agglomeration is an important factor in Chicago and North Shore
clusters; Excelerate Labs & HealthBox are prominent accelerators
locally; Strong ‘portfolio’ organization in remaining clusters

25. New Jersey Solar PV Cluster 2008 - 2010
Fruchterman-Reingold layout
In NodeXL
This analysis revealed significant
gaps between solar PV research
& development and solar PV
component manufacturing.
Grid layout in NodeXL
Production Core
Research
Core

26. Next Steps
Academic Research
• Publications
• Presentations at SSTI, TCI Global
• Complete County-level application – St. Mary’s
County, MD CEDS
• Seek NSF SciSIP funding for additional network
research; validation & calibration of the
economic model
• Pending proposal with NIST to evaluate their
impact on innovation and commercialization
(alternative metrics to patent counts)
• Collaboration with UMD HCIL on improvements
to visualizations and NodeXL software
Commercialization
• Launch startup company (fall 2014)
• Engage ten pilot communities / regions over the
next two years
– Mix of different sizes, scales, level of organization,
density
– Focus primarily on manufacturing regions
– Some with cluster strategies, some without
• Pilot studies may include
– A network report (limited version of Illinois
Roadmap)
– Traditional cluster analysis using the Harvard tool
for regions that don’t have it
– An interactive network model
– On-site training & Technical Assistance
• Evaluation of performance across all pilot
regions