Knowledge Across Borders

Knowledge Across Borders
Accelerate Building Trust to Unleash Innovation

Martha G Russell
Innovation Ecosystems Network
Stanford Media X led Research Initiative

October 7, 2010

Martha G Russell
• Public-private partnerships – for science, technology & development
– Tecnopolis, MAMTech, IC2 Institute, Incubators linking SMEs to Value Chain,
CSATA, Agricultural Experiment Station, UNIDO

• Research consortia: University – Industry IDR Research initiatives for
education, research and outreach
– Microelectronic and Information Sciences Center
– Center for the Development of Technology Leadership
– Burnt Orange Productions
– IC2 Institute (Innovation, Creativity, Capital) Think and Do Tank

• Technology Transfer, Marketing and Organizational Change
– Internet2 Sociotechnical Summit, 1999
– Brand relationships, Retail messaging, Youth markets

Although people can communicate anywhere,
anytime, it’s difficult for anyone to have all the
insights necessary at any one time for major
decisions on the complex global issues

Innovation takes at least two.
Team skills are required.
There are winners and loosers.

The Innovation Ecosystems Network (IEN) brings together an
international interdisciplinary team that seeks to develop and
diffuse novel data and tools for understanding the catalytic impact
of regional ICT experiments.

Innovation Ecosystems & Value Co-Creation
Innovation Ecosystems Transformation Framework

A dynamic innovation ecosystem is characterized by a continual realignment of synergistic relationships of people, knowledge, and resources that promote
harmonious growth of the system in agile responsiveness to changing internal and external forces.
Innovation Ecosystems refer to the inter-organizational, political, economic, environmental, and technological systems through which a milieu conducive to
business growth is catalyzed, sustained, and supported.
Value is co-created for the innovation ecosystem through events, impacts and coalitions/networks that emerge from a shared vision of the desired
transformations. Data-driven metrics measure, track and visualise the transformation, empowering interaction with feedback for the shared vision.

www.innovation-ecosystems.org

Research Problem/Questions

Theme: How can data-driven visual social network analysis
provide insights on innovation ecosystems?

We look for insights that can be used to:
• Identify and empower influential individuals for critical actions
• Connect components to catalyze the evolution of the ecosystem
• Develop and implement programs (meetings, funding, initiatives) to foster
co-creator networks
• Communicate complexity to co-create vision
• Measure and transform an innovation ecosystem

How do co-creation networks enable local/regional ROI on
innovation investments made for globalization?

Work in progress!

Structure of the presentation
• Innovation models are changing
• The places of innovation are changing
• Preliminary results from
– Executive Women in Tech-Based Companies
– Investments into and from China
– Norway
• Value Co-Creation

Models of innovation

eClusters !
Collaborative
Innovation
Open innovation- Networks- Gloor
Chesbrough 2003 2005
Strategic
Innovation- Hamel
and Prahalad 1994

End-user Innovation-
von Hippel 1986

Economic Innovation
(producer innovation)-
Schumpeter 1934

Innovation Ecosystems
Silicon Valley Norway
The highest concentration of National and regional level
entrepreneurial high-tech innovation systems and
companies in the world; policies & support

Government-Academia-
STANFORD:
Entrepreneurial management Industry relations
Federal funding for fundamental research The network of Norwegian universities and
Problem-oriented laboratories polytechnics, technology centers,
Faculty leaves and industry affiliates programs,
and other operations…
Students as inventors, disseminators, and workforce
Encouraging student entrepreneurship on campus …
Silicon Valley dense but ad hoc social networks and
Knowledge
nearby planting ground for ideas, startups, &
funding
Innovation Ecosystem
NetworksResources
People Transformation

Shared vision

Infrastructure for Resource Flows
- - - Relationships
The Way We USED to Think About Organizations New Organizational Chart Based on Relationships

Relationship-Focused Co-Creation Infrastructure
(Companies are interlocked through
key people – information flow,
norms, mental models.(Davis,1996)

(Visual) Social Network Analysis
“. . . allows investigators to gain new
insights into the patterning of social
connections, and it helps
investigators to communicate their
results to others.“ (Freeman, 2009)

Relationship Interlocks
• Executives and key employees
– Transfer of technologies and knowledge, professional networks, business
culture, value-chain resources

• Directors
– US Fortune 500 firms interlocked (shared directors) with average 7 other firms
• Corporate governance embedded and filtered through social structures
– Executive compensation, strategies for takeovers, defending against takeovers
• Gerald F. Davis, “The Significance of Board Interlocks for Corporate Governance,” Corporate Governance 4:3, 1996

• Investors and service providers
– Awareness of external forces, competitive insights, resource leverage

• Relationship interlocks provide
– Social relationship “filter” for governance, information flow & norms
– Transfer of implicit and explicit know-how
– Mental models

http://fusionenterprises.ca/Business_Training.php

Archetypes of Social Business
Design

• Ecosystem – a community of
connections
• HiveMind – a socially
calibrated mindset of
individuals
• Dynamic Signal - the constant
multi-faceted means of
collaboration
• Metafilter- a method of
finding signals in vast amounts
of noise

Social Roles in Social Media

• Answer person
– Outward ties to local isolates
– Relative absence of triangles
– Few intense ties

• Reply Magnet
– Ties from local isolates often inward only
– Sparse, few triangles
– Few intense ties

 Discussion person
 Ties from local isolates often inward only
 Dense, many triangles
 Numerous intense ties

Journal of Social Structure
“Visualizing the Signatures of Social Roles in Online Discussion Groups”
http://www.cmu.edu/joss/content/articles/volume8/Welser/

Through personal relationships
companies have interconnects

http://www.fabcats.org/owners/feeding/info.html http://www.flickr.com/photos/manpsing/2618332693/

Passive Learning Active Learning

Traditional Data Gathering Methods

http://www.flickr.com/photos/tomatoskin/1339929731/

Have to react QUICKLY

http://www.flickr.com/photos/clydeorama/3495284608/

Data to measure/track innovation?
Social News Organizations
Media

Federation

Private Visualization
Data

Analysis
Mining

IEN Dataset
Global dataset, includes China

Updated quarterly with 20% growth each quarter

Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves”
Technical
Martha Report. Media X, Stanford University, Feb.2010.

Making Relationships Visible

Willie Framework, OPAALS, 2010.

Data for Visualization & Knowledge Crystallization

Accessing Data Streams about Innovation Building a Dataset on Innovation

Crystallisation Through Visualisation The Card-Mackinlay-Shneiderman visualisation
reference model:(Card et al., 1999; Miksch,
2005)

Towards Actionable Co-Creation Insights
Relationship interlocks structure We apply these methods and tools to
resource flows for co-creation. better understand how local/regional
investments made for globalization can
Openly accessible data provides return benefits to the local region.
directional results. Data can be federated
to co-create datasets.
Visual network analysis
• Reveals co-creation relationships Make complex relationships known for
• People, companies, funding sharing and co-creation
• Reveals patterns of co-creation
• Existing edges and potential links
• Provides analytical opportunities
• Augment dataset with data from
multiple sources, if needed
• Communicates complex relationships
to diverse groups

Johari Window, Joseph Luft and Harry Ingham, 1955

Place of innovation
Innovation
Acceleration
Networks !

Innovation
Cluster- Yim
Regional
2008, 2002
Innovation
Systems-
Clusters- Porter
Metcalfe 1995
1998, Saxenian
1994

Menlo Park (Research Park) 1948, Stanford Industrial Park 1951,
Research Triangle Park 1959

Localized concentrations -
Marshall 1890

.

Technology-based companies - worldwide, Dec 2009

35,000 companies include:
Sectors: Advertising, biotech, cleantech, consulting, ecommerce, enterprise,
games_video, hardware, legal, mobile, network_hosting, public relations,
search, security, semiconductor, software, web, other firms serving these.

Investment profiles from Ltd to public, financing rounds identified
Merger & Acquisition profiles

Technical Report. Media X, Stanford University, Feb.2010.

.

. Employees in technology-based companies - worldwide, Dec 2009


.

Technology-based companies – worldwide
by employee size and sector, Dec 2009


Number of European Technology-based companies
Dec 2009


.

by employee size, Dec 2009


By sector, Dec 2009


European Technology-based companies
By sector and number of employees, Dec 2009


The new maps may be
based on the connections
- rather than on distance.

Example: Executive Women
in Technology-Based Companies
• National dependence on science, technology, math for
competitiveness
• Shortage of women entering, staying, leading
• In tech-based companies,
– roughly 8 % executives are women
• Cleantech sector lowest
– Fewer women in: enterprise, semiconductor and mobile
• Biotech sector highest
– More women in public relations, legal, consulting

What interventions can attract more women to leadership
positions in technology-based companies?

Type of Networks Company Executives, Investors
And Board Members in Technology-Based Companies

Figure 1: Point-to-Point Figure 2: Tree Figure 3: Complex Tree

Figure 4: Simple Star Figure 5: Complex Star Figure 6: Mesh Figure 7: Complex Mesh

Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report

Networks of Female and Male Executives
in Companies in the Clean Tech Sector


in Companies in the Biotech Sector


in Companies in the Public Relations Sector


in Companies in the Web Services Sector


Networks of Female Executives
in Companies – All Sectors


CTOs
the CTO of doctr.com CTO at Hemarina Vice President
Co-founder of Engineering at Survey
HEMARINA Monkey


CTOs – R&D Execs
Advisor at
Chief Software Editor at Principal Research PlaceBlogger
Yandex Scientist at Yahoo! Was a VP at
Netscape and AOL, a
senior director of
Product Development
at Yahoo


Creative CMOs – Biz Dev
Director of User Product Marketing VP, Marketing at Loopt
Experienceof Kosmix Manager at Google Was VP Marketing at
Was Principal UI Worked in Public Project Playlist
Designer at Bebo Relations at Apple,
Marketing at Tiny
Pictures,


CEOs
CEO of Piazzza CEO of NUS Enterprise at
worked at Facebook on the National University of
CEO of SeedCamp their News Feed Team Singapore
was part of the Was Managing Director,
Venture team at 3i Investments, of Bio*One
Capital Pte Ltd


Board Members
CEO of FON USA and
Advisor at Betwyx Co-Chair Disney Media president of the US Advisory
Was VP, Western Networks and Board
Sales at Glam President, Disney-ABC Board of Directors of Posit
Media. Television Group Science, Sabrix,
Was VP of sales at AccountNow, Danger,
MySapce QuinStreet, The Threshold
Group and the Board of
Directors of the NVCA


Founders
Founder/CEO
SmartWork Network
Founder of
TinyMassive
Co-founded Flickr
Formerly COO
Ran Yhoo Tech Dev
Wireless @
group
Realhome.com
Co-founded Brickhouse
Now product Officer at
Hunch


Founders
Founder of Google CEO and Founder of
Webmaster Central LiveHit
Co-founder at
Now works for Ignition Was Vice President of
23andMe
Partners as an Products and Marketing
„entrepreneur in residence‟ at Piczo


Investors
Invested in Fluidinfo; The
Investor at Extrodinaries; Factual;
InnerRewards A Partner with Accel Partners Vizu;Square; Vurve;
Was executive Board at Wetpaint; Trulia; Fluidinfo; ChallengePost;
digital strategist Kosmix; Jaser Design; Airship Ventures; Joobili;
at Johnson & Imperva; Forescout; Glam Dopplr; Wee Web
Johnson Media


What is
Silicon Valley?

The highest concentration of
entrepreneurial high-tech companies
in the world
In 2009 nearly 50%
of US VC went to
Silicon Valley’s.

SV is characterized
by dense networks
of innovation.

Silicon Valley
Number of technology companies by sector – High proportion are small cos (startups)


Example: Chinese International Investments
Context of Investments into/from China
Socially constructed dataset, in English, openly
available– all challenges in China

Socially Innovation Ecosystems Dataset:
Constructed
Data •323 technology-based companies with one or
more locations in China
•42 Chinese, 77 foreign investment firm
Social •Investment into China US$ 5.4 B
Network •Investment originating from China
Analysis US$ 3.1 B

Insights explored:
Insights into
Innovation
The flow of financial resources into and out of
China

More illustrative than descriptive/prescriptive
results

Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell, A Network Analysis of Investment Firms as Resource Routers in Chinese Innovation
Ecosystem, Journal of Networks, Fall, 2010. Innovation Ecosystem Network

More Specific: Context of eCIS sector
eCommerce and electronic security=
eCommerce, software search, network hosting, mobile, games &video, enterprise

Initial Data Analysis:
53% (113) of the Chinese companies
Socially
Constructed from eCIS business sector
Data
50 % (66) of the foreign companies
are from the eCIS business sector
Social
Network Toward Insights about:
Analysis

Patterns and differences in the
Insights into characteristics of investment flows
Innovation
into and from China


HARVEST
Investments from Chinese
(making investments)


CULTIVATION
Investments into China
(receiving investments)

Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell
A Network Analysis of Investment Firms as Resource Routers in Chinese Innovation Ecosystem, Journal of Networks, Fall, 2010.
Innovation Ecosystem Network

Emerging Chinese business clusters linked
by firms’ relatioships

Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell
A Network Analysis of Investment Firms as Resource Routers in Chinese Innovation Ecosystem, Journal of Networks, Fall, 2010.

Topline Findings

• Cultivation / Harvesting modes - value co-
creation
• Chinese interlocks at the investment firm level
– Government-led investment firms
– Knowledge of government guarantees
– Investments in firms that return benefits to China
• Global interlocks at both investment firm and
enterprise levels
• Opportunity network & value co-creation
http://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg

http://www.slowtrav.com/blog/chiocciola/Geirangerfjord.jpg

Example: Norwegian Tech-based Companies
Their Branch Offices and Their Financial Orgs

Example view to IEN dataset in Gephi. Companies are selected
with keyword search “Norway + Norwegian;” the funding
Links show relationships organizations associated with those companies are added Nodes
represent companies and their investors; edges indicate resource
flows. The network layout is created with Yifan Hu Multilevel
PRELIMINARY algorithm and nodes are inflated according to their indegree, i.e.
the number of the connected investors.

Advisors & Investors Expand Access
Investors leverage co-creation
opportunities with investments in
multiple companies. Intl companies not
shown.

Companies leverage value co-creation
opportunities through relationships with
multiple investors. Some investors are
international.

Timeline analysis of investment events
reveals patterns of co-investment – an
indication of intention to co-create value
and, perhaps, stimulus programs.

IEN Dataset, July 2010

International Relationships for
Value Co-Creation
Huge opportunities for
international
relationships lie 2 & 3
degrees out from
Norwegian companies

IEN Dataset, July 2010

Example view to IEN dataset for keyword search. Nodes represent companies and their previous and current
employees. The network layout is created with Fruchterman Reingold algorithm and nodes are inflated according to
their outdegree. Protocols for anonymity are evolving.

Globalization of Innovation Ecosystems

Norwegian tech-based
companies with financing
are more likely to have
networked relationships.

Norwegian tech-based
companies have access to
global relationships
through current board
members, investors, and IEN Dataset, July 2010
key personnel.

Discussion & Takeaways

Knowledge crystallization provides co-creation feedback loop: also support for
interventions, action research, policy analysis.

Visualizations reveal multidimensional complexities.

SNA metrics highlight patterns of ecosystem relationships.

Technically, our framework for tracking, processing and visualizing data enables
the parallel uses of various state of the art analysis tools.

Data sources abound and can be federated for co-creation of analytical & actionable
insights. Collaborations are welcome.

Discovering the story behind numbers and their visualizations requires context,
perspective, interaction and iteration!


What do we know to ask?
What can we learn that we don’t
know to ask?
Make complex relationships known for
sharing and co-creation

http://4.bp.blogspot.com/_qFju91K89HM/SxRpABd1DTI/AAAAAAAABjw/6LaSJfjfk-I/s1600/Unexpected_Guests.jpg

Innovation Ecosystems Network
• Martha G Russell, PhD, martha.russell@stanford.edu
– Sr. Research Scholar, HSTAR Institute
– Associate Director, Media X at Stanford University

• Neil Rubens, PhD, neil@hrstc.org
– Assistant Professor, Graduate School of Information Systems
– University of Electro-Communications, Tokyo

• Jukka Huhtamäki, jukka.huhtamaki@tut.fi
– Researcher, Lecturer
– Hypermedia Laboratory (HLab) of Tampere University of Technology (TUT).

• Kaisa Still, PhD, kaisastill@yahoo.com
– Knowledge Management Specialist
– Beijing DT Electronic Technology Co., Ltd

• Mario Gastel, mariogastel@zeelandnet.nl
– Graduate student, Texas Advertising, UT Austin
– Fulbright Scholar (2009-11)
• Jiafeng (Camilla) Yu, camillayu@gmail.com
– M.A. in Advertising in Planning Track
– The University of Texas at Austin

http://www.innovation-ecosystems.org

Appendix
IEN Work in Progress
Regional case studies are underway:
•Cap Digital, Paris
•Birmingham Science Park Aston
•New York City Media Labs

Recent & Future presentations
July 31, Huangshan, China, “A Network Analysis of Investment Firms as Resource Routers in Chinese Innovation
Ecosystem,” International Symposium on eCommerce and Internet Security 2010.

August 2, 2010, Hong Kong University of Science and Technology, “Identifying Value Co-creation in Innovation
Ecosystems Using Social Network Analysis,” Inaugural Lecture: Innovation Forum.

August 5, 2010, University of Electro-Communications, Tokyo, Japan, “Leveraging Social Media for Analysis of
Business Networks in Regional Technology Development.”
September 14－17, 2010, Nokia, Finland, “Social Networks and Co-creation in Innovation Ecosystems,” EBRF 2010.

September 18-19, 2010, Beijing, China, “Innovation Ecosystems: New Insights with Network Approach,” Beijing First
Global World City Conference.
October 5, 2010, Skei, Norway, “Innovation Ecosystems in Traditional and Changing Cultures: Examples from
Minnesota and Silicon Valley”, Norwegian Information Technology Forum.
October 7, 2010, Olso, Norway, “Knowledge Across Borders: Accelerate Building Trust to Unleash Innovation,”
Business Institute.
October 22, 2010, Madrid, Spain, “Using Social Media to Leverage Triple Helix Insights in Innovation Ecosystems,”
Workshop at Triple Helix Conference VIII, October 12, 2010, Madrid, Spain.
November 7-10, 2010, Austin, TX, “Using Data-Driven Social Network Analysis for Insights on Innovation and Change,”
INFORMS, Austin, TX.
November 14 – 17, 2010, Sacramento, CA, “Social Media Conversations and Value Networks in the Green-tech
Innovation Ecosystem,” 2010 Behavior, Energy and Climate Change Conference.

Collaboration is invited.
Let’s Get Started!
Martha.Russell@stanford.edu 68

Knowledge Across Borders

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (20)

Similar to Knowledge Across Borders

Similar to Knowledge Across Borders (20)

Knowledge Across Borders