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Identifying Value Co-creation in Innovation Ecosystems Using Social Network Analysis
Innovation Ecosystems Network,Martha G Russell, Neil Rubens
August 2, 2010
Innovation takes at least two.Team skills are required.There are winners and loosers.
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 is Social
The Knowledge Revolution is here.What can we learn to improve our play?
• Martha G Russell, PhD, [email protected]– Sr. Research Scholar, HSTAR Institute– Associate Director, Media X at Stanford University
• Neil Rubens, PhD, [email protected]– Assistant Professor, Graduate School of Information Systems– University of Electro-Communications, Tokyo
• Jukka Huhtamäki, [email protected]– Researcher, Lecturer– Hypermedia Laboratory (HLab) of Tampere University of Technology
(TUT).
• Kaisa Still, PhD, [email protected]– Knowledge Management Specialist– Beijing DT Electronic Technology Co., Ltd
http://www.innovation-ecosystems.orgInnovation Ecosystems Network
• Mario Gastel, [email protected]– Graduate student, Texas Advertising, UT Austin– Fulbright Scholar (2009-11)
• Jiafeng (Camilla) Yu, [email protected]– M.A. in Advertising in Planning Track– The University of Texas at Austin
http://www.flickr.com/photos/ritavitafinzi/2192500407/
Tan, Steinbach, Kumar; 2004
“There is no data like more data” (Mercer at Arden. House, 1985)
2,000 points 500 Points8,000 points
“There is no data like more data” (Mercer at Arden. House, 1985)
http://www.iro.umontreal.ca/~bengioy/yoshua_en/research_files/CurseDimensionality.jpg
Could be easier to find patterns
More Data is Need
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Higher Dimensions: Double Edged Sword
Innovation Ecosystems NetworkInnovation 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.
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.
Optimizing the impact of investments made by stimulus programs and public and private
stakeholders is a quest shared by developers around the world.
A clear understanding of how to invest local resources for global participation that will
accrue benefits to the local area has yet to be fully articulated, and metrics to
measure interim progress are greatly needed. IEN aims to fill this void.
Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.
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Innovation EcosystemsDataset
# of Companies # of People
Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.
Models of Innovation
Economic Innovation (producer innovation)- Schumpeter 1934
End-user Innovation- von Hippel 1986
Strategic Innovation- Hamel and Prahalad 1994
Open innovation- Chesbrough 2003
Collaborative Innovation Networks- Gloor 2005
From organizations to single users to networked individuals
?eClusters
The Place for Innovation
Localized concentrations - Marshall 1890
Menlo Park (Research Park) 1948, Stanford Industrial Park 1951, Research Triangle Park 1959
Clusters- Porter 1998, Saxenian 1994
Regional Innovation Systems- Metcalfe 1995
Innovation Cluster- Yim 2008, 2002
From localized to regional to virtual shared spaces
?Innovation Acceleration
Networks
.
Number of US Technology-based companiesBy sector, Dec 2009
Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.
Need for Updating
“The global map of businesses is increasingly dominated by geographically concentrated groups of companies and related economic actors and institutions”The Use of Data and Analysis as a tool for cluster policy, Green Paper on international best practices and perspectives prepared for the European Commission, November 2008
“Members of a cluster can be sometimes located worldwide, but linked through information and communication technologies… the term e-cluster is used” Danese, Filippini, Romano, Vinelli 2009
“Technological trends are causing a change in the way innovation gets done in advanced market economies”Baldwin & von Hippel November 2009, Harvard Business School Working Paper 10-038
“Recognizing that a capacity to innovate and commercialize new high-technology products is increasingly a part of the international competition for economic leadership, governments around the world are taking active steps to strengthen their national innovation systems”Understanding Research, Science and Technology Parks: Global Best Practices, National Research Council of the National Academies, Report 2009
Regional technology-based economic development
Distance
Old
New
The New Organizational Chart
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
The new maps may be based on the connections - rather than on distance.
Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.
CleanTech
Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.
BioTech
Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.
PR
Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.
Web
Kaisa Still, Neil Rubens, Jukka Huhtamäki, and Martha G. Russell , “Networks of Executive Women in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.
CTOs
CMOs
Investors
Founders
Roles
http://4.bp.blogspot.com/_qFju91K89HM/SxRpABd1DTI/AAAAAAAABjw/6LaSJfjfk-I/s1600/Unexpected_Guests.jpg
Question?
• What interlock patterns characterize investments into technology-based companies being made by Chinese investment firms?
• How are these patterns similar or different to those made by the rest of the world into China?
Context of Investments in/from China
Insights into Innovation
Social Network Analysis
Socially
Constructed
Data
Socially constructed dataset, in English, openly available– all challenges in China
Innovation Ecosystems Dataset: •323 technology-based companies with one or more locations in China•42 Chinese, 77 foreign investment firm•Investment into China US$ 5.4 B•Investment originating from ChinaUS$ 3.1 B
Insights explored:
The flow of financial resources into and out of China
More illustrative than descriptive/prescriptive results
NodeXL, Tableau
Innovation Ecosystem Network
Initial Data Analysis:53% (113) of the Chinese companies from eCIS business sector
50 % (66) of the foreign companies are from the eCIS business sector
Toward Insights about:
Patterns and differences in the characteristics of investment flows
into and from China
More Specific: Context of eCIS sectoreCommerce and electronic security=
eCommerce, software search, network hosting, mobile, games &video, enterprise
Insights into Innovation
Social Network Analysis
Socially
Constructed
Data
Innovation Ecosystem Network
HARVESTInvestments from Chinese
(making investments)
Innovation Ecosystem Network
CULTIVATIONInvestments into China
(receiving investments)
Innovation Ecosystem Network
Network metrics
Innovation Ecosystem Network
Emerging Chinese business clusters linked by investment firms
Innovation Ecosystem Network
• 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-creationhttp://successbeginstoday.org/wordpress/wp-content/unexpected2.jpg
Topline Findings
http://www.fabcats.org/owners/feeding/info.html http://www.flickr.com/photos/manpsing/2618332693/
Passive Learning Active LearningFURTHER RESEARCH• Personal relationships/opportunity networks • Time series analysis• Expansion of data
– Chinese language press releases – Chinese business registries
Innovation Ecosystems Network Regional Studies with Global Perspective
China, Norway, Finland
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Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” Technical Report. Media X, Stanford University, Feb.2010.
Discussion
Data, Tools, Questionswww.innovation-ecosystems.org
Innovation Ecosystem Network
Insights into Innovation
Social Network Analysis
Socially
Constructed
Data