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Identifying Value Co-creation in Innovation Ecosystems Using Social Network AnalysisInnovation Ecosystems Network,Martha G Russell, Neil RubensAugust 2, 2010,[object Object]
8 2-10 hkust eng
8 2-10 hkust eng
8 2-10 hkust eng
8 2-10 hkust eng
Innovation takes at least two.Team skills are required.There are winners and loosers.,[object Object],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,[object Object],Innovation is Social,[object Object]
The Knowledge Revolution is here.,[object Object],What can we learn to improve our play?,[object Object]
http://www.innovation-ecosystems.org,[object Object],Innovation Ecosystems Network,[object Object],[object Object]
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,[object Object]
“There is no data like more data” ,[object Object],(Mercer at Arden. House, 1985),[object Object],“There is no data like more data” ,[object Object],(Mercer at Arden. House, 1985),[object Object],Tan, Steinbach, Kumar; 2004,[object Object],2,000 points,[object Object],500 Points,[object Object],8,000 points,[object Object]
Higher Dimensions: Double Edged Sword ,[object Object],More Data is Need,[object Object],http://wissrech.ins.uni-bonn.de/research/projects/engel/engelpr2/pr2_thumb.jpg,[object Object],Could be easier to find patterns,[object Object],http://www.iro.umontreal.ca/~bengioy/yoshua_en/research_files/CurseDimensionality.jpg,[object Object]
Innovation Ecosystems Network,[object Object],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.,[object Object],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.,[object Object],Optimizing the impact of investments made by stimulus programs and public and private stakeholders is a quest shared by developers around the world.,[object Object],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.,[object Object]
.,[object Object],Innovation Ecosystems,[object Object],Dataset,[object Object],35,000 companies include:,[object Object],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.,[object Object],Investment profiles from Ltd to public, financing rounds identified,[object Object],Merger & Acquisition profiles,[object Object],Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” ,[object Object],Technical Report.  Media X, Stanford University, Feb.2010.,[object Object]
# of Companies,[object Object],# of People,[object Object],Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” ,[object Object],Technical Report.  Media X, Stanford University, Feb.2010.,[object Object]
Models of Innovation,[object Object],From organizations to single users to networked individuals  ,[object Object],eClusters,[object Object],?,[object Object]
The Place for Innovation,[object Object],From localized to regional to virtual shared spaces,[object Object],Innovation Acceleration,[object Object],Networks,[object Object],?,[object Object]
.,[object Object],Number of US Technology-based companies,[object Object],By sector,  Dec 2009,[object Object],Neil Rubens, Kaisa Still, Jukka Huhtamaki, Martha G. Russell “Leveraging Social Media for Analysis of Innovation Players and Their Moves” ,[object Object],Technical Report.  Media X, Stanford University, Feb.2010.,[object Object]
Need for Updating ,[object Object],Regional           technology-based    economic 							development ,[object Object],“The global map of businesses is increasingly dominated by geographically concentrated groups of companies and related economic actors and institutions”,[object Object],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,[object Object],“Members of a cluster can be sometimes located worldwide, but linked through information and communication technologies… the term e-cluster is used” ,[object Object],Danese, Filippini, Romano, Vinelli 2009,[object Object],“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,[object Object],“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,[object Object]
Distance,[object Object],Old,[object Object],New,[object Object]
The New Organizational Chart,[object Object]
Relationship Interlocks,[object Object],Executives and key employees,[object Object],Transfer of technologies and knowledge, professional networks, business culture, value-chain resources ,[object Object],Directors,[object Object],US Fortune 500 firms interlocked (shared directors) with average 7 other firms,[object Object],Corporate governance embedded and filtered through social structures ,[object Object],Executive compensation, strategies for takeovers, defending  against takeovers,[object Object],Gerald F. Davis, “The Significance of Board Interlocks for Corporate Governance,” Corporate Governance 4:3, 1996,[object Object],Investors and service providers,[object Object],Awareness of external forces, competitive insights, resource leverage,[object Object],Relationship interlocks provide,[object Object],Social relationship “filter” for governance, information flow & norms,[object Object],Transfer of implicit and explicit know-how,[object Object],Mental models,[object Object],http://fusionenterprises.ca/Business_Training.php,[object Object]
The new maps may be based on the connections -  rather than on distance.,[object Object]
CleanTech,[object Object],Kaisa Still,  Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,,[object Object], “Networks of Executive Women  in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.,[object Object]
BioTech,[object Object],Kaisa Still,  Neil Rubens, JukkaHuhtamäki, and Martha G. Russell ,,[object Object], “Networks of Executive Women  in Technology-Based Innovation Ecosystems,” Technical Report , Media X, Stanford University, May.2010.,[object Object]

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8 2-10 hkust eng

Notes de l'éditeur

  1. Please think of several patterns and outliers in bicicles picture.ASK AUDIENCE---So let me just mention a few:Color is one of the patters that jumps out right awayFor example there is a lot of aluminum colorsYellow bike jumps out as an outlierIf we look closer we may also notice that there is only one bike where the handles are greenOnly a few bikes have their seat covered with plasticBikes are more or less lined upThere is a bike that is facing the wrong way though----------Even in these small dataset there are so many patterns and outliersBut how many of them are interesting; that really depends.We try to find patterns that are novel; since telling people that bicycles tend to have two wheels is perhaps not so interesting.What is interesting also depends on the purpose;A person checking whether bicycles have permit for parking – is looking for a specific outliersWhen I look for my own bike; I have a different outlier in mindSo ability to spot things that are interesting is extremely important.Outliers are normally discarded in data mining …Because you are often trying to find a pattern, and outliers screw up things.In business, some outliers have become very successful as described in the following book.So we thing it is interesting to look not only for patterns but also for outliers
  2. Can’t do data mining without the data; so we need data and the more the better – since then we can see patterns more clearly
  3. Also when we have more dimensions it is easier to spot patterns
  4. Now let me briefly describe a case of how we utilized the above mentioned principles.In our project we try to understand innovation, so have gathered the data on companies, people and money.What makes this data set different, besides its timeliness is the majority of data (thanks to social media) is about small companies having between 1 – 5 employees.A lot of innovation happens there so it is important to track.
  5. This shows how the models of innovations have evolved reflecting the changes
  6. This shows how we have evolved from the local/regional activities
  7. We can also look at the companies by sector
  8. At the core of this research we have what initially were called “regional technology-based economic development”– however each of the three parts has experienced changes, which calls for updating the whole concept
  9. So far I have shown analysis based on the spatial distance;However the aspects of distance is changing;We don’t know where these people are physically located but they seem to be in the same space.
  10. So the new maps may be based on the connections; rather than on distance.For this analysis we have utilized an open source tool called NodeXL
  11. My name is Neil Rubens, I am not a journalist; I am a data miner – but I think in essense it is not so different.
  12. It is rare that the data is simply brought to us on a silver platterWe have to try hard to actively acquire it
  13. This map indicates the location of the companies. Size of circle indicates number of companies.For this part of analysis we have used Tableau Software.