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Data-Driven Analysis of Co-Creation in Innovation EcosystemsJukka Huhtamäki, Martha G Russell, Neil Rubens and Kaisa StillEBRF 2010, September 15-16, Nokia, Finland www.innovation-ecosystems.org
Innovation Ecosystems & Value Co-Creation 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. Innovation Ecosystems Transformation Framework: 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: ,[object Object]
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
Measure and transform an innovation ecosystemThis study: How do co-creator networks enable local/regional ROI on innovation investments made for globalization?  Work in progress! www.innovation-ecosystems.org
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)
Data for Visualisation & Knowledge Crystallisation   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)
Investments as Value Co-Creation Companies leverage value co-creation opportunities through relationships with multiple investors. Some investors are international. Investors leverage co-creation opportunities with investments in multiple companies. Intl companies not shown. Timeline analysis of investment events reveals patterns of co-investment – an indication of intention to co-create value. Example view to IEN dataset in Gephi. Companies are selected with keyword search “Finland + Finnish;” the funding organizations associated with those companies are added  Nodes represent companies and their investors; edges indicate resource flows. The network layout is created with YifanHu Multilevel algorithm and nodes are inflated according to their indegree, i.e. the number of the connected investors.  ILLUSTRATIVE
Investments As Value Co-Creation ILLUSTRATIVE Degree distribution Example view to IEN dataset in NodeXL. Nodes represent companies and their investors; companies are selected with keyword search “Finland + Finnish”. Nodes are inflated according to their indegree, i.e. the number of investors of a company. Finnish Industry Investment is the main investor with outdegree 17 (betweenness centrality 1965).

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Innovation Ecosystems at EBRF 2010, Nokia, Finland

  • 1. Data-Driven Analysis of Co-Creation in Innovation EcosystemsJukka Huhtamäki, Martha G Russell, Neil Rubens and Kaisa StillEBRF 2010, September 15-16, Nokia, Finland www.innovation-ecosystems.org
  • 2. Innovation Ecosystems & Value Co-Creation 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. Innovation Ecosystems Transformation Framework: www.innovation-ecosystems.org
  • 3.
  • 4. Identify and empower influential individuals for critical actions
  • 5. Connect components to catalyze the evolution of the ecosystem
  • 6. Develop and implement programs (meetings, funding, initiatives) to foster co-creator networks
  • 7. Measure and transform an innovation ecosystemThis study: How do co-creator networks enable local/regional ROI on innovation investments made for globalization? Work in progress! www.innovation-ecosystems.org
  • 8. 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)
  • 9. Data for Visualisation & Knowledge Crystallisation   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)
  • 10. Investments as Value Co-Creation Companies leverage value co-creation opportunities through relationships with multiple investors. Some investors are international. Investors leverage co-creation opportunities with investments in multiple companies. Intl companies not shown. Timeline analysis of investment events reveals patterns of co-investment – an indication of intention to co-create value. Example view to IEN dataset in Gephi. Companies are selected with keyword search “Finland + Finnish;” the funding organizations associated with those companies are added Nodes represent companies and their investors; edges indicate resource flows. The network layout is created with YifanHu Multilevel algorithm and nodes are inflated according to their indegree, i.e. the number of the connected investors. ILLUSTRATIVE
  • 11. Investments As Value Co-Creation ILLUSTRATIVE Degree distribution Example view to IEN dataset in NodeXL. Nodes represent companies and their investors; companies are selected with keyword search “Finland + Finnish”. Nodes are inflated according to their indegree, i.e. the number of investors of a company. Finnish Industry Investment is the main investor with outdegree 17 (betweenness centrality 1965).
  • 12. Employee Mobility As Value Co-Creation ILLUSTRATIVE Example view to IEN dataset for keyword search “Tampere”. Nodes represent companies and their previous and current employees. The network layout is created with FruchtermanReingold algorithm and nodes are inflated according to their outdegree. Protocols for anonymity are evolving.
  • 13.
  • 14. Discussion & Takeaways Knowledge crystallisation provides co-creation feedback loop: also support for interventions, action research, policy analysis. Visualisations reveal multidimensional complexities. SNA metrics highlight patterns of ecosystem relationships. Technically, our framework for tracking, processing and visualising data enables the parallel uses of various state of the art analysis tools. Data sources abound; can be federated for co-creation of analytical & actionable insights. Collaborations are welcome. Discovering the story behind numbers and their visualisations requires context, perspective, interaction and iteration! www.innovation-ecosystems.org
  • 15. AppendixIEN Work in Progress Regional case studies are underway: Cap Digital, Paris Birmingham Science Park Aston New York City Media Labs Norwegian Regional Development Future presentations September 18-19, 2010, Beijing, China, “Innovation Ecosystems: New Insights with Network Approach”, Beijing First Global World City Conference, September 18-19, 2010, Beijing, China. October 5, 2010, Oslo, Norway, “Innovation Ecosystems in Traditional and Changing Cultures: Examples from Minnesota and Silicon Valley”, Norwegian Information Technology Forum October 5, 2010, Oslo, Norway. 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.

Hinweis der Redaktion

  1. Innovation Ecosystem Network is an international, interdisciplinary collaboration of researchers studying innovation ecosystems using data-driven visualizations. It was established March 2010, and it includes the co-authors of this paper, Jukka Huhtamäki, Martha G Russell, Neil Rubens,Kaisa Still, along with a growing international community of collaborators.This presentation will share some work in progress using data-driven analysis of co-creation in innovation ecosystems.The data used in this analysis is drawn from the IEN Dataset, which was begun in December 2009.it is updated quarterly.This dataset has been developed from openly available information on the web, from press releases and socially constructed data, parsed into a dataset of companies, investment events, and people – executives, board members and investors. In this presentation, we will show you some of our early results. The IEN is open to collaboration and federation on this dataset, and we invite discussion with you afterward on additional questions we might pursue together.
  2. Our research questions center on innovation ecosystems.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.Around the world, policy makers, program leaders, researchers and entrepreneurs want to optimize the impact of their investments.We believe value co-created through a cycle of shared vision and transformations. The people who participate in events create coalitions and networks whose impacts can be measured and tracked with data-driven visualizations, revealing changes. The interaction of key people, using feedback about the transformation, serves to evolve – to co-create – their shared vision.
  3. The Innovation Ecosystems Network has been studying co-creation from several perspectives.We look for insights that can be used to:Communicate complexity to co-create visionIdentify and empower influential individuals for critical actionsConnect components to catalyze the evolution of the ecosystemDevelop and implement programs (meetings, funding, initiatives) to foster co-creator networks Measure and transform an innovation ecosystemFor example, a recent paper in the Journal of Networks reported our study on “A Network Analysis of Investment Firms as Resource Routers in the Chinese Innovation Ecosystem.” In this presentation, I would like to share early results and invite your interest in this larger question:How do co-creator networks enable local/regional ROI on innovation investments made for globalization?I am asking this question specifically about companies (and their people) with associations to Finland.
  4. Relationships provide the infrastructure for resource flows. This is especially important as information technology and globalization have changed the way we think about organizations.These resources might be financial; they might be informational; they might be access to markets or materials. Among executives and key employees, relationships are the basis for the transfer of technologies and knowledge, professional networks, business culture, value-chain resources, and mental models.Corporate governance is embedded and filtered through social structures in the relationships among Directors.These relationships influence co-creation of things such as: executive compensation, strategies for takeovers, defending against takeovers.Through relationships with investors and service providers, businesses co-create an awareness of external forces, of competitive insights, and they are able to leverage resources.Relationship interlocks provide a social relationship “filter” for governance, for information flow & norms. Relationships are the vehicle for co-creating and transferring mental models, as well as implicit and explicit know-how.Using social network analysis we can visualize the patterning of social connections and relationships.
  5. IEN Dataset is derived from English language resources. Some caveats needed for generalizing results to non-english speaking countries.
  6. Example view to IEN dataset in Gephi. Companies are selected with keyword search “Finland + Finnish;” the funding organizations associated with those companies are added Nodes represent companies and their investors; edges indicate resource flows. The network layout is created with YifanHu Multilevel algorithm and nodes are inflated according to their indegree, i.e. the number of the connected investors. Companies leverage value co-creation opportunities through relationships with multiple investors. Some investors are international.Investors leverage co-creation opportunities with investments in multiple companies. Not shown here are international companies linked through ielationships with the same investors.Timeline analysis of investment events reveals patterns of co-investment – an indication of intention to co-create value.What do we see in Funding in Finland:Finnish Industry Investment, Nexit Ventures, Veraventures, Most investment firms have invested in a few investments. Investments from Finland and from elsewhere? Is collaboration Finnish or international?PRINCIPLES AND CONCEPTSNetwork structure: random, small world or scale free? (Barabási, 2003)Network properties:density, cohesion () Phenomena driving network evolution:homophily, reciprocity and transitivity (cf. Giuliani and Bell, 2008)Actor roles: hubs and connectors (Barabási, 2003; Heer, 2005)peripheral, central connector, broker (Hansen, Schneiderman and Smith, 2010)SNA metrics (Wasserman and Faust, 1994):centrality: betweenness centrality, actor degree centralityprestige: actor degree prestige, actor proximity prestige, rank prestige - also rage rank (cite{pagerank1999})
  7. PRINCIPLES AND CONCEPTSNetwork structure: Is the network random, small world or scale free? (Barabási, 2003)Network properties:density, cohesion Phenomena driving network evolution:homophily, reciprocity and transitivity (cf. Giuliani and Bell, 2008)Actor roles: hubs and connectors (Barabási, 2003; Heer, 2005)peripheral, central connector, broker (Hansen, Schneiderman and Smith, 2010)SNA metrics (see Wasserman and Faust, 1994):centrality: betweenness centrality, actor degree centralityprestige: actor degree prestige, actor proximity prestige, rank prestige - also page rank (cite{pagerank1999})