Innovation Ecosystems Summit Brochure

Innova&on Ecosystems Summit 11 July 2011

Innova&on Ecosystems Network Innova&on Ecosystems refer to the inter-‐organiza&onal, poli&cal, economic, environmental, and technological systems through which a milieu conducive to business growth is catalyzed, sustained, and supported. A dynamic innova&on ecosystem is characterized by a con&nual realignment of synergis&c rela&onships that promote growth of the system. In agile responsiveness to changing internal and external forces, knowledge, capital and other vital resources flow through these rela&onships. The Innova&on Ecosystems Network is an interna&onal consor&um of data partners, analysis partners and community-‐ of-‐prac&ce partners, dedicated to iden&fica&on and visualiza&on of success factors in technology-‐based development. Through research collabora&ons, quarterly mee&ngs, and resource sharing, we seek to iden&fy paRerns of success and key interven&on points in innova&on ecosystems and enhance sharing of insights among the diverse groups of people. Par&cipa&on in the Innova&on Ecosystems Network is open to Media X member companies and to affiliated partners. -‐ Martha G. Russell Associate Director of Media X at Stanford University Senior Research Scholar at HSTAR at Stanford University Innova&on Ecosystems Network

Agenda

8:00 -‐ 8:30 Registra&on and Con&nental Breakfast Welcome and Introduc&ons 8:30 -‐ 8:45 Martha Russell, Chuck House, Keith Devlin Infrastructure for Innova&on: Systems of Interdependencies Moderator: Marguerite Hancock -‐-‐Norman Jacknis, Infrastructure for Innova&on and Regional Economic Growth 8:45 -‐ 10:15 -‐-‐Torger Reve, Crea&ng Innova&on Dynamics Through Global Knowledge Hubs: An Empirical Analysis of Norway -‐-‐Jim Spohrer, City Ecosystems of the 21st Century Posters, Camilla Yu – See appendix A 10:15 -‐ 10:45 Break and Networking Organiza&onal Systems for Innova&on: Who Leads? Who Follows? Moderator: Kaisa S&ll -‐-‐John Roese, HUAWEI NA R&D Innova&on 10:45 -‐ Noon -‐-‐Willem Jonker, EIT ICT Labs: A New European Approach to ICT Innova&on Ecosystems -‐-‐Yan Xu, Redeﬁning Technology and Innova&on Industry Within the Context of Ubiquitous Innova&on Noon -‐ 1:00 pm Lunch and Networking Resource Networks in Greentech: First Mover Advantages and Boundary-‐Spanning Ac&vi&es Moderator: Martha Russell 1:00 -‐ 2:00 -‐-‐Steve Eichenlaub, The Corporate Venture Investment Ecosystem -‐-‐Deepak Jeevankumar, The Venture Capital Ecosystem -‐-‐Greg Callman, Angels/Agencies 2:00 -‐ 2:20 Break and Networking Analyzing and Visualizing Networks Moderators: Jukka Huhtamäki, Neil Rubens -‐-‐Kimihiko Iwamura, Anatomy of a Personal Network 2:20 -‐ 3:30 -‐-‐Sean Gourley, Mapping the World’s Technology -‐-‐Mathieu Bas&an, Where are Networks? -‐-‐Rahul Basole, Visualiza&on of Converging Ecosystems Knowledge Transfer in Innova&on Ecosystems Moderator: Martha Russell -‐-‐Dan Wang, Brain Drain and Brain Gain 3:30 -‐ 4:30 -‐-‐Egils Milberg, Indicators to Build Shared Vision -‐-‐Chenyang Xu, Insights from Global Scou&ng and Working with Universi&es and Startups 4:30 -‐ 5:30 Networking 5:30 on, Please join the Triple Helix Associa&on Conference, July 11-‐14. Separate registra&on is required. Innova&on Ecosystems Summit

Informa&on •  Tweet about the Innova&on Ecosystems Summit: TwiRer Hashtags: #IESummit, #IEN, #MediaXStanford •  Follow Media X (@MediaXStanford) and Innova&on Ecosystems Network (@IEN_Stanford) on TwiRer •  Media X hRp://mediax.stanford.edu/summit2011.html •  Innova&on Ecosystems Network: hRp://www.innova&on-‐ecosystems.org

Welcome and Introduction

Welcome and Introduc&on Martha G. Russell Dr. Martha G. Russell is Senior Research Scholar at the Human Sciences and Technology Advanced Research (HSTAR) Ins&tute at Stanford University and Associate Director of Media X at Stanford University. She is a Senior Fellow at the Ins&tute for Innova&on, Crea&vity and Capital (IC2) at The University of Texas at Aus&n. She studies innova&on ecosystems using data-‐driven visualiza&on methods for systems analysis and is promo&ng the development of new media metrics for the persuasive impact of interac&ve, place-‐based and social media. Martha has deep experience in cross-‐sector research collabora&on ini&a&ves and interdisciplinary research management. She has established collabora&ve research ini&a&ves in technology leadership and informa&on sciences, pioneered early public-‐private partnerships in microelectronic and informa&on sciences and in manufacturing technologies. Martha has led several entrepreneurial startup ventures in medical technology, agricultural technologies, and consumer marke&ng. She is on the Advisory Boards for Journal of Interac&ve Adver&sing and Technology Forecas&ng and Social Change. Innova&on Ecosystems Summit

Welcome and Introduc&on Charles “Chuck” House Chuck House is Senior Researcher in Stanford’s HSTAR (Human Science and Technology Advanced Research) Ins&tute and Execu&ve Director of Media X. House was instrumental in establishing Stanford’s Values, Technology, Science and Society program that presaged today’s Science Technology and Society Department, he also was a co-‐founder of CITS, the Center for Informa&on Technologies and Society at the University of California, Santa Barbara. House has an extensive industry background – a long development career at HewleR-‐Packard was followed by execu&ve roles at Informix, Veritas, Dialogic and Intel Corpora&ons. He also has experience with start-‐ ups and small companies, selling units to Motorola, TI, Intel, Broadcom, and Centerline. Chuck will be speaking at the IIRUSA-‐sponsored Back End of Innova&on conference taking place October 17-‐19 2011 in La Jolla, CA.

Welcome and Introduc&on Keith Devlin Dr. Keith Devlin is a co-‐founder and Execu&ve Director of the universitys HSTAR ins&tute, and co-‐founder of the Stanford Media X research network, and a Senior Researcher at the Center for the Study of Language and Informa&on. He is a World Economic Forum Fellow and a Fellow of the American Associa&on for the Advancement of Science. His current research is focused on the use of diﬀerent media to teach and communicate mathema&cs to diverse audiences. He also works on the design of informa&on/reasoning systems for intelligence analysis. Other research interests include: theory of informa&on, models of reasoning, applica&ons of mathema&cal techniques in the study of communica&on, and mathema&cal cogni&on. He has wriRen 30 books and over 80 published research ar&cles. Recipient of the Pythagoras Prize, the Peano Prize, the Carl Sagan Award, and the Joint Policy Board for Mathema&cs Communica&ons Award. In 2003, he was recognized by the California State Assembly for his "innova&ve work and long&me service in the ﬁeld of mathema&cs and its rela&on to logic and linguis&cs." He is "the Math Guy" on Na&onal Public Radio. Innova&on Ecosystems Summit

Infrastructure for Innovation:Systems of Interdependencies

Infrastructure for Innova&on: Systems of Interdependencies Moderator: Marguerite Gong Hancock Marguerite Gong Hancock is Associate Director of the Stanford Program on Regions of Innova&on and Entrepreneurship (SPRIE), an interdisciplinary and interna&onal research program at Stanford University’s Graduate School of Business. A poli&cal economist, Marguerite leads research ini&a&ves, conferences, and publica&ons on topics ranging from "China 2.0: The Rise of a Digital Superpower" to "Smart Green Ci&es: New Technologies, Models, Strategies.” Marguerite co-‐directs an execu&ve educa&on program, "Leading Innova&ve and Entrepreneurial Regions in the Global Economy.” She is co-‐editor of books published by Stanford including The Silicon Valley Edge (2000), Making IT: The Rise of Asia in High Tech (2006), and China’s Quest for Innova&on (2008). Currently, she is co-‐authoring a book on the drivers and global implica&ons of the ascendance of China’s internet industry.

Infrastructure for Innova&on: Systems of Interdependencies Infrastructure for Innova&on and Regional Economic Growth Norman Jacknis, Internet Business Solu&ons Group, Public Sector, Cisco Informa&on highways connect local people and businesses to global partners and opportuni&es. The dynamic networked organiza&on requires technology, process and culture. Dr. Norman Jacknis is Director, Cisco IBSG Public Sector (the company’s open innova&on and pro-‐ bono strategic advisory group). Before joining Cisco in Feb. 2008, Jacknis served more than ten years as CIO and commissioner of Westchester County, NY government. Under his leadership, Westchester County won numerous awards, including one of the global top seven Intelligent Communi&es. Government Technology selected him as one the “Top 25 Doers, Dreamers and Drivers.” At Cisco, he has worked with several na&onal organiza&ons of senior public oﬃcials, including the US Conference of Mayors, with special focus on developing their strategy for future-‐oriented economic growth. His recent wriRen work includes a blog for state/local elected execu&ves and a chapter for the book, “CIO Leadership for Ci&es & Coun&es.” Jacknis received his Doctorate, Masters and Bachelors degrees from Princeton University. Innova&on Ecosystems Summit

Infrastructure for Innova&on: Systems of Interdependencies Crea&ng Innova&on Dynamics Through Global Knowledge Hubs: An Empirical Analysis of Norway Torger Reve, Wilh Wilhelmsen Chair, Strategy and Industrial Compe&veness, BI Norwegian, School of Management, Norway Metrics for 6 driving forces of knowledge-‐driven innova&on. Torger Reve currently holds the Wilh Wilhelmsen Chair in Strategy and Industrial Compe&&veness at BI Norwegian School of Management, where he also heads the Center for Mari&me Compe&&veness. Torger Reve has been President at BI Norwegian School of Management, 1997-‐2005. He is currently a member of the board of directors at Ekornes ASA, a leading interna&onal furniture manufacturer. He is also chairman of the Council of Strømme Founda&on which is a Microﬁnance NGO working in Africa, Asia and La&n America, and member of the R&D councils of Mari&me Port Authori&es (MPA) of Singapore and SIMULA, a center of excellence in soxware industry.

Infrastructure for Innova&on: Systems of Interdependencies City Ecosystems of the 21st Century Jim Spohrer, Director, Almaden Services Research, IBM Almaden Research TwiRer: @JimSpohrer Blog: "Spohrer on Service” hRp://service-‐science.info/archives/category/blogs/spohrer A network of interfacing systems describes complex interdependencies in 21st century ci&es. Educa&onal ins&tu&ons renew knowledge resources across many of these systems. Jim Spohrer is the Director of IBM University Programs Worldwide at the IBM Almaden Research Center in San Jose, California, where he works to understand the co-‐ evolu&on of ci&es and universi&es as &ghtly-‐coupled holis&c service systems. Previously, Jim was the founding Director of Service Research in IBM Research, the founding CTO of IBM Venture Capital Rela&ons Group in Silicon Valley California, as well as an Apple Dis&nguished Engineer Scien&st Technologist. Jim received a B.S. in Physics from MIT in 1978, and a Ph.D. in Computer Science from Yale University in 1988. Innova&on Ecosystems Summit

Organizational Systems for Innovation: Who Leads? Who Follows?

Organiza&onal Systems for Innova&on: Who Leads? Who Follows? Moderator: Kaisa S&ll Dr. Kaisa S&ll currently works for VTT Technical Research Centre of Finland and collaborates with Stanford’s Innova&on Ecosystems Network. Her research interests include innova&on, technology transfer, and the role of technology, with a focus on informa&on and knowledge crea&on, sharing, and management -‐ emphasizing support for collabora&on and coopera&on in organiza&ons as well as in community seyngs. Recent studies include mobile, online and social networking communi&es, innova&on ecosystems, and innova&on indicators. Dr. S&ll has over 10 years of cross-‐sector business and academic experience in Finland, USA and China.

Organiza&onal Systems for Innova&on: Who Leads? Who Follows? HUAWEI NA R&D Innova&on John Roese, Senior Vice President and GM North American R&D at Huawei Simultaneously innova&ng technologies and developing markets requires crea&ng a dynamic ecosystem. What are the fastest changing components? Which elements are the most stable? John Roese is the Senior Vice President and GM North American R&D for Huawei. He is an industry recognized Chief Technology Oﬃcer/R&D Execu&ve within the enterprise, carrier, wireless, wire line, security and IT sectors with a proven history of transforming and opera&ng both focused and extremely large R&D organiza&ons, providing industry thought leadership and vision and evangelizing that future to both customers and the wider industry of press, analyst, investor and partners. His areas of exper&se include vision crea&on and evangelism within the broader telecom and IT industry; opera&onal execu&ve leadership of large scale R&D organiza&ons in excess of $1B; enterprise and carrier technology and market exper&se; ecosystem development and partnering; and technical exper&se in a wide area of disciplines including silicon development, hardware design, soxware design, systems and applica&ons (20 granted and pending patents). John is an accomplished author, public speaker and external representa&ve of the company to the press, analysts, investors and industry. Innova&on Ecosystems Summit

Organiza&onal Systems for Innova&on: Who Leads? Who Follows? EIT ICT Labs: A New European Approach to ICT Innova&on Ecosystems Willem Jonker, CEO, EIT ICT Labs EIT ICT Labs is a new ini&a&ve by the European Union intended to turn Europe into a global leader in ICT innova&on. It aims to fulﬁll this mission by establishing a new type of partnership between leading companies, research centers, and universi&es in Europe. As a Knowledge and Innova&on community, EIT ICT Labs speeds up ICT innova&on by bringing people together from diﬀerent countries, disciplines and organiza&ons via mobility programs and co-‐loca&on centers. Through the transforma&on of higher educa&on, EIT ICT Labs breeds entrepreneurial top ICT talent by promo&ng crea&vity and entrepreneurial spirit. EIT ICT Labs’ research ac&vi&es are focused on broader and faster industrializa&on of research results in order to generate world-‐class ICT business. Prof. Dr. (Willem) Jonker is the CEO of EIT ICT Labs. Prof. Dr. Jonker has a broad background in ICT, both in industry as well as in academia. He studied mathema&cs and computer science at Groningen University, worked at Delx University of Technology, received his PhD from the University of Utrecht, and is a part-‐&me full professor in computer science at Twente University. Prof. Dr. Jonker’s industrial experience covers telecommunica&ons (KPN), IT (European Computer industry Research Centre, Munich) and consumer electronics (Philips). He has held posi&ons as researcher, interna&onal project leader, department head, sector head, and account manager. In 2006 he was appointed Vice President Philips Research. Prof. Dr. Jonker has served European ICT research in various ways, amongst others as project leader, reviewer, and advisor.

Organiza&onal Systems for Innova&on: Who Leads? Who Follows? Redefining Technology and Innova&on Industry Within the Context of Ubiquitous Innova&on Yan Xu, Associate Dean, EMBA, Execu&ve Programs & China Strategy, HKUST Hong Kong’s 5 year plan for ac&va&ng innova&on throughout the economy – technology, service, educa&on, and government. Who leads? Who follows? Yan Xu is Associate Dean of the HKUST Business School, Hong Kong University of Science and Technology (HKUST). Yan’s research and teaching interests include technology and innova&on management and policy, as well as regulatory policy of telecommunica&ons. He has provided extensive consul&ng and execu&ve training for the various organiza&ons and enterprises. Tradi&onal defini&on of technology and innova&on industry tends to designate certain specific industrial sectors as technology and innova&on industry. As a result, government policy has ignored vast industrial sectors and has hindered the overall development of innova&on. On the basis of his project for the Central Policy Unit of Hong Kong Government, Yan proposed a new approach to redefine the technology and innova&on industry. Innova&on Ecosystems Summit

Resource Networks in Greentech: First MoverAdvantages and Boundary-Spanning Activities

Moderator: Martha G. Russell

Resource Networks in Greentech: First Mover Advantages and Boundary-‐Spanning Ac&vi&es The Corporate Venture Investment Ecosystem Steve Eichenlaub, Managing Director, Placorm Technologies, Cleantech, and Healthcare Sectors, Intel Capital Accelera&ng innova&on in exis&ng and emerging ecosystems. Criteria and &meframe for managing the risks and beneﬁts of corporate venture investments Interfacing corporate decision and strategy cycles with startup evolu&on and uncertain&es. Steve Eichenlaub joined Intel Capital in 1998 and is a vo&ng member of the Pla}orm Technologies, Cleantech, and Healthcare investment commiRees. Steve leads a worldwide team of investment managers driving equity and technology licensing rela&onships with early-‐ and mid-‐stage companies to expand, align and accelerate the fron&ers of technology in the context of driving posi&ve ﬁnancial returns for Intel. Prior to Intel, Steve worked at leading soxware companies Adobe Systems and Mentor Graphics, and at start-‐ups Silicon Compiler Systems and GammaMetrics. He holds a BS in Electrical and Nuclear Engineering from UC Berkeley, and an MBA from Harvard Business School. Innova&on Ecosystems Summit

Resource Networks in Greentech: First Mover Advantages and Boundary-‐Spanning Ac&vi&es The Venture Capital Ecosystem Deepak Jeevankumar, Senior Associate, Growth Catalyst Partners TwiRer: @dj4tec Ac&va&ng synergy across new en&&es from different ecosystems. Empowering focused energy with the big picture. Deepak Jeevankumar is a Venture Capitalist at General Catalyst Partners. Deepak focuses on investments in new and exis&ng technology business, specifically clean energy. Prior to joining GC, Deepak worked at Sun Microsystems and was an intern at the Yale Investments Office. At Sun, he worked with Sun’s Chief Architect in designing some of the world’s fastest supercomputers and headed Sun’s Asia-‐Pacific High Performance Compu&ng team. He was also responsible for many green compu&ng business development ini&a&ves in this space.

Resource Networks in Greentech: First Mover Advantages and Boundary-‐Spanning Ac&vi&es Agencies and Angels Greg Callman, Commercializa&on Advisor -‐ ARPA-‐E at U.S. Department of Energy Seeding the science, seeking the market, and making connec&ons in between. First mover advantages. Greg Callman is a Commercializa&on Adviser at the Advanced Research Projects Agency for Energy (ARPA-‐E) of the U.S. Department of Energy. Greg also served DOE as a member of the Recovery Act Team under the direc&on of MaR Rogers. Before joining DOE, Greg directed corporate development for a Bay Area biochar venture, and previously founded a strategy and opera&ons consultancy in The Netherlands. Greg studied Energy Policy and Finance at Johns Hopkins, SAIS, and Biochemistry at the University of Virginia. Innova&on Ecosystems Summit

Analyzing and Visualizing Networks

Analyzing and Visualizing Networks Moderator: Jukka Huhtamäki Jukka Huhtamäki (M.Sc, Hypermedia) is a researcher, a post-‐graduate student, and a teacher working for the Hypermedia Laboratory (HLab) at Tampere University of Technology, Finland and collaborates with Stanford’s Innova&on Ecosystems Network. His research interests include visual social media analy&cs, methods of streamlining social network visualisa&on and informa&on visualisa&on, user and informa&on modeling, and the development methods and implementa&on technologies of social, adap&ve, and distributed hypermedia. Currently, Jukka is working to develop data-‐driven visual analysis processes for insights on social media usage and innova&on diﬀusion. Innova&on Ecosystems Summit

Analyzing and Visualizing Networks Moderator: Neil Rubens Dr. Neil Rubens is Assistant Professor at the Knowledge Systems Laboratory, University of Electro-‐Communica&ons, Japan. He is the Director of Ac&ve Intelligence Research Group and collaborates with Stanford’s Innova&on Ecosystems Network. He holds a Ph.D. degree from the Tokyo Ins&tute of Technology and a M.Sc. degree from the University of MassachuseRs. His research focuses on developing Ac&ve Intelligence systems -‐-‐ self-‐ adaptable systems that ac&vely acquire data and learn in an unsupervised/semi-‐supervised manner.

Analyzing and Visualizing Networks Anatomy of a Personal Network Kimihiko Iwamura, Founder, Managing Director, Valley Breeze Consul&ng, LLC; Tipping Point Ventures The rela&onship origins and organiza&onal background of a personal network Kimi is a seasoned strategist and cross-‐border business launcher. He guides new cross-‐border business from ini&al strategy to execu&on and collaborates with Stanford’s Innova&on Ecosystems Network. Kimi ini&ated and managed more than 10 collabora&ve R&D projects between Japanese companies and R&D organiza&ons in Silicon Valley, including Stanford University, UCB, and Lawrence Livermore Na&onal Laboratories. He has 20 years experience developing cross-‐border marke&ng, business alliances, and partnerships in Silicon Valley. He is also a visi&ng scholar at Stanford University. Innova&on Ecosystems Summit

Analyzing and Visualizing Networks Mapping the World’s Technology Sean Gourley, Co-‐founder and CTO, Quid, Inc. Integra&ng patent, publica&on and business informa&on for network analysis and insights. What is revealed and what is hidden? Sean Gourley is Quid co-‐founder and CTO, and did research into the mathema&cs of war for his PhD thesis at Balliol College, Oxford. His ﬁndings appeared as the featured ar&cle in "Nature" (December 2009) and were the subject of a popular TED talk (2009). His work on sta&s&cal analysis, probability, and algorithm development applied to complex systems and large datasets inspired the crea&on of Quid. Sean is a Rhodes Scholar PhD in Physics (Complexity) from the University of Oxford; his undergraduate degree in Physics is from the University of Canterbury, Christchurch, New Zealand.

Analyzing and Visualizing Networks Where are Networks? Mathieu Bas&an, Data Scien&st at LinkedIn & Gephi Sogware Architect TwiRer: @mathieubas&an Blog: hRp://gephi.org/blog Using Exploratory Network Analysis of innova&on, patents, companies, and publica&ons. What personal insights are provided through LinkedIn InMaps? What is revealed and what is hidden? Mathieu Bas&an is the co-‐founder of the Gephi open-‐ source project. He has a M.Sc. in Computer Science from University of Technology of Compiègne in France and is a highly mo&vated technical leader with a passion for soxware development, data visualiza&on and open-‐ source communi&es. Since 2007, Mathieu is developing the Gephi pla}orm and animates the vibrant community. Recognized for its performance, usability and extensible design, the Gephi soxware is supported by the Google Summer of Code program and received the Duke’s Choice Award in 2010. Mathieu recently moved to California to work in the Data Analy&cs team at LinkedIn. There, he has worked on InMaps, an interac&ve visualiza&on for a personal LinkedIn network, and con&nues to focus on data-‐driven products. Innova&on Ecosystems Summit

Analyzing and Visualizing Networks Visualiza&on of Converging Ecosystems Rahul C. Basole, Ph.D., Tennenbaum Ins&tute, Georgia Tech Network analysis can show diﬀerent perspec&ves: periscope, periphery, and ecosystem. What is revealed and what is hidden in each perspec&ve? Rahul C. Basole is Research Scien&st in the Tennenbaum Ins&tute at the Georgia Ins&tute of Technology. His research focuses on innova&on management and technology strategy in complex enterprise systems. In par&cular, Dr. Basole conducts research on the modeling, analysis, and visualiza&on of extended enterprise networks and business ecosystems in domains such as mobile telecommunica&ons, biotechnology, healthcare, and global manufacturing.

Knowledge Transfer in Innovation Ecosystems

Knowledge Transfer in Innova&on Ecosystems Moderator: Martha G. Russell

Knowledge Transfer in Innova&on Ecosystems Brain Drain and Brain Gain Dan Wang, PhD Candidate, Stanford University Department of Sociology TwiRer: @dansalright Highlights and indicators from a study of knowledge transfer by former J1 Visa holders. Dan Wang is a Ph.D Candidate in Sociology at Stanford University, focusing on how knowledge is diffused, recombined, and generated in networks within and between organiza&ons. His past research has examined the effect of Chinas changing patent laws on domes&c R&D collabora&on, tac&cal diffusion through American social movement organiza&on networks, and knowledge transfer in academic co-‐authorship networks. He received his BA in sociology and compara&ve literature from Columbia University. Innova&on Ecosystems Summit

Knowledge Transfer in Innova&on Ecosystems Indicators to Build Shared Vision Egils Milberg, Execu&ve Director, Washington Economic Development Commission Feedback and repor&ng cycles for public and private ini&a&ves. Egils Milberg is the execu&ve director of the Economic Development Commission of Washington State. The Commission is charged with developing a long term economic development strategy. He is a noted thought leader and strategist in global innova&on, advanced manufacturing, compe&&veness and public-‐private partnerships. He held previous posi&ons as president and founder of the Center for Accelera&ng Innova&on, president of the Na&onal Coali&on for Advanced Manufacturing, president of the Ins&tute for Illinois, Deputy Assistant Secretary for produc&vity, technology and innova&on for the U.S. Commerce Department, and execu&ve director the President’s Commission on Industrial Compe&&veness. He is a graduate of Harvard College.

Knowledge Transfer in Innova&on Ecosystems Insights from Global Scou&ng and Working with Universi&es and Startups Chenyang Xu, General Manager, Technology-‐to-‐Business Center, Siemens Managing aRen&on on the things that maRer most. Chenyang Xu is General Manager of Technology-‐to-‐ Business Center (TTB), a part of Siemens Corpora&on, located in Berkeley, California. He is responsible to drive TTB’s open disrup&ve innova&on processes, including the iden&ﬁca&on, incuba&on, and investment of promising disrup&ve technologies by partnering with promising innovators and entrepreneurs outside of Siemens to introduce innova&ve products to markets and launch promising start-‐up companies. He earned his Ph.D. in Electrical and Computer Engineering from Johns Hopkins University. He is a member of the Industry Advisory Board of UC Berkeley (EE/CS) and a member of the advisory board at the University of California’s Center for Informa&on Technology Research in the Interest of Society (CITRIS). Innova&on Ecosystems Summit

Appendix A: Posters

Coordinator: Camilla (Jiafeng) Yu Camilla Yu works for Media X at Stanford University, Silicon Valley Innova&on Ins&tute and collaborates with Stanford’s Innova&on Ecosystems Network. Her research interest and work experience covers social media, online marke&ng, mobile applica&ons and project management in Silicon Valley, Aus&n and Shanghai. Camilla is also a strategic planner and brand consultant for companies and organiza&ons. Her recent study analyzed TwiRer to understand branding and reputa&on of innova&on hubs. Camilla graduated from the master program in the University of Texas at Aus&n. Her passion is to build connec&ons between people, companies and regions in the Innova&on Ecosystems Network.

University & Alumni Other Nodes Alumni Network Analysis University Alumnus Company Stanford Financial Org. Size (degree log-scaled) MIT Company Relations (education, employment, investment) Harvard Person Berkeley Other University Universities Size (Centrality log-scaled) (a) Stanford University. (d) UC Berkeley. (b) Harvard University. (c) MIT.Alumni Connections are important relationship resources that contribute to auniversitys character. Although alumni connections represent networks,evaluations tend to ignore network qualities, from which an alumni network getsits name. We show that by analyzing alumni connections as networks, it ispossible to reveal different characteristics of alumni networks.The ﬁgure shows ego-centric alumni networks of four universities (Stanford,Harvard, MIT, Berkeley) consisting of universities, alumni and companies thatalumni are associated with through employment, investment or board levelpositions. While alumni networks share many characteristics, differences amongalumni networks include ratio of companies/alumni, collaboration patterns (e.g.persistence of relationships), and new alumni metrics -- network measures.Innovation Ecosystems refer to the inter-organizational, political, economic,environmental, and technological systems through which a milieu conducive tobusiness growth is catalyzed, sustained, and supported. More Information:N. Rubens, M. G. Russell, R. Perez, J. Huhtamäki, K. Still, D. Kaplan, and T. Okamoto. "Alumni Network Analysis". In IEEE Education Engineering (EDUCON 2010), Apr 2011. Universities in the Innovation Ecosystem Network http://innovation-ecosystems.org

B)*"C)*1" H**&?)I&*"J4&->-/,-"E8+/"" D09B9"%)*5+5)/," Brain drain and brain gain K,5+)"L")/"E/)*7&25"F*+?,2-+/>"B,()2/,*/"&7"E&4+&3&1>A"E/)*7&25"F*+?,2-+/>" M83>"!!A"#N!!" 5=.)*1G-/)*7&259,58" The movement of people and knowledge in an era of economic globalization What knowledge do return migrants The Global Careers Survey What barriers stand in the way of bring back to their home countries? brain circulation? Measuring knowledge… 53% of respondents successfully transferred knowledge from the U.S. to … transfer success companies in their home countries. … type (e.g. technical) 35% of respondents report that the … novelty knowledge they transferred was better in terms … quality of quality than their domestic co-workers. Respondents: 4,108 Skilled Immigrant Workers in U.S. … tacitness -  J1 Visas sponsored by CDS International 55% of returnee respondents want to -  81 Different Countries, 1,377 different U.S. Host Companies come back to the U.S. to work on a long-Strategy -  Industries include software, finance, media, fashion, museums, etc. term to permanent basis.1.  Ask respondent to recall most recent knowledge -  Age range: 24 – 39 transfer scenario. -  Career history, knowledge transfer activities, location preferences2.  Ask respondent to describe knowledge along a matrix of dimensions. Which countries benefit from skilled Home Country US Returnee knowledge transfer by type and home country income 0.6 Company Company High Income Ctry. return migration? Upper-Middle Income Ctry. 0.5 Lower Middle/Low Income Ctry. !" #" 0.4 Knowledge transfer success by returnee home country Returnee entrepreneurship by returnee home country 1.0 0.20 0.3 $" 0.9 0.2 0.15 Proportion of respondents 0.1 0.8 0.0 Workplace Inter-org 0.10 Technical Product Relations Relations Workflow 0.7 Knowledge transfer success by type of knowledge !"#  $%&()%*+%,- Proportion reporting entrepreneurial activity Proportion reporting knowledge transfer success 0.05 0.90 0.6 0.85 %&()*+,-".+/0")"12,)/,2"+*/,2*)/)+&*)3"(2,-,*4," 0.80 0.5 0.00 Italy )5&(/"&2,"6*&.3,51,"72&"2,/82*,,-9" Italy India Brazil China Japan Brazil China Poland France Austria Mexico Turkey Austria Poland France Mexico Canada Canada Malaysia 0.75 Germany Malaysia Romania Germany Singapore Singapore Switzerland Switzerland Korea, Rep. United Kingdom 0.70 !.#-/+,0(%++-122%3%+44- 0.65 :,/82*,,-".0&"2,/82*,5";,4)8-,"&7")";,<,2"=&;" Proportion of reporting knowledge transfer success 0.60 Technical Workflow Inter-org Relations Antonio (from Portugal) Simon (from U.K.) &((&2/8*+/>"/2)*-7,22,5"6*&.3,51,"&2," Software engineer, Google, 2008 Software engineer, Google, 2008 [Currently, engineer with Google in Zurich, [Currently, leads a research team at a software -844,--7833>"/0)*"/0&-,".0&"2,/82*,5";,4)8-,"/0,+2" Knowledge transfer success by other dimensions of knowledge plans to move back to U.S.] company in U.K.] ?+-)-",@(+2,59" 1.0 0.8 Yes !5#-/+267)%489-:,1;-8)*+-<)0%,(=-6%>-?@- No “I was wasting my work “I manage the workflow of 0.6 experience in Portugal… my team in the same way <)*96%=- 0.4 the IT industry is not that we were managed at :,/82*,,-".&26+*1"7&2"/0,"-),"4&()*>")/"0&,")-" 0.2 developed enough for me Google… because of that, /0,>".,2,");2&)5"/2)*-7,2"&2,"/,40*+4)3A";8/"3,--" Proportion of reporting knowledge transfer success 0.0 Tacit? Novel? Better than Coworkers? to apply the skills [I my team is the most *&?,3"6*&.3,51,9" acquired while at Google].” productive one in our unit.”

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Russell, Camilla Yu, Kaisa Still, Jukka Huhtamaki, Raphael Perez, and Neil Rubens. *5&/).,+-3+&+-+,$;&3#, "/4+&*),<&5+3(-#/#$1+* +*.),&2)-1 )/01* )2+,13)-&"1#2)** 0)-&).+10) <))1 )=++2&)=(), 04"#1* *<;74+/ 3(1*#/451#-* Innovation Ecosystems refer to the inter-organizational, Current Greentech Ecosystem: 2110 nodes, 650 edges Level 1: =#-+&6+-54,+&),5-+,* 3,+)516+&3151=+-,#/)-0&*3(42)-- 3(1-)&*#/),&#.+, 723&5+3(-#/#$1+* $+&+-+,$; 3/13<)"1/15; “Value Co-Creation Networks and Social Media Conversations in the Green Tech Innovation 2)>.+*5&+-61,#-2+-5)/&*;*5+2* -#64*&2#04* +3#*;-5(+51> *#/),&+-61,#-2+-5)/&5+3(-#/#$1+* #+5 3+:&3),"#-&3)15)/ 2),<&*5+6+-* 01,+35&0,16+&*;*5+2* *()<+0&$/#")/&$,#4 *3)-.1-0 political, economic, environmental, and technological #.+,(#4*+&0;-)213* ,+-5)/13 ,40+-5&+-+,$; $+,),0&3#,"+55 $,+$&2),51-&: economic, environmental, and technological systems through Ecosystem,” BECC, November, 2010. $,++-/1)-5&*;*5+2* *4-,4- $,++-/1-+&1-04*5,1+* 1-6+-+,$; 3#$+-,)&*#/), *5),/1$(5&1-6+*52+-5* 3),/;/+&$,#.5(&),5-+,* *(+,,;&3#454 0;-)*+3 Includes 1371 green tech companies (international), which are +-5,#;&6+-54,+* 3(,1*&*(++()- Work on this research has been, in part, sponsored by: ARPAe, VTT, and Center for Frontier Science and Engineering UEC (MEXT). @4)++0&@&2#51.)/) ,13(),0&.#-$ )-)-0&0)-1+/ 1$+) )/<#/ 0++&7#,<&3)15)/&: 5(+&$,++-&.); .)//;&(4-5+, (#,1=#-&74+/&3+//&5+3(-#/#$1+* +0.),0&7+-*5+, 5)2)*+<&(#/01-$* systems through which a milieu conducive to business ,13<&0+71+4> )-0,+.&,&$),2)- 5,)-*13 5(#2)*&-$ 2#(1+ ?)3@4+*&*1-#-3+//1 ?12&*(1+/0 2),<&/+)2)- +6+,$,++-&3/+)-&+-+,$; ,+-+.)"/+&74+/&,#0435* which a milieu conducive to business growth is catalyzed, #,1$#&,+*#4,3+&),5-+,* 210,#3&-+.&5+3(-#/#$; ,6,&*;*5+2* ()/#*#4,3+ ?12&24,(;&: #51242&+-+,$; ,)*+,&5+3(-#/#$1+* linked to 440 individuals (at the executive, board and investment #3),1-)&5+3(-#/#$1+* )--+&3/)1,+&",#4$(5#- ?)-&<#+(/+, ?)-+5&?)2+* +-3)-) 7,>&#/;2+,* *4-3)&71-)-31)/ *40++&0(),)- growth is catalyzed, sustained, and supported. 03.)7+,* +#/+>&5+3(-#/#$1+* 213()+/&#/*<; <-1$(5*&",10$+&3)15)/&),5-+,* $5&*#/), "+)3#-&#.+, +>1+ *)21,&<)4/ 0+"1&3#/+2)- /),*&(1-,13(* -+>5+,,) #-&*+213#-0435#, .1-0+-*15; /#6+31-+2) #.+,:*.153( #2-1$410+ ?)12+&,#/0)- $,+$#,;&(&-+/*#- *#/)13> #.+,&1--#6)51#-* )/+>&#31--+10+ ";,#-&.;3#77 sustained, and supported. 1*,)+/&3/+)-5+3(&6+-54,+* $1//)2#,&*5+(+-* ;4-3+;&5+3(-#/#$;&0+*$-&*;*5+2* *#/),3 1-#61)&3)15)/ /0&) ),3&71-)-31)/ ",1$(561+.&*;*5+2* ?)-+&7#,,+*5 5+/+0;-+&5+3(-#/#$1+* $,++-&?#"&*10+, levels), and 304 financial organizations ;,#-&*#/), )@4)$,#&74-0 )@.1*+ (10&/)"* ,6> *4*5)1-)"/+&+-+,$; *4*5)1-)"/+&0+6+/#2+-5&5+3(-#/#$; ",43+&71*3(+, /#4);&+/0)0) .)6+/)-0&6+-54,+&),5-+,* Value is co-created for the #45*2),5&#.+,&*;*5+2* ecosystem through 2+5,#/1$(5 $,++-&/4$ )5.)5+, ,13+/#3< ,16+,5#&,+-+.)"/+* *)/2#-&,1 ,#//&3)//&$,#4 -+.&+-+,$1+*&1-6+*5 innovation 5,)-*"1#01+*+/ *)",1&*)-*#; 21<)&*)/21 5,1)35)&#.+,&5+3(-#/#$1+* 3),/#*&+*1-)/ ;5()$#,)*&*#/), )/23(1 /),,;&/+-(),5 )/+>&(##< $,#*#/), +-+,31+-5&*;*5+2*&5+3(-#/#$1+* 4/5,)&+/+35,#-13* 213()+/&3),5+- 3,)1$&0,1*3#// 34,5&0#.0; 3/+)-&+-+,$;&6+-54,+&$,#4 $,++-&.)6+/+-$5( *1>5,#- 3#--#5)5+&5+3(-#/#$1+* 616+&-)-# *+-+,$+-&0+613+* *;*5+2.),+ 0)610&3),5+- 2+1,&)2),1-&: .),,+-&.+1** ,#*(1-1&1-5+,-)51#-)/&"1#&+-+,$; 31,,4*&5+3(-#/#$1+* -)54,)/&$)*&),5-+,* 5$&$,#.5( events, impacts and coalitions/networks that emerge from )33+,)&6+-54,+&),5-+,* -3"&6+-54,+* =+&$+- $+#0;-)213* 2)55+,&-+5.#,< /0<&*#/), *#/),&-)51#- 3#--+352&5+3(-#/#$;&*#/451#-* 6+-5;> 5+2)*+< ,#/#$13 451/15;&*3)/+&*#/), ?1-$&?1-&+/+35,13&5+3(-#/#$1+* 3),"#-7/#. ),1*0;-+&*;*5+2* +/+6)-3+&,+-+.)"/+&*31+-3+* +6&*#/), Value is co-created for the innovation ecosystem through events, 5,)-*/43+-5 $,++-0+$,++&3#2 )"" *?7&6+-54,+* 61,$1-&$,++-&74-0 0,+.&/)-=) a shared vision of the desired transformations. Data-driven -+4.)6+&2+013)/ *+-3+,&,+1** +/+3), 0)-&"1,0.(1*5+// 7#,+*1$(5&$,#4 3+//+,) *+//)-&+-+,$;&2)-)$+2+-5 213()+/&?&$,++, (5+3&(;0,#$+-&5+3(-#/#$;&+-+,$; 1-7#5+3(&+-5+,,1*+*#/#$; 71+/061+.&*#/451#-* )2;,1*&"1#5+3(-#/#$1+* "),,;&*&*5+,-/1$(5 *1/)5,#-1> 43*0&6#-/1+"1$&3+-5+, +3#&+2/#1* ),512)-&6+-54,+* ,+-+.)"/+&+-+,$;&$,#4 3;,+**&*+213#-0435#, metrics measure, track and visualise the transformation, 15)/1)&+//+5* impacts and coalitions/networks that emerge from a shared vision *1/61$+- *+6+-&*+)*&.)5+, ##,?)&,#5#-13* 215*4"1*(1&+/+35,13 3#4/#2"&5+3(-#/#$1+* 3)*5/+&*)7+5;&/1215+0 3/+)-*3)+* *125+< ?#()-&5,1 .1//1)2&?&54,-+, )/)-&+4*5)3+ "/4+&*#4,3+ ),51*&3)15)/&2)-)$+2+-5 /#,+-)&<&3/),< 1#*1/&+-+,$; 233)//&"+--+55&/).,+-3+ $,++-*3,#// +-*5#,)$+ +/+35,)0,16+ 71"+,*+-*1-$ @4+-3( 3/+)-/## <.(#4,* +6)&*#/(+12 0)$&6+-54,+* with =+2 for the shared 51#7# +-+,$;&213,# "+/<1-&1-5+,-)51#-)/ 0;-)42 $+6# empowering interaction )54/&*)-$()/feedback +-+,$;&3#-6+,*1#-&0+613+* vision. ,+*+),3(&5,1)-$/+ 1//1-#1*&6+-54,+* -#4-3&+2)1/&2),<+51-$ *#/),&1-5+$,)5+0&5+3(-#/#$1+* *,1-$&6+-54,+* +/+2+&2+013)/ of the desired transformations. Data-driven metrics measure, track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and visualize the transformation, empowering interaction with +>)-*1#-&3)15)/&),5-+,* "4//&2##*+&+-+,$; "1//&<1-$*/+; /1",)&7454,+&74-0 <+)(#/+&*#/),&#.+, *<;.);&*#75.),+ 3),"#/;513&2)5+,1)/* #35#4*&6+-54,+* .(+"&6+-54,+* <15&(4-5+,&$#,0#- 2#2+-542&+-+,$; ?#(-&,4-</ 5+5,)615)+&"1#*31+-3+ ,#+,&1-04*5,1+* 1?+-<#&2#"1$),0 21*+,.),+ *<+/5)&*#75.),+ 3#.+, 4,15;&,#0435* 5(1-<+3# )//#;&6+-54,+* feedback for the shared vision. )**16*;*5+2* *+2,14* nodes (),,1*&2+01)&1-3 ?#(-&-4$+-5 23<1--#-&3/),<+ $"&+-61,#-2+-5)/ .#,/0&+-+,$;&/)"* Level 3 (two $+-#2)513) out from Level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otential Greentech Ecosystem: 6532 nodes *#45(+,-&45+ 3#2+51516+&#.+,&6+-54,+* +.)&$,=+3(-1< -)5,1>&*+),)51#-* 74*1#-&$+#(;*13)/ "#"&2+53)/7+ )75+,0#> *#/)1,+01,+35 5,1)-$/+&+)<&),5-+,*&: 3(,1*&*++, <+15(&$,1-*5+1- -+54-; 615)/3()1- )2)0+4*&3)15)/&),5-+,* 6+,01+2 21/+*&+/+35,13&6+(13/+* -+1/&,12+, +3#/+35 -#,5(+,-&/1$(5&6+-54,+&3)15)/ *54),5&3,).7#,0&: ,1-31/+&3)15)/&(#/01-$* 1:"7 0#4$&+$)- 0)6+&2)$1// 3(,#2)51- 0)-1+/&/+77 ,)5)&24<(+,?++ 2)*)5&1=4 +-()*+&+-+,$; )3()5+*&#.+, Includes companies (international), individuals (at the *<1*# /42+-=&1-3 )2++ ,1-31/+&+-+,$;&/1215+0 *#/1>&"1#74+/* $),;&/)2"+,5 ;#4,&+-+,$; ,12)6+,) .+)5(+,"1// +,7+35&3#22+,3+ 3#,)*.#,<* )0)2&"+,,+; 3#-5,#/)5( >4-/1$(5 0,&>4-21-$&0+-$ ,+34,6+ *5),.##0 "1#74+/"#> +-/1-<&$+#+-+,$; *4-/1-< *4-/1$(5&(#5#-13* ?)3#&*#/),*1 3()5&.15(&.#2+- )*+-&)+,#$+/* 2)55&$#/0+- (#.),0&2#,$)- -#,013&.1-0#.+, )-0,+.&,#2)-* 2)3@4),1+&3)15)/&74-0* -)451/4*&*#/),&+-+,$; ),3)01)-&-+5.#,<* ,#?+35&7,#$ <&,&*,10(), ,13&74/# )+>&3#-*5,4351#- +3#*2),5&5+3(-#/#$1+* )-$+/+-#&$,#4 "),-+;&*3()4"/+ *+$+51* ",+-3# 1-5+2)51>1: <*<&#.+,&6+-54,+ 1+2#-5+3( 6#/5)$+&*+34,15; *+-*#,.),+&*;*5+2* 5+,+*)&+-$+/(),0 @4)-5)*#/ .)*)53(&.1-0 (;2#51#- organizations that are linked to companies, individuals and 0)12+,&1-04*5,1+* +>+34516+&1-5+,2+01),;&1-3 </0&+-+,$;&5+3(-#/#$1+* ,#6+-&+-+,$; ,+*#-*16+/#)0 /;--+&,)12#-0# t Greentech Ecosystem: 2110 nodes, ,13#2 -+>)-5 )!:%*;*5+2* $/#")/&,+-+.)"/+&+-+,$;&-+5.#,<&$,++- 213()+/&*1/6+,5#- 1-5+/13/#40&5+3(-#/#$; ?#(-&)/7)-# )351#&3#,#,)51#-&*#75.),+ /+0-#6)51#-&1-3 +>3+/+,$; /#.&3),"#-&)33+/+,)5#, )/1+0&,#3+**&5+3(-#/#$; /++&)-0&?4-+&*5+1- )1,3415; 3/+)-&#.+,&0+*1$- 12),)&3#,#,)51#- /#34*&5+3(-#/#$1+* ?)21+&+() "/)1,&$),#4 )/$+-#/&"1#74+/dges *#2+.(+,+&1- 21#> 6),+2) $,10:(#2+ +,13&(#77+,5&: #.+,2)-0 )-#,)213&#.+, 21/3#2&6+-54,+*&),5-+,* +5,)&*#/), 5+,)/;*&3)15)/ +-+,$;*)66;&3#2 3),/#*&+,+) *#/),7/),+ 2)1-*5,+)2&+-+,$; $/)0;*&<#-$ 1-$+&.)5+,5+3(-#/#$1+* ,;#* 6)/+-3+&5+3(-#/#$; 1+<&*+=1)/&56es 1371 green tech companies (inter- 61,;0&5+3(-#/#$1+* 0,;&/4"+ .#,/0&/)-$4)$+&3#224-13)51#-* +-+,$;&,+3#22+,3+ #51*#/), 10+)/)" /1@410&+-61,#-2+-5)/&*#/451#-* ,#3<#,5&3)15)/&),5-+,* *#45(.+*5&.1-0#.+, -#,5(+,-&#.+,&*;*5+2* ,)?&)5/4,4 ?)1&3(#1 4@2&5+3(-#/#$1+* ,+-+.)"/+&+-+,$;&3#,#,)51#- 7/>&213,# <#54,) 1"+,0,#/) ?)21+&1,+/)-0 $,++-&")*51&+3#*;*5+2* ,+)/&$##0*&*#/), 213(+/+&2),=#/) ",1)-&7/##0 -+53;3/+, 0)6+&7)3(+551 0+/(1 4-16+,*)/&24*13&$,#4 ?12&2)5(+*#- *,1-$&3)15)/&)*1) 71,*5&*#/), (;3,+5+ ,#3</+;&6+-54,+* -)(42&*(),72)- al), which are linked to 440 individu- %&"1#(),2)3+4513)/* 01)-+&/#61$/1# "/##2&+-+,$; )06)-3+0&+/+35,#-&"+)2* <#-),<) *4*5)1-> 3/1+,&.1-0#.+, .)55"#5 *+-*31+-5 61,+-5&+-+,$;&*;*5+2* )"#4-0&*#/), $,++-+)<&5+3(-#/#$1+* ),0+*5) 3,)5#-&+@415;&),5-+,* .15,1315; the executive, board and investment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Approximately, 50,000 ,+*#4,3+<,)75 ?2"&+-+,$1+ *#,)) +01$,++&5+3(-#/#$1+* )<+-+,?1&+/+<5,1<&4,+512 1--#5+3(&*#/), .)/5+,&/&*3(1-0/+, +,3+516+&1>+/ +6+,+)0; 4,+*+-*+ -4)/1$(5 31-),1# 3),/&7,+0,1<&.+55+,2),< .);-+&<+)*5 C. Braemar Energy Ventures ,12+*5),&*#/), /4-)&1--#6)51#-* 1,&)4/&0+3,)+2+, 2)55&)12#-+551 rson *4*5)1-)"/+&5+3(-#/#$1+*&74-0 =+,#&2#5#,3;3/+* )6)-5142&5+3(-#/#$1+* "1//&?#; +-+,$; companies, 71,000 people, Interl Capital D. 2500 financial institutions. This data Braemar Energy Ventures is a leading 3/+)-&(),"#,* *)$),&<)*), ",;)-5&?&5#-$ *<;2+5+, 1//421-+> ,)-$+&74+/* 0)-&21//+,&% ,+0&",)-3(&5+3(-#/#$1+* 213()+/&"&*3(.)" (#+&5+3(&$/#")/ )=4,+&#.+, mpany 4-15+0&+3#+-+,$; "4==+,5.15 5(#2)*&+&3)1- Intel *3#55&1,.1- 3,;*5)/*#/ #2-1&3)15)/ was gathered in July 2010. Capital’s vision is to be the preeminent global 3;)-5# ,*. +=+//+,#- *;-5(+513&$+-#213* )73&71,*5&71-)-31)/ M. G. Russell, C. Yu, K. Still, J. Huhtamaki, R. Perez, and N. Rubens, 4"10;-+ /1&<)&*(1-$ )2"+,&3)*+ 0)610&(),5 +0,#&2#-+#&: .1-0*10+ investing organization in the world. Their mission is to +5+,&0&(+-1$ *1/13#-&3/#3<* -+#(1,+ "1#5+3(#-#2; 4/#$1> 61,$1-1)&)3516+&)-$+/&-+5.#,< +-+,$;&1-*10+ +/+35,#-&0)5)")*+ have more than 100 years of combined ,;)-&*215( "Value Co-Creation Networks and Social Media Conversations in the Green Tech Innovation Ecosystem", 040/+;&().+* 0)1-&7&0+$,#77 <,&*,10(),nance ,+3;3/+2)53( /+-5;.);* )21+//+&/)<+ 10+)7#,$+&5+3(-#/#$; *42)-5&2)-0)/ 1-3) 7&3),/&$,42+5 ,32&5+3(-#/#$1+* 0)610&?&,+-0 *#*6+-54,+* +*,15&3)15)/&),5-+,* 2,&?);&7+,$4*#- energy experience, and an investment *;/6)1-&,#** 1-71-+#- 2(1&+-+,$;&),5-+,* 6*+&3#, Behavior, Energy and Climate Change Conference (BECC), Washington DC, Nov.29 - Dec.2, 2010 *5, #77*+5> 0,&#/16+,&5()/2)-- 315;&/1$(5&3)15)/ ,;)-&)//1* $,++-.)6+&,+)/15; $,++-&,16+, support of Intel’s strategic objectives. *4-2#04/), $+,)/0&"43</+; record that dates back to the mid-1980s. )/+>)-0+,&,)1 *5+6+-&6)-&(#,-+ ")-0+/&3),)-#&: *-)0+3 0,)<+,&/)"#,)5#,1+* 0)--;&*5+7)-13 More Information: 3),"#-&(4" "+*5&*#/), Work on this research has been, in part, sponsered by: ARPAe, VTT, and Center for Frontier Science and Engineering UEC/MEXT. *2),5*;-3( =1)0&5)**)"+(?1formation: ")3<4&*#/),&$+-+,)5#, ,;)-&*.)$), +5+,&.)$-+, )/+>&<1--1+, http://innovation-ecosystems.org (+/1>&.1-0 .+"1-$ -15,#07 >3+/)+,# 2#&"?#,-+*5)0&% #5#-;novation-ecosystems.org Description Source: Company Websites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

Martha G. Russell, Camilla Yu, Kaisa Still, Jukka Huhtamaki, Raphael Perez, and Neil Rubens. Innovation Ecosystems refer to the inter-organizational, “Value Co-Creation Networks and Social Media Conversations in the Green Tech Innovation Ecosystem,” BECC, November, 2010. political, economic, environmental, and technological Work on this research has been, in part, sponsored by: ARPAe, VTT, and Center for Frontier Science and Engineering UEC (MEXT). 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. Level 3 (two nodes out from Level 1): Potential Greentech Ecosystem: 6532 nodes Includes companies (international), individuals (at theLevel 1: organizations that are linked to companies, individuals andCurrent Greentech Ecosystem: 2110 nodes,650 edgesIncludes 1371 green tech companies (inter-national), which are linked to 440 individu-als (at the executive, board and investment A. New Enterprise Associates NEA provides venture and growth capital to help innovative entrepreneurs and business leaders build transformational, industry-leading companies around the world. Investment focus: principally early-stage companies in information technology, medical and life sciences.Data is drawn from scrapingonline press releases in Englishand parsing data into database,then searching social media B. Vantagepoint Venture Partnersand socially constructed VantagePoint Venture Partners has builtwebsites for additional factsand relationships to data that isfederated. energy, lighting, water, materials andApproximately, 50,000 transportation. They believe this groupcompanies, 71,000 people, of critical industries is undergoing a modernization that will fundamentally re-data was gathered in July 2010. shape the global economy. C. Braemar Energy Ventures Person D. Interl Capital Braemar Energy Ventures is a leading Company Intel Capital’s vision is to be the preeminent global investing organization in the world. Their mission is to have more than 100 years of combined Finance energy experience, and an investment support of Intel’s strategic objectives. record that dates back to the mid-1980s.More information:www.innovation-ecosystems.org Description Source: Company Websites

InvestorRank – Using the concept of network centrality in order to predict future performance ! Chris Farmer & Niko Bonatsos— General Catalyst Partners!Introduction! Methodology! Conclusions! Just as Googleʼs PageRank orders search results based on how many links each page gets from other sites, InvestorRank looks at the connections between VC firms. Whenever two VC firms co-invest in the same deal, that creates a bond between them. If one VC firm follows another one in a later round, that boosts the rank of the earlier investor!Recent Trends Results!And? For Future releases…! @chriswfarmer @bonatsos For further information! Please contact nbonatsos@generalcatalyst.com

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Appendix B: Sponsors

HSTAR HSTAR is a Stanford interdisciplinary research center focusing on people and technology. H-‐STAR, the Human-‐Sciences and Technologies Advanced Research Ins&tute, is a Stanford interdisciplinary research center focusing on people and technology — how people use technology, how to beRer design technology to make it more usable (and more compe&&ve in the marketplace), how technology affects peoples lives, and the innova&ve use of technologies in research, educa&on, art, business, commerce, entertainment, communica&on, na&onal security, and other walks of life. Among the large, complex, global problems that are at the heart of the H-‐STAR research agendas are: •  Reducing complexity of technology to enable its universal uses for work, learning and other vital sectors of life •  Closing digital divides across class, race, gender, age and na&ons, so that access to and fluencies with technologies can provide equal opportuni&es to learn and work produc&vely for personal and societal well-‐being •  Accelera&ng innova&on in the crea&on and diffusion of products and services that beRer meet human needs •  Solving security and trust problems of compu&ng, communica&ons, and informa&on systems at home, work and in governmental affairs •  Ensuring pervasive safety and health of people over the lifespan with human-‐centered technology innova&ons HSTAR pursues its mission in a number of ways, all built on our core belief in the power of collabora&on: we organize interdisciplinary grants, contracts, and other funding opportuni&es; we bring together faculty to work collabora&vely on projects — both across the campus and in collabora&on with faculty at other universi&es around the world; and we organize events such as lectures, small seminars, workshops and conferences, some&mes through our Media X program. Innova&on Ecosystems Summit

Media X Media X is Stanfords catalyst for industry and academic research partnerships on the impact of informa&on and technology on society. Drawing on the world class capabili&es of over 90 Stanford research leaders and their graduate students, Media X s&mulates fundamental insights into innova&on, helping accelerate successful outcomes. Media X is a forum for virtual and physical mee&ngs, an incubator of ideas, and a programma&c framework to encourage and support mul&-‐disciplinary research ini&a&ves. Its mission is to provide new insights on the rela&onship between people and technology, how technology affects peoples lives, how to beRer design products and services to make them more usable (and more compe&&ve in the marketplace), and the innova&ve use of technology in research, educa&on, art, entertainment, commerce, communica&ons, and na&onal security. Media X is the industry-‐facing program of HSTAR. Media X has an open and collabora&ve culture and outlook. Stanford researchers have trusted rela&onships with researchers in Media X member companies. Corporate members have a unique chance to benefit from the exchange of crea&ve ideas; interact with researchers on cri&cal ques&ons; brainstorm on product development; collaborate with other member companies and make important connec&ons. Members have early access to premium content and opportuni&es to influence key outcomes and sponsor visi&ng scholars. The Media X Visi&ng Scholar program helps world-‐changing innovators from academia, government, the non-‐profit sector and industry become part of the Stanford community and amplify the impact of their remarkable projects and ac&vi&es. Scholars are drawn from many disciplines that reflect the diversity of the Media X community.

inspire brillance ge he ©2011 Cisco Systems, Inc. All rights reservedit s where learning doesn t always take placein a classroom and where discovery canhappen anywhere, at any time.it s where video has opened the door tolearning and collaborating in a whole new way,and where class is always in session.it s where every single person can connectwith teachers of all kinds wherever they may be.it s where great minds can easily come together,so it s also where the sky is the limit.Learn more at cisco.com/go/education

VTT Technical Research Center of Finland VTT Technical Research Center of Finland (hRp://www.vR.fi/index.jsp) is a globally networked mul&-‐technological contract research organiza&on. VTT provides high-‐end technology solu&ons and innova&on services. VTT enhances customers’ compe&&veness, thereby crea&ng prerequisites for society’s sustainable development, employment, and wellbeing. VTT Technical Research Centre of Finland is the biggest mul&-‐technological applied research organiza&on in Northern Europe. It provides high-‐end technology solu&ons and innova&on services. From its wide knowledge base, VTT can combine different technologies, create new innova&ons and a substan&al range of world class technologies and applied research services thus improving its clients compe&&veness and competence. VTT is a front-‐runner in the world of technology and an integral part of Finland’s innova&on system. Through its interna&onal scien&fic and technology network, VTT can produce informa&on, upgrade technology knowledge, create business intelligence and value added to its stakeholders. One example of its vast network is the Sindi-‐project (Social media supported indicators for monitoring and evalua&ng user driven innova&on), in which it partners with Tampere University of Technology, Hypermedia Laboratory and Stanford Media X IEN in exploring innova&on ecosystems.

Tampere University of Technology -‐ Hypermedia Laboratory Hypermedia Laboratory is a research, educa&on and service unit at the Department of Mathema&cs at Tampere University of Technology (TUT). From its establishment in 1994, Hypermedia Laboratory has been working ac&vely in the field of hypermedia in research, development and teaching. Simply put, the term ‘hypermedia’ refers to modeling and organizing informa&on and services so that the users, tasks and context are all appropriately taken into account. In addi&on, since developing and maintaining non-‐trivial services is expensive, the specifica&ons and design must aim for efficient produc&on and management. Typical applica&ons of hypermedia include web-‐based services (for example, a social media site or electronic commerce), virtual learning environments, user-‐profiled documenta&on, and mobile informa&on systems that exploit the ideas of, for example, recommenda&on systems. The mul&disciplinary research group here at Hypermedia Laboratory consists of experts on hypermedia, usability, mathema&cs, pedagogy, computer science and social sciences. All of our experts place strong emphasis on user-‐centered design and on the added value of Web-‐based solu&ons. Innova&on Ecosystems Summit

The University of Electro-‐Communica&ons The University of Electro-‐Communica&ons is a na&onal university in Tokyo, Japan. It specializes in the disciplines of computer science, the physical sciences, engineering and technology. It was founded in 1918. Knowledge Systems Laboratory Is directed by Prof. Toshio Okamoto and focuses on the system development of intelligent web-‐based educa&onal systems u&lizing the ar&ﬁcial intelligence technologies such as e-‐Learning, Web based collabora&ve learning including Recommending and Knowledge mining func&ons. Ac&ve Intelligence Group Is a part of the Knowledge Systems laboratory and is directed by Asst. Prof. Neil Rubens. The group focuses on developing Ac&ve Intelligence systems – self-‐adaptable systems that ac&vely acquire data and learn in an unsupervised/ semi-‐supervised manner. These systems are applied to a variety of areas including eLearning, innova&on, informa&on retrieval, recommender systems, bioinforma&cs, etc.

Innova&on Ecosystems Network Innova&on Ecosystems Network (IEN) Op&mizing the impact of investments made by s&mulus 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 par&cipa&on that will accrue benefits to the local area has yet to be fully ar&culated, and metrics to measure interim progress are greatly needed. Innova&on Ecosystems Network aims to fill this void. The research ini&a&ve was established in 2009. The team is composed of collaborators dispersed in different con&nents with mul&-‐cultural background and global insights. The Innova&on Ecosystems Network is an interna&onal consor&um of data partners, analysis partners and community-‐of-‐prac&ce partners, dedicated to data-‐driven visualiza&on of success factors in technology-‐based business development. Through research collabora&ons, quarterly mee&ngs, and resource sharing, we seek to iden&fy paRerns of success and key interven&on points in innova&on ecosystems and enhance sharing of insights among the diverse groups of people. Par&cipa&on in the Innova&on Ecosystems Network is open to Media X member companies and to affiliated partners. IEN TRANSFORMATION FRAMEWORK Translate, measure and transform an innova&on ecosystem Innova&on Ecosystems Summit

Innova&on Ecosystems Network IEN Publica&ons Huhtamäki, J., Russell, M. G., S&ll, K., & Rubens, N. (2011). A Network-‐Centric Snapshot of Value Co-‐ Crea&on in Finnish Innova&on Financing. Open Source Business Resource, 13-‐21. Huhtamäki, J., Russell, M. G., S&ll, K., Rubens, N., & Yu, C. (2011). Business Angels and Investment Organiza&ons as Networked Co-‐creators of the Finnish Innova&on Ecosystem. Proceedings of Triple Helix IX Interna&onal Conference: “Silicon Valley: Global Model or Unique Anomaly?" 11-‐14 July 2011, Stanford, California, USA. Rubens, N., Russell, M., Perez, R., Huhtamäki, J., S&ll, K., Kaplan, D., & Okamoto, T. (2011). Alumni network analysis. In the proceedings of the IEEE Second Annual Global Engineering Educa&on Conference (EDUCON), 4-‐6 April 2011, Amman, Jordan (pp. 606-‐611). Rubens, N, S&ll, K., Huhtamäki, J. and Russell, M. G. (2010). A Network Analysis of Investment Firms as Resource Routers in Chinese Innova&on Ecosystem, Journal of Networks, Fall. Rubens, N., S&ll, K., Huhtamäki, J., and Russell, M.G., (2010) “Leveraging Social Media Analysis for Innova&on Players and Their Moves.” Technical Report, Innova&on Ecosystems, Media X at Stanford University. Russell, Martha G. and Smith, Marc A. (2011) “Network Analysis of a Regional Ecosystem of Axerschool Programs,” Axerschool MaRers, Winter. Russell, M. G., S&ll, K., Huhtamäki, J., Yu, C., & Rubens, N. (2011). Transforming Innova&on Ecosystems through Shared Vision and Network Orchestra&on. In the proceedings of Triple Helix IX Interna&onal Conference: “Silicon Valley: Global Model or Unique Anomaly?" 11-‐14 July 2011, Stanford, California, USA. S&ll, K., Russell, M. G., Huhtamäki, J., Turpeinen, M., & Rubens, N. (2011). Explaining Innova&on with Indicators of Mobility and Networks: Insights into Central Innova&on Nodes in Europe. In the proceedings of Triple Helix IX Interna&onal Conference: “Silicon Valley: Global Model or Unique Anomaly?" 11-‐14 July 2011, Stanford, California, USA. S&ll, K., Russell, M. G., Huhtamäki, J., Yu, C., & Rubens, N. (2011). Gender and Innova&on: Networks of Execu&ve Women in Technology-‐Based Companies. In the proceedings of Triple Helix IX Interna&onal Conference: “Silicon Valley: Global Model or Unique Anomaly?" 11-‐14 July 2011, Stanford, California, USA. Yu, C., S&ll, K., Russell, M. G., Rubens, N., & Huhtamäki, J. (2011). Social Media, Reputa&on and Branding of Innova&on Hubs: A Periscope Using Content Analysis of TwiRer. In the proceedings of Triple Helix IX Interna&onal Conference: “Silicon Valley: Global Model or Unique Anomaly?" 11-‐14 July 2011, Stanford, California, USA.

Innova&on Ecosystems Network IEN Presenta&ons & Workshops May 10, 2010, Stanford University, Stanford, CA “Internal and External Innova&on Ecosystems in China 2.0 , Stanford Program on Regions of Innova&on and Entrepreneurship. Internal and External Innova&on Ecosystems in China 2.0. November 14 – 17, 2010, Sacramento, CA “Value Co-‐Crea&on Networks and Social Media Conversa&ons in the Green Tech Innova&on Ecosystem,” 2010 Behavior, Energy and Climate Change Conference. November 7-‐10, 2010, Aus&n, TX “Using Data-‐Driven Social Network Analysis for Insights on Innova&on and Change,” INFORMS, Aus&n, TX. October 12, 2010, Madrid, Spain “Using Social Media to Leverage Triple Helix Insights in Innova&on Ecosystems,” Workshop at Triple Helix Conference VIII, October 12, 2010, Madrid, Spain. October 7, 2010, Olso, Norway “Knowledge Across Borders: Accelerate Building Trust to Unleash Innova&on,” Business Ins&tute. October 5, 2010, Skei, Norway “Innova&on Ecosystems in Tradi&onal and Changing Cultures: Examples from Minnesota and Silicon Valley,” Norwegian Informa&on Technology Forum. September 18 to 19, 2010, Beijing, China “Innova&on Ecosystems: New Insights with Network Approach”, Beijing First Global World City Conference September 14 17, 2010, Nokia, Finland “Social Networks and Co-‐crea&on in Innova&on Ecosystems,” EBRF 2010. Innova&on Ecosystems Summit

Innova&on Ecosystems Network IEN Presenta&ons & Workshops August 5, 2010, University of Electro-‐Communica&ons, Tokyo, Japan “Leveraging Social Media for Analysis of Business Networks in Regional Technology Development,” Invited seminar. August 2, 2010, Hong Kong University of Science and Technology “Iden&fying Value Co-‐crea&on in Innova&on Ecosystems Using Social Network Analysis,” Inaugural Lecture: Siemens Innova&on Forum. July 31, Huangshan, China “A Network Analysis of Investment Firms as Resource Routers in Chinese Innova&on Ecosystem,” Interna&onal Symposium on eCommerce and Internet Security 2010 (pre-‐print pdf). June 1, 2010, Stanford University, Media X Workshop Social Network Analysis: New Tools, Data, and Ques&ons March 5, 2010, Stanford University, Media X Workshop Innova&on Ecologies

Innova&on Ecosystems Network SINDI – A Collabora&on Project Sindi is about social media supported indicators for monitoring, evalua&ng and visualizing user-‐driven innova&on. It is a collabora&on project between VTT Technical Research Centre of Finland, Hypermedia Laboratory at Tampere University of Technology and Innova&on Ecosystems Network at Media X at Stanford University. The goal of the project is to develop and validate indicators for measuring the process and impact of user-‐driven ICT supported service innova&on. Furthermore, the project aims at suppor&ng visualiza&on and making meaning of the indicators within their contexts, especially in the contexts of educa&on and well-‐being. The project concentrates on exploi&ng the increasingly diverse digital socially constructed databases, and social media. Sindi aRempts to address innova&on ac&vi&es and its indicators at the micro-‐level as well as macro-‐level. Innova&on Ecosystems Summit

Innova&on Ecosystems Network IEN at Triple Helix 9 Tue (July 12) Wed (July 13) Thu (July 14) 9:30 – THEMATIC WORKSHOP 11:00 Accelera&ng Trust Through Telepresence: Rela&onship Resources and Triple Helix Dependencies for Co-‐crea&ng Innova&on (organized by Media X and Cisco) Teleconference mee&ng arranged at Cisco, San Jose—bus transporta&on provided 11:30 – PLENARY SESSION: THEMATIC WORKSHOP: SESSION PS 18 – MANAGEMENT AND CAPACITY-‐ 1:00 “Building innova&on Snapshots, Movies and BUILDING FOR EFFECTIVE TRIPLE HELIX ecosystems: global and Interac&ve Tools: Analyzing PARTNERSHIPS regional factors” and Communica&ng the HRP T116 McCaw Hall Power of Rela&onships in the User-‐driven social innova&on: roles and Chair: Martha Russell, Triple Helix (organized by knowledge of university, business, government Senior Researcher, Human Media X, Stanford University) and the community of users in the case of web-‐ Sciences Technology based service Advanced Research SESSION PS1 – TRIPLE HELIX Ins&tute (H-‐STAR), INDICATORS SESSION PS 19 – COMMUNICATION OF Innova&on Ecosystems HRP T116(Health Research& INNOVATION AND SOCIAL MEDIA Network, Associate Policy Building) HRP T138B Director, Media X at Explaining innova&on with Social media, reputa&on and branding of Stanford University indicators of mobility and innova&on hubs: A periscope using network networks: Insights into analysis of TwiRer central innova&on nodes in Europe SESSION PS16 – LIVING INNOVATION: CHALLENGES AND OPPORTUNITIES LK 204,Li Ka Shing Center Transforming innova&on ecosystems through shared vision and network orchestra&on 2:00 – SESSION PS9 – NEW FORMS 4:00 OF FINANCING INNOVATION LK 204,Li Ka Shing Center Business Angels and investment organiza&ons as networked co-‐creators of the Finnish innova&on ecosystem SESSION PS 10 – THE GENDER DIMENSION IN SCIENCE, TECHNOLOGY, INNOVATION, TECHNOLOGY TRANSFER AND ENTREPRENEURSHIP LK 208, Li Ka Shing Center Gender and Innova&on: Networks of Execu&ve Women in Technology-‐Based Companies

Appendix C: Media X Initiatives

Publish on Demand Publish on Demand Publish on Demand is a Media X research ini&a&ve, led by Professor Michael Genesereth, Computer Science, in conjunc&on with Dr. Roland Vogl, Law School and CodeX, the Stanford Center for Legal Informa&cs. The overall goal of this ini&a&ve is to improve accessibility and dissemina&on of scholarly works and other educa&onal materials in academic ins&tu&ons around the world. The research seeks to bring clarity to the oxen ambiguous legal rules applicable to the use of academic content by conver&ng those rules into computa&onal instruc&on sets. This capability could considerably reduce or remove the obstacles students’ and researchers’ face when they aRempt to acquire rights to content included in a custom. This research can also help to enable automated nego&a&on for copyrights in conjunc&on with a print or digital retrieval request. With greater clarity of copyright restric&ons, the ability to easily acquire permission to use content, and the automa&on of copyright nego&a&ons, the prepara&on of course materials could become significantly easier and less costly. Importantly, resolving ambiguity and streamlining processes for copyright transac&ons for many types of educa&onal content will poten&ally unleash innova&on and crea&vity in instruc&onal materials, with poten&al benefits to the quality of educa&onal. Concerns over the rising cost of educa&onal materials give cause for a close examina&on of exis&ng distribu&on methods for academic content, with the aim of finding ways to minimize cost and maximize accessibility and effec&veness. Clearing copyrights for course materials can be a manual, labor-‐intensive process, and oxen cost-‐prohibi&ve . Copyright licensing agencies can assist in this clearance process only if the work sought is part of an exis&ng catalogue of copyrighted works and readily available for licensing. Research conducted by CodeX in 2010 iden&fied a wide range of criteria for classifying copyright licenses. SIPX uses these classifica&ons to codify license and copyright data, which is then recorded into a centralized database and connected with the content governed by the copyright license. The process of codifying a copyright license is complex and involves extrac&ng relevant data from legal documents at varying levels of legal sophis&ca&on. This ‘license database’ captures many different types of situa&ons, including but not limited to: • iden&fying pre-‐exis&ng subscrip&on or licensed content (when a subscrip&on has been purchased on behalf of certain users, for certain rights to certain materials, such as if a school library purchased subscrip&on access to a journal database on behalf of its students and professors, which may or may not include the right for professors or students to copy the subscrip&on materials into course readers ). • iden&fying public domain content (when a work is in the public domain and can be freely used by every user with no royalty payment); Innova&on Ecosystems Summit

Publish on Demand Publish on Demand iden&fying crea&ve commons and royalty-‐free condi&onal use content (when a work can be used under certain condi&ons with no royalty payment, depending on the user’s desired ac&vity, such as if an author does not want to charge royal&es for users seeking to use his research paper for educa&onal purposes, but will charge royal&es for users seeking commercial use); As part of the ini&a&ve, the researchers have created the Stanford Intellectual Property Exchange (SIPX), a new online pla}orm thatserves as a copyright registry, a copyright marketplace exchange, and a copyright clearance service which can connect with third party distribu&on pla}orms. SIPX brings value to copyright owners by crea&ng a convenient, integrated way for automated transac&ons for copyrighted materials that are not covered by pre-‐exis&ng licenses or subscrip&ons. During the Spring 2011 quarter, the researchers used SIPX as a concept proof in connec&on with Print on Demand on the Stanford campus to demonstrate instant and cost-‐saving copyright clearance for three course readers. Typically, over 75% of what students pay for in a course reader is royal&es to copyright owners and the service charge for asking for permission to use the content in a course reader. SIPX reduced the cost drama&cally, both by automa&ng the clearance process, and iden&fying any pre-‐ exis&ng licenses available through the Stanford Libraries so that duplicate royalty payments were eliminated. In this demonstra&on, course readers were made available through Print on Demand with lower cost and in book quality using “PrintGroove” on the Konica Minolta BizHub. Publish on Demand leverages research conducted on SIPX through the CodeX center, which began in 2005 under the Media X research theme, “Online Media Content.” Early Results: •  Lee, F. (2011). An empirical analysis of costs, labor and copyright issues in course reader prepara&on: A case study of SIPX Spring 2011 Print on Demand deployment . •  Yu, C., Russell, M., & Lee, F. (2011). Student Aytudes and Preferences for Cost and Format Op&ons in Personalized, Cost Subsidized Print on Demand Course Materials. For more informa&on about SIPX, contact: Dr. Roland Vogl, Execu&ve Director, CodeX, The Stanford Center for Legal Informa&cs, rvogl@stanford.edu or 650-‐723-‐8532 For more informa&on about Print on Demand Course Readers, contact: Franny Lee, fslee@stanford.edu For more informa&on about Publish on Demand, contact: Martha Russell, Associate Director, Media X at Stanford University, martha.russell@stanford.edu

Knowledge Worker Produc&vity Incremental and Transforma&onal Innova&on in Knowledge Worker Produc&vity A serious produc&vity gap exists between available knowledge and how it is used. Like a hole in a bucket, this gap is responsible for significant loss of resources and compe&&ve advantage. Development cycles are shortening, product and service life&mes are shrinking, global compe&&on is intensifying, and the impera&ve for op&mizing knowledge resources and their use has become startlingly evident. As knowledge resources slip through that gap, profitability, innova&on, product and service quality, and growth are diminished. Enterprises are not fully engaging the energy and intellect of the employees whom they compete to aRract and retain. Organiza&ons don’t fully harvest the benefits of the technologies they provide for employees. If these underused technologies and human capital were employed even modestly beRer, the produc&vity gap could be reduced and growth could be drama&cally accelerated, transforming the compe&&veness, velocity, growth and profitability of established and emerging organiza&ons. Many enterprises are aware of the knowledge-‐worker produc&vity problem. Some are exploring ways to iden&fy and provide access to informa&on resources across globally distributed teams. IT departments are experimen&ng with technology services that aRempt deep seman&c linking in document access and management. Others aRempt to evaluate cultural influences on crea&vity in knowledge work and for knowledge workers in order to increase familiarity and trust. Around the world, organiza&ons are restructuring, to leverage principles of open innova&on for outsourcing. All these trends converge on new opportuni&es for products and services to increase produc&vity and accelerate growth by increasing produc&vity in knowledge work. And they point to the need to beRer understand how people work with knowledge – individually, in teams and in organiza&ons – and how enterprises can leverage these insights for new tools and processes. Acquiring and maintaining the organiza&onal complements of knowledge management is a real cost to organiza&ons, but it is also a poten&al source of massive value, able to increase corporate compe&&veness through incremental and transforma&onal innova&on. Differences exist in the value percep&on of incremental and radical innova&on across individualis&c and collec&vis&c cultures. Understanding the counter-‐intui&ve impact of some system changes is essen&al for sustainable change. Radical changes to knowledge-‐management systems or work processes come at a price, yet may offer unprecedented benefits from the transforma&ons they enable. Research is needed for fundamental insights to op&mize cri&cal decision pathways, iden&fy poten&al metrics and enhance management strategies. Results from this research may enable knowledge workers to be more crea&ve, facilitate informa&on sharing to s&mulate ideas, add value to data with context, enhance the efficiency and effec&veness of work processes, leverage human intelligence with ar&ficial Innova&on Ecosystems Summit

Knowledge Worker Produc&vity Incremental and Transforma&onal Innova&on in Knowledge Worker Produc&vity intelligence for decision making, help people at remote loca&ons work together, s&mulate crea&vity of individuals and team, smooth the transi&on between individual work and group work, and create new ideas by sharing, visualizing, collec&ng, analyzing, synthesizing, and brainstorming. Background Workshop: Jan 18, 2011 , Knowledge Management Workshop, Stanford University Incremental and Transformational Innovation for Measurable Improvements in Knowledge Worker Productivity Augmenting Knowledge the Brain in Practice Reinventing Creativity Workflow Incremental & Transformational Innovation Agile Collaboration Networks in Teams

Knowledge Worker Produc&vity Incremental and Transforma&onal Innova&on in Knowledge Worker Produc&vity Background Papers: •  Russell, M. & Jacobstein, N. (2011). Incremental and Transforma&onal Innova&on For Measurable Improvements In Knowledge Worker Produc&vity. •  S&ll, K. (2011). Measuring Knowledge Worker Produc&vity. •  Mishra, S., Kim, H., & Hinds, P. (2011). Crea&vity and Culture: A Literature Review. •  Genesereth, M. & Dar, Z. (2011). Knowledge Management: Technological Literature Review. Selected Projects: From twenty-‐ﬁve interdisciplinary proposals received from departments across the en&re Stanford campus, seven concept-‐proving research projects have been awarded to explore new ques&ons that will guide the development of insights in the next 5 years. Crea&vity and Culture: Understanding Team Crea&vity and What Fosters It • Pamela Hinds, Associate Professor, Department of Management Science & Engineering • Hannah Hyunjee Kim, PhD student, Department of Management Science & Engineering Using Video Game Placorms to Understand Thinking Styles of People Engaged in Collabora&on • Jeremy Bailenson, Department of Communica&on • Leo Yeykeles, PhD student, and VRITS Undergraduates Process Integra&on Placorm: Enabling Process Transparency Within Teams and scaling of Process Knowledge Across the En1re Firm • Mar&n Fischer, Professor, Civil and Environmental Engineering, Director, Center for Integrated Facility Engineering (CIFE) • Larry Leifer, Professor, Mechanical Engineering Design, Director, Hasso PlaRner Design Thinking Research Program, Director, Center for Design Research • Mar&n Steinert, Deputy Director, Center for Design Research • Ben Schwegler, Consul&ng Professor, Civil and Environmental Engineering, Stanford University, Senior Vice President / Chief Scien&st, Walt Disney Imagineering • Reid Senescu, PhD Candidate, Civil and Environmental Engineering, and Engineer, Arup • Cisco Riordan, Undergraduate, Computer Science, EteRNA: Accelera&ng Knowledge Crea&on for RNA Bioengineering through Internet-‐Scale Gaming • Rhiju Das, Professor, Stanford Biochemistry & Physics • Daniel Schwartz, Professor, School of Educa&on • Adrien Treuille, Carnegie Mellon University, Computer Science Innova&on Ecosystems Summit

Knowledge Worker Produc&vity Incremental and Transforma&onal Innova&on in Knowledge Worker Produc&vity A Journey from Islands of Knowledge to Mutual Understanding In Global Business Mee&ngs • Renate Fruchter, Civil and Environmental Engineering, Director of Project Based Learning Lab • Kincho H. Law, Professor, Civil and Environmental Engineering Designing Technologies that Mediate Human Social Interac&on: Strategies for Effec&ve Coopera&on and Collabora&on • Abhay Sukumaran, Ph.D. candidate in Communica&on • Clifford Nass, Thomas M. Storke Professor in Communica&on The U&lity of Calming Technologies in Improving Produc&vity Neema Moraveji, doctoral student at Stanford University’s Learning Sciences and Technology Design program • BJ Fogg, Consul&ng Professor at Stanford University, Director, Stanford Persuasive Technology Lab • Jeff Heer, Assistant Professor in Computer Science, Informa&on Visualiza&on. • Roy Pea, Professor, Educa&on, Director of Stanford University’s Learning Sciences and Technology Design research program

Media X Research Themes Media X Research Themes Media X Research Themes The Media X RFP program allows member companies to collaborate with Stanford researchers on edge ques&ons. Edge ques&ons have a &me horizon of 3 to 7 years. They oxen revolve around complex issues that are not yet well-‐defined. Member companies work with the Media X leadership team to ar&culate a research challenge, which is then issued broadly throughout the Stanford research community. Proposals are reviewed and concept-‐proving projects are selected for funding. Oxen researchers from Media X member companies establish residency at Stanford to collaborate on the research projects, providing all the benefits of first informa&on. Results are disseminated openly. In many cases results of Media X research projects provide valida&on of the new ques&on or method and lead to significant funding from public or private resources. Media X RFP programs are financed through gixs from member companies. The Media X RFP process is dis&nc&ve from internal corporate R&D ini&a&ves in its ability to tap the intellect of Stanford research leaders, many of whom are already well-‐funded, on ques&ons that have not before been ar&culated. The combina&on of Silicon Valley entrepreneurial culture, ac&vely engaged industry partners, Stanford thought leadership, and the energe&c crea&vity of bright mo&vated graduate students and post docs infuses the Media X RFP process with unique possibili&es. Media X research themes draw upon the full technological, cultural and intellectual resources at Stanford. COLLABORATION Advanced human communica&on technologies. Exploring the fusion of virtual and physical worlds for advanced human communica&ons. Interac&ve technologies for social interac&on and collabora&on. Using interac&ve technology in social interac&on and collabora&on in produc&vity contexts, including synchronous and asynchronous uses of text, graphics, voice and video. Use of mobile devices in collabora&on. Researching mobile device-‐centric interac&ve technology used in collabora&on in the context of mul&media. Measuring and Increasing Measurable Produc&vity in Knowledge Management: Metrics for incremental and transforma&onal improvements in produc&vity of people who work with informa&on. IMAGE, SPEECH AND LANGUAGE PROCESSESING Natural language research: Basic and strategic research, training and technology transfer in speech and language processing. Video processing, cataloging, retrieval, and reuse. Using interac&ve technologies related to video processing, cataloging, retrieval and reuse, with a view to the development of automated systems to support video libraries. Innova&on Ecosystems Summit

Media X Research Themes Media X Research Themes PARTICIPATION Online media content. Evalua&ng consumers as publishers or establish ontologies of content. Learning and training. Interac&ve technologies rela&ng to learning and training, focusing on the integra&on of technology and an understanding of human psychology and social behavior to enhance understanding and performance. Innova&on Ecosystems: Network analysis of employment, investment and educa&onal rela&onships for shared vision and transforma&on. HUMAN-‐MACHINE INTERACTION AND SENSING Human-‐machine interac&on and sensing. Research on human-‐machine interac&on and sensing that focuses on the detec&on or sensing of human-‐comprehension, emo&onal states, gestures or touch. Sensing and control. The integra&on of technology and the understanding of human psychology and social behavior that can lead to new technologies that enable natural interac&on with informa&on and the physical world. Emo&on detec&on from video capture of facial expression. Enabling vehicles to automa&cally perceive driver emo&ons and determine the drivers alertness/fa&gue in order to provide a reliable and ac&onable safety index. Publish on Demand: Training a Printer for Copyright Analysis and Nego&a&on FORM FACTORS Mobile devices and alterna&ve form factors. Researching mobile communica&on devices and services focusing on the device itself, the use cases for that device, the interface employed to render that device useful, and the connec&vity opportuni&es and needs required to make that device part of the "connected" compu&ng ecosystem.

Media X Reading Media X Reading Blascovich, Jim and Bailenson, Jeremy (2011) Inﬁnite Reality: Avatars, Eternal Life, New Worlds, and the Dawn of the Virtual Revolu@on. Harper Collins: New York, NY. Goldman, R., Pea, R. D., Barron, B. & Derry, S. (2007). (Eds.) Video Research in the Learning Sciences. Lawrence Erlbaum Associates: Mahwah, NJ. House, Charles and Price, Ray (2009) The HP Phenomenon: Innova@on and Business Transforma@on. Stanford University Press: Stanford, CA. Nass, Cliﬀord, with Yes, Corina (2010) The Man Who Lied to His Laptop: What Computers Can Teach Us About Human Rela@onships. Penguin Group (USA). PlaRner, Hasso , Meinel, Christoph, Leifer, Larry, Eds. (2011) Design Thinking: Understand – Improve – Apply. Springer. PlaRner, Hasso; Meinel, Christoph; Leifer, Larry (2011) (Eds.) Design Thinking Research: Studying Co-‐crea@on in Prac@ce. Springer. Reeves, Byron and Reed, J. Leighton (2009) Total Engagement: Using Games and Virtual Worlds to Change the Way People Work and Businesses Compete. Harvard Business School Publishing: Boston, MA. Innova&on Ecosystems Summit

Prepared by Innova&on Ecosystems Network, 2011 Printed on Konica Minolta BizHub Digital version is available on www. Innova&on-‐ecosystems.org

Innovation Ecosystems Summit Brochure

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