MedTech I.Q.

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2nd in a 4 Part Series ... MedTechIQ and the National Science Foundation "Next Generation Social Network" Study

Colleagues,

Please see below the 2nd in a 4 part series of posts from Dr. Leigh Jerome, Phd, Principal Investigator of the National Science Foundation (NSF) funded study on "Next Generation Social Networks" involving MedTech-IQ.

ENJOY!

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Next Generation Social Networks: The promise of transformative collaboration (second in a four-part series)

Social networks provide a natural bridge between organizations, geography, disciplines and sectors. Social networking sites, however, were developed as and have been primarily used for social engagement and entertainment. This article, the second in a four-part series, will discuss the promise of next generation social networking platforms and the challenges to be overcome in order to create global, distributed opportunities for innovation.

Innovation involves transforming knowledge and technologies into profitable products and services for national and global markets which. The speed of technological change and market evolution makes the challenge to innovate urgent and continuous. Innovative firms generate higher global market share, higher growth rates, higher profitability and higher market valuations.

In this era of globalized innovation and intensely competitive markets, the new roadmaps for innovation call for the removal of barriers to cooperation, supporting public-private partnering, leveraging resources, and facilitating the exchange of scientific and technological knowledge. The nature of technological innovation requires a shift from specialized silos of knowledge generation to more open, interactive and collaborative platforms that broaden access to science globally. When knowledge that is trapped in vertical silos can be released in networks of cross-sector innovation value chains will emerge that reach across distance, expertise and organizations.

Distributed networks enable the allocation of activities according to strengths and resources to create more effective and efficient R&D processes, according to the shifting needs of specific projects. The ability to absorb new ideas, create spillovers and turn them into action is critical to a high innovation performance.

Email and Internet transactions are the most common mechanisms for distributed collaboration. However, millions of people engage in social network sites such as Facebook and are thus becoming more sophisticated in regard to collaborative technologies and strategies. Social networking tools are increasingly attractive for academic, industry and government researchers who can see the innovative potential, efficiencies and increased reach made available via social network platforms. Social networking sites offer a robust and versatile platform for cross-cutting knowledge exchange with collaborative technology capabilities including messaging, wikis, blogs, profiles and continuous updates.

While the potential of social networks is significant, there is a kind of evolutionary hurdle to clear before we will use the available tools to reach that potential. Social network sites are primarily organized around people, not topics or interests. They are basically structured as personal (or "egocentric") networks, with the individual at the center of their own community. Social networks are used to maintain personal networks with people that we already know.

Social network sites per se have been not designed for or approached by participants as platforms for knowledge exchange and spillover. The goal of cross-cutting knowledge exchange amongst multi-disciplinary scientists and trilateral sector constituency is a very different focus than friending and social exchange. New features and strategies are required that can help us use network platforms in ways other than maintaining already existing communities. An NSF funded project will give MedTechIQ members new opportunities for boundary spanning and collaborative innovation.

Innovation events increase when there is a rich flow of knowledge from diverse sources where a collision of ideas and spillovers are likely. Knowledge production creates an innovation potential that can then be realized through networks where users, producers, entrepreneurs and policy-makers collaborate in transaction spaces. Knowledge spillovers are more likely in these cross-sector networks characterized by diversity and interactivity. But we must address the challenge before us. The absence of structures and strategies for creating and sustaining new distributed collaborative relationships is a barrier that must be overcome to maximize our innovative potential. The payoff will be the development of a thick, dynamic network that can stretch beyond where co-location is possible.

To meet this challenge, we need to strategically bridge gaps within and between our networks where ties do not already exist. We must learn how to use profiles to find resonant opportunities and develop tools that help us link groups or clusters that are aligned. As individuals in small communities position themselves as bridges to other networks and clusters we begin to create a network of networks where these individuals are thus perfectly positioned to receive and absorb new knowledge and perspectives that may trigger a flood of “eureka” moments that spark innovations. The transformational capacity of distributed networks is very real once we adapt for this potential to be realized. Industry, academia and government, joined in a series of connected distributed networks, will discover new opportunities for social and economic gains.

The third of this series on next generation social networks will lay out the plan for pushing our MedTechIQ boundaries to connect with other like-minded scientists, innovators and policy makers.

References

Boyd DM and Ellison NB (2007) Social network sites: Definition, history and scholarship. Journal of Computer Mediated Communication 13(1), article 11. [WWW document] http://jcmc.indiana.edu/vol13/issue1/boyd.ellison.html (accessed 02 August 2009).

Burt RS ( 2000) The Network Structure of Social Capital. Research in Organizational Behavior (Barry MS and Sutton, RI Eds), pp 345-423, JAI Press, Greenwich, CT.

Granovetter M (1973) The Strength of Weak Ties. American Journal of Sociology 78(6), 1360-1380.

Harmaakorpi V (2004) Building a competitive regional innovation environment: The regional development platform method as a tool for regional innovation policy. Doctoral Dissertation, Helsinki University of Technology.

Jerome, L. (manuscript under review). Innovation in social networks: Knowledge spillover is not enough.

Milbergs, E. (2004). Measuring innovation for national prosperity. National Innovation Initiative - Innovation Framework Report, 3.0, IBM Corporation. Available at: www.innovationecosystems.com (accessed 6 June 2009).

Nowotny H, Scott P, and Gibbons M (2001) Re-thinking Science: Knowledge and the public in an age of uncertainty. Polity Press, Cambridge, UK.

Pew Research Center Report (2008) Social networking and online videos take off: Internet's broader role in campaign 2008. Internet and American life project [WWW document] http://people-press.org/reports/pdf/384.pdf (accessed 05 September 2009 ).

Thompson, K. (2006), ‘Social network analysis: An introduction’, Social Networking, 16. Online. Available HTTP: a href="http://www.bioteams.com/2006/03/28/social_network_analysis.html">http://www.bioteams.com/2006/03/28/social_network_analysis.html>; (accessed 30 December 2008).

Tyrrel, P. (2007). Sharing the idea: The emergence of global innovation networks. The Economist Intelligence Unit, The Economist. Available at: http://www.gencat.cat/diue/doc/doc_41824369_1.pdf (accessed 26 December 2009).

UK, Department of Trade and Industry (2003). Competing in the global economy: The innovation challenge. Available at: http://www.berr.gov.uk/files/file12093.pdf (accessed 13 May 2009).

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