Metrics for Capturing Crucial Social Dynamics of Innovative Regions: Tools for Informing S&T Policy

(NSF # 0914793)

Mary Lindenstein Walshok, University of California, San Diego, Principal Investigator

Project Description:

Why are some regions in the United States more efficient and successful in the transfer and commercialization of scientific knowledge? What characteristics are unique to these thriving regions? What lessons can be applied for future science and innovation policy?

Scholars have shown that the presence of major scientific research institutions alone does not produce social and economic benefit in a region; other factors include hard assets such as R&D expenditures, patents and venture capital, and the critical mass and propinquity of scientific talent. However, less has been said to-date about the role of social dynamics.

We believe that an important but understudied factor in determining a region’s success in the transfer and commercialization of scientific knowledge — leading to economic growth and development — is the density and diversity of S&T (science and technology)-focused boundary-spanning groups, which are cross-functional groups focused primarily on S&T innovation and commercialization, such groups typically bring together a combination of two or more participants in the innovation system such as translational researchers, business services providers, entrepreneurs, funding source decision makers (such as angel investors, venture capitalists, foundation executives and government officials), policy specialists, or real estate developers. These groups can also include functional spheres such as sales and marketing, finance, accounting, applied research, design and engineering, or HR, and can either be within a single industry or between multiple industries. Boundary-spanning groups can be formal organizations as well as more informal, self-organizing communities of interest. Our hypothesis is that higher rates of innovation, quantified using the annual number of S&T startups as a surrogate variable, are associated with a larger, more active array of boundary-spanning groups.

How knowledge flows from research institutions, circulates throughout the region, and eventually translates into commercial applications is shaped by a complex ecosystem of interdependent factors, beginning with breakthrough ideas, through proof of concept, to market potential, and finally to companies that are built on science-based products. Critical to the robustness of this ecosystem are a number of factors, typically called “cultural and social dynamics,” which can be assessed by the choice of relevant, surrogate quantifiable metrics. Developing such metrics and correlating them with successful knowledge flows between research institutions and dynamic regional commercialization ecologies can result in indicators which are useful to setting science and innovation policy, both locally and nationally. This pilot study identifies and measures social factors — in this case, the density and diversity of formal and informal boundary-spanning groups — that may distinguish vibrant regions with the capacity to innovate from those that do less, in order to better understand the processes by which investments in S&T research are transformed into beneficial social and economic outcomes.

By focusing on actionable metrics, the increased understanding of previously-uncharacterized aspects of knowledge flows may lead directly to new mechanisms available for optimization by policy makers. A recommended data structure will be developed so that other research institutions or their regions may also perform self assessments and thus contribute to the test data used to assess and enhance the model.

This page last updated Jan 13, 2010.