Global CONNECT™: a network committed to growing new technology clusters worldwide



NSF SciSIP - Global CONNECT

 

Methodology:

As this study is an effort to quantify and bring analytical rigor to difficult-to-measure social and cultural factors, over the course of the study we will be refining currently identified analytical tools and introducing additional ones, if appropriate.

This research focuses on three different regions in the United States, which have similar research and education profiles in science and technology (S&T): San Diego, St. Louis, and Philadelphia. Each has internationally-ranked medical schools. Each has a record of significant research activities in the life sciences, for example, San Diego has biotech, Philadelphia has pharmaceuticals, and St. Louis has ag-bio. Each has major universities and research centers, which receive large federal grants (UC San Diego, University of Pennsylvania, Washington University in St. Louis). However, each varies greatly in its social landscape, which potentially causes differing innovation and commercialization paths and outcomes. The purpose of this research is to discover the specific ways in which regions differ in their social dynamics through examining attributes of S&T boundary-spanning groups (such as overlapping participants/members, participant/member diversity, event types and frequency) as well as identifying university-industry collaborations (such as corporate affiliates programs), and in what ways these correlate with innovation, as measured by the rate of S&T startups in the region. Our research strategy employs the following processes:

1. Properly define the key parameters

The following will be preliminarily defined by the research team, with the input of key Project Advisors from each of the regions who are actively involved in innovation, entrepreneurship, and S&T-based companies:

        • Geographic reach of each region;
        • Characteristics of the formal and informal boundary-spanning groups within each region.

        2. Build our basic knowledge about regional characteristics through the utilization of aggregate databases

      The data in which we are interested are:
      • Population characteristics;
      • Descriptors of key clusters and economic activities;
      • Amount and size of research institutions, as well as the amount and character of research funding coming to each region annually;
      • Patenting and licensing rates;
      • Dependent variable: Number of S&T startups based on Dunn and Bradstreet’s database of “new to the world” companies using NSF’s set of high-technology NAICS codes to provide a uniform definition of S&T.

A draft of our Code Book lists the specific data we intend to collect, in addition to the source(s) that will be used.

 

3. Qualify boundary-spanning groups

A series of one-on-one interviews will be conducted with twelve to eighteen “key players” in each region. The characteristics of the sample of individuals interviewed will represent what has come to be recognized as the key components in any innovation ecosystem, and are outlined as follows:

              • Creators of knowledge – basic researchers and inventors, i.e., research centers;
              • Translators and integrators – applied researchers and in many places, technology “scouts and brokers”;
              • Early enablers – commercialization centers, networks advisors, coaches and mentors, incubators, and business plan competitions;
              • Early stage funders – angel, institutional, government;
              • Sources of capital – equity, venture, etc.;
              • Growth and exit enablers – business service providers, i.e., lawyers, accountants;
              • Observers, commentators, promoters – i.e. business and science writers;
              • Individual champions, validators, community leaders.

Each community will have similar, though not identical, organizations and provisions through which the above are served. The purpose of these interviews will be to gain a better understanding of each region’s dynamic and to learn of prominent boundary-spanning groups and/or people. The interview topics include the following:

              • Overview of importance placed on innovation and S&T startups in the region’s overall economic development strategy;
              • Identification of the four to five most significant formal initiatives to support innovation and their key characteristics;
              • How initiated and governed;
              • Who is in the group;
              • How is it funded;
              • Deliverables and benchmarks;
              • Request help in getting access to materials describing meetings, activities and members, etc.
              • What would the innovation community be missing, were this organization not here?
              • How do things really get done in this community? What organizations, groups or individuals are essential for new ideas or ventures to get traction?
              • What is the level and type of private sector involvement/investment in new initiatives and/or business ventures?
                      • Pro-bono time
                      • In kind services
                      • Cash, property, development, facilities
                      • Connections and contacts
              • Would you work with us to review lists of both formal and informal networks you know or are a part of as we identify them?

 

4. Gather further data on boundary-spanning groups

We are attempting to marry qualitative and quantitative approaches in order to discover, describe, and tabulate the numbers and variety of boundary-spanning groups within each of the three regions we are studying. The following methods will be employed in order to identify these groups:

        • Web search based on leads provided in informational interviews with key players from each region;
        • Structured web search on each of the three regions in which key words and phrases will be used to search for formal and informal groups, in order to supplement the list generated from the above task. The list of key words and phrases are still being developed, and will we posted once finalized.
        • Web search of each region’s primary research institutions (identified by their research budgets) and their boundary-spanning groups (such as corporate affiliates programs, research centers, etc). Since not all university groups will be boundary-spanning (see Definitions), each will be considered on a case-by-case basis.

While identifying these groups on the web, we will also be collecting preliminary information on them such as:

  • Description/Mission;
  • Group leader and contact information;
  • Age of the group;
  • Active member/participant types, i.e., entrepreneurs, researchers, business service providers, if available;
  • Event frequency.

A draft of our Code Book outlines the full set of data we intend to collect on boundary-spanning groups.

 

5. Finalize list and interview groups for additional information

With the help of our regional key informants and key players, we will finalize our list of boundary-spanning groups, limiting it to those that they feel are the most important to promulgating research innovation and cluster growth in their region. Both a web survey and telephone interview protocol will be developed for follow up information on each of the groups. What we will be looking for in these surveys and interviews are insights into the key activities and the perceived benefits of participating in these various groups. These interviews will supplement the information that was already gathered from the web. We will also be documenting the extent of overlapping memberships across the boundary-spanning groups that are identified.

A draft of our Code Book outlines the full set of data we intend to collect on boundary-spanning groups.

 

6. In addition to our dependent variable (number of S&T startups), we will collect and use the following data for each region to standardize the main factors which either have been found to or are strongly believed to affect startup rates:

  • Geographic/Demographic traits (region type, total area, population);
  • Workforce traits (working-age population, R&D workforce, IP/Patent attorney workforce, research workforce average wage);
  • Education (number of STEM graduates, number of students enrolled in STEM majors);
  • Research institutions (number, number of SBIR/STTR awards granted, amount of federal funding, number of licenses executed);
  • Patent activity (number of applications, number granted);
  • Funding sources (total amount of VC investment, number of VC deals).

Documenting research steps and developing protocols and a code book for the entire research process will be key to methodological activity. Our goal is to provide frameworks, tools, and approaches to securing useful information about boundary-spanning groups in a way that can be replicated in other communities and correlated with innovation outcomes, such as our measure of the number of annual startups in the S&T sectors.

 

This page last updated Jan 13, 2010.

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