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Linking Science to Finance: What Happens to High-Tech Firms that Receive Government Research Grants?

Description of research project

This project seeks to discover which technology ideas become successful. The method is analysis of a large social network of principal investigators, government grant-winning firms, and venture capital companies. In the tradition of the Sociology of Innovation, the central research question concerns the old adage: ‘don’t put all your eggs in one basket.’ In what contexts should the government fund many different companies, and in what contexts should it concentrate its effort in similar firms?

The U.S. government awards $4 billion every year to thousands of small high-tech companies. These companies draw from industries such as health care, computer science, environmental science, and aeronautical engineering. The program has three goals: (1) stimulating the economy by supporting the commercialization of new technologies, (2) developing companies that can provide the government with needed technology, (3) more evenly distributing funding by state, gender, and racial background, than what is available from private venture capital.

Description of work that will be assigned to research assistants

The main work assigned to research assistants will be searching through public and private databases to understand outcomes of high-tech, high-growth U.S. firms (venture capital funding, patenting, government procurement contracts, initial public offerings). I will be doing this extensively as well so we can discuss the process together. I have already developed a protocol that clarifies how we will go about getting this information.

Throughout the term, I will be happy to explain the structure of the government grant program, describe the venture capital process for start-up companies, and reflect on the network methods and structural theory being developed. Given student interest, other tasks could include analysis of the innovation literature (I have already collected the papers), or searching for the CVs (resumes) of the principal investigator associated with each firm.

 

Other Information

Supervising Faculty Member: Mark Mizruchi, Professor in Sociology, Organization Studies, and Management

Graduate Student: Dylan Nelson, PhD Student in Sociology, MA in Applied Statistics

Contact information: dknelson@umich.edu

Average hours of work per week: 6-10, flexible during midterms and finals

Range of credit hours students can earn: open, appropriate to hours worked

Number of positions available: 2