To investigate the extent to which founders can influence their firms, I formulate a framework that considers the interaction between three main facets of founding teams' backgrounds, namely, industry status, entrepreneurially relevant demographic features, and social capital. As the propositions and illustrations suggest, the presence of one type of capital may reduce the dependence on or need for others. The model has applicability to a variety of industries with uncertain outcomes resulting from the commercialization of early-stage technology (e.g., biotechnology, nanotechnology, software, or hardware) or subjective quality (e.g., restaurants or movies).
This chapter examines eleven regions in the United States in the 1980s and 1990s that were all rich in resources—ideas, money, and skills—which might have led to the formation of life sciences clusters. Yet only three of the regions—the San Francisco Bay Area, Boston, and San Diego—developed into robust industrial districts for biotechnology. Most research on the emergence of high-tech cluster samples on successful cases and traces backward to find a developmental pattern. In contrast, rather than read in reverse from a positive outcome, the chapter builds networks forward from their early origins, revealing three crucial factors: organizational diversity, anchor tenant organizations that protect the norms of a community and provide relational glue across multiple affiliations, and a sequence of network formation that starts with local connections and subsequently expands to global linkages.
In this study, I ask: (1) is industry evolution or isomorphism theory a better model for understanding the change (lack-there-of) among founding team demographics over time? (2) Does region moderate which founding team demographics are prevalent and valued? To answer these questions, I analyse the demographic features of Boston and San Francisco Bay area biotechnology founding teams formed over a period of more than 30 years. I then examine whether there is a financial benefit -in terms of the value of their first investment -for having certain demographic features. I find that there are significant differences between Boston and San Francisco in (1) who becomes founders, (2) the rate at and ways in which demographic features evolve over time, and (3) the features of the founding teams that are rewarded by venture capitalists through higher initial investments. My results demonstrate the importance of treating region and industry age as moderators rather than controls.
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