Austin, Boston, Silicon Valley, and New York: Case studies in the location choices of entrepreneurs in maintaining the Technopolis - Stephens, Bryan; Butler, John Sibley; Garg, Rajiv; Gibson, David V. (Technological forecasting & social change, 2019)
This study uses institutional theory and the “Technopolis” wheel to investigate the movement of technology entrepreneurs and why they “stick” to well-established entrepreneurial ecosystems in Silicon Valley, Austin, Boston, and New York City. We detail the historical development of the entrepreneurial ecosystem in each location, with a particular focus on the institutions and support structures that link and sustain key resources that are central to technology clusters. We operationalize key segments of the Technopolis wheel including (1) networks and connectedness, (2) investment capital, and (3) innovation and R&D. The empirical analysis specifies models testing for location-specific variation in the influence of these factors on entrepreneur location choice. We supplement this with analysis of interview data from 45 technology entrepreneurs with direct experience in these locations. We find that higher degrees of connectedness in Austin and Silicon Valley are an important factor in retaining potential entrepreneurs and several institutions were linked to facilitating tie formation and accessing key resources within the Technopolis. We also find that the frequency of funding opportunities positively influences entrepreneurs moving to Austin, Boston, and Silicon Valley to immediately start a company. In Boston, we find a positive association between patents and staying in Boston to launch a startup and we find that older entrepreneurs living in New York and Silicon Valley are less likely to remain and start a company. •Silicon Valley, Austin, and Boston are top three entrepreneurial hubs.•Silicon Valley and Austin startups are enabled by local connectedness.•Boston startups are influenced by the innovation in the city.•New York startups are created by younger entrepreneurs.•Big data can help us parameterize the key segments in Technopolis wheel.