In recent years, the number of early-stage ventures based on deep technologies (e.g., artificial intelligence, big data, quantum computing, among others) has been growing. A deep-tech startup is a “company founded on a scientific discovery or meaningful engineering innovation” (CHATURVEDI, 2015, p. 1). The success of these startups is uncertain, as they require long/slow R&D cycles to transform technologies into suitable innovations for markets. For these reasons, studies show that these ventures are less attractive to venture capitalists. Deep-tech entrepreneurship is more concentrated in developed contexts. Studies on entrepreneurial cities focus on high-growth or business birth rates. So far, there are few studies on deep-tech startups from a city level perspective, i.e., which aim to reveal which factors drive or inhibit the creation of these startups. Therefore, the purpose of this article is to assess whether the resource endowment of cities influences the number of deep-tech startups. In this study, we apply a Stochastic Frontier Analysis (SFA) to a database composed of 68 cities, e.g., the San Francisco Bay Area, São Paulo, and Shenzhen, among others. To create our database, we collect data about deep-tech startups from Crunchbase and data about entrepreneurial cities' resources and actors, we collect data from Research Organization Registry, Crunchbase, and StartupBlink. Our results showed the concentration of Education and Research Institutions, Business Incubators, Accelerators, and Venture Capitalists Investors are good predictors of entrepreneurial activity based on deep technology.
Comissão Organizadora
Comissão Científica
Complete tool for submission, evaluation and publication of proceedings for scientific events.
