Title: Ecosystems of green entrepreneurship in perspective: evidence from Brazil

Authors: Bruno Fischer; Adriana Bayona-Alsina; Anne Kathleen Lopes Da Rocha; G. Hermínio Salati Marcondes De Moraes

Addresses: School of Applied Sciences, University of Campinas, Pedro Zaccaria, 1300, Jardim Santa Luiza, Limeira, São Paulo, Brazil; Higher School of Economics, National Research University, 20 Myasnitskaya Ulitsa, Moscow, 101000, Russia ' School of Applied Sciences, University of Campinas, Pedro Zaccaria, 1300, Jardim Santa Luiza, Limeira, São Paulo, Brazil ' School of Applied Sciences, University of Campinas, Pedro Zaccaria, 1300, Jardim Santa Luiza, Limeira, São Paulo, Brazil ' School of Applied Sciences, University of Campinas, Pedro Zaccaria, 1300, Jardim Santa Luiza, Limeira, São Paulo, Brazil

Abstract: While our comprehension on the configurations and dynamics of entrepreneurial ecosystems has advanced significantly, there remains a conspicuous gap in how localised phenomena shape transitions towards environmentally sustainable regions - particularly outside the scope of advanced nations. Accordingly, our research explores how entrepreneurial ecosystems affect the emergence of green entrepreneurship within a developing country context. The empirical setting comprises data from the State of São Paulo, Brazil for the period 2002-2019. Econometric estimations involved generalised estimating equations for count data in a panel dataset. Results highlight that entrepreneurial ecosystems for green entrepreneurship appear to strongly rely on research universities, innovation habitats and connections to global value chains. These findings contribute to policymaking processes looking to further connect the promotion of knowledge-intensive entrepreneurship with environmentally sustainable transitions within entrepreneurial ecosystems.

Keywords: knowledge-intensive entrepreneurship; KIE; green entrepreneurship; ecosystems of entrepreneurship; entrepreneurial ecosystems; bioeconomy; bio-based entrepreneurship; developing countries; Brazil; panel data; negative binomial estimations; generalised estimating equations.

DOI: 10.1504/IJTLID.2022.121475

International Journal of Technological Learning, Innovation and Development, 2022 Vol.14 No.1/2, pp.52 - 77

Received: 24 Mar 2021
Accepted: 11 Sep 2021
Published online: 15 Mar 2022 *