Categories: Event, Research

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Categories: Event, Research

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Taking its origins in Van De Ven (1993) and Isenberg (2010) seminal work, the Entrepreneurial Ecosystem concept is by design meant to understand entrepreneurial dynamics in a given territory. Research on Entrepreneurial Ecosystem (EE) received a growing interest (Velt, Torkkeli and Laine, 2020). It produced interesting results at a macro level of analysis, mainly producing econometric oriented results or theoretical papers (Cao and Shi, 2020), or at a micro level of analysis (Theodoraki and Messeghem, 2017) by the observation of small groups of EE actors such as incubators or accelerators, or entrepreneurs behaviors. The few existing observations and attempts to theorize EE as a whole scale invited various critics and calls recently to enter the “black box” of the Entrepreneurial Ecosystem by conducting rigorous scientific research under a social science perspective (Acs, 2018). Some scholars focused on complexity (Roundy, Bradshaw and Brockman, 2018) or network (Ben Letaifa, Edvardsson and Tronvoll, 2016; Busch and Barkema, 2020; Purbasari, Wijaya and Rahayu, 2020b) perspectives without being able to identify proper causal relationships.
The understanding of how EEs are organized, and the impact of their specific configuration or attributes on their outcomes are essential to conduct performative policy and strategies in order to stimulate entrepreneurship using Network theory (Amezcua et al., 2013; Fuster et al., 2019). But actually very few scholars conducted analysis of the entrepreneurial ecosystem as a whole (Goswami, Mitchell and Bhagavatula, 2018; Thompson, Purdy and Ventresca, 2018; Muñoz et al., 2020), and those used macro or micro-level evidence. The missing link of Entrepreneurial Ecosystem research at a whole scale weakens the ability to properly theorize this field of research.
The analysis of the empirical properties of EE as a whole raises the fundamental nature of EE composition in terms of actors and components, as well as its configuration or archetypal pattern. EE are mainly made of organizations such as government, entrepreneurship centers, investors and financiers, incubators and universities (Ratinho et al., 2020). But if the universities roles have been analysed regarding the entrepreneurial phenomenon (Purbasari, Wijaya and Rahayu, 2020a), the nature, role, and relationship of the overall ecosystem actors hasn’t been properly defined. We know that various kinds of organizations have a specific and direct role regarding entrepreneurship, such as incubators or accelerators, business angels as individuals or associations, fablabs, co-working spaces, etc. They are organized as a network to provide supporting resources and services to entrepreneurs and nascent enterprises (Minà and Dagnino, 2015; Albourini et al., 2020). But network perspective, even if omnipresent in the EE field of research, hasn’t been empirically mobilized to describe its actors’ relationships (Busch and Barkema, 2020). Theories and methods mobilized in the adjacent field of Innovative Ecosystem have demonstrated the interest of Network perspective research (Adner and Kapoor, 2010; Furr and Shipilov, 2018; Autio and Thomas, 2020; Shipilov and Gawer, 2020).
The unexplored perspective of EE’s inter-organizational ties configuration and organizational pattern of EE as a whole is interesting to investigate how it impacts the strength and trends of entrepreneurial dynamics in a given territory. We know that a network central actor (Burt, 1995) impacts a network innovation capability (Galvin et al., 2020), leading us to observe how, in Entrepreneurial Ecosystems, the nature of its central actor affects its performance regarding Entrepreneurial Dynamic strength and evolution. In this paper we explore this perspective, by conducting an Network Theory analysis in low income countries in Africa, through the study of interorganizational ties between EE actors, using Quantitative Graph Theory method and measures. To understand the causal relationship between EE central actor nature and its outcomes, we use fuzzy-set Qualitative Comparative Analysis (fsQCA). The purpose of this paper is to feed social science oriented research on EE, and highlight the causal conditions of a EE performance by the study of its central actor role.

 

GUENEAU, G., CHABAUD D., CHALUS SAUVANNET M.C.

 

Pre-conference Workshop BCERC 2021 Entrepreneurial Ecosystems and Territories, Online, June 9th 2021

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