Benham Azhdari, Jean Bonnet, Sébastien Bourdin (p)

Salma Hichri

'see extended abstract'

Éva Somogyiné Komlósi (p), Tamás Sebestyén, Ákos Tóth-Pajor, Zsolt Bedő

Sébastien Bourdin

A specific entrepreneurial ecosystem (EE) supporting or limiting entrepreneurial innovation characterizes territorial units. Consisting of several quasi-complementary individual entities and contextual factors, it is questionable whether these elements are of equal importance within a given ecosystem. Access to and mobilization of entrepreneurial resources (information, knowledge) is facilitated by social networks within the EE. Consequently, this study considers networking as a crucial output of EEs: the extent and quality of networking determines various characteristics of the ecosystem itself. Networking works as a cohesive mechanism between actors and institutions at different levels, so its absence or low level has a negative impact on entrepreneurship. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), we explore those configurations of micro, meso and macro elements of the EE of ICT firms in a Hungarian city (Pécs) which result in low or high level networking performance. We find that different networking levels require different conditions. Only those ecosystems show very high-quality networking that perform well in both the necessary and sufficiency components. Also, different ecosystem configurations are required for high informal, formal, or external networks. These results provide policy makers with a more advanced understanding of how EEs work, thereby supporting a more efficient allocation of scarce resources.

Hanene Ben Ouada Jamoussi, Salma Hichri (p), Walid Keraani

Éva Somogyiné Komlósi

Context and originality of the subject
The rapidity with which cities are developing and the resulting urban problems have forced policy makers to look for new solutions to address sustainability issues (Simmons et al., 2018). Technology companies have proposed some solutions based on information and communication technologies to help use existing resources efficiently ( Kummitha, 2018). They have thus contributed to the socio-economic transition approach implemented in cities and the emergence of "smart cities". However, while the increased use of these technologies may have solved many urban problems, they have also been a source of problems affecting the social and environmental quality of life of the inhabitants (United Nations, 2017). It was therefore essential to design solutions that allow cities to become not only "smart" but also sustainable (Carrière, 2015).
The responses of different types of actors in the processes of transitioning to more sustainable production and consumption patterns (Markard et al., 2012) have been widely studied. However, the importance of entrepreneurs in this regard has not been sufficiently emphasized. While they seem to be well placed to design solutions contributing to the sustainable transition of cities, their approaches and involvement in this process have not received sufficient attention from the scientific community. Indeed, despite the scale and importance of smart and sustainable cities, entrepreneurship researchers continue to ignore their impact(Letaifa, 2015) and the immense range of opportunities they offer (Quin, 2018 ).
The urban problems and challenges facing cities today have opened up research to different forms of entrepreneurial activity. These challenges represent opportunities for those who wish to reduce economic behaviors that degrade society and the environment (Cohen and Winn, 2007). They have given rise to a new type of sustainable entrepreneurial activity focused on improving well-being through for-profit, hybrid, or nonprofit business models. This type of entrepreneurship offers opportunities to address the failures of public or private services and can help solve important socio-economic, cultural and environmental problems (Dacin et al. 2010). The city thus becomes a kind of sustainable innovation platform or laboratory for testing and developing innovative and collaborative solutions, also involving the business community.
Research objective
The current challenges facing cities around the world present a multitude of opportunities for sustainability-oriented and city-conscious entrepreneurs. These should help mitigate some of these challenges, reconciling wealth disparities, economic and social inclusion, and environmental issues (Fors and Lennerfors, 2019). However, and despite the importance of sustainable entrepreneurship and its significant impacts on urban development (Glaeser et al., 2010), it has not been sufficiently studied. The empirical phenomenon itself remains scarce (Renko, 2013) and its understanding is still lacking (Hanohov and Baldacchino, 2018). A major challenge for researchers and practitioners is to understand the process by which creative and sustainable solutions can solve complex and persistent urban problems and improve urban life, as well as the different dimensions that influence the course of this process. In response to the need to better understand sustainable entrepreneurial initiatives aimed at the development of sustainable cities, this article focuses on entrepreneurial dynamics that are based on the Social Solidarity Economy and whose action is combined in urban settings.

Methodology
Drawing on existing theories in ordinary entrepreneurship research (Shane and Venkataraman, 2000) and emerging studies in the field of sustainable entrepreneurship, we seek to illuminate the dynamics through which urban problems are addressed. We wish to study the impact of sustainable entrepreneurship in a context that combines the creation of social, environmental and economic values on the improvement of the quality of life in cities, as measured by the evolution of the Quality of Life Index (QLI). A first exploratory analysis showed the great disparity of the QLI on an international scale. Artificial intelligence tools allowed us to identify the process underlying the evolution of the QLI (ARIMA process). A panel database is collected over 10 years (2012 - 2022) and for 87 countries with different levels of QLI observed with respect to about 15 variables. Estimation of a dynamic panel model with the QLI as dependent variable has identified the most influential components of quality of life. These factors are used in various simulations. Different scenarios for predicting the level of quality of life according to its most significant determinants are tested and have allowed us to synthesize evaluation and reporting tools for urban growth and regeneration.
Contrary to our expectations, our first results highlight the importance of the role of the innovation ecosystem in the short- and long-term propagation of the shock of innovative firms.