Abstract for: Identifying the founding elements of a sustainable entrepreneurial ecosystem, an analysis on global warming problem.

The concept of “sustainable entrepreneurial ecosystem” refers specifically to the local context able to produce positive outcomes for society and the environment. The overall outcome of the local ecosystem is unclear. Many authors are asking for empirical clarification on the impact of an entrepreneurial ecosystem on environmental sustainability (Audretsch et al., 2024; Chaudhary et al., 2024a; Theodoraki et al., 2022). Through an analysis of literature, this study develops a comprehensive causal framework illustrating how ecosystem structural characteristics, policy interventions, and institutional contexts influence entrepreneurial activities that generate climate impacts. Then, the study employed a stock-and-flow system dynamics model, translating the dynamic hypothesis into a simulation model. The core structure consists of a double co-flow chain: one tracking green startups that mature into green firms, and another tracking brown startups that mature into brown firms. To evaluate the model's behaviour under different conditions and to identify high-impact elements of a sustainable entrepreneurial ecosystem, an explorative sensitivity analysis was conducted using Vensim simulation software. The sensitivity analysis identifies which model parameters most significantly impact the entrepreneurial ecosystem's carbon emissions. Parameters demonstrating a substantial effect are defined as the "founding elements" of a sustainable ecosystem. These elements are classified into three distinct categories: internal, interactional, and external. Integrating green innovations quickly is the only internal factor that significantly reduces carbon emissions; startup demographics have a negligible impact. Furthermore, market competition accelerates the green transition. Ultimately, the "imitation effect"—where mature companies adopt technologies developed within the startup ecosystem—is vital for driving down overall emissions. Linguistic refining