Beyond linearity : quantifying SDG saturation in complex national innovation ecosystems

This study investigates the complex, nonlinear dynamics of the achievement of Sustainable Development Goals (SDGs) within national innovation ecosystems (NIEs), addressing a critical gap in understanding SDG saturation. Studying this topic is crucial because, despite the growing importance of sustainability issues in innovation ecosystem research driven by social and economic pressure, the literature remains fragmented and undecided, lacking a clear understanding of complex governance and operational frameworks in NIEs. Employing the Bass diffusion model, we analyze 22 years of SDG Index score data (2000-2021) from 177 countries/regions. The model quantifies SDG saturation time, accounting for complex interdependencies and threshold effects overlooked by traditional linear models. Findings reveal characteristic S-shaped adoption curves for most countries, indicating initial slow progress, acceleration driven by imitation, and eventual saturation. Geographical and socioeconomic clustering analyses highlight distinct patterns in SDG progress that depend on the peculiarities of complex systems in national contexts. High-income countries exhibit greater innovation efforts but lower saturation potential due to the proximity to SDG ceilings, while lower-income countries face complex structural constraints. The Bass model proves effective for forecasting SDG saturation and informing policy interventions in complex systems like NIEs, emphasizing the need for context-dependent governance and resource allocation to accelerate equitable sustainable development across the globe.