Innovation system decision-making is a core component in promoting incentives and conditions necessary for the emergence of innovation. It also plays a critical role in guiding policy and modeling strategies that aim to promote science, technology, and entrepreneurship at national, regional, and local levels. Decision-makers often select innovation system models that do not align with contextual scope, data accessibility, or institutional conditions, undermining their implementation. The lack of alignment between innovation system model assumptions and contextual realities undermines analysis and policy design, particularly when trying to implement a regional model on a national scale without any sort of adaptation. This study presents a framework that aligns innovation system models to specific contexts by providing a decision-making system based on structural analysis. Using a comprehensive collection of relevant previous studies related to the theoretical evolution of innovation system models, this research provides insights regarding the most used types and techniques to compare innovation systems comprising national and regional ISs, helix models, and innovation and entrepreneurship ecosystems. For each model, explanatory potential via structural analysis is operationalized through five indicators derived from multilevel graphs: geopolitical scope, number of actors, vertical and horizontal density, and Shannon’s entropy. These indicators are then systematized into dimensions comprising two feasibility filters and three mechanism-related dimensions, forming the basis for a minimum viable innovation system model selection heuristic. This structural analysis shows that ecosystem lenses capture distributive and adaptive interaction structures; helix models emphasize coordination and governance; and national or regional innovation systems underscore policy reach and institutional boundaries. The results provide a numerical analysis of three different contexts—a national mission, a city entrepreneurship program, and a regional coordination upgrading effort—highlighting areas for improvement in planning, project implementation, and public policy design.
Malagón et al. (Fri,) studied this question.