Identifying and Analyzing Drivers of Innovation Ecosystem Development in Iran: A Future-Oriented Approach

The aim of this study is to develop a strategic foresight framework for Iran’s innovation ecosystem by identifying key drivers and trends and examining the causal relationships among them. The research adopts an exploratory–explanatory mixed-methods approach. In the qualitative phase, the study population consisted of experts in Iran’s innovation ecosystem, and data were collected through semi-structured interviews and analyzed using thematic analysis. The findings of this phase led to the identification of a set of key drivers at institutional, economic, technological, human, social, and geopolitical levels. The most salient drivers include innovation governance, macroeconomic stability, the innovation financing system, human capital, emerging technological transformations, commercialization capacity, and geopolitical constraints and sanctions. Based on these results, a conceptual model of the research was developed. In the quantitative phase, data were collected from managers and professionals actively involved in the national innovation ecosystem, and the proposed model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of the quantitative analysis indicate that institutional and economic drivers have a direct and significant impact on the dynamics of the innovation ecosystem and exert a stronger influence than technological and cultural drivers. In contrast, technological drivers primarily exert indirect effects through mediating variables such as human capital and commercialization capacity. Furthermore, geopolitical constraints, as a contextual variable, significantly moderate the interaction patterns among other drivers.