Nonlinear Modeling of the Impact of Institutional–Developmental Indicators on Iran\'s Gross Domestic Product Using the Response Surface Methodology (in Persian)

Purpose: This study investigated the nonlinear impact of three institutional–developmental indicators of e-government development, human development, and governance effectiveness on Iran’s GDP during the period 2010–2024. The main objective was to determine not only their individual effects but also their optimal combinations for enhancing sustainable economic growth. Methodology: The research was quantitative and applied, relying on global secondary data. Response Surface Methodology (RSM) was employed to analyze linear, quadratic, and interactive effects among the variables. This approach allowed for the construction of second-order models and the identification of optimal policy points, which conventional linear econometric models often fail to capture. Findings: The results show that e-government development exerts the strongest and most significant positive influence on GDP growth, highlighting its significant role in economic performance. Governance effectiveness also demonstrates a positive and accelerating relationship, confirming that improvements in institutional quality drive stronger economic expansion. By contrast, human development exerts a positive effect at lower levels but encounters diminishing returns beyond a threshold, indicating a “saturation effect” that may reduce efficiency in resource-constrained contexts. Originality: For the first time in Iran, this study applies RSM to model nonlinear institutional effects on GDP, offering an innovative framework for data-driven policy analysis. Recommendations: Policymakers should prioritize strengthening e-government and improving governance effectiveness. Moreover, organizations should design human development strategies with attention to marginal returns to ensure long-term productivity.