Innovation Ecosystems in Africa: Leveraging Triple Helix Twins and Knowledge Spillovers for Sustainable Development

ABSTRACT This study introduces the triple helix twins (THT) framework, integrating digital twin technology into the triple helix (TH) model to enhance sustainable innovation and knowledge spillover in African Union (AU) member states. It addresses the limitations of the traditional TH model in resource‐constrained environments by utilizing digital twins to optimize collaboration, knowledge flows, and decision‐making. The study combines Data Envelopment Analysis (DEA) with digital twin simulations and a two‐stage econometric framework using a multi‐method approach. Structural equation modeling (SEM) and System Generalized Method of Moments (SYS‐GMM) address endogeneity and dynamic relationships, while spatial autoregressive modeling (SAR) captures regional spillover effects. Threshold effect modeling identifies nonlinearities between digital infrastructure and innovation efficiency. The dataset covers 47 AU member states (2015–2024), analyzing input variables such as the Education Index, industrial value‐added, and R&D expenditure, alongside output indicators like patents granted and entrepreneurial activity. The findings highlight the THT framework's potential to bridge institutional gaps, foster innovation‐driven growth, and strengthen technological capacity. However, infrastructure deficits, weak absorptive capacity, and policy misalignment must be addressed. This study advances theoretical discourse by positioning THT as an adaptive alternative to TH, offering strategic insights for sustainable innovation‐led growth in Africa.