Multi‐Regional Diffusion Modes of Emerging Technologies: Modeling and Simulation Under Technological Learning Uncertainty

ABSTRACT Technological learning and diffusion effects intrinsically drive the development of emerging technology capabilities. However, technological learning is fraught with significant uncertainty, and the spatiotemporal diffusion process across heterogeneous regions adds complexity to crafting effective adoption strategies. Existing research has seldom explored the multi‐regional diffusion modes of emerging technologies under such technological learning uncertainty. Accordingly, this study develops a multi‐regional system optimization model that endogenizes both uncertain technological learning and spatial diffusion effects. Through scenario simulations, the impacts of three distinct diffusion modes (one‐way, circular, and unintentional) on the adoption pathways of emerging technologies are analyzed and compared. The simulation results reveal that: (1) Reducing learning uncertainty, shortening inter‐regional distance, enhancing the technology diffusion effect, and policymakers adopting a more aggressive risk attitude can significantly promote the adoption of emerging technologies. (2) Following the technological spillover of an emerging technology, the diffusion of an existing technology can influence its diffusion path in all three modes. (3) The circular diffusion mode was the most economical strategy from a total system cost perspective and demonstrated the strongest resilience to the uncertainties associated with technological learning. These findings provide valuable theoretical insights for policymakers to design robust strategies for deploying emerging technologies across regions. This study contributes to a better understanding of the technology diffusion process under uncertainty and presents a framework for enhancing diffusion efficiency and mitigating systemic risks.