AI–enabled green hydrogen adoption for sustainable transportation: The moderating role of network capability

The move of low-carbon transport relies on combining digital technology integration and clean energy projects. In this paper, artificial intelligence (AI) enables sustainable transportation (ST) by promoting the adoption of green hydrogen (GHA). It examines the role of network capability (NC) and AI in an emerging-economy context. Based on the Resource-Based View (RBV) model, AI is conceived as a strategic technological capability that drives hydrogen planning, optimization and operational efficiency, while NC is a relational capability which enhances ecosystem coordination. Data were gathered from 181 transport professionals at Iran's Ministry of Roads and Urban Development and analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show AI has a strong tendency to promote green hydrogen adoption, while AI as well as GHA play a positive role in sustainable transportation performance. Network capability has a significant direct impact on sustainability performance and has a positive moderation effect on the relationship between GHA and ST which in turn amplifies the effect of hydrogen when it is combined with a strong inter-organizational coordination. Despite this, AI does not directly boost network capability, meaning that investment in technologies alone is not enough to develop collaborative capacity and must be coupled with institutional and governance systems. This study adds to the existing scholarship in hydrogen strategy, framing it in Iran's natural gas-rich environment, assessing trade-offs between blue versus green hydrogen pathways and water-resource limitations in that context, and determining the impact of these for foreign direct investment attraction. Through this integrated approach to digital transformation, hydrogen transition, and ecosystem capabilities, this research enhances emerging synergies between AI-enabled analytics and sustainable mobility with strategic implications for policymakers and transportation leaders who are embarking on the path to long-term decarbonization. • AI accelerates green hydrogen adoption in transport systems. • Network capability amplifies hydrogen's sustainability impact. • AI alone does not directly build network capability. • PLS-SEM validates mediation and moderation effects. • Results guide integrated digital–hydrogen strategies for decarbonized mobility.