Unleashing the power of digital twin and big data as a new frontier for smart mobility: An ecosystem perspective

• This study explores the role of digital twin technology and big data in the context of smart mobility. • An integrative framework based on an ecosystemic perspective is proposed, comprising two iterative loops to analyze digital twin and big data applications in smart mobility. • The first iterative loop connects technology service providers with mobility stakeholders, demonstrating how AI-driven, user-centric mobility solutions are co-created through perceptive and responsive mechanisms. • The second iterative loop links mobility stakeholders with end-users, enhancing operational efficiency through user-generated knowledge, ultimately improving mobility experiences and urban transportation systems. • The study highlights the interplay between big data and ecosystem dynamics in the application of digital twin technology for smart mobility. Nowadays, a new concept of the smart city, driven by technological advancements, has emerged with a significant impact on various domains, including mobility. Among these technologies, the digital twin has recently gained attention; however, its impact on smart mobility, particularly in correlation with big data, remains underexplored. Based on these considerations, this paper aims to investigate the role of digital twin technology in conjunction with big data in the context of smart mobility. A case study approach has been adopted to analyze the Italian context. Results highlight the ecosystem elements and identify the primary drivers for sustainable growth in integrating digital twin and big data technologies within smart mobility. Two iterative loops have been identified connecting technology service providers with mobility stakeholders, illustrating how artificial intelligence-driven, user-centric mobility solutions are co-created through perceptive and responsive mechanisms, and linking mobility stakeholders with end-users, enhancing operational efficiency through user generated knowledge, ultimately leading to improved mobility experiences and urban transportation systems. This study contributes to the literature by providing a structured analysis of digital twin applications in smart mobility, emphasizing the interplay between big data and ecosystem dynamics. The findings offer theoretical and practical implications, highlighting opportunities for policymakers, technology providers, and mobility operators to foster sustainable and data-driven urban mobility solutions. Finally, directions for future research are discussed, outlining potential advancements in digital twin integration for smart mobility ecosystems.