AI Readiness as a Pathway to Sustainable Competitiveness in Tourism Transport: Evidence from an Integrative SEM Model

Artificial intelligence (AI) is transforming demand forecasting in the tourism transportation sector, delivering unprecedented accuracy in volatile, seasonal, and customer-sensitive environments. Yet, many firms struggle to translate AI's potential into performance due to gaps in technological and organizational readiness. Drawing on the resource-based-view (RBV) and the Technology-Organization-Environment (TOE) framework, this study develops and tests an integrative model linking digital infrastructure, employee skills, and managerial support to AI adoption and, consequently, business performance. We use Structural Equation Modeling (SEM) with bootstrapping to test direct and indirect effects. The results confirm that all three dimensions of readiness significantly boost AI adoption, which improves operational efficiency, occupancy rates, customer satisfaction, and profitability. It is crucial that AI adoption fully mitigates the effects of employee skills and managerial support, while partially mitigating those of digital infrastructure, reflecting its dual role in analytics, through both AI and other means. The study contributes theoretically by clarifying the mechanism by which readiness translates into value and offers practitioners a roadmap for successful AI assimilation in high-uncertainty service contexts.

@article{Frikha2025,
  title     = {AI Readiness as a Pathway to Sustainable Competitiveness in Tourism Transport: Evidence from an Integrative SEM Model},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {12},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Mohamed Amine Frikha},
  doi       = {10.14569/IJACSA.2025.0161289},
  url       = {https://doi.org/10.14569/IJACSA.2025.0161289}
}