Intelligent Mobility and Executive Logistics: Developing A Predictive Framework for Real-Time Travel Risk and Resource Optimization

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@article{1722757,
      author = {Adeola Olajubu},
      title = {Intelligent Mobility and Executive Logistics: Developing A Predictive Framework for Real-Time Travel Risk and Resource Optimization},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {3},
      pages = {342-360},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722757.pdf},
      abstract = {Increasing complexity and unpredictability of the transportation environment call for an intelligent approach to executive logistics. Traditional methods of executive travel management usually involve scheduled travel, established travel patterns, and predetermined routes and reactively respond to any disturbances. This study proposes an abstract predictive model of applying intelligent mobility solutions in executive logistics, especially focusing on travel-risk assessment and resource optimization. Based on existing literature reviews on artificial intelligence, machine learning, IoT technologies, GPS-based mobility analytics, travel-time prediction, dynamic routing, and predictive logistics in general, the paper reviews ways how such technologies could be used in order to make proactive decisions in mobility. The proposed model involves real-time data gathering, predictive analysis, travel-risk assessment, travel-time forecasting, dynamic re-routing, and resource allocation, forming a continuous decision-making loop. The proposed decision-making process allows for making transportation decisions considering not only expected travel time but also its reliability, travel risks, schedule of executives, vehicle availability, etc. This paper posits that leveraging these competencies may enable a shift from an otherwise reactive transportation function to become a proactive and adaptive organizational capability. This approach could be applied in various domains, including executive corporate transportation, fleet management, time-sensitive mobility planning, and logistics operations involving highly reliable operations. In conclusion, the research demonstrates that the fusion of artificial intelligence, mobility data, and optimization is capable of establishing the basis for a new generation of executive mobility systems.},
      keywords = {intelligent mobility; executive logistics; predictive analytics; travel-risk prediction; artificial intelligence; dynamic routing; resource optimization; real-time mobility data; travel-time forecasting.},
      month = {September},
      doi = {https://doi.org/10.64388/IREV10I3-1722757}
  }