Artículo
    Materias > Ingeniería
    Universidad Europea del Atlántico > Investigación > Artículos y libros
    Abierto
    Inglés
    This study examines how quantum computing, quantum algorithms, and AI-quantum hybrid models enhance logistics efficiency and sustainability in e-commerce. Logistics optimization is analyzed to improve routing, scheduling, and resource allocation. The mixed-method design combines a cross-sectional survey of professionals with semi-structured interviews. Quantitative data were analyzed using structural equation modeling in SmartPLS, and qualitative data were thematically assessed. A perception-based analysis examined how professionals perceive quantum-based logistic models compared to traditional AI-driven approaches. Professionals believe that these models can enhance logistics optimization, increasing efficiency and sustainability. Respondents perceived that quantum models could outperform AI-driven approaches, particularly in routing and freight scheduling, but highlighted high implementation costs, limited expertise, and cross-industry collaboration. Logistic optimization mediates the relationship between quantum technology and performance outcomes. This study provides empirical evidence on industry perceptions and strategic guidance for firms considering quantum logistics. Quantum-enabled logistics enhance operational performance and support global sustainability goals. The findings underscore the opportunities and challenges of quantum logistics, offering guidance for research and adoption strategies.
    metadata
    Khan, Muhammad; Amin, Farhan; Din, Minhaj Ud; Abid, Muhammad Ali; de la Torre, Isabel; Caro Montero, Elisabeth y Delgado Noya, Irene
    mail
    SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, irene.delgado@uneatlantico.es
    
      
        
          
        
    
    
    
(2025)
Enhancing e-commerce logistics efficiency and sustainability via quantum computing and artificial intelligence-based quantum hybrid models.
    The Journal of Supercomputing, 81 (15).
    
     ISSN 1573-0484