%0 Journal Article
%@ 1573-0484
%A Khan, Muhammad
%A Amin, Farhan
%A Din, Minhaj Ud
%A Abid, Muhammad Ali
%A de la Torre, Isabel
%A Caro Montero, Elisabeth
%A Delgado Noya, Irene
%D 2025
%F uneatlantico:17861
%J The Journal of Supercomputing
%K E-commerce · Logistics · Supply chain · Quantum computing · Logistics optimization; AI-quantum hybrid models
%N 15
%T Enhancing e-commerce logistics efficiency and sustainability via quantum computing and artificial intelligence-based quantum hybrid models
%U http://repositorio.uneatlantico.es/id/eprint/17861/
%V 81
%X 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.