TY - JOUR ID - uneatlantico17861 N2 - 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. TI - Enhancing e-commerce logistics efficiency and sustainability via quantum computing and artificial intelligence-based quantum hybrid models Y1 - 2025/10// KW - E-commerce · Logistics · Supply chain · Quantum computing · Logistics optimization; AI-quantum hybrid models JF - The Journal of Supercomputing VL - 81 UR - http://doi.org/10.1007/s11227-025-07959-4 SN - 1573-0484 A1 - Khan, Muhammad A1 - Amin, Farhan A1 - Din, Minhaj Ud A1 - Abid, Muhammad Ali A1 - de la Torre, Isabel A1 - Caro Montero, Elisabeth A1 - Delgado Noya, Irene AV - public IS - 15 ER -