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A Comprehensive Survey of Artificial Intelligence and Robotics for Reducing Carbon Emissions in Supply Chain Management

Author

Listed:
  • Mariem Mrad

    (Faculty of Economics and Management of Sfax-Tunisia, Sfax 1013, Tunisia)

  • Mohamed Amine Frikha

    (Applied College, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Younes Boujelbene

    (Faculty of Economics and Management of Sfax-Tunisia, Sfax 1013, Tunisia)

Abstract

Background : Artificial intelligence (AI) and robotics are increasingly pivotal for reducing carbon emissions in supply chain management (SCM); however, research exploring their combined potential from a sustainability perspective remains fragmented. This study aims to systematically map the research landscape and synthesize evidence on the applications, benefits, and challenges. Methods : A systematic scoping review was conducted on 23 peer-reviewed studies from the Scopus database, published between 2013 and 2024. Data were systematically extracted and analyzed for publication trends, application domains (e.g., transportation, warehousing), specific AI and robotic technologies, emissions reduction strategies, and implementation challenges. Results : The analysis reveals that AI-driven logistics optimization is the most frequently reported strategy for reducing transportation emissions. At the same time, robotic automation is commonly associated with improved energy efficiency in warehousing. Despite these benefits, the reviewed literature consistently identifies significant barriers, including the high energy demands of AI computation and complexities in data integration. Conclusions : This review confirms the transformative potential of AI and robotics for developing low-carbon supply chains. An evidence-based framework is proposed to guide practical implementation and identify critical gaps, such as the need for standardized validation benchmarks, to direct future research and accelerate the transition to sustainable SCM.

Suggested Citation

  • Mariem Mrad & Mohamed Amine Frikha & Younes Boujelbene, 2025. "A Comprehensive Survey of Artificial Intelligence and Robotics for Reducing Carbon Emissions in Supply Chain Management," Logistics, MDPI, vol. 9(3), pages 1-25, August.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:3:p:104-:d:1717434
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    References listed on IDEAS

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    1. Bárbara Ferreira & João Reis, 2023. "A Systematic Literature Review on the Application of Automation in Logistics," Logistics, MDPI, vol. 7(4), pages 1-17, November.
    2. Yang, Wen & Ma, Jianhua & Fan, Ao & Zhang, Jinyi & Pan, Yanchun, 2024. "Effectiveness of policies for electric commercial vehicle adoption and emission reduction in the logistics industry," Energy Policy, Elsevier, vol. 188(C).
    3. Ding, Heping & Liu, Conghu, 2024. "Carbon emission efficiency of China's logistics industry: Measurement, evolution mechanism, and promotion countermeasures," Energy Economics, Elsevier, vol. 129(C).
    4. Fabio De Felice & Antonella Petrillo, 2021. "Green Transition: The Frontier of the Digicircular Economy Evidenced from a Systematic Literature Review," Sustainability, MDPI, vol. 13(19), pages 1-26, October.
    5. Meriem Riad & Mohamed Naimi & Chafik Okar, 2024. "Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization," Logistics, MDPI, vol. 8(4), pages 1-26, November.
    6. Krochmalny, Krystian & Niedzwiecki, Lukasz & Pelińska-Olko, Ewa & Wnukowski, Mateusz & Czajka, Krzysztof & Tkaczuk-Serafin, Monika & Pawlak-Kruczek, Halina, 2020. "Determination of the marker for automation of torrefaction and slow pyrolysis processes – A case study of spherical wood particles," Renewable Energy, Elsevier, vol. 161(C), pages 350-360.
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