IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v11y2024i11p22-30.html
   My bibliography  Save this article

The Impact of Artificial Intelligence in Logistics and Supply Chain in the USA – Focusing on Leading Industries in the 21st Century

Author

Listed:
  • Benjamin Kwame Amponsah

    (Westcliff University, United States of America (USA))

  • Paul Boadu Asamoah

    (Westcliff University, United States of America (USA))

  • Manso Frimpong

    (Westcliff University, United States of America (USA))

Abstract

Artificial Intelligence plays a crucial role in global supply chain management and logistics. It builds opportunities for cost reduction in purchase requirement planning, demand forecasting, sales/marketing, transportation, packaging, warehousing, inventory, production planning, finance, customer services, and information services. It also offers a competitive edge to the firms utilizing it. Artificial intelligence will likely make insightful decisions and improve efficiency via exceptional capabilities. This research aims to highlight the contributions of AI to supply chain management and logistics by using a thorough literature review and systematic review of the current literature from the internet. This will focus on AI applications within top American industries, such as e-commerce, retail, pharmaceuticals, and automotive, by leveraging artificial intelligence tools such as machine learning, route optimization, predictive analytics, and robotics. This paper evaluates the benefits and challenges associated with artificial intelligence adoption, providing an extensive overview of how AI tools are rebuilding SCM performance while also spotlighting the challenges linked to implementation and data security. By supplementing the literature review with case studies and data analysis, this research highlights the pivotal role of AI in shaping the future of logistics and supply chain management in the 21st Century. This research shows that although AI provides significant opportunities for innovation and growth, it presents damaging challenges; hence, strategic planning and investment are needed to overcome these intertwined challenges. This study also offers insight and recommendations for industry stakeholders and policymakers aiming to leverage the full potential of AI in logistics and supply chain management operations.

Suggested Citation

  • Benjamin Kwame Amponsah & Paul Boadu Asamoah & Manso Frimpong, 2024. "The Impact of Artificial Intelligence in Logistics and Supply Chain in the USA – Focusing on Leading Industries in the 21st Century," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(11), pages 22-30, November.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:11:p:22-30
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-11-issue-11/22-30.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrsi/articles/the-impact-of-artificial-intelligence-in-logistics-and-supply-chain-in-the-usa-focusing-on-leading-industries-in-the-21st-century/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    2. Catarina N. S. Silva & Justas Dainys & Sean Simmons & Vincentas Vienožinskis & Asta Audzijonyte, 2022. "A Scalable Open-Source Framework for Machine Learning-Based Image Collection, Annotation and Classification: A Case Study for Automatic Fish Species Identification," Sustainability, MDPI, vol. 14(21), pages 1-13, November.
    3. Ghasri, Milad & Ardeshiri, Ali & Zhang, Xiang & Waller, S. Travis, 2024. "Analysing preferences for integrated micromobility and public transport systems: A hierarchical latent class approach considering taste heterogeneity and attribute non-attendance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    4. Wu, Min & Wang, Nanxi & Yuen, Kum Fai, 2023. "Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    5. Mochen Liao & Kai Lan & Yuan Yao, 2022. "Sustainability implications of artificial intelligence in the chemical industry: A conceptual framework," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 164-182, February.
    6. Zulamir Hassani, Afdhal & Yusoff, Fazirah & Wan Zain, Wan Nor Aisyah, 2021. "Fair and Responsible in Logistics IR 4.0," MPRA Paper 108432, University Library of Munich, Germany.
    7. Marya Butt & Ander de Keijzer, 2022. "Using Transfer Learning to Train a Binary Classifier for Lorrca Ektacytometery Microscopic Images of Sickle Cells and Healthy Red Blood Cells," Data, MDPI, vol. 7(9), pages 1-21, September.
    8. Sohani Liyanage & Hussein Dia & Rusul Abduljabbar & Saeed Asadi Bagloee, 2019. "Flexible Mobility On-Demand: An Environmental Scan," Sustainability, MDPI, vol. 11(5), pages 1-39, February.
    9. Pamucar, Dragan & Deveci, Muhammet & Gokasar, Ilgin & Tavana, Madjid & Köppen, Mario, 2022. "A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    10. Jae-joon Chung & Hyun-Jung Kim, 2020. "An Automobile Environment Detection System Based on Deep Neural Network and its Implementation Using IoT-Enabled In-Vehicle Air Quality Sensors," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    11. Jin, Hui & Liu, Yue & Wu, Telan & Zhang, Yanpei, 2022. "Site-specific optimization of bus stop locations and designs over a corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    12. Tahmineh Ladi & Shaghayegh Jabalameli & Ayyoob Sharifi, 2022. "Applications of machine learning and deep learning methods for climate change mitigation and adaptation," Environment and Planning B, , vol. 49(4), pages 1314-1330, May.
    13. Eugène Loos & Maria Sourbati & Frauke Behrendt, 2020. "The Role of Mobility Digital Ecosystems for Age-Friendly Urban Public Transport: A Narrative Literature Review," IJERPH, MDPI, vol. 17(20), pages 1-16, October.
    14. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    15. De Obesso Arias, María de las Mercedes & Pérez Rivero, Carlos Alberto & Carrero Márquez, Oliver, 2023. "Artificial intelligence to manage workplace bullying," Journal of Business Research, Elsevier, vol. 160(C).
    16. Suleiman Hassan Otuoze & Dexter V. L. Hunt & Ian Jefferson, 2021. "Neural Network Approach to Modelling Transport System Resilience for Major Cities: Case Studies of Lagos and Kano (Nigeria)," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    17. Maryann Osadebamwen Asemota, 2023. "Facial Recognition Technology For Recruitment In The Russian Workplace," HSE Working papers WP BRP 126/STI/2023, National Research University Higher School of Economics.
    18. Victor Anderson Hodibert & Adriana Narkwa Anderson (PhD) & Kate Neequaye, 2024. "AI/Robotics in the Tourism and Hospitality Sector: Technological Realities and Imaginaries in the Ghanaian Context," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(1), pages 2471-2480, January.
    19. Tomas Ramirez-Guerrero & Mauricio Toro & Marta S. Tabares & Ricardo Salazar-Cabrera & Álvaro Pachón de la Cruz, 2022. "Key Aspects for IT-Services Integration in Urban Transit Service of Medium-Sized Cities: A Qualitative Exploratory Study in Colombia," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    20. Fahad Alrukaibi & Rushdi Alsaleh & Tarek Sayed, 2019. "Applying Machine Learning and Statistical Approaches for Travel Time Estimation in Partial Network Coverage," Sustainability, MDPI, vol. 11(14), pages 1-18, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjc:journl:v:11:y:2024:i:11:p:22-30. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrsi/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.