IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i20p9081-d1770616.html

GenAI Technology Approach for Sustainable Warehouse Management Operations: A Case Study from the Automative Sector

Author

Listed:
  • Sorina Moica

    (Faculty of Engineering and Information Technology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Târgu Mureș, Romania)

  • Tripon Lucian

    (Logistics of Innovations Group, Bosch Automotive SRL, 515400 Blaj, Romania)

  • Vassilis Kostopoulos

    (Faculty of Engineering and Information Technology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Târgu Mureș, Romania
    Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece)

  • Adrian Gligor

    (Faculty of Engineering and Information Technology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Târgu Mureș, Romania)

  • Noha A. Mostafa

    (Department of Industrial Engineering, Zagazig University, Zagazig 44519, Egypt
    Department of Mechanical Engineering, The British University in Egypt, El-Sherouk 11837, Egypt)

Abstract

The emergence of Generative Artificial Intelligence (GenAI) is reshaping logistics and supply chain operations, offering new opportunities to improve efficiency, accuracy, and responsiveness. In the automotive manufacturing sector, where high-volume throughput and precision are critical, the integration of AI technologies into warehouse management represents a strategic advancement. This study presents a case analysis of the implementation of AI-driven reception processes at an Automotive facility in Blaj, Romania. The research focuses on the transition from manual operations to automated recognition using industrial-grade imaging systems integrated with enterprise resource planning platforms. The integrated approach used combines Value Stream Mapping, quantitative performance analysis, and statistical validation using the Wilcoxon Signed-Rank Test. The results reveal a substantial reduction in reception time up to 79% and significant cost savings across various operational scales with improved data accuracy and minimized logistics failures. To support broader industry adoption, the study proposes a Cleaner Logistics and Supply Chain Model, incorporating principles of sustainability, ethical compliance, and continuous improvement. This model serves as a strategic framework for organizations seeking to align AI adoption with long-term operational resilience and environmental responsibility. The findings validate the operational and financial advantages of AI-enabled warehousing management in achieving sustainable digital transformation in logistics.

Suggested Citation

  • Sorina Moica & Tripon Lucian & Vassilis Kostopoulos & Adrian Gligor & Noha A. Mostafa, 2025. "GenAI Technology Approach for Sustainable Warehouse Management Operations: A Case Study from the Automative Sector," Sustainability, MDPI, vol. 17(20), pages 1-25, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:9081-:d:1770616
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/20/9081/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/20/9081/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Afonso Vaz de Oliveira & Carina M. Oliveira Pimentel & Radu Godina & João Carlos de Oliveira Matias & Susana M. Palavra Garrido, 2022. "Improvement of the Logistics Flows in the Receiving Process of a Warehouse," Logistics, MDPI, vol. 6(1), pages 1-23, March.
    2. Wenwen Chen & Yangchongyi Men & Noelia Fuster & Celia Osorio & Angel A. Juan, 2024. "Artificial Intelligence in Logistics Optimization with Sustainable Criteria: A Review," Sustainability, MDPI, vol. 16(21), pages 1-22, October.
    3. Zhencheng Fan & Zheng Yan & Shiping Wen, 2023. "Deep Learning and Artificial Intelligence in Sustainability: A Review of SDGs, Renewable Energy, and Environmental Health," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    4. Henriett Matyi & Péter Tamás, 2023. "An Innovative Framework for Quality Assurance in Logistics Packaging," Logistics, MDPI, vol. 7(4), pages 1-13, November.
    5. Nijolė Batarlienė & Aldona Jarašūnienė, 2024. "Improving the Quality of Warehousing Processes in the Context of the Logistics Sector," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    6. Boone, Tonya & Fahimnia, Behnam & Ganeshan, Ram & Herold, David M. & Sanders, Nada R., 2025. "Generative AI: Opportunities, challenges, and research directions for supply chain resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 199(C).
    7. Yotsaphat Kittichotsatsawat & Wassanai Wattanutchariya & Akkasit Jongjareonrak & Phisit Seesuriyachan, 2025. "Enhancing Manufacturing Operations Within the Supply Chain for Sustainable Frozen Shrimp Production," Sustainability, MDPI, vol. 17(6), pages 1-20, March.
    8. Abhishek P.G. & Maheshwar Pratap, 2020. "Achieving Lean Warehousing Through Value Stream Mapping," South Asian Journal of Business and Management Cases, , vol. 9(3), pages 387-401, December.
    9. Yueyang Liu & Yan Jiang, 2025. "The Impact of Supply Chain Quality Management on Firm Performance in Manufacturing Business: The Moderating Role of Digital Intelligence," Sustainability, MDPI, vol. 17(9), pages 1-28, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:bcp:journl:v:9:y:2025:i:30:p:448-463 is not listed 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. Amandeep Sharma & Prateek Kakkar & Susheela Hooda & Mahender Singh Kaswan, 2026. "How Does Gen- AI Reshape Supply Chain, Logistics, and Manufacturing? A Systematic Bibliometric Review," SN Operations Research Forum, Springer, vol. 7(1), pages 1-28, March.
    2. Sumit Tripathi & Roma Trigunait & Dinesh Chandra Pandey, 2025. "A Behavioral and Environmental Framework for Sustainable Retail Forecasting and Decision-Making," Circular Economy and Sustainability, Springer, vol. 5(7), pages 5935-5963, December.
    3. Shuzhao Dong & Bin Yang, 2025. "Research on Composite Robot Scheduling and Task Allocation for Warehouse Logistics Systems," Sustainability, MDPI, vol. 17(11), pages 1-27, May.
    4. Munirah Ghazali & Vassilios Makrakis & Nelly Kostoulas-Makrakis & Nooraida Yakob & Rabiatul Adawiah Ahmad Rashid & Widad Othman & Nanung Agus Fitriyanto, 2024. "Predicting Teacher’s Information and Communication Technology-Enabled Education for Sustainability Self-Efficacy," Sustainability, MDPI, vol. 16(13), pages 1-13, June.
    5. Iouri Semenov & Marianna Jacyna & Izabela Auguściak & Mariusz Wasiak, 2025. "Hybrid Human–AI Collaboration for Optimized Fuel Delivery Management," Energies, MDPI, vol. 18(19), pages 1-25, September.
    6. Abdulmajeed Faihan Alotaibi, 2024. "Ethical Guidelines of Integrating Artificial Intelligence in Healthcare in Alignment with Sustainable Development," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 59(4), pages 51710-51716, November.
    7. Shaip Gashi, 2025. "The impact of logistics innovations on costs and profitability of manufacturing enterprises," Management and Business Articles, Management and Business, vol. 3(2), pages 66-76, December.
    8. Gabriela Badareu & Marius Dalian Doran & Mihai Alexandru Firu & Ionuț Marius Croitoru & Nicoleta Mihaela Doran, 2024. "Exploring the Role of Robots and Artificial Intelligence in Advancing Renewable Energy Consumption," Energies, MDPI, vol. 17(17), pages 1-17, September.
    9. de Jesus Pacheco, Diego Augusto & Møller Clausen, Daniel & Bumann, Jendrik, 2023. "A multi-method approach for reducing operational wastes in distribution warehouses," International Journal of Production Economics, Elsevier, vol. 256(C).
    10. Ewa Kulińska & Małgorzata Dendera-Gruszka, 2022. "New Perspectives for Logistics Processes in the Energy Sector," Energies, MDPI, vol. 15(15), pages 1-22, August.
    11. Aylin Erdoğdu & Faruk Dayi & Ferah Yildiz & Ahmet Yanik & Farshad Ganji, 2025. "Combining Fuzzy Logic and Genetic Algorithms to Optimize Cost, Time and Quality in Modern Agriculture," Sustainability, MDPI, vol. 17(7), pages 1-41, March.
    12. Wei, Renfeng & Li, Yong & Liu, Yanfeng, 2025. "Progress in underground thermal energy storage: research contents, hotspots, and development trends," Applied Energy, Elsevier, vol. 401(PB).
    13. Małgorzata Gawlik-Kobylińska, 2025. "Operational Roles of Artificial Intelligence in Energy Security: A Triangulated Review of Abstracts (2021–2025)," Energies, MDPI, vol. 18(16), pages 1-23, August.
    14. Izabela Jonek-Kowalska & Wieslaw Grebski, 2024. "Comparative Analysis of Domestic Production and Import of Hard Coal in Poland: Conclusions for Energy Policy and Competitiveness," Energies, MDPI, vol. 17(20), pages 1-22, October.
    15. Kristina Čižiūnienė & Greta Draugelytė & Edgar Sokolovskij & Jonas Matijošius, 2025. "Improving Small Parcel Delivery Efficiency and Sustainability: A Study of Lithuanian Private Delivery Company," Sustainability, MDPI, vol. 17(5), pages 1-19, February.
    16. Hussein, Jelili Babatunde & Workneh, Tilahun Seyoum & Kassim, Alaika & Ntsowe, Khuthadzo & Melesse, Sileshi F. & El-Mesery, Hany S. & Zicheng, Hu, 2025. "A review of the use of artificial intelligence in renewable energy for food processing and preservation process optimisation, challenges, and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).
    17. Yanmeng Tao & Ying Yang & Shuaian Wang, 2025. "A Data-Driven Semi-Relaxed MIP Model for Decision-Making in Maritime Transportation," Mathematics, MDPI, vol. 13(18), pages 1-37, September.
    18. Shahriar Hasan Ratul & Md. Ismail Hossain & H. M. Belal & Palash Saha & Md. Ashikur Rahman, 2026. "Navigating Sustainability through Flexible Hyperautomation and Reverse Logistics in the B2B Sector: Implications for the Electronics Industry," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 27(1), pages 99-121, March.
    19. Ionica Oncioiu & Diana Andreea Mândricel & Mihaela Hortensia Hojda, 2025. "Artificial Intelligence-Enabled Digital Transformation in Circular Logistics: A Structural Equation Model of Organizational, Technological, and Environmental Drivers," Logistics, MDPI, vol. 9(3), pages 1-28, August.
    20. Xuhui Chen & Guanghui Cheng & Yong He, 2025. "Mathematical Modeling and Optimization of Platform Supply Chain in the Digital Era: A Systematic Review," Mathematics, MDPI, vol. 13(17), pages 1-33, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:20:p:9081-:d:1770616. 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: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    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.