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Ai Adoption In Supply Chain Management: Strategies For Enhancing Effectiveness And Operational Efficiency

Author

Listed:
  • Md. Mehadi Hassan

    (Pabna University of Science and Technology, pabna, Bangladesh)

  • Md.Saiful Islam

    (San Francisco Bay University, 161 Mission Falls Lane, Fremont, CA 94539, USA)

  • Rajib Halder

    (General Banking (Officer), Dutch-Bangla Bank PLC.)

  • Jannatul Ferdousi

    (San Francisco Bay University, 161 Mission Falls Lane, Fremont, CA 94539, USA)

  • Md. Abdullah Al Mamun

    (Senior Officer and Branch Operation Manager)

  • Shimul Chowdhury

    (Fairleigh Dickinson University, Vancouver, Canada)

  • Jannatul Ferdous Sweety

    (American International University-Bangladesh Pubali Bank PLC. Dhaka)

Abstract

This research studies the use of artificial intelligence (AI) in supply chain management (SCM) to boost operational efficiency and effectiveness. The major purpose is to create and evaluate AI-driven techniques that improve multiple areas of SCM, including demand forecasting, inventory management, and logistics. Employing a quantitative research methodology, the study blends Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models to assess structured and time-series data from multiple SCM sources. The technique incorporates data preparation, model training, and performance assessment, concentrating on important metrics such as precision, recall, accuracy, and F1-score. The CNN model attained a remarkable accuracy of 92.5%, proving its exceptional performance in predicting and controlling SCM operations. The results emphasize the considerable potential of AI technologies in enhancing SCM effectiveness and operational efficiency, giving vital insights for firms aiming to harness AI for competitive advantage. This study adds to the area by presenting a thorough framework for incorporating AI into SCM and suggesting best practices for boosting performance.

Suggested Citation

  • Md. Mehadi Hassan & Md.Saiful Islam & Rajib Halder & Jannatul Ferdousi & Md. Abdullah Al Mamun & Shimul Chowdhury & Jannatul Ferdous Sweety, 2025. "Ai Adoption In Supply Chain Management: Strategies For Enhancing Effectiveness And Operational Efficiency," Information Management and Computer Science (IMCS), Zibeline International Publishing, vol. 8(1), pages 18-24, June.
    • Handle: RePEc:zib:zbimcs:v:8:y:2025:i:1:p:18-24
    DOI: 10.26480/imcs.01.2025.18.24
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    References listed on IDEAS

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    1. Dong, Yutong & Jiang, Hongkai & Wang, Xin & Mu, Mingzhe & Jiang, Wenxin, 2024. "An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
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