The emergence of Industry 4.0 has brought transformative changes to supply chain management, introducing advanced technologies that challenge and reshape traditional operational practices. These innovations are designed to enhance supply chain efficiency, agility, and resilience, offering organizations the opportunity to overcome existing challenges and stay competitive. This study seeks to evaluate the adoption levels of the key Industry 4.0 practices in Moroccan supply chains, using the Best Worst Method (BWM) to systematically rank them based on their levels of implementation and their strategic importance to improving supply chain performance. Data was gathered from 15 expert respondents with diverse expertise in supply chain management and Industry 4.0 technologies. The analysis identifies the most widely adopted practices, such as IoT and big data analytics, alongside those with lower levels of integration, such as additive manufacturing and autonomous robots. The findings offer critical insights for organizations transitioning toward digitalized supply chains. By contributing to the academic discourse on the prioritization and implementation of Industry 4.0 practices, this research offers a valuable resource for scholars and decision-makers working to navigate the complexities of digital transformation in supply chains.

Keywords:

Industry 4.0, Supply chain Technology, Digitalization, Best Worst Method

@article{oscm-2025-581,
  title={Evaluating Industry 4.0 Technologies for Supply Chain Optimization: A Best-Worst Method Approach},
  year={2025},
  author={Samah Mahmah and Salah Oulfarsi and Ikram Ait Hammou},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={18},
  number={2},
  pages={215--223},
  doi={10.31387/oscm0610463}
}

Samah Mahmah, Salah Oulfarsi, Ikram Ait Hammou (2025). Evaluating Industry 4.0 Technologies for Supply Chain Optimization: A Best-Worst Method Approach. Operations and Supply Chain Management: An International Journal, 18(2), 215-223. https://doi.org/10.31387/oscm0610463