The Role of Business Intelligence in Supply Chain Optimization A Case Study of the Carrefour Market in Jordan
DOI:
https://doi.org/10.56294/dm2025747Keywords:
Business Intelligence, Supply chain, Carrefour Market, Artificial Intelligence, JordanAbstract
Introduction: This study examines the role of Business Intelligence (BI) in the supply chain operations of Carrefour Market, a Jordanian retail leader. It uses a case study approach to assess the effectiveness of BI tools in inventory management, demand planning, and supplier development, aiming to improve efficiency and competitiveness.
Methods: The study demonstrates how BI tools, such as real-time analytics, data visualization, and predictive modeling, have been used to solve key supply chain problems. The study also explores the process of implementing BI, including staff training and fostering a data intelligence culture.
Results: The findings show that BI has positively impacted the company's key performance indicators (KPIs), such as inventory turnover rates, order fulfillment accuracy, and supply chain resiliency.
Conclusions: The study concludes that BI resolves operational processes and provides strategic perspectives for development and responsiveness to the evolving retail climate. The case study suggests initiatives for other retailers to improve supply chain performance using BI technologies.
References
Kester, Q. A., & Preko, M. (2015). Business intelligence adoption in developing economies: a case study of Ghana. International Journal of Computer Applications, 975, 8887.
Al-Momani MM, Al-Momani IM. Exploring the impact of big data on companies' business intelligence strategies in the digital era. Edelweiss Appl Sci Technol. 2024;8(5):883-91.
Bathaei, A., & Streimikiene, D. (2024). Sustainable supply chains in the Middle East: Challenges, opportunities, and strategic solutions. Proceedings of the 36th RSEP International Conference on Economics, Finance and Business, Madrid, Spain. https://doi.org/10.19275/RSEPCONFERENCES327
Al-Momani MM, Abbas N, Saleem TA, Basha M, Jubran AH, Al-Sawaie K, et al. The role of business intelligence on digital economic transformations (case study: E-government in Jordan). In: Artificial Intelligence (AI) and Finance. Cham: Springer Nature Switzerland; 2023. p. 308-16.
Colla, E., & Dupuis, M. (2002). Research and managerial issues on global retail competition: Carrefour/Wal‐Mart. International Journal of retail & distribution management, 30(2), 103-111.
Hugos, M. H. (2024). Essentials of supply chain management. John Wiley & Sons.
Radhakrishnan, S. (2023). AI-DRIVEN BUSINESS INTELLIGENCE: FORECASTING MARKET TRENDS AND CONSUMER BEHAVIOR. CONFLUENCE OF CURIOSITY, 73.
Gundersen, P., Schmidt, I. K., & Raulund-Rasmussen, K. (2006). Leaching of nitrate from temperate forests affects of air pollution and forest management. Environmental Reviews, 14(1), 1-57.
Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775-788.
Frazelle, E. (2020). Supply chain strategy: the logistics of supply chain management. McGraw-Hill.
Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International journal of production economics, 176, 98-110.
Lambert, D. M., & Enz, M. G. (2017). Issues in supply chain management: Progress and potential. Industrial marketing management, 62, 1-16.
Feil, K., Baumbach, T., & Little, R. (2014). Global supply chain management: Leveraging processes, measurements, and tools for strategic corporate advantage.
Sanders, N. R. (2014). Big data driven supply chain management: A framework for implementing analytics and turning information into intelligence. Pearson Education.
Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019). Big data and predictive analytics and manufacturing performance: integrating institutional theory, resource‐based view and big data culture. British Journal of Management, 30(2), 341-361.
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188.
Trkman, P., McCormack, K., De Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision support systems, 49(3), 318-327.
[14] Al-Momani, M. M., & Al-Momani, I. M. (2024). Exploring the impact of big data on companies' business intelligence strategies in the digital era. Edelweiss Applied Science and Technology, 8(5), 883-891.
Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International journal of accounting information systems, 9(3), 135-153.
Al-Momani, M. M., Abbas, N., Saleem, T. A., Basha, M., Jubran, A. H., Al-Sawaie, K., ... & Dahlan, M. (2023). The Role of Business Intelligence on Digital Economic Transformations (Case Study: E-Government in Jordan). In Artificial Intelligence (AI) and Finance (pp. 308-316). Cham: Springer Nature Switzerland.
Fosso Wamba, S., & Mishra, D. (2017). Big data integration with business processes: a literature review. Business Process Management Journal, 23(3), 477-492.
Al-Momani, M. M. (2024). Maximizing Organizational Performance: The Synergy of AI and BI. Revista de Gestão Social e Ambiental, 18(5), e06644-e06644.
Fosso Wamba, S., & Queiroz, M. M. (2020). Blockchain in the operations and supply chain management: Benefits, challenges and future research opportunities. International Journal of Information Management, 52, 102064. https://doi.org/10.1016/j.ijinfomgt.2019.102064
Belhadi, A., Kamble, S., & Fosso Wamba, S. (2022). Building supply-chain resilience: An artificial intelligence-based technique and decision-making framework. International Journal of Production Research, 60(14), 4487-4507. https://doi.org/10.1080/00207543.2022.2029998
Rejeb, A., Keogh, J. G., & Treiblmaier, H. (2021). The potentials of augmented reality in supply chain management: A state-of-the-art review. Management Review Quarterly, 71(3), 675-711. https://doi.org/10.1007/s11301-020-00193-8
Al-Momani MM. Maximizing organizational performance: The synergy of AI and BI. Rev Gest Soc Ambient. 2024;18(5):e06644.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Mohammad Musa Al-Momani, Ahmad Awadallah, Bilal Alnassar, AbdelRahman Ismail, Mohammed Nassoura, Nabil Abudarwish (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
