Open Access
Issue
SHS Web Conf.
Volume 225, 2025
2025 3rd International Conference on Financial Management and the Digital Economy (ICFMDE 2025)
Article Number 01018
Number of page(s) 11
Section Digital Economics & Behavior
DOI https://doi.org/10.1051/shsconf/202522501018
Published online 13 November 2025
  1. Y. Li, Z. Chen, M. Rungtusanatham, Artificial intelligence in supply-chain and operations management: Integrative review and future agenda. Int. J. Prod. Res. 61(12), 1-25 (2023) [Google Scholar]
  2. S. Bose, Retailers use AI for in‑store experimentation and customer service. Street Fight Mag. (2018) [Google Scholar]
  3. K. Jarek, G. Mazurek, Marketing and artificial intelligence. Cent. Eur. Bus. Rev. 8, 46–55 (2019) [CrossRef] [Google Scholar]
  4. W. Verbeke, K. Dejaeger, D. Martens, J. Hur, B. Baesens, New insights into churn prediction in the telecommunication sector: A profit‑driven data‑mining approach. Eur. J. Oper. Res. 218, 211–229 (2012) https://doi.org/10.1016/j.ejor.2011.09.031 [Google Scholar]
  5. D. Nair, M.J. Saenz, Pair people and AI for better product demand forecasting. MIT Sloan Manag. Rev (2024) https://sloanreview.mit.edu/article/pair-people-and-ai-for-better-product-demand-forecasting/ [Google Scholar]
  6. N. Groen, S. Zakharov, Introduction of AI‑based sales forecasting: How to drive digital transformation in food & beverage outlets. In Proc. Digital Transformation Conf (2024) https://link.springer.com [Google Scholar]
  7. R. Batista, M. Becerra, AI adoption in professional-service firms: A TOE-based study. Technol. Forecast. Soc. Change 200, 123456 (2024) [Google Scholar]
  8. L. Santos, et al. Artificial intelligence and strategic decision-making: Evidence from European multinationals. Strategy Sci. 9(2), 190-208 (2024) [Google Scholar]
  9. E. Brynjolfsson, A. McAfee, The business of artificial intelligence. Harv. Bus. Rev. (2017) https://hbr.org/2017/07/the-business-of-artificial-intelligence [Google Scholar]
  10. Y.R. Shrestha, S.M. Ben‑Menahem, von Krogh G. Organizational decision‑making structures in the age of artificial intelligence. Calif. Manag. Rev. 61, 66–83 (2019) https://doi.org/10.1177/0008125619862257 [Google Scholar]
  11. T.H. Davenport, R. Ronanki, Artificial intelligence for the real world. Harv. Bus. Rev. 96, 108–116 (2018). [Google Scholar]
  12. X. Wang, Y. Zhou, L. Chen, AI and the new quality-productive forces of enterprises: An empirical study. Enterprise Econ. 41(3), 112-130 (2024) [Google Scholar]
  13. F. Chen, Y. Zhao, Enhancing supply-chain management with deep learning and machine learning. Expert Syst. Appl.231, 120173 (2024) https://www.sciencedirect.com/science/article/pii/S2199853124001732 [Google Scholar]
  14. D. J. Devarahosahalli, AI-augmented decision making: A framework for enterprise workflow transformation. J. Enterp. Inf. Syst. 19(1), 1-22 (2025) [Google Scholar]
  15. A. Garcia-Molina, A. Ruiz-Martinez, AI adoption dynamics in SMEs vs. large firms: A systematic review. J. Small Bus. Manag. 63(2), 250-275 (2025) [Google Scholar]
  16. F. Chen, Y. Zhao, Enhancing supply-chain management with deep learning and machine learning. Expert Syst. Appl.231, 120173 (2024) https://www.sciencedirect.com/science/article/pii/S2199853124001732 [Google Scholar]
  17. R. Khan, et al. Impact of artificial intelligence on customer-relationship management: A multi-country study. Asia-Pac. J. Mark. Logist. 36(1), 23-45 (2024) https://www.researchgate.net/publication/389811656 [Google Scholar]

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