Marketing (2025) · 91-96-betler

AI-DRIVEN DEMAND FORECASTING AS A TOOL FOR SUSTAINABLE FMCG DISTRIBUTION

F. Sh. Jamoliddinov

Derekkózde oqıw PDF

Annotaciya

This thesis explores AI-driven demand forecasting as a strategic tool for sustainable FMCG distribution. It shows how AI enhances inventory accuracy, reduces waste, and optimizes logistics. Global best practices (Unilever, P&G) illustrate realworld applications, while the case for Uzbekistan emphasizes digital integration to align with green economy goals.

Metadata derekkózi: jurnal OAI-PMH arxivi · Sindex tolıq mátindi saqlamaydı, derekkózge silteme beredi.

Dáyeksóz alıw

APA 7 
F. Sh. Jamoliddinov (2025). AI-DRIVEN DEMAND FORECASTING AS A TOOL FOR SUSTAINABLE FMCG DISTRIBUTION. Marketing, 91-96.
GOST R 7.0.5 
F. Sh. Jamoliddinov AI-DRIVEN DEMAND FORECASTING AS A TOOL FOR SUSTAINABLE FMCG DISTRIBUTION // Marketing. 2025. С. 91-96.
BibTeX 
@article{jamoliddinov2025,
  author  = {F. Sh. Jamoliddinov},
  title   = {AI-DRIVEN DEMAND FORECASTING AS A TOOL FOR SUSTAINABLE FMCG DISTRIBUTION},
  journal = {Marketing},
  year    = {2025},
  pages   = {91-96}
}
RIS 
TY  - JOUR
AU  - F. Sh. Jamoliddinov
TI  - AI-DRIVEN DEMAND FORECASTING AS A TOOL FOR SUSTAINABLE FMCG DISTRIBUTION
JO  - Marketing
PY  - 2025
SP  - 91
EP  - 96
ER  -