Milano, Riccardo (A.A. 2023/2024) Leveraging AI for strategic decision-making in e-commerce: sase study of RDX sport's prediction algorithms. Tesi di Laurea in Digital business and workplace technology, Luiss Guido Carli, relatore Paolo Spagnoletti, pp. 62. [Bachelor's Degree Thesis]

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Abstract/Index

Context and overview of the XDEMAND project. Literature review. Introduction to AI in e-commerce. AI in demand forecasting. AI in price optimization. AI in inventory management. Identifying gaps in current research. Methodology. Overview. Use of AI tools in the research process. Case study design. Data collection. Data preprocessing and transformation. Data analysis techniques. Analysis of XDEMAND functionality. Demand analysis. Price sensing and optimization. Stock sensing and inventory management. Integration and user interaction. Implementation and results. Demand forecasting implementation. Price sensing and optimization. Stock sensing and inventory management. Integration and business impact. Findings and discussion. Demand forecasting findings. Price optimization findings. Stock sensing and inventory management findings. Final discussion and contribution to e-commerce operations. Broader implications and future research directions. Industry implications of XDEMAND’s AI-driven system. Theoretical contribution to AI in e-commerce.

References

Bibliografia: pp. 59-62.

Thesis Type:	Bachelor's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18)
Chair:	Digital business and workplace technology
Thesis Supervisor:	Spagnoletti, Paolo
Academic Year:	2023/2024
Session:	Autumn
Deposited by:	Alessandro Perfetti
Date Deposited:	19 Mar 2025 11:51
Last Modified:	19 Mar 2025 11:51
URI:	https://tesi.luiss.it/id/eprint/41298

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