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BOOK CHAPTERS – CRC Press 2024 : CALL FOR BOOK CHAPTERS – CRC Press (Taylor & Francis Group)AI in Demand Forecasting for Ecommerce Application

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When Jul 5, 2024 - May 31, 2025
Where CRC Press (Taylor & Francis Group)
Abstract Registration Due Aug 23, 0024
Submission Deadline Apr 11, 2024
Notification Due Dec 30, 2024
 

Call For Papers

Dear Professor (s),
Greetings of the Day!
It is our pleasure to invite you to contribute to the book entitled "AI in Demand Forecasting for Ecommerce Application” will be published by CRC Press (Taylor & Francis Group). Co-authored chapters are also welcome. I am certain that your contribution to this topic and/or other related research areas would make an excellent addition to this publication. All the chapters of the book will be published by CRC Press and all Taylor & Francis publications have direct feed to Scopus.
Note: There is no publication charge. It is completely free.
Abstract Submission: 23/08/2024
Notification Date: 25/09/2024
Full chapter Submission: 04/11/2024
Notification of acceptance: 30/12/2024
Submission Procedure:
Please submit your full chapter (fitted in scope) having minimum 15 pages and maximum 25 pages.
Chapter Submission Mail ID: crcbook.aidemandforecasting@gmail.com
Please feel free to contact on: bhuvaneshwari.p@manipal.edu/jayita.saha@manipal.edu
We welcome book chapter contribution on the following (but not limited to) topics:
1. Foundations of Demand Forecasting: Traditional Methods vs. AI Approaches
2. Applications of AI Techniques for Enhanced Demand Prediction in e-commerce
3. Reinforcement and Ensemble Learning Techniques for Robust Demand Forecasting in e-commerce
4. Challenges and Opportunities in Implementing AI Techniques for Demand Forecasting
5. Application of Causal inference in forecasting of demands in ecommerce
6. Emphasize the importance of Causal inference to build personalized recommendation system
7. AI techniques to build dynamic model based on causal relationship
8. Optimization Techniques for Improving AI-driven Demand Forecasting in E-commerce
9. Optimized solution to allocate resource applying causal inference
10. Future Directions and Emerging Trends in AI-driven Demand Forecasting for E-commerce
11. Ethical Considerations and Responsible AI Practices in Demand Forecasting
12. Case Studies and Real-world Applications of AI in E-commerce Demand Forecasting

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