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International Journal of Science, Strategic Management and Technology

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INTELLIGENT FOOD ORDERING SYSTEM WITH BEHAVIORAL PREDICTION AND DYNAMIC PRICING: A MACHINE LEARNING APPROACH

AUTHORS:
Vaibhav Pratap Singh
Mentor
Minhaj Nezami
Affiliation
Department of Information Technology Noida Institute of Engineering and Technology Greater Noida, Uttar Pradesh, India
DOI: 10.55041/ijsmt.v2i5.173
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

The digital transformation of the food industry has led to a surge in online food delivery platforms. However, most existing systems operate on static models that do not account for individual user behavior or real-time market fluctuations. This paper proposes an Intelligent Food Ordering System (IFOS) that integrates behavioral prediction and dynamic pricing models to optimize user experience and restaurant profitability. By leveraging Long Short-Term Memory (LSTM) networks for predicting user ordering patterns and a Reinforcement Learning (RL) framework for dynamic pricing, the system adapts to demand shifts and individual preferences. Experimental results demonstrate that the proposed system increases customer retention by 15% and improves restaurant revenue by 12% compared to traditional static systems.

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PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 05
Review Rounds:
2
Article Type:
Research Article
Publication Date:
May 11 2026
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Singh, V. P. (2026). Intelligent Food Ordering System with Behavioral Prediction and Dynamic Pricing: A Machine Learning Approach. International Journal of Science, Strategic Management and Technology, 02(05). https://doi.org/10.55041/ijsmt.v2i5.173

Singh, Vaibhav. "Intelligent Food Ordering System with Behavioral Prediction and Dynamic Pricing: A Machine Learning Approach." International Journal of Science, Strategic Management and Technology, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i5.173.

Singh, Vaibhav. "Intelligent Food Ordering System with Behavioral Prediction and Dynamic Pricing: A Machine Learning Approach." International Journal of Science, Strategic Management and Technology 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i5.173.

References
1.Yusof et al., “Utilizing artificial intelligence (AI) in customer’s purchase intentions on online food delivery service,” International Journal of Tourism and Hospitality in Asia Pasific, 2024.

2.Gore, P. K. Mishra, and S. Gore, “Improvisation of food delivery business by leveraging ensemble learning with various algorithms,” in 2023 Int. Conf. on Self Sustainable Artificial Intelligence Systems (ICSSAS), 2023, pp. 221–229.

3.K. Sathyabama, M. A. A. Ra, and M. R. Gukan, “AI-driven expiry prediction and dynamic pricing system for retail inventory management utilizing ARIMA and LSTM models,” in 2024 Int. Conf. on Emerging Research in Computational Science (ICERCS), 2024, pp. 1–6.

4.Zibaie, M. Beliaev, M. Alizadeh, and R. Pedarsani, “Dynamic pricing for multi-modal meal delivery using deep reinforcement learning,” Future Transportation, 2025.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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