ARIMA-Driven Vegetable Pricing and Restocking Strategy for Dual Optimization of Freshness and Profitability in Supermarket Perishables

Hongliang Li, Jun Liu, Jiangjie Qiu, Yunsen Zhou, Xu Zhang, Yuming Wang () and Wei Guo ()
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Hongliang Li: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Jun Liu: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Jiangjie Qiu: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Yunsen Zhou: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Xu Zhang: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Yuming Wang: School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
Wei Guo: School of Mechanical Engineering, Nantong University, Nantong 226019, China

Sustainability, 2024, vol. 16, issue 10, 1-26

Abstract: In the evolving landscape of perishable goods management, where the balance between minimizing waste and maximizing profitability is paramount, this work introduces an innovative approach to pricing and inventory decisions for products with limited shelf lives, focusing on vegetables in supermarkets. The contribution lies in its integration of an automated pricing and restocking decision model that leverages autoregressive integrated moving average (ARIMA) forecasting techniques alongside dynamic pricing strategies tailored to the goods’ freshness and remaining shelf life. The study uses a comprehensive sales, spoilage rates, and customer demand dataset to apply ARIMA forecasting for optimal restocking and adjusts prices dynamically based on product freshness, promoting competitive pricing and waste reduction. The results demonstrate the model’s effectiveness, reducing spoilage rates by up to 30% and increasing profitability margins by about 15%, highlighting its practical utility in real-world scenarios. The research highlights the potential for supermarkets to improve perishable goods inventory management, leading to significant economic benefits and reduced food waste. This study contributes to sustainable retail practices aligning with global responsible consumption and production initiatives, offering a scalable economic efficiency and environmental stewardship solution.

Keywords: ARIMA forecasting; dynamic pricing; inventory optimization; freshness (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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