Sustainable Retail Inventory Strategies Using Circular Economy Models and Predictive Analytics
Keywords:
Circular Economy, Predictive Analytics, Sustainable Retail, Inventory Management, Supply Chain OptimizationSynopsis
Retailers face increasing pressure to meet sustainability goals while managing inventory efficiently. Circular economy (CE) models and predictive analytics (PA) offer transformative potential by reducing waste, improving resource utilization, and forecasting demand more accurately. This paper explores integrated strategies combining CE and PA for sustainable inventory management in retail. A comparative analysis shows that a hybrid approach results in up to 29% cost savings and 35% fewer stockouts.
References
[1] Sarkis, J. (2023). Green Supply Chain Management and Circular Economy Analytics. International Journal of Production Economics, 257, 108749.
[2] Anugula Sethupathy, U.K. AI-powered cybersecurity mesh for financial networks: a real-world deployment case study. International Research Journal of Modernization in Engineering Technology and Science, 6(11), 6461–6466 (2024). https://doi.org/10.56726/IRJMETS64276
[3] Govindan, K., Soleimani, H., & Kannan, D. (2022). Reverse Logistics and Circular Retail Models. Journal of Cleaner Production, 348, 131–142.
[4] Ivanov, D. (2021). Predictive Resilience in Supply Chains. International Journal of Logistics Management, 32(1), 123–139.
[5] Wang, Y., & Zhang, D. (2020). Smart Retail Logistics Using AI. Transportation Research Part E, 138, 101–118.
[6] Bocken, N. M. P., de Pauw, I., Bakker, C., & van der Grinten, B. (2019). Product Design and Business Models for a Circular Economy. Journal of Industrial and Production Engineering, 36(5), 308–320.
[7] Anugula Sethupathy, U.K. (2022). API-driven architectures for modern digital payment and virtual account systems. International Research Journal of Modernization in Engineering Technology and Science, 4(8), 2442–2451. https://doi.org/10.56726/IRJMETS29156
[8] McKinsey & Company. (2024). Closing the Loop in Retail: Predictive Circularity. Insights Report.
[9] Kogan, M. et al. (2023). Machine Learning for Demand Forecasting in Circular Retail. Procedia Computer Science, 214, 241–249.
[10] Reike, D., Vermeulen, W., & Witjes, S. (2021). Circular Economy in the Retail Sector. Resources, Conservation and Recycling, 135, 239–248.
[11] Ghosh, D., & Hossain, M. S. (2020). Leveraging IoT and Analytics in Sustainable Retail. Sustainability Analytics Journal, 2(3), 97–113.
[12] Papetti, A., et al. (2023). Inventory Lifecycle Modeling in CE. Procedia CIRP, 104, 1234–1240.
[13] Xie, W., & Ma, H. (2022). Inventory Optimization Using Circular Models. Journal of Business Logistics, 43(2), 189–203.
[14] Chatterjee, S., Rana, N. P., & Sharma, R. (2021). Retail 4.0 and Circular Supply Chains. Information Systems Frontiers, 23(1), 57–73.
Published
Series
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
