Structural Limitations of Push Inventory Management Systems in High Environmental Variability Conditions
- 1 CEO at ABM Cloud Intuiflow, Kyiv, Ukraine
Abstract
The article examines the structural limitations of push-type inventory management systems as an integral property of decision architecture under conditions of high environmental variability, stochastic lead times, and fragmented distribution networks. The analysis is based on a comparative review of contemporary studies addressing safety stocks, the bullwhip effect, buffer parameterization, production–inventory planning, and warehouse centralization strategies. It is shown that isolated optimization of order quantity or service level does not ensure system stability and leads to reproducible trade-offs between holding costs, stockout probability, and flow throughput. The study argues that the primary source of instability lies in the forecast-centric decision sequence “inventory-production-distribution,” which amplifies sensitivity to demand dispersion and temporal deviations. It is demonstrated that increasing safety stocks performs a function of local fluctuation compensation while simultaneously scaling systemic imbalances when misaligned with production capacities and replenishment lead times. Particular attention is given to distribution architecture and the risk-pooling effect, indicating that centralization reduces variability amplitude without eliminating its forecast-driven nature, whereas signal-buffer and pull logics enhance flow adaptability but do not guarantee the removal of structural constraints. It is shown that managerial stability is determined by the coherence of informational, resource, and spatial contours rather than by the precision of individual parameters. The article may be useful for researchers of logistics systems, supply chain management professionals, and developers of inventory planning models under uncertainty.
- Aiello, G., Muriana, C., Quaranta, S., & Abusohyon, I. A. S. (2025). A Sustainable Inventory Management Model for Closed Loop Supply Chain Involving Waste Reduction and Treatment. Cleaner Logistics and Supply Chain, 16, Article 100244. https://doi.org/10.1016/j.clscn.2025.100244
- Bayard, S., Grimaud, F., & Delorme, X. (2024). Demand Driven Material Requirement Planning: Core Concepts and Analysis of Its Behavior on a Case Study. IFAC-PapersOnLine, 58, 1054-1059. https://doi.org/10.1016/j.ifacol.2024.09.134
- Demiray Kırmızı, S., Ceylan, Z., & Bulkan, S. (2024). Enhancing Inventory Management through Safety-Stock Strategies—A Case Study. Systems, 12, Article 260. https://doi.org/10.3390/systems12070260
- Fernandes, N. O., Djabi, S., Thürer, M., Ávila, P., Ferreira, L. P., & Carmo-Silva, S. (2025). The DDMRP Replenishment Model: An Assessment by Simulation. Mathematics, 13, Article 3483. https://doi.org/10.3390/math13213483
- Fleuren, T., Merzifonluoglu, Y., Sotirov, R., & Hendriks, M. (2025). Production-Inventory Planning in High-Tech Low-Volume Manufacturing Supply Chains. International Journal of Production Economics, 288, Article 109687. https://doi.org/10.1016/j.ijpe.2025.109687
- Gao, D., Liu, C., & Sun, X. (2025). Analysis of Bullwhip Effect and Inventory Cost in an Omnichannel Supply Chain. Journal of Theoretical and Applied Electronic Commerce Research, 20, Article 182. https://doi.org/10.3390/jtaer20030182
- Ghanem, M., Hamzeh, F., Seppänen, O., Shehab, L., & Zankoul, E. (2021). Pull Planning versus Push Planning: Investigating Impacts on Crew Performance from a Location-Based Perspective. Frontiers in Built Environment, 8, Article 23. https://doi.org/10.3389/fbuil.2022.980023
- Javadi, S. M., Sadjadi, S. J., Teimoury, E., & Makui, A. (2025). Material Requirements Planning with a Novel Lot Sizing Method and a New Algorithm for Production Scheduling. Scientific Reports, 15, Article No. 27637. https://doi.org/10.1038/s41598-025-13197-8
- Krajčovič, M., Gabajová, G., Gašo, M., & Schickerle, M. (2024). Parameter Setting for Strategic Buffers in Demand-Driven Material Resource Planning through Statistical Analysis and Optimisation of Buffer Levels. Applied Sciences, 14, Article 3012. https://doi.org/10.3390/app14073012
- Milewski, D. (2025). The Combined Decision Problem: “Pull” vs. “Push” and the Degree of Centralization of Warehousing in the Field of Physical Distribution with a Special Focus on the Polish Market. Applied Sciences, 15, Article 3970. https://doi.org/10.3390/app15073970