Inventory Management Systems in the Construction Trade

Citation: Elmurat Erkin Uulu, "Inventory Management Systems in the Construction Trade", Universal Library of Business and Economics, Volume 02, Issue 02.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper examines modern methods and information technologies for inventory management in the construction trade, aimed at optimizing working capital and ensuring uninterrupted supply to construction sites. The relevance of the study is determined by the fact that inventories of construction materials account for 60–65% of the total estimated cost of a project and maintain the Days Inventory Outstanding ratio at 50–60 days, which exerts significant pressure on contractors’ liquidity and increases the cost of capital servicing. The objective of the work is a systematic analysis of the methods and information technologies for inventory management in construction trade—from classical replenishment models (EOQ, JIT) to the buffer-based DDMRP approach and cloud-based WMS/IoT platforms. The novelty of the study lies in the combined comparative review of traditional and modern tools: RFID and BLE identification, GPS marking of oversized materials, offline/online mobile scanning, DDMRP buffers, ML “short-horizon” forecasting, and integration of CO2-footprint environmental metrics. A five-block architecture of an IMS is presented, and a practical “factory-to-site” case in Kyrgyzstan is described, demonstrating a 20–30% reduction in markup chains and a decrease in maintenance frequency at medical facilities. The main conclusions demonstrate that a modular platform with a continuous cycle—“identification – forecasting – replenishment – mobile warehouse – analytics – integration”—transforms seasonal and geographic uncertainty into a manageable asset: inventory accuracy increases to 95%, DDMRP buffers maintain a 99% service level, AI algorithms improve availability of 40% of SKUs without expanding storage footprint, and environmental metrics become part of financial reporting. This paper will be useful for executives and specialists in logistics, procurement, IT integration, and financial control within the construction industry.

Keywords: Inventory Management, Construction Trade, EOQ, JIT, DDMRP, WMS, IoT, RFID, Machine Learning, Mobile Scanning, Environmental Metrics.

https://doi.org/10.70315/uloap.ulbec.2025.0202008