Inventory Management System

This research addresses the Inventory Management Systems (IMS) play a crucial role in maintaining optimal stock levels, reducing operational costs, and enhancing customer satisfaction in both retail and industrial environments. This paper presents the design, development, and evaluation of a custom-built Inventory Management System aimed at improving stock tracking and reducing manual errors. The system leverages database technology and a user-friendly interface to facilitate real-time monitoring and reporting. The research demonstrates significant improvements in inventory accuracy and operational efficiency following the implementation of the system. The In today’s fast-paced and competitive business environment, effective inventory management is essential for ensuring operational efficiency, reducing costs, and meeting customer demand. Inventory Management Systems (IMS) have evolved significantly from traditional manual tracking methods to sophisticated, technology-driven platforms that offer real-time visibility, automation, and data analytics capabilities. This paper explores the fundamental concepts, components, and strategies involved in modern inventory management. It discusses various inventory control methods, such as Just-In-Time (JIT), Economic Order Quantity (EOQ), and ABC analysis, highlighting how these techniques help in maintaining optimal stock levels and preventing excess or shortage. The study also examines the integration of advanced technologies like cloud computing, Internet of Things (IoT), artificial intelligence (AI), and blockchain in inventory systems, which have transformed how businesses manage supply chains, forecast demand, and respond to market fluctuations. Furthermore, the paper analyzes the benefits of implementing an IMS—including improved accuracy, cost savings, and enhanced customer satisfaction—while also addressing common challenges such as system integration, data reliability, and cost of implementation. Through case studies and current trends, the research provides insights into how organizations can adopt innovative inventory solutions to stay agile, scalable, and competitive in an increasingly digital economy. This comprehensive exploration serves as a valuable resource for businesses, researchers, and students aiming to understand and improve inventory management practices in various industries.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-18
DOI
https://doi.org/10.5281/zenodo.17971715
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Inventory Management System

Zenodo (CERN European Organization for Nuclear Research)
Forecasting Techniques and Applications
article

Inventory Management System

article en

Abstract

This research addresses the Inventory Management Systems (IMS) play a crucial role in maintaining optimal stock levels, reducing operational costs, and enhancing customer satisfaction in both retail and industrial environments. This paper presents the design, development, and evaluation of a custom-built Inventory Management System aimed at improving stock tracking and reducing manual errors. The system leverages database technology and a user-friendly interface to facilitate real-time monitoring and reporting. The research demonstrates significant improvements in inventory accuracy and operational efficiency following the implementation of the system. The In today’s fast-paced and competitive business environment, effective inventory management is essential for ensuring operational efficiency, reducing costs, and meeting customer demand. Inventory Management Systems (IMS) have evolved significantly from traditional manual tracking methods to sophisticated, technology-driven platforms that offer real-time visibility, automation, and data analytics capabilities. This paper explores the fundamental concepts, components, and strategies involved in modern inventory management. It discusses various inventory control methods, such as Just-In-Time (JIT), Economic Order Quantity (EOQ), and ABC analysis, highlighting how these techniques help in maintaining optimal stock levels and preventing excess or shortage. The study also examines the integration of advanced technologies like cloud computing, Internet of Things (IoT), artificial intelligence (AI), and blockchain in inventory systems, which have transformed how businesses manage supply chains, forecast demand, and respond to market fluctuations. Furthermore, the paper analyzes the benefits of implementing an IMS—including improved accuracy, cost savings, and enhanced customer satisfaction—while also addressing common challenges such as system integration, data reliability, and cost of implementation. Through case studies and current trends, the research provides insights into how organizations can adopt innovative inventory solutions to stay agile, scalable, and competitive in an increasingly digital economy. This comprehensive exploration serves as a valuable resource for businesses, researchers, and students aiming to understand and improve inventory management practices in various industries.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Forecasting Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Inventory Management System · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS