Omni-Channel Order Management in U.S. Retail: Architectural Evolution, Operational Sustainability, and Customer Experience Optimization

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Authors: USA Independent Researcher, Vinay Babu Gurram
Cited by: 0

Abstract

The U.S. retailing industry has undergone a radical transformation with online shopping being integrated into the physical storefront operations that making the omni-channel Order Management Systems essential in the survival race. This article will trace the development of OMS systems since they have evolved to be large, ERP-based systems to decentralized, cloud-based systems that rely on microservices, event-driven protocols, and intelligent algorithms. Some of the major issues addressed include the division of inventory information, inefficient order routing decisions, system overload during peak shopping times, and the increasing necessity to incorporate environmental responsibility into daily practice. Combining the latest technology with the focus on green, the Sustainable Omni-Channel Order Management Framework has five interrelated levels: Customer Interaction, Order Orchestration, Inventory Intelligence, Fulfillment Optimization, and Analytics and Feedback. Implementing this architecture entails revising technical architecture, coping with data quality challenges, developing new workforce capabilities, different ways of handling relationships with suppliers, and how these transformations redefine competition. The framework demonstrates how next-generation OMS platforms can enhance operational outcomes, reduce environmental harm by smart routing and enhanced prediction, and provide happier customers in complex retail networks. The architectural plans and sustainability concepts presented here provide retailers with a starting point in a trade-off between profit targets and environmental responsibilities in addressing the expectations of the shoppers to provide seamless and flexible delivery choices.

Fields of Study & Subjects

Digital Innovation in Industries Supply Chain and Inventory Management Consumer Retail Behavior Studies

Publication details

Journal / source
The American Journal of Engineering And Technology
Volume
08
Issue
01
Pages
168–177
Publication date
1 January 2026
Language
EN