Production
https://prod.org.br/article/doi/10.14488/1980-5411.20250102
Production
Systematic Review

The evolution of omnichannel fulfillment: from efficiency to AI-driven responsiveness

Nicollas Luiz Schweitzer de Souza; Bruna Rigon de Oliveira; Julia Bremen; Enzo Morosini Frazzon

http://dx.doi.org/10.14488/1980-5411.20250102 Production, vol.36, e20250102, 2026
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Abstract

Paper aims: This research maps the evolution of intelligent omnichannel fulfillment models via a Systematic Literature Review (SLR), addressing the gap in literature which lacks a comprehensive synthesis of these models and their critical trade-offs.

Originality: The study provides an evolutionary framework that organizes the field's progression. Its primary contribution is charting this trajectory as a response to the evolving trade-off between cost efficiency and operational responsiveness.

Research method: A PRISMA-guided Sistematic Literature Review was conducted using Scopus and Web of Science databases, covering publications from database’s inception to November 2025. An initial 1,975 papers were screened, resulting in a final in-depth qualitative analysis of 33 core articles.

Main findings: The analysis reveals the evolutionary trajectory for fulfillment models. The field progresses from (1) operational efficiency in warehousing and transportation via heuristics to (2) inventory positioning strategies under uncertainty using stochastic models, and culminating in (3) Artificial Intelligence (AI)-driven approaches focused on supply chain resilience and lead-time compression. This progression is shown to be a direct response to the limitations of each preceding paradigm, proposing approaches that prioritize both scalability and responsiveness.

Implications for theory and practice: For researchers, this study offers a consolidated state-of-the-art framework and a structured research agenda focused on AI-based solutions, operational realism, and new decentralized decision structures. For practitioners, it serves as a guide to select appropriate models based on operational complexity and strategic goals, identifying AI as the key enabler for the next generation of adaptive fulfillment systems.

Keywords

Fulfillment, Omnichannel, Logistic, Ecommerce, Artificial Intelligence

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Submitted date:
10/30/2025

Accepted date:
04/16/2026

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