Schematic Review on the Application of Blockchain and IoT Integration with Sentiment Analysis in Supply Chain Management

This schematic review presents a comprehensive comparative analysis of the integration of blockchain technology, sentiment analysis, and IoT devices within the domain of supply chain management. By exploring the intersection of these cutting-edge paradigms, the study investigates their collective impact on augmenting transparency, traceability, and operational efficiency across a variety of supply chain ecosystems. Synthesizing insights from diverse industries, the review systematically assesses the implementation, advantages, and challenges associated with lever-aging blockchain for secure data exchange, sentiment analysis for real-time insights, and IoT devices for data acquisition to bolster food traceability systems within dynamic supply chain settings. Additionally, the review examines the adaptability, scalability, and interpretability of these technologies, providing valuable insights into their synergistic potential and limitations within the intricate landscape of supply chain operations. With a focus on the significance of data integrity, trust mechanisms, and sentiment-driven decision-making, this abstract serves as an indispensable guide for practitioners, researchers, and stakeholders navigating the strategic integration of blockchain, sentiment analysis, and IoT devices in contemporary supply chain frameworks.

Authors

Publication Details

Published
2025-02-07
DOI
https://doi.org/10.1109/etis64005.2025.10961615
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Schematic Review on the Application of Blockchain and IoT Integration with Sentiment Analysis in Supply Chain Management

A John, G. Sreenu, Akash Ajith, P T Althaf et al.
Blockchain Technology Applications and Security
article

Schematic Review on the Application of Blockchain and IoT Integration with Sentiment Analysis in Supply Chain Management

A John, G. Sreenu, Akash Ajith, P T Althaf, Kevin Joby
article en

Abstract

This schematic review presents a comprehensive comparative analysis of the integration of blockchain technology, sentiment analysis, and IoT devices within the domain of supply chain management. By exploring the intersection of these cutting-edge paradigms, the study investigates their collective impact on augmenting transparency, traceability, and operational efficiency across a variety of supply chain ecosystems. Synthesizing insights from diverse industries, the review systematically assesses the implementation, advantages, and challenges associated with lever-aging blockchain for secure data exchange, sentiment analysis for real-time insights, and IoT devices for data acquisition to bolster food traceability systems within dynamic supply chain settings. Additionally, the review examines the adaptability, scalability, and interpretability of these technologies, providing valuable insights into their synergistic potential and limitations within the intricate landscape of supply chain operations. With a focus on the significance of data integrity, trust mechanisms, and sentiment-driven decision-making, this abstract serves as an indispensable guide for practitioners, researchers, and stakeholders navigating the strategic integration of blockchain, sentiment analysis, and IoT devices in contemporary supply chain frameworks.

Openalex Percentile: Top 90%
Blockchain Technology Applications and Security
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.