Calls for Papers (special): Information Resources Management Journal (IRMJ)


Special Issue On: Deep Learning Technology for the Supply chain Intelligence in E-Business

Submission Due Date
2/25/2022

Guest Editors
Dr. Carlos Enrique Marin, District University Francisco Jose de Caldas, Bogota, Colombia.
Dr. Dinesh Samuel, Oxford Brookes University, Oxford, United Kingdom.
Dr. Nallappan Gunasekaran, Shibaura Institute of Technology, Saitama, Japan

Introduction
A new and rapidly moving supply chain intelligence and experience have been widely sought after by consumers and manufacturers as key governors of their success and productivity. Intelligence is where IT systems can 'make decisions' about transactions to target human interference were appropriate. Through delivery notices, invoices and payments, thousands of trades and transactions pass daily between many buyers and suppliers from orders and confirmations in supply chain intelligence. It is essential to automatically monitor the accuracy of these data exchanges as they occur. Business supply chains produce a wide range of data and quantities. Recent COVID-19 lockdowns in markets in various parts of the globe have taken the supply chain of vital goods to the fore. Removing the lockout ensures production, inventories, raw material availability, transport, and consumer demand are tightly matched through supply chain intelligence. It could be accomplished by those firms that had already invested in digital channels. Supply Chain Analytics came to their aid and helped them fulfil their demands. Essential tasks such as procurement and organizational planning, purchasing, production, distribution and storage, logistics and sales are interlinked through a well-planned supply chain management system that can turn the supply chain's efficiency.

Objective
When technology and knowledge merge, companies can see a quicker step toward automation. Intelligent technology such as machine learning is now being integrated into transactions to predict risk, fraud and enforcement issues, Prompt detection of supplier differences, such as overcharges or late payments. Equipped with this knowledge, companies can review their buyer-supplier relationships regularly, renegotiate payment terms if appropriate, and perhaps even move to more secure and open trading partners in supply chain intelligence for E-business. The significant challenges for supply chain intelligence for E-Business is transaction transparency, Unpredictable cost variation for transportation and Secured network channel. In future, incorporation of advanced Artificial Intelligence based technology could be used to predict the price inflations, Data Security and Transparency issues in supply chain intelligence for E-business. Hence, supply chain intelligence for E-Business can perform Analytical, prescriptive, predictive and cognitive analytics to solve challenges, minimize risks, forecast potential outcomes based on internal and external data, and respond to consumer demands promptly. This special issue invites new algorithm, models and data structures to advance supply chain Intelligence for E-Business.

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Deep Learning Technology for the Supply Chain Intelligence in E-Business on or before February 25th, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Dr. Carlos Enrique Marin
Dr. Dinesh Samuel
Dr. Nallappan Gunasekaran
Guest Editors
Information Resources Management Journal (IRMJ)
cemontenegrom@udistrital.edu.co; rsamuel@brookes.ac.uk; nallappan.gunasekaran.b1@shibaura-it.ac.jp