AI and Machine Learning for Supply Chain Management

in Special Issue   Posted on September 28, 2020 

Information for the Special Issue

Submission Deadline: Thu 03 Sep 2020
Journal Impact Factor : 2.507
Journal Name : Electronic Commerce Research
Journal Publisher:
Website for the Special Issue: https://www.springer.com/journal/10660/updates/17914778
Journal & Submission Website: https://www.springer.com/journal/10660

Special Issue Call for Papers:

Electronic Commerce Research is seeking submissions to a forthcoming Special Issue on AI and Machine Learning for Supply Chain Management.

The present market is constantly evolving and the demands from customers keep getting dynamic with time. This had led to the need for innovative technologies for the management of goods. Existing competition in the market has compelled the supply chain to operate faster and satisfy the demand criteria. A supply chain consists of suppliers, companies, and customers. Planning, acquiring of raw materials, manufacturing, delivering and returning of goods are the main processes in a supply chain. Supply chain management (SCM) is the concept of handling the product from its drafting stage to its shipment to the customers. It involves several stages such as product development, commercialization, manufacturing flow management, demand management, customer relationship management, and return management. The objectives of SCM should be a reduction of inventory to reduce cost, on-time delivery and improvement of sales. 
 
The main concerns of supply chain management are lack of progressive reports from relevant suppliers, risk management and sustainability. Since the market has developed along with the needs of customers, SCM should also develop in terms of technology. Conventional management technologies are still followed in the supply chain which is also one of the reasons for the failure of a supply chain. SCM has a large number of management stages varying from procurement to delivery. It is difficult to manage all the stages with accuracy and precision. With the help of artificial intelligence and machine learning, several intensive decisions can be made. Artificial intelligence (AI) is simply a machine that does work smartly and depends on success while Machine learning is a machine that has the ability to learn on its own and focuses on accuracy more than success. Such innovative techniques can help in analyzing the data obtained from various stages of SCM. Even the most precarious decision such as conflicts between inventory and production can be made with the available analyzed data. 
 
Artificial intelligence finds optimal solutions for every process and solves complex problems in management. By forecasting the demand, AI can help in increasing productivity and provides smart inventory management. Machine learning improves the quality management of products with assistance in physical inspection and tracking the supplier details. This further ensures the on-time delivery of the product. This special issue “AI and Machine Learning for Supply Chain Management” present us with a platform to discuss the latest advances in supply chain management.

The topics of interest are but not limited to:

  • A study on supply chain management and related theories
  • Risk assessment using artificial intelligence in supply chain management
  • Machine learning-based demand-driven supply chain management
  • Artificial intelligence for supplier selection and management
  • Smart logistics management using artificial intelligence
  • Development of machine learning-enabled sustainable supply chain management
  • The customer feedback system for improvement of service in SCM
  • Design of supply chain for smart customized services
  • Innovation in customer service relationship management using artificial intelligence
  • Significance of technology-enabled services in SCM
  • Product-based SCM vs. Service based SCM
  • Optimization techniques for supply chain management
  • Strategies for warehouse and inventory management in SCM
  • Conflict management for supply chain management

Timeline
Last Date for Manuscript Submission: 03 September 2020
Notification to Authors: 16 November 2020
Revised Manuscript Due: 25 January 2021
Decision Notification: 28 March 2021

Guest Editors
Ching-Hsien Hsu (Managing Guest Editor)
College of Information and Electrical Engineering
Department of Computer Science,
Asia University, Taiwan
Email: [email protected]

AmAmir H. Alavi
Department of Civil and Environmental Engineering,
Department of Bioengineering,
Swanson School of Engineering,
University of Pittsburgh, USA
Email: [email protected]

Mianxiong Dong  
Department of Sciences and Informatics
Muroran Institute of Technology
Muroran, Hokkaido, Japan
Email: [email protected]

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