Calls for Papers (special): International Journal of Information Systems and Supply Chain Management (IJISSCM)


Special Issue On: Intelligent Decision Support Systems for Supply Chain Management System

Submission Due Date
10/15/2020

Guest Editors
Prof. Srikanta Patnaik
Department of Computer Science and Engineering, SOA University, India
srikantapatnaik@soauniversity.ac.in

Prof. Jian Wang
Department of Computer Science, School of Information Engineering and Automation, Kunming University of Science and Technology
jianwang@kmust.edu.cn

Prof. Wen Long
Hunan Vocational College of Modern Logistics
806135262@qq.com

Engineer/Manager
Bin Hu
China Mobile Communications Corporation, Xiangtan Branch, China
13973280302@139.com

Introduction
As the business environment of organizations is changing constantly, it is evident that intelligent and strategic Decision Support Systems (DSS) are required for successful and tactical management of organizations and sustaining competitive advantages. Some of the common threats that are imposed on current managers and decision makers include availability of a number of choices regarding demand conflicts, product order priorities, exploring new risks and opportunities. The adoption of intelligent DSS frameworks and alignment of artificial intelligence as well as machine learning techniques to the system are improving the overall organizational performance. The novel intelligent DSS frameworks are being considered to capable of not only managing information and material flow but also understanding and fulfilling customers’ requirements to attain their satisfaction. Moreover, the advent of data analytics has made decision making easier, faster and more accurate. Integration of various data analytics techniques into Decision Support Systems enables it to further explore and analyze real-time data and generate insights to assist managers in making significant decisions regarding various contexts. Supply Chain Management is one of the significant yet crucial areas of an organization which contributes to the customers’ satisfaction. Thus recently, it has received a lot of attentions from researchers to overcome limitations strategically.

Supply Chain Management systems can be both product and service oriented. The interdependency in relationships among multiple organizations as well as multiple stakeholders makes management of supply chain networks more complex. Again, the existence of dynamicity among the interaction of different components of the supply chain network complicates it further. Some of the complex contributors of the supply chain network involve collaboration among the components and co-operation along the distribution chains, design of several business processes, management of lifecycle of several operations, various KPIs, operational and strategic drivers and finally the service level agreements that are responsible for successful management of supply chains. Thus, managing these components over a dynamically changing environment leads to successful completion of organizational processes. The challenge of addressing the complexity existing between these dynamic components can be managed by emphasizing on real-time data and information generated by the supply chain network as the product/service progress through the network. However, the enterprise based supply chain networks generates huge amount of data from sensor-based devices, computers and smart phones. This huge amount of data is widely termed as Big Data which creates opportunities to derive new insights from these data that can add value to critical decisions. Monitoring and consistent analysis of this timely and effective information about current status of the components is vital for making decisions regarding further course of action in the supply chain network. Also, other significant metrics can be defined to measure the performance of individual components as well as overall network.

Objective
This special issue will seek novel methodologies and concepts related to the development and adoption of intelligent DSS for managing the existing complex supplier-consumer issues beyond traditional approaches. It further attempts to motivate researchers to highlight their efforts to develop new approaches of DSS that integrates machine learning and artificial intelligence based techniques to handle real-time dynamic data. It also tries to bridge the gap between empirically derived strategies and relevant methods and the ones employed in real-time environment.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited to) the following:

- Planning of distributed supply chain networks
- Supply chain vendor selection
- DSS for production planning and control
- Development of strategies and tools for associated value chains
- Empirical models for AI-based DSS in SCM
- Functional constructs in SCM
- Formulating logistic functions integrating AI
- Machine learning based scheduling techniques
- Knowledge based Decision Support Systems
- Intelligent decision-making workflows
- Multivariate techniques for Decision making in SCM and Logistics
- Application of intelligent DSS to SCM based problems
- Understanding System dynamics in SCM
- Risk management structures for SCM
- Multi criteria Decision Making in SCM and Logistics
- Partnership formation supply chain networks
- Multi-Objective Decision Making
- Evaluation of decision-making scenarios in SCM
- Cross functional supply chain networks
- Effective information system based frameworks for SCM
- Sustainable DSS for SCM
- Network resilience in supply chain networks
- Quality management through DSS in SCM
- Integration and coordination in supply chain networks
- Inbound and Outbound Logistics

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Intelligent Decision Support Systems for Supply Chain Management System on or before March 15, 2020. 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:
Srikanta Patnaik
Guest Editor
International Journal of Information Systems and Supply Chain Management (IJISSCM)
E-mail: srikantapatnaik@soa.ac.in