CLOSED Call for Papers: Special Issue on Intelligent Big Data Analytics and IoT-Powered Smart Supply Chain Management for Sustainable Production

Supply chain management (SCM) plays a vital role in every industrial sector. This directly influences the success of the business and improves overall customer satisfaction. However, due to the pandemic and changing business markets, the prevailing uncertainty has created international trade disputes, causing overall supply chain disruption. If left unaddressed, these disruptions will lead to catastrophic consequences affecting the enterprises’ ability to deliver products and drive revenue, causing the deterioration of long-lasting brands. Furthermore, the process of SCM itself is a complex task, and it requires increased coordination among the various supply chain actors (people and processes). Thus, the SCM process is crucial to ensure a strong reputation, increased return of investment, and efficiency measures. In the view of smart SCM, every entity associated with the system is connected. It helps to predict the unremarkable events that make a greater difference in the complex ecosystem—ultimately paving the way for smart and sustainable production.

Intelligent big data analytics and IoT are the two major disruptive techniques that significantly accelerate smart SCM processes. Intelligent big data analytics is basically used to extract the hidden facts that are not known previously from a large quantity of data. On the other hand, the IoT devices connected to the Internet collect a huge amount of data. The prime objective of using these techniques in the smart value chain is to effectively deal with the pool of business data from the connected IoT devices and harness its potential using intelligent big data analytics to learn its patterns and trends. If these technologies are used appropriately to derive insights from the huge amount of IoT data, they can create niche opportunities to improve customer value. The patterns and trends extracted are analyzed using machine learning algorithms and aids in making predictive analytics and data-based learning of the supply chain risks. This provides increased visibility to the entire supply chain process. Besides, the property of IoT connects the people, processes, and data across the networked ecosystem, where it helps to collect, measure, and exchange the live supply chain data–thus offering improved access to the real-time business data and transforming the conventional supply chain structure into an innovative, transparent, intelligent, and hyperconnected process. Some of the significant benefits of implementing big data analytics and IoT in the smart supply chain include an efficient forecast of the movement and arrival of products, real-time location tracking, improved contingency planning, warehouse management, improved resource management, automation, and sustainability measures.

This special issue aims to bring out the effective ways in which intelligent big data analytics and IoT technology will transform the smart supply chain process for sustainable production. Research works focusing on effective implementation of these techniques for faster decision-making, proactively mitigating delayed risks, and efficiency are most welcomed. Topics include:

  • Assessing the impacts of sustainable operations on SCM using intelligent big data analytics and IoT
  • Real-time business intelligence with big data analytics and IoT for sustainable production
  • Innovative intelligent big data analytics for smart and sustainable SCM
  • Business process optimization and SCM using intelligent big data analytics and IoT
  • Smart transformation of production and logistics management using intelligent big data analytics and IoT
  • Intelligent big data analytics for enhanced operational responsiveness and system maintenance for sustainable production
  • Resilient SCM and risk assessment using intelligent big data analytics and IoT
  • Challenges and opportunities of using intelligent big data analytics and IoT for smart and sustainable production and SCM
  • Intelligent big data analytics for demand forecasting and automatic defect detection
  • Intelligent predictive analytics for route optimization in sustainable SCM and production

Important Dates

Submission Deadline: 26 April 2022
Authors Notification: 11 June 2022
Revised Papers Due: 13 September 2022
Final Notification: 14 October 2022

Submission Guidelines

For author information and guidelines on submission criteria, please visit the TBD Author Information page. Please submit papers through the ScholarOne system, and be sure to select the special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal.


Please contact the lead guest editor at

Guest Editors

  • Tu Nguyen, Kennesaw State University, USA (lead guest editor)
  • Vincenzo Piuri, University of Milan, Italy
  • Joel Rodrigues, Federal University of Piauí (UFPI), Teresina – PI, Brazil
  • B. B. Gupta, National Institute of Technology, Kurukshetra, India
  • Lianyong Qi, Qufu Normal University, China
  • Shahid Mumtaz, Instituto de Telecomunicações, Portugal
  • Warren Huang-Chen Lee, National Chung Cheng University, Taiwan
Special Issue on Intelligent Big Data Analytics and IoT-Powered Smart Supply Chain Management for Sustainable Production
26 April 2022