Call for book chapter proposal
Editors:
Iman Rahimi, Young Researchers & Elite Club, Iran (email:iman83@gmail.com)
Amir H. Gandomi, Professor of Data Science, University of Technology Sydney, Australia (email:gandomi@uts.edu.au)
Simon Fong, University of Macau, Macau (email: ccfong@um.edu.mo )
M. Ali Ülkü, Professor of Supply Chain Analytics, Dalhousie University, Canada (email: ulku@dal.ca)

Project summary:
The study of big data is continuously evolved and expanded, and the main attributes of big data are now expanded into “5V” concept consisting of Volume, Velocity, Variety, Veracity, and Value. As Big Data has undergone a transition from being an emerging topic to a growing research area, it has become necessary to classify the different types of research and examine the general trends of this research area. Our continuous efforts to create more sophisticated technology to collect data at different stages of supply chain have resulted in the new era of supply chain analytics. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery. Using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. The concurrence of events such as growth in adoption of supply chain technologies, data inundation and a shift in management focus from heuristics to data-driven decision making have collectively led to the rise of big data era. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. Using these techniques, we can overcome the widespread obstacles to making the most of Big Data in the supply chain -- and increase cost efficiencies from the data we are already generating. This should allow the potential research areas for future investigation to be identified. As a valuable asset for decision-making, Big Data Analytics (BDA) can play a pivotal role in transforming and improving the functions of supply chain.
In this book, we will discuss the results of a recent large-scale achievement on BDA topics among supply chain management (SCM) professionals. In other words, this book intends to show a diversity of supply chain management issues that may benefit from BDA, both in theory and practice.

A non-exhaustive list of topics we invite to be considered for inclusion in this book are as follows:
• Optimization techniques for supply chain data analytics
• Supply chain analytics application
• Strategic sourcing
• Supply chain network design
• Product design and development
• Demand planning
• Procurement
• Production
• Inventory
• Logistics and distribution
• Supply chain agility and sustainability
• Supply chain analytics technology and implementation
• Internet of thing with application for disaster response
• Role of operations management and big data
• Production management
• Operations management
• Risk management
• Computing and information technologies
• Information management
• Future application of big data Analytic in supply chain
• Finance
• Healthcare
• Manufacturing
• Sustainability
• Managerial implications

Schedule

Chapter proposals  November 15, 2019
Decisions from editors  Nov 30, 2019
Full submission of chapters  Jan 31, 2020
Feedback of reviews  Mar 31, 2020
Revised chapter submission  Apr 28, 2020
Final acceptance notifications  May 30, 2020


Please submit your proposal here: https://cutt.ly/foM0MX