A new book edited by Professor Hassan Qudrat-Ullah provides research results and shares experiences in the area of supply chain management in a post-pandemic world.
Qudrat-Ullah, who teaches in the Faculty of Liberal Arts & Professional Studies’ School of Administrative Studies, researches dynamic decision making, system dynamics modelling, computer-simulated interactive learning environments, and energy planning models.
The book, Understanding the Dynamics of New Normal for Supply Chains – Post COVID Opportunities and Challenges, published by Springer, explores the “new normal” of the business supply chain. The didactic approach informs global enterprises on how to deal with the most significant issues in the current supply chain management.
Through a series of informative essays, the book provides an in-depth analysis of post-COVID opportunities and challenges. The book acts as an initiative for readers to understand the risks, opportunities and concerns resulting from the pandemic situation and is a key driver for business management among industry professionals and enterprises.
Readers will learn new insights and procedures to better manage multitier supply chains, predictability, and estimation of binding capacity. Understanding the Dynamics of New Normal for Supply Chains – Post COVID Opportunities and Challenges details modelling and technology-based customer demand and response management solutions.
New techniques, methods and perspectives dealing with the estimation, acceleration or deceleration, and flexibility of logistics capacity are particularly emphasized throughout the manuscript. Real-world cases dealing with various aspects of the new normal for supply chains are analyzed.
The book is useful for industry professionals and enterprise firms in business management to effectively understand risks, opportunities and the pandemic situation.
Qudrat-Ullah is a professor of decision sciences at York University. Understanding the Dynamics of New Normal for Supply Chains – Post COVID Opportunities and Challenges is part of the Springer Complexity Series.
Originally published in YFile.