Re-Imagining Supply Chain Management

Supply chain management is a substantially complex area for many businesses due to its diverse set of actions, agents, decisions, risks, and uncertainties. Consequently, supply chains often break up in disarray due to their structural complexity coupled with risks and uncertainties in the absence of clear objectives. I--k Biçer addresses these issues by uncovering the fundamental trade-offs of supply chain management, their economic causes, and strategic implications. He offers a novel framework of supply chain management based on its role in economic systems. The framework shows four effective supply chain strategies according to business models and organizational sensitivity to operational trade-offs. Furthermore, it offers a detailed account of the digital transformation of supply chains, elaborating on crucial aspects of the design and implementation of digitalization. This is an indispensable source for supply chain professionals, consultants, economists, and policymakers with a keen interest in supply chain management.

I--k Biçer is an Associate Professor of Operations Management and Information Systems in the Schulich School of Business at York University in Toronto, Canada. He is also area director of the Ph.D. program and director of an executive certificate program in supply chain management. He teaches graduate-level courses about digital transformation, predictive modeling, and prescriptive analytics in the Tech MBA, MBAN, and MMAI programs at Schulich School of Business, as well as conducting research on uncertainty modelling and convolutional optimization techniques and their applications to supply chains. I--k has worked on several digital transformation projects with various firms, some of which feature in this book.  The author of 15 top research papers, his work has appeared in Harvard Business Review, Journal of Operations Management, and Production and Operations Management.  He has also published a graduate-level textbook, Supply Chain Analytics: Uncertainty Modeling Approach (2023).