Supply Chain Management and Corporate Governance: Artificial Intelligence, Game Theory and Robust Optimisation is the first innovative, comprehensive analysis and analytical robust optimisation modelling of the relationships between corporate governance principles and supply chain management for risk management and decision-making under uncertainty in supply chain operations. To avoid corporate failures and crises caused by agency problems and other external factors, effective corporate governance mechanisms are essential for efficient supply chain management. This book develops a new collaborative robust supply chain management and corporate governance (RSCMCG) model and framework that combines good corporate governance practices for risk management strategies and decision-making under uncertainty. This model is developed as a principal-agent game theory model, and it is digitalised and computed by Excel algorithms and spreadsheets as an artificial intelligence and machine-learning algorithm. The implementation of the RSCMCG model provides optimal supply chain solutions, corporate governance principles and risk management strategies for supporting the company to achieve long-term benefits in firm value and maximising shareholders' interests and corporate performance while maintaining robustness in an uncertain environment. This book shows the latest state of knowledge on the topic and will be of interest to researchers, academics, practitioners, policymakers and advanced students in the areas of corporate governance, supply chain management, finance, strategy and risk management.