The relationship between ownership structure and firm performance has been studied extensively in corporate finance and corporate governance literature. Nevertheless, the mediation (path) analysis to examine the issue can be adopted as a new approach to explain why and how ownership structure is related to firm performance and vice versa. This approach calls for full recognition of the roles of agency costs and corporate risk-taking as essential mediating variables in the bi-directional and mediated relationship between ownership structure and firm performance.

Based on the agency theory, corporate risk management theory and accounting for the dynamic endogeneity in the ownership–performance relationship, this book develops two-mediator mediation models, including recursive and non-recursive mediation models, to investigate the ownership structure–firm performance relationship. It is demonstrated that agency costs and corporate risk-taking are the ‘missing links’ in the ownership structure–firm performance relationship. Hence, this book brings into attention the mediation and dynamic approach to this issue and enhances the knowledge of the mechanisms for improving firm’s financial performance.

This book will be of interest to corporate finance, management and economics researchers and policy makers. Post-graduate research students in corporate governance and corporate finance will also find this book beneficial to the application of econometrics into multi-dimensional and complex issues of the firm, including ownership structure, agency problems, corporate risk management and financial performance.


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.