Aviation is a complex system, and the investigation and modelling of aviation accident causation can suffer from being artificially manipulated into non-complex models and methods. This book addresses this issue by developing a new approach to investigating aviation accident causation through information networks, which centralise communication and the flow of information as key indicators of a system's health and risk. The book's new model offers many potential developments and some key areas are studied in this research, maintaining firm focus on the overall health of a system.

Thomas G.C. Griffin, DHL Aviation, Kingdom of Bahrain. Mark S. Young, Brunel University, London, UK. Neville A. Stanton, University of Southampton, UK

1 Introduction 2 Modelling a Dynamic World 3 A Complex Approach to a Complex Scenario 4 Development of a Study 5 Extending the Potential of Information Networks: A Bayesian Approach 6 Can We Validate Networks Derived from Incident Data Through Simulation? A Pilot Study 7 Incidents versus Accidents: An Industrial Study 8 Conclusions