Safety Causation Analysis in Sociotechnical Systems: Advanced Models and Techniques: (541 Studies in Systems, Decision and Control)

This book provides a comprehensive view on theories, models, and techniques used to investigate and analyze incidents and safety causalities occurring in sociotechnical systems. Consisted of intricately interconnected components, sociotechnical systems are always prone to incidents. These incidents can ensue with adverse effects on employees and the public, the environment, and company's properties and reputation. Sometimes, a single incident has the potential to terminate the operation of a business forever. As incidents are multi-factorial and not easy to comprehend, they should be investigated systematically in a structured way so as to find their root causes and prevent them from recurring. Consequently, there have been developed many theories, models, and techniques aimed at accomplishing this goal. However, each approach has its own upsides and downsides, and there is no universal one applicable to all cases. Therefore, researchers and practitioners may sometimes find it difficult to select the most appropriate approach for the given case. After introducing theories, models, and techniques pertaining to incident investigation and safety causalities modeling, this book explains each one in details and discusses their pros and cons. The book aims to provide the audience with a step-by-step guidance for performing incident investigation and analysis. At the end of each chapter an example is analyzed by the introduced tool. Finally, the book offers criteria based on which an incident analysis technique can be selected.

Table of Contents:
An overview on accident investigation and analysis in sociotechnical systems.- Accident investigation process.- Data gathering tools and techniques.- Simple sequential linear accident models/theories.- Complex linear models.- Simple and Complex Linear causation techniques.- Systemic techniques.- Introduction of system thinking and sociotechnical systems.- Systems thinking methods (Complex non-linear models).- Accident Indices.- Agent-Based Modelling (ABM).- System Dynamics.- Application of Machine learning algorithms in accident analysis.- Application of Data-driven algorithms in accident analysis.- System Experts.- Discussion and Conclusion.

About the Author :
Esmaeil Zarei joined as Associate Professor of Safety Science the Embry-Riddle Aeronautical University (ERAU) in Oct 2022. Before that, he was with the Center for Risk, Integrity and Safety Engineering (C-RISE) at the Memorial University of Newfoundland, Canada (2020–23). He worked for over two years as Faculty Instructor, 2012–14, and three and half years as Assistant Professor, 2017–20, in the Department of Occupational Health and Safety Engineering in Iran. Prior to joining the faculty, he had also worked as Safety and Risk Engineer for three years at the Iranian Petroleum Health Organization. During these periods, he held different positions like Founder and Director of Safety, Occupational Health Labs and Student Research Center, and Executive Manager in the Industry Innovations & Partnerships Office. He also taught over 1000 hours of continuous training in Safety and Risk Engineering subjects in various industries like oil and gas, steel manufacturing, and mining. Esmaeil is deeply passionate about creating impact through innovative science and engineering, focusing on Safety, Risk, Resilience Engineering, and Human Factors/Reliability. He conducts primary research in these areas, particularly in emerging sectors like the Hydrogen Economy and critical industries such as Aviation and Process Industries. At the Robertson Safety Institute (RSI) at ERAU, he generates fundamental knowledge applied to diverse sociotechnical systems. With experience spanning four universities in three countries since 2012, Esmaeil collaborates actively with industry partners and leading academic institutions worldwide. He has (co)supervised over 20 Master's and Ph.D. Theses and serves on Editorial Boards  for reputable journals at Elsevier. His contributions rank him among the top 2% of scientists by Stanford University for three consecutive years since 2021.