Necessary Condition Analysis (NCA): Principles and Application

Necessary Condition Analysis (NCA) is a new research method for data analysis. Its unique feature is the use of 'necessary but not sufficient' logic to detect the critical 'must have' factors in datasets, rather than average effects. This book introduces this methodology at an advanced level, taking readers through the theoretical underpinning and its varied application in empirical research across the social sciences and beyond. Aimed at PhD students and researchers, data analysts, practitioners, and others, the book helps readers develop a deeper understanding of the NCA approach and apply it effectively and with high-quality standards. It brings together the fundamentals of NCA and integrates the most recent methodological advancements and tools. No prior knowledge of NCA is required but readers would benefit from familiarity with the basics of research methodology.Key features: Addresses a new data analysis method Provides a deeper understanding of the method Includes hands on practical recommendations for application

About the Author

Jan Dul is the founder of NCA. He is professor of Technology and Human Factors at the Rotterdam School of Management, Erasmus University, Netherlands. His background spans the technical, medical, and social sciences. His more than 200 publications include articles in leading journals and books translated into multiple languages. He is a frequent speaker at academic and professional events worldwide and has shared his expertise with over 50 companies. He has received several awards and recognitions in business and management and in human factors and ergonomics.