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.

List of Figures List of Tables Preface Acknowledgements 1 Introduction I Principles 2 Causality 3 Theory 4 Mathematics 5 Statistics 6 Credibility II Application 7 Hypothesis 8 Data 9 Data analysis 10 Reporting 11 Multimethod studies 12 NCA in practice Summary and personal reflection III Additional materials Appendix A Nomenclature and glossary B Software C Publications D Affine transformations E Simulations for TPR and TNR F Necessity and the traditional experiment G Correlation by necessity H Demonstration NCA with PLS-SEM I Bottleneck distance table Bibliography

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.

“Jan Dul has written a wonderful book that provides researchers with a rigorous and practical framework for explicitly theorizing the necessary conditions that must be present to make an outcome possible, and that their absence guarantees the absence of the outcome. By systematically integrating theory development, research design, and data analysis, the book shows how to identify “must-have” conditions. Importantly, this book equips researchers with concrete tools to generate more precise, impactful contributions that advance cumulative knowledge.”
- Herman Aguinis, Avram Tucker Distinguished Scholar and Professor of Management, The George Washington University, USA