Conducting necessary condition analysis: for business and management students

Table of Contents Chapter 1: Introduction Chapter 2: Philosophical Assumptions and Logic of NCA Chapter 3: Basic Components of NCA Chapter 4: Data Analysis with NCA Chapter 5: NCA Examples Chapter 6: Strengths and Weaknesses Glossary References Appendix 1: From Research Question to Hypotheses for NCA Appendix 2: Installing R, RStudio, NCA R and Importing Your Dataset Appendix 3: Writing Up Your NCA Study

Part of SAGE's Mastering Business Research Methods series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support students by providing in-depth and practical guidance on using a chosen method of data collection or analysis. Necessary Condition Analysis (NCA) is an emerging method of data analysis, based on the idea that research factors can be necessary for an outcome: if the condition is not there, then the result will not occur. These necessary conditions are everywhere, and NCA is an intuitive and straightforward means of finding and testing data, either as a standalone tool or as a complement to other research methods. This book is an invaluable guide to using NCA effectively in business and management dissertations, and offers practical guidance and insight into how to successfully transcribe and analyse data using the NCA approach in research projects. Jan Dul is Professor of Technology and Human Factors at Rotterdam School of Management, Erasmus University, The Netherlands.