HSU-Doktorandenweiterbildung 2017: Necessary Condition Analysis (NCA) – A novel view on causality and on empirical data analysis

Institution: Erasmus University, Rotterdam/Helmut-Schmidt-University Hamburg

Jan Dul, Rotterdam School of Management, Erasmus University
Sven Hauff, Helmut Schmidt University

Date: 12.10.2017 – 10 a.m. to 15 p.m.

Place: Hamburg Business School, Hamburg University

Room: tba

Language of instruction: English

Registration: You can register for the course until 05.10.17 by email to Sven Hauff (hauff@hsu-hh.de)


What is NCA?
NCA is a novel, user-friendly methodological approach, recently published in Organizational Research Methods that understands cause-effect relations as “necessary but not sufficient” (not as additive logic used in regression). A necessary condition implies that without the right level of the condition a certain effect cannot occur. This is independent of other causes, thus the necessary condition can be a bottleneck, critical factor, constraint, disqualifier, etc. In practice, the right level of necessary condition must be put and kept in place to avoid guaranteed failure. Other causes cannot compensate for this factor. Thus NCA provides a novel view on causality and on empirical data analysis.

Whom is NCA for?
NCA is applicable to any discipline, and can provide strong results even when other analyses such as regression analysis show no or weak effects. By adding a different logic and data analysis approach, NCA adds both rigor and relevance to your theory, data analysis, and publications. NCA does not require advanced statistical or methodological knowledge beforehand. It can be used in both quantitative research as well as in qualitative research. You can become one of the first users of NCA in your field, which makes your publication(s) extra attractive.

What will be discussed in the seminar?
The seminar consists of two parts:

  1. In the first part (1-2 hours) we will discuss the method and its applications in different management fields. We will explain the differences between necessity logic and traditional additive logic and describe the relevance of necessary conditions for theory and practice.
  2. Immediately afterwards, in the second part (1-3 hours depending on the number of participants) we will discuss the method in more detail. In particular we will focus on the participants’ research areas and datasets. We will also demonstrate how to use the NCA software to identify/test potential necessary conditions in empirical data sets. Participants who are interested in a demonstration of the method on their dataset can bring their dataset on a USB drive (e.g., excel.csv file) or perform an NCA analysis on their own computer.

More information:

  • erim.nl/nca
  • Dul, J. (2016) Necessary Condition Analysis (NCA): Logic and methodology of “necessary but not sufficient” causality, Organizational Research Methods, 19(1), 10-52.