Track 06_13 – Necessary Condition Analysis. Method and Applications
Necessary Condition Analysis is a novel and promising empirical research methodology that
can be applied in all disciplines. NCA understands cause-effect relations in terms of
“necessary but not sufficient”; this means 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. By adding a different logic and data analysis approach,
NCA adds both rigor and relevance to theory, data analysis, and publications.

The aim of this track is to bring together researchers who are already applying the method
or interested in using it. NCA is a user-friendly method that requires no advanced
statistical or methodological knowledge beforehand. However, since NCA is a
rather newmethodology, several questions remain. This track will provide the opportunity for
methodology focused discussions and exchange of experience. We will focus on the
foundations of the method, its application in different disciplines, and its advantages in
comparison to other methods (e.g., regression-based methods, QCA). Therewith, the track
will not only help to advance ongoing research projects but also serves as a multidisciplinary
forum to explore the latest research, applications, and developments surrounding the use of
NCA.

We encourage submissions of advanced research projects (full paper, competitive sessions)
as well as work in progress (extended abstract, paper and idea development sessions).
Papers are welcome from any field as long as they use NCA either as core method or a
complement to other methods.

For more information on NCA please visit the NCA website (www.erim.nl/nca) or read NCA’s
core paper (free access): Dul, J. (2016) Necessary Condition Analysis (NCA): Logic and
methodology of “necessary but not sufficient” causality, Organizational Research Methods,
19(1), 10-52.

Proponents:
Sven Hauff, Helmut Schmidt University;
Jan Dul, Rotterdam School of Management;
Florence Allard-Poesi, Université Paris-Est;
Nicole Richter, University of Southern Denmark