Necessary condition analysis: New applications for market researchers

Abstract

Necessary condition analysis (NCA) is a recent methodological advancement that is quickly being adopted by researchers. Whereas most path modeling techniques (multiple regression, PLS-SEM, CB-SEM, etc.) assume an additive or sufficiency logic, NCA employs a necessity logic, where it examines an independent variable’s level of performance necessary to achieve a certain level in the dependent variable. As a result, NCA is designed to identify must have levels of performance for independent variables. While NCA can be used on its own, most researchers recommend employing NCA as a complementary analysis tool. In this article, we propose that NCA can be a useful complement to the Kano model, key driver analysis, and importance-performance analysis. This article examines how NCA can be used in conjunction with these research methods and puts forth a call to action for future research.