CEF.UP – MaR – ECO Seminar/Webinar

Friday – January 26^th, 2024, at 1:00 p.m. | Room 305| Online

“Necessary condition analysis (NCA) with archival data: backgrounds and illustration”

Jan Dul – Rotterdam School of Management, Erasmus University (Netherlands)

Abstract:

“Necessary Condition Analysis (NCA; Dul 2016, 2020, 2021) is an emerging method that is now used in many business and management research fields and beyond. NCA understands cause-effect relations as “necessary but not sufficient” and not as probabilistic causality. “Necessary” means that an outcome will not occur without the right level of the condition, independently of the rest of the causal structure (thus the condition can be a “bottleneck”, “critical factor”, or “constraint”). In practice, the right level must be put and kept in place to avoid guaranteed failure and to allow the outcome to exist. NCA can be used as a stand-alone tool or in combination with regression-based approaches (e.g., multiple regression analysis, structural equation modeling) or Qualitative Comparative Analysis (QCA). By adding a different logic and data analysis approach, for instance through the reuse of data with a necessity causal perspective, NCA adds both rigor and relevance to theory and data analysis and provides new possibilities for impactful publications.”