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Professional Development Workshop

Necessary Condition Analysis (NCA): Logic, Theory, Methodology, and New Applications

Academy of Management Annual Meeting 2020

August 9, 2020 from 20:45 to 22:45 CEST

Workshop Description

In this workshop you will learn how to conduct Necessary Condition Analysis. This emerging method was recently published in the journal Organizational Research Methods (2016, 2018) and is further described in the Sage book ‘Conducting Necessary Condition Analysis' (2020). NCA is now used in many fields including Strategy, OB, HRM, Operations, and Entrepreneurship and International Management.

NCA understands cause-effect relations as “necessary but not sufficient” and not as additive and average logic that is used in regression analysis. “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”, “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 and other approaches. By adding a different logic and data analysis approach, NCA adds both rigor and relevance to theory and data analysis. This interactive session familiarizes scholars with the method and has two parts. Part 1 is a general introduction discussing the importance of necessary conditions, illustrated with examples from different fields. Part 2 helps participants to become the first users of NCA in their field, with a practical demonstration about the application of NCA on how to build necessity theories, and how to analyze data for testing such theories using the NCA software.

For more information about NCA see www.erim.eur.nl/nca or contact jdul@rsm.nl. No preparations required.

Workshop Information

Workshop Sponsors: Human Resource Management (HR) Division, Research Methods (RM) Division, Strategic Management (STR) Division, (OCSM) Division.