Advancing scientific inquiry through data reuse: Necessary condition analysis with archival data

Abstract

This article discusses the importance of reusing existing data in research. In addition to reuse data for replication of earlier findings and for answering extended or new research questions, we propose a third application of data reuse: studying the phenomenon from an alternative causal perspective. We focus on the reuse of data with a necessity causal perspective (“if not X, then not Y”) as employed in necessary condition analysis (NCA). Such reuse of data offers additional insights compared with those obtained from the conventional probabilistic causal perspective (“if X, then probably Y”) as employed in regression analysis. NCA is gaining recognition in various fields, including strategic management. Reusing data for conducting NCA is an efficient way to get new causal insights. We provide recommendations on how to use NCA with existing data and emphasize the importance of transparency when reusing data.