Academy of Management Discoveries

The mission of Academy of Management Discoveries (AMD) is to publish phenomenon-driven empirical research that theories of management and organizations neither adequately predict nor explain. Data on these poorly-understood phenomena can come from any source, including ethnographic observations, lab and field experiments, field surveys, meta-analyses, construct validation research, and replication studies. AMD welcomes exploratory research at the pre-theory stage of knowledge development, where it is premature to specify hypotheses, and which generates surprising findings likely to stimulate and guide further exploration and analysis. This research must be grounded in rigorous state-of-the-art methods, present strong and persuasive evidence, and offer interesting and important implications for management theory and practice.

2015

The year Discoveries was first published

Number of Discoveries videos

Discoveries publishes quarterly in March, June, September and December

Contact the Discoveries Publishing Department

Michael Malgrande
Editorial Services Director

Editorial Team

Calls for Submission

AMD publishes management research guided by empirical abduction and induction, or in other words, studies which use data exploration to:

Surface significant new or emerging phenomenon using any number of empirical approaches including rich description, quantitative construct validation, and/or empirical taxonomic analyses.
Identify and explore surprising relationships using rigorous qualitative and/or quantitative methods in order to develop plausible explanations for those relationships and provide a grounded basis for innovative theorizing.
Studies that leverage the data to offer plausible explanations for the mechanisms underlying these relations and/or the conditions governing them are likely to be published as full-length papers.
Studies exposing stylized facts and providing evidence of their consistent and non-spurious nature without examining mediators or moderators likely to be published as “Discoveries-in-Brief".
Leverage original, secondary or “big” data and any number of alternative approaches (including lab and field/quasi-experiments, meta-analyses and replication studies) in order to offer empirically-driven insights into and/or a plausible resolution of critical anomalies and discrepant findings.