STR Members,
Have interesting findings that are not well explained by current theories? Struggling with how to retrofit interesting data into a "theoretical framework" suitable for publication? Want to be more upfront and transparent about your data mining? If the answer is "yes" to any or all of these questions, consider submitting to
Academy of Management Discoveries.
AMD is a premier journal for the empirical exploration of data describing or investigating compelling phenomena where there is a lack of clear, explanatory, existing theory. The goal with every AMD paper is to use empirical explorations, and the novel theoretical explanations such findings suggest, to open new lines of inquiry in management research.
At AMD, we encourage transparency and openness in presenting research. Authors are able to present the results of data mining without the need to "reverse engineer" any theoretical framework or hypotheses (HARKing). AMD publishes discoveries resulting from the exploration of both quantitative and qualitative data sources.
Want to learn more? Check out
Academy of Management Discoveries for information on the journal, on our
COVID special research theme, on
Discoveries-in-Brief, our creative writing initiative, and how to submit a
Registered Report.
We are interested in seeing more STR authors in AMD and look forward to your submissions!
Most sincerely,
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Kevin W. Rockmann, PhD
Professor of Management and Dean's Scholar
Editor-in-Chief, Academy of Management Discoveries
PhD Program Director
George Mason University
School of Business
Fairfax Square, Office 252
9900 Main Street, MSN 1E6
Fairfax, Virginia 22031
krockman@gmu.eduwww.kevinrockmann.comwww.highqconnections.com------------------------------