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Dear AIB Colleagues,



There’s been quite a bit of controversy about “Hypothesizing after Results
are Known” (HARKing), including mentions to it in several recently
published JIBS editorials. The following article available at
http://www.hermanaguinis.com/pubs.html provides empirical results about
when, why, and how different forms of HARKing are good, bad, or
inconsequential for the credibility of research results—I am posting this
on AIB-L because this journal is not on the radar screen of most IB
researchers:



·       Murphy, K. R., & Aguinis, H. 2019. HARKing: How badly can cherry
picking and question trolling produce bias in published results? Journal of
Business and Psychology, 34: 1-17.



The Abstract is below. Please email any reactions/comments directly to me
at [log in to unmask] (rather than the entire distribution list). I will post
a summary of responses. I look forward to your reactions to this article
and further discussion about this important issue.



All the best,



--Herman.



*Herman Aguinis, Ph.D.*

Vice President-Elect, *Academy of Management*

Avram Tucker Distinguished Scholar and Professor of Management

The George Washington University School of Business

2201 G Street, NW

Washington, DC 20052

*http://hermanaguinis.com/ <http://hermanaguinis.com/> *



*ABSTRACT*
The practice of hypothesizing after results are known (HARKing) has been
identified as a potential threat to the credibility of research results. We
conducted simulations using input values based on comprehensive
meta-analyses and reviews in applied psychology and management (e.g.,
strategic management studies) to determine the extent to which two forms of
HARKing behaviors might plausibly bias study outcomes and to examine the
determinants of the size of this effect. When HARKing involves
cherry-picking, which consists of searching through data involving
alternative measures or samples to find the results that offer the
strongest possible support for a particular hypothesis or research
question, HARKing has only a small effect on estimates of the population
effect size. When HARKing involves question trolling, which consists of
searching through data involving several different constructs, measures of
those constructs, interventions, or relationships to find seemingly notable
results worth writing about, HARKing produces substantial upward bias
particularly when it is prevalent and there are many effects from which to
choose. Results identify the precise circumstances under which different
forms of HARKing behaviors are more or less likely to have a substantial
impact on a study’s substantive conclusions and the field’s cumulative
knowledge. We offer suggestions for authors, consumers of research, and
reviewers and editors on how to understand, minimize, detect, and deter
detrimental forms of HARKing in future research.

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