All posts by admin

Measure: Servant Leadership

Servant Leadership

Liden, R. C., Wayne, S. J., Meuser, J. D., Hu, J., Wu, Junfeng, Liao, C. (2015). Servant leadership: Validation of a short form of the SL-28. The Leadership Quarterly, 26, 254-269.

Liden, R. C., Wayne, S. J., Zhao, H., Henderson, D. (2008). Servant leadership: Development of a multidimensional measure and multi-level assessment. The Leadership Quarterly, 19, 161-177

Congrats to 2017 Research Methods Division Award Winners

The Research Methods Division presented awards at the 2017 Academy of Management Annual Meeting, held in Atlanta, GA. You can also click here to find a full list of Research Methods Division Award Winners.

Sage Publications/RMD Distinguished Career Award
Chester Arthur Schriesheim, University of Miami

Sage Publications/RMD/CARMA/Lawrence R. James Early Career Award
George C. Banks, University of North Carolina at Charlotte


Sage Publications/Robert McDonald Advancement of Organizational Research Methodology Award
“Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology”
Published in Organizational Research Methods (2012);16, 15-31.
Dennis A. Gioia, Penn State University
Kevin G. Corley, Arizona State University
Aimee L. Hamilton, University of Denver

SAGE/RMD Best Division Paper Award
“Insufficient Effort Responding as a Meaningful Construct and Partial Function of Latent Aggression”
Justin A. DeSimone, University of Alabama
Kristl Davison, University of Memphis
Jeremy Lee Schoen, University of Mississippi
Mark N. Bing, University of Mississippi

SAGE/RMD Best Division Student Paper Award
“When ANOVA Gets It Wrong: A Re-Introduction of the Regression Discontinuity Design”
Nicolas Bastardoz, University of Lausanne

2017 RM Division Election Results

The results of the 2017 Research Methods Division elections are in. Members selected Zhen Zhang as Program Chair-elect and Stan Gully as Representative-at-Large.

We are saddened to note that Stan Gully recently passed away. His work on behalf of the research methods community, and to the Academy of Management as a whole, over the years has been extraordinary. Stan was a great influence on many scholars in the field in many ways, and his contributions will live on.

2017 Research Methods Division Award Nominations

The Research Methods Division of the Academy of Management is asking for nominations for three awards:

Distinguished Career Award (sponsored by Sage Publications)
Awarded to distinguished scholars who have made significanat contributions to the advancement of research methodology.

Early Career Award (sponsored by Sage Publications and CARMA)
Awarded to scholars who have made distinguished contributions to research methods, practice, and education during their early career stage. Candidates for the 2017 award must have received their PhD no earlier than 2010.

Robert McDonald Achievement of Organizational Research Methodology Award (Sage Publications)
Awarded to an organization-related article or book chapter that has made a significant contribution to research methodology.

For consideration, nominations must be received by March 15, 2017. Please consider nominating individuals in our field you believe should be recognized for their contributions.

Full information about how to nominate someone is available for download here. And, you can view prior award winners here.

If you have any questions, please feel free to contact Awards Committee Chair, Andreas Schwab (

AOM 2016 RM Division Award-Winning Papers

Congratulations to the following award-winning papers for the 2016 Academy of Management Annual Conference.

Sage/RMD Best Division Paper Award Winner

Dichotomizing Network Data Can Change the Meaning of Actor Centrality, by Noah Eisenkraft (University of North Carolina, Chapel Hill)

Monday, August 8, 9:45 pm – 11:15 pm, Anaheim Convention Center, 304A 

This paper explores the consequences of calculating actor centrality-how connected actors are to the other members of a larger group-with dichotomized network data. I argue that the meaning of actor centrality may change when researchers convert valued network data into a binary network. Data from eight archival data sets suggests that centrality describes overall connectedness when the network is dichotomized at a low cut point-e.g., when even acquaintances count as ties-but transforms into a measure of cliquishness/relationship exclusivity when the network is dichotomized at a high cut point–e.g., when friends, but not acquaintances, count as ties. Researchers who dichotomize network data may unknowingly use centrality estimates that do not map onto their theoretical construct of interest. Link to this paper’s session here.

SAGE/RMD Best Division Student Paper Award Winner

A Critical Note on the Prevalent Use of the Standard Deviation as Diversity Measure, by Kim De Meulenaere (KU Leuven)

Monday, August 8, 9:45 pm – 11:15 pm, Anaheim Convention Center, 304A 

This study gives serious consideration to the prevalent use of the standard deviation (SD) to measure diversity. Whereas prior literature has argued that diversity is not a unitary construct but can be conceptualized as separation, variety, or disparity-all engendering fundamentally different effects-, so far diversity scholars have largely used one measure, SD, to operationalize each of these different types of diversity when studying continuous, and in particular ratio-scale, variables. This study carefully scrutinizes the behavior of SD and argues that it is not appropriate to measure either separation, or variety, or disparity. We introduce a framework of alternative operationalizations that align well with the different conceptualizations of diversity-i.e., the polarization index (Pol) for separation, Blau’s heterogeneity index (Blau) for variety, and the Gini index (Gini) for disparity. Using a sample of 5,892 Belgian firm observations (2008-2011) and taking the example of age diversity, we illustrate empirically the overlaps and differences between SD, Pol, Blau, and Gini, as well as their differential effects on a firm-level outcome variable: labor productivity. Link to this paper’s session here.