ASQ PAPER DEVELOPMENT WORKSHOP:
IMPROVING EVIDENCE PRESENTATION IN MANAGEMENT RESEARCH
Introduction
The presentation of evidence in management scholarship has fallen behind the cutting edge, and our journals show significantly less advanced and flexible evidence presentation than our neighboring disciplines, which have learnt more from the sciences. The ASQ Paper Development Workshop aims to start closing the gap by introducing forms of evidence presentation commonly used outside management, including graphical approaches. The session focuses on developing papers in progress through direct mentoring and panel discussions on improved presentation of evidence. The goal is to start a movement towards better presentation of data, main findings and model implications, in ways that are tailored to the theoretical and empirical contribution, and study context, instead of being standardized across papers. As an author's journal, ASQ wants to encourage authors to feel less constrained by institutionalized "classic traditional" formats and write papers which highlight their own voice most effectively.
Practicalities
The PDW is Saturday Aug 5 4:00-6:00pm at Atlanta Marriott Marquis.
It is targeted toward scholars who have work in progress that they would like to improve through modern methods of evidence presentation, and who are interested in being ambassadors and mentors to peers who also have this interest. We ask that each applicant submit a CV and paper for discussion during the workshop, and that the same paper (possibly updated) be used for the workshop discussion. Participants will be selected from applicants who have submitted their application by the closing date of Friday May 25.
Please send the application to henrich.greve@insead.edu
The PDW has the following elements: (1) Presentation of evidence options (Henrich R. Greve); (2) Group discussion of papers (Led by mentors); (3) Panel discussion (Mentors).
The following ASQ editors and editorial board members have agreed to serve as mentors for the workshop: Henrich R. Greve, Mary Benner, Anne Bowers, Forrest Briscoe, J.P. Eggers, Marc-David L. Seidel, and Batia Wiesenfeld.
Details
Cumulative scholarship in management is held back by an unrecognized and significant problem: Our papers have become isomorphic, using a highly standardized and restrictive presentation of evidence style. This is in contrast with neighboring disciplines such as sociology and economics, which have learnt from the natural sciences that there is a wide range of options for presenting evidence, and that the evidence shown in each paper should be tailored to the theory, context, and data available. We think that the author's voice is held back when researchers believe that journals reward isomorphism and the full range of methods is not well known or used. This PDW aims to address both concerns to help authors, and subsequently the field, develop scholarship to its maximum potential. First, every mentor and panelist in the PDW is associated with ASQ to signal our strong interest in greater diversity of evidence presentation. We have this interest because more flexibility allows authors to present their evidence more effectively and have their voice heard more clearly. Second, the PDW spreads knowledge through a presentation of some options available, followed by developmental roundtable mentoring discussions to help participants maximize the impact of their own work through growth-fostering interactions between scholars, and a summary panel.
The tools below are some examples often used in other disciplines. They are too numerous to include all in one paper, but that is exactly the point: the good scholar looks at the theory and data and customizes the presentation of evidence to fit. Papers can be improved by selectively:
1. Using tools to give an early indication of the phenomenon and explanatory variable importance even before estimating the models, to motivate the paper:
a. Graphing the phenomenon to show that there is a meaningful distribution of the outcome the author is trying to explain
b. Graphing the distribution of the main independent variables, and how they covary with the outcome, ignoring all control variables
c. Mapping outcomes that occur over space, especially if the explanatory variables are also spatial
d. Tracing outcomes that unfold over time, especially if the explanatory variables also change over time
e. Showing distributions of key variables, especially if they differ from the usual (normal) distributions and have substantive interest such as links to the outcome
2. Looking for additional analyses showing variations of the explanation. Additional analyses does not mean alternative statistical models, but rather:
a. Examination of whether new insights can be gained from using alternative variables for the main constructs
b. Analysis of subsamples that provide useful comparisons or refined hypotheses
3. Displaying findings in ways that provide more insight:
a. Showing graphs comparing estimates and actual outcomes on the same graph and tables or graphs of prediction accuracy gained by the theoretical variables
b. Quantifying how much has been explained and how much variation remains to explain, as an indicator of future research opportunities
Henrich R. Greve, INSEAD
Editor, Administrative Science Quarterly