AOM-CAP@CARMA

AOM-CAP CARMA Logo

What is AOM-CAP@CARMA?

CARMA (the Consortium for the Advancement of Research Methods and Analysis) is an interdisciplinary, non-profit educational unit based at Texas Tech University that helps faculty, graduate students, and professionals stay current with developments in research methods and statistics, especially within the management and organizational sciences. It offers continuing education through webcast lectures, short courses, panels, and other resources, supports teachers of methods, and builds a scholarly community around research methodology. Since its founding in 1997 by Dr. Larry J. Williams, CARMA has reached hundreds of universities worldwide and thousands of users through its programs and CARMA Video Library.

The Community Accelerator Program (CAP) emerged from AOM’s Vision 2030 to connect scholars, institutions, and ideas that had long been underrepresented in our community. CAP is building bridges across continents, strengthening local and regional schools, research centers, and scholarly associations, and expanding the global reach of management scholarship. CAP activities include hosting high-impact academic development workshops, mentorship for emerging scholars, supporting regional research and publishing, and supporting early career researchers.

View a list of current AOM-CAP Participants; for more information on how to be a part of the Academy of Management’s Community Accelerator Program, visit the AOM-CAP website.

AOM-CAP@CARMA Video Collection

The AOM-CAP@CARMA Video Collection is a curated collection of recordings from the extensive CARMA Video Library. Existing videos in the collection are outlined below.

As new content is developed specifically for CAP events, it will be added to the collection.

Introductory Research Methods

  • Addressing the ‘Too Much Theory’ Problem in Management Research – Dr. Peter Bamberger

  • Combining Case Study Designs for Rigorous Research – Dr. Lakshmi Balachandran Nair
  • Dirty Data – Dr. Justin DeSimone
  • Interpreting Interaction Effects – Dr. Jeremy Dawson

International Scholars

  • Nuisance of Control Variables – Dr. Paul Hünermund
  • Qualitative Research for Maximum Impact – Dr. Kevin Corley
  • Questionnaire Measures as IVs – Dr. Paul Antonakis
  • SEM with Experimental Data – Dr. Bert Weijters
  • Theoretical Triangulation – Dr. Joep Cornelissen

Ask the Experts Panels

  • Causal Design – Dr. Andrew Loignon, Dr. Ben Lewis, and Dr. Kyle Bradley
  • Endogeneity – Dr. Lindsey Greco, Dr. Aaron Hill, and Dr. Sarah Wolfolds
  • Multilevel Analysis – Dr. Dan Beal, Dr. James LeBreton, and Dr. Janaki Gooty

New Doctoral Student Workshop Series

  • Welcome to Academia – Dr. Andrew Hanna, Dr. Chris Winchester, and Dr. Betty Zhou
  • Ethics, Open Science, and Scientific Integrity – Dr. George Banks, Dr. Gilad Chen, and Dr. Andreas Schwab
  • Connecting Theory to Methods – Dr. Ernest O’Boyle and Dr. Paul Spector

Additional CARMA Programs

Learn more about the non-CAP programming and benefits that CARMA has to offer.

Institutional Memberships

CARMA’s Institutional Membership gives faculty and doctoral students at member schools full access to its rich set of research methods resources. For an annual fee, anyone with the institution’s email address can create their own CARMA User Accounts. Members receive free, unlimited access to live online educational events, including Webcast Lectures, Ph.D. Prep Panels, Ask the Editor Panels, workshops, and more, with interactive Q&A and recordings added to CARMA’s on-demand Video Library of 250+ sessions. Institutional members also receive a 50% discount on short course registrations.

Live Online Short Courses

CARMA is offering a series of live online short courses from Monday, June 1, through Thursday, June 4, 2026, and Monday, June 8, through Thursday, June 11. Choose from courses covering qualitative or quantitative research topics, including generative AI for qualitative work, publishing with interview data, theorizing qualitative research, advanced regression for mediation and moderation, experience sampling methods, machine learning and natural language processing, and panel analysis with macro data. Instructors are experienced methodological scholars, many with editorial roles in top journals. Participants may be eligible for ECTS credits.