2025-2026 CARMA-AOM Affiliate Program

Quantitative studies are increasingly relying on inference to the best explanation (IBE) or modern abduction. I discuss how historical methods—hermeneutics, contextualization, and source criticism—can improve IBE by helping scholars arrive at “best” explanations that are lovely, in the sense that they are useful, general, and provide meaning, and likely, in the sense that they are close to the truth. Further, I discuss how such scholarly work can be presented within the constraints of a typical management journal article. I propose an abductive testimonial structure, termed PEEBI, which consists of five sections in which the authors take prior knowledge and theories, establish the context and observations that are worthy of scholarly interest, identify candidate explanations that may explain the observed patterns, evaluate the candidate explanations, determine the best explanation and their reasoning for accepting it, and abstract the best explanation to a more generalizable theoretical contribution. This structure foregrounds transparency and the author’s judgment, elevating the reader’s role by providing them with the information to make their own informed judgments.

As behavioral scientists studying organizations and their members increasing integrate technology into their research, they are also increasingly conducting interdisciplinary research without realizing it and with limited expertise in the technology domain they are borrowing from. This has created an epidemic of poorly designed, poorly developed, and poorly understood technologies in organizational research studies. The resulting shortcomings, rather than minor methodological concerns, often threaten the fundamental validity and generalizability of those studies. In this talk, we’ll tackle this problem by exploring how and why the assumptions of behavioral organizational science and technology domains differ. Next, given this foundation, we’ll discuss how organizational researchers can build better technologies through modern engineering practices, select better technologies for inclusion in their research, and better work with technology teams in support of their research goals.

Qualitative meta-studies (QMS) are increasingly recognized as a fruitful qualitative methodology in management research. QMS serves as an umbrella term for scientific inquiries that reanalyze and synthesize rich, contextualized qualitative case studies or case material to generate novel theoretical insights and enhance the transferability of qualitative findings. In this lecture, we will explore different approaches to QMS and their epistemological foundations examine the kinds of theoretical and practical insights they can generate, and challenge some of the common myths surrounding this methodology. The session provides a hands-on introduction to QMS and illustrates, through empirical examples, the core methodological choices in QMS as well as the reflective, yet often implicit, meta-practices essential for deriving meaningful results from QMS.

An effective strategy for conducting high-quality qualitative research under academic publication pressures begins with deliberate choices about what data to collect and how to collect it. In this talk, we’ll explore strategic approaches to designing qualitative data collection that enhance analytical potential and methodological rigor. I’ll present practical strategies for context selection, sampling, and design choices that leverage variance and process. We’ll discuss how to design studies for meaningful contrasts and comparisons, and develop research protocols that generate rich, comprehensive data. This session emphasizes the critical front-end decisions that determine what data you have available and how they enable the development of compelling theoretical insights. Participants will gain practical tools for establishing a foundation for logical, persuasive methods sections that demonstrate scholarly rigor.

Advances in immersive technologies are transforming how scholars can study organizational behavior. This workshop introduces synthetic field studies—a next-generation research approach that uses virtual reality (VR) to simulate lifelike organizational environments while maintaining experimental control. Building on evidence that VR video vignettes heighten participants’ attention and emotional engagement, thereby amplifying the validity of observed employee reactions, we demonstrate how researchers can design, implement, and analyze such virtual organizations as dynamic experimental contexts. The workshop further explores how generative Al (GenAl) can extend these simulations by populating them with Al-powered actors capable of enacting realistic behaviors, dialogues, and decisions. Together, these tools allow researchers to replicate complex social dynamics, test organizational interventions at scale, and bridge the long-standing gap between laboratory precision and field realism. Participants will gain hands-on insights, design principles, and ethical considerations for deploying synthetic field studies in their own organizational research.

Websites represent a crucial avenue for organizations to reach customers, attract talent, and disseminate information to stakeholders. Despite their importance, strikingly little work in the domain of organization and management research has tapped into this source of longitudinal big data. In this paper, we highlight the unique nature and profound potential of longitudinal website data and present novel open-source code- and databases that make these data accessible. Specifically, our codebase offers a general-purpose setup, building on four central steps to scrape historical websites using the Wayback Machine. Our open-access CompuCrawl database was built using this four-step approach. It contains websites of North American firms in the Compustat database between 1996 and 2020—covering 11,277 firms with 86,303 firm/year observations and 1,617,675 webpages. We describe the coverage of our database and illustrate its use by applying word-embedding models to reveal the evolving meaning of the concept of “sustainability” over time. Finally, we outline several avenues for future research enabled by our step-by-step longitudinal web scraping approach and our CompuCrawldatabase.

This webcast will focus on explicating a method for doing abductive research with qualitative data. In abduction researchers initially identify an anomaly that contradicts or cannot be explained by existing theory and subsequently they develop novel explanations that account for the anomaly using theoretical imagination. I explicate how abduction inverts many of the steps in a typical inductive qualitative process. Rather than avoiding theoretical interference, abduction starts by engaging with prior theory. Instead of data and theory being tight coupled throughout the research process, the link between explanations and data are initially loosely coupled and then tighten over time. Rather than rigor residing in initial coding, in abduction rigor is obtained through systematic sampling and analysis of empirical data at the end of the process. This webinar thus reconsiders core tenets of qualitative research to help researchers develop impactful contributions to organizational theory.