2025-2026 Schedule of Events

Historical Methods and PEEBI Testimonial
Structure for Abductive Studies in Strategy

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.

How to Engineer Technologies to Ensure the
Validity of Research Using Them

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

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.

Strategic Data Collection for Qualitative Studies

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.

Virtual Reality Tools for Organizational Research

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.

Manipulation in Organizational Research

While other applied sciences (e.g. medicine) embrace different types of manipulation designs, organizational scholarship has not. This course unpacks how our field came to adhere to ‘true experiments’ as the one proscriptive standard and introduces participants to a broader available toolkit. Together, we will touch on three topics. First, we will define and distinguish the different ways that manipulations can be deployed, analyzed, and interpreted in support of hypotheses, focusing on two archetypes­─ treatments and primes that differ in whether the manipulation itself is of theoretical interest─ and their creative derivations (e.g., interventions and invariant prompts). Second, we will review each type’s current prevalence and usage in our field. Third, we will conclude with a discussion of the costs and benefits of each and a summation of best practices. Following Schabram, Myers, and Hardin (in press), this course highlights that researchers have more options than they may realize when it comes to manipulation designs but each choice requires different claims of accuracy and causality.

Internet Scraping

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 CompuCrawl database.

The Practicalities of Mixing Methods: From Design to Publication

Multimethod research promises substantial benefits — the ability to generate and test theory within a single manuscript, triangulation across methodological traditions, and more complete understanding of complex organizational phenomena. Yet these benefits accrue only when the research is deliberately designed and genuinely integrated. Drawing on a review of 238 articles published in the Academy of Management Journal (Wellman et al., 2023), this session examines the practicalities of mixing methods in management research. I first introduce five empirically derived archetypes of multimethod research — methodological triangulation for hypothesis testing, methodological triangulation for theory development, test-and-explore, explore-and-test, and full research cycle — and show that the field overwhelmingly defaults to a single archetype (triangulation for hypothesis testing, 75%), leaving considerable theoretical potential untapped. I then identify three common pitfalls observed in editorial review: poor justification for mixing methods, poor methodological fit with the state of existing theory, and poor theoretical complementarity across studies. To address the integration challenge, I draw on Tunarosa and Glynn’s (2017) relational algorithms framework, demonstrating how different conceptual connectors between methods (beyond the default “and”) open up richer integration possibilities — including simultaneous, full-cycle, and mono-logic strategies. The session concludes with four practical recommendations: employ less common archetypes, explain the rationale for mixing methods explicitly and early, ensure theoretical and operational alignment across studies, and use supplementary materials thoughtfully. Throughout, I emphasize that more methods are not inherently better — the value of multimethod research lies not in the combination itself, but in the theoretical coherence and integration it enables.

Many social scientists interact with large language models primarily through chat interfaces, copying and pasting code between a browser and their IDE. Agentic coding tools like Claude Code, Codex, and Gemini CLI offer a fundamentally different workflow: they operate directly in the researcher’s file system, maintain project context, and execute multi-step tasks autonomously. This webcast will introduce these tools, explain their advantages over chatbot interfaces for empirical research, and provide practical guidance on getting started. The talk will also address uses beyond coding, including drafting and reviewing papers, building presentations, and managing other research tasks. Best practices and lessons learned from sustained use of these tools will be discussed throughout.​​​​​​​​​​​​​​​​