Springtime Papers and a Guest Column on Qualitative Research

Deputy Editor (and alpaca expert) Andrew Nelson explains qual for quants

Spring is all around us here in St. Louis, where the magnolias are in full bloom, the allergies are exploding, and tornadoes are flying by like tenure clocks. With spring comes spring break for the kids, which in no way impacts productivity for those of us working at home. Not a bit. Particularly when half the basketball team shows up to hang out.¹ Today we have a lot of content for you. Gordon put together four forthcoming papers on very timely topics: visa waivers and inventions, refugee entrepreneurs, technology implementation in health care clinics, and cognitive networks. Why are these highly relevant? Hmm. . . Oh, and did I mention that one of them was funded by the NSF?

We also have a guest column by Deputy Editor Andrew Nelson, who handles all qualitative papers submitted to the journal. This is a crucial job for the journal, given that my qualitative expertise is similar to my bassoon skills, and Andrew is a remarkable scholar and editor, among other things. My observation in this role is that most quant scholars have little sense about how qualitative research works, with some even believing it is basically “talking to some folks.” Here at Organization Science we think it’s really important for qual and quant folks to read and understand each others work. So definitely check out his column after the forthcoming papers.

Relatedly, I’m happy to announce that we’ve appointed our first editorial comfort alpaca, Suzy, who is available to authors after rejections and to editors after getting three papers assigned to you in one week. We considered other camelid species, but my traumatic childhood experiences feeding the neighbors’ spitting llama steered us toward this friendlier (and poofier) option.² INFORMS denied our request for a grooming budget but Andrew kindly agreed to host Suzy on the Oregon farm in exchange for her protecting the family goat from angry beavers and sasquatch.

I’ll be back in the next week with some (mostly coherent) thoughts I’ve put together on how we cite existing and concurrent research in our papers. Until then, enjoy the papers and column!

-Lamar

Newly Accepted Papers:

Fast Friends: The Impact of Short-Term Visits on Firms’ Invention Outcomes

Hyo Kang, John C. Eklund

Can short-term "visits" between international R&D centers enhance invention within multinational firms? The authors investigate the impact of the staggered rollout of the U.S. Visa Waiver Program (VWP) to 41 countries and reveal a fascinating trend: global pharmaceuticals benefiting from the VWP enjoyed a notable increase in both the quantity and scope of their inventions. Why is this interesting and important? The findings emphasize that even brief face-to-face interactions play a crucial role in facilitating the flow of tacit knowledge and fostering collaboration across geographically dispersed R&D centers. Notably, these benefits are amplified when there is an intermediate knowledge gap between centers or when cultural distances are greater, illustrating how short interactions help bridge both knowledge and cultural divides. Readers will gain valuable insights into enhancing R&D strategies and informing public policy to capitalize on globally mobile talent, highlighting how even brief visits can influence inventive performance.

In Search of a Soft Landing: How Premigration Work Attainments Influence Identity Transformation Processes of Refugee Entrepreneurs

Joris Amin, Elco van Burg, Wouter Stam

Highly educated refugees bring rich professional experiences to their host countries but face the challenge of reconciling their past identities with new professional realities. This study explores how these individuals navigate identity transformation through entrepreneurship—a path that enables them to chart a more personal career trajectory that better reflects their unique talents and aspirations. It reveals an intriguing paradox: pre-migration achievements can both empower and complicate navigating new professional landscapes. The authors find that refugees who embrace a flexible perspective on their prior work achievements experience a more seamless transition. By uncovering the key behavioral and cognitive practices behind this process, this research offers valuable insights for policymakers and practitioners to better support refugees’ resettling in their new societies.

Path Coherence and Disruption in Routine Dynamics

Inkyu Kim, Brian T. Pentland, Kenneth A. Frank, Julie Ryan Wolf

Our goal is to theorize about mechanisms that predict the dissolution and formation of network paths after a disruption. In this study, we propose that path coherence in narrative networks functions like homophily in social networks, but with a completely different underlying mechanism. Path coherence provides a way to explain both the persistence of existing paths and the formation of new paths, both of which are essential to the on-going enactment of routines after a disruption. Interestingly, our results show that coherent paths are up to 14 times more likely to persist and up to 40 times more likely to form than less coherent paths. This study reveals that path coherence, continuity of context, is strongly associated with the persistence and formation of paths and organizational routines.

A Cognitive Network Perspective on Creativity: Theorizing Network Mobilization Scripts

Claudio Biscaro, Fabrizio Montanari

We think of social networks as objective facts. But, how we perceive and use them is deeply personal. Our mental maps of the social network (cognitive networks) influence how we use it. In our paper, we reveal two approaches to network mobilization used by the members of a creative studio to elaborate creative ideas. We call them network mobilization scripts, which are influenced by cognitive networks.

Creating-in-a-Studio is the script adopted by those who perceive themselves in loose network. By relying on a small group of colleagues and engaging in deep, often humorous, discussions, the script helps individuals delve deep into the nuances of ideas and seek useful analogs in the depth of common ground.

What Quantitative Researchers Need to Know About Qualitative Research?

-Andrew Nelson

I wasn’t there. But the story as I heard it was that two senior scholars, one quantitative and one qualitative, were on a panel together at AOM, many years ago. The qualitative scholar described his work. The quantitative scholar then said it sounded “like journalism, not real research.” A melee ensued, and the meeting room suddenly resembled something out of the movie Roadhouse.

Okay, I made that last bit up. But the story—the first part; the true part—points to a lack of understanding about qualitative research that, in different forms and at times, persists. So when Lamar invited me to write a piece on “what quantitative scholars need to know about qualitative research,” I jumped at the chance. And then I swiftly solicited insights from some of my fellow editors at OrgSci who work with qualitative submissions: Grace Augustine, Daphne Demetry, Anne-Laure Fayard, and Sharon Koppman. They’re responsible for any insightful points below. I’m responsible for the bits that lead to expletive-laden outbursts (or, less exciting, pointed comments questioning certain claims).

To begin, we should of course acknowledge that “qualitative” and “quantitative” are descriptions of research approaches, not people. Most scholars in our field receive exposure to and (some degree of) training in both approaches. Moreover, many scholars, including me, have published both qualitative and quantitative research. Indeed, I was trained that it’s not about the method, it’s about the question—and different questions suggest different methods.

All of that said, quantitative work continues to dominate many top management journals, including Organization Science. Many PhD programs require formal coursework in quantitative methods but not in qualitative methods. And aside from reading qualitative articles, many scholars have little experience with qualitative work. Hence, this short piece.

To set expectations, this is not a guide for how to conduct qualitative research. There are several fabulous reflections, articles, and books on qualitative research methods, and I can’t possibly do justice to them here. Instead, following Lamar’s prompt, this is a brief reflection on features, characteristics, and misconceptions, all organized into a “Top 8” list (because Lamar’s word limit doesn’t leave quite enough space for a “Top 10” list).

1. Goal

An oft-drawn distinction is that qualitative work is “theory-building” whereas quantitative work is “theory-testing.” Some may take issue with that generalization, but it remains true that, typically, qualitative research doesn’t aim to test or “prove” anything. Instead, the emphasis is on generating new insights and new perspectives, with sensitivity to nuance and context. In other words, the ultimate measure might be, “did I learn something new?”

Relatedly, qualitative research often is motivated by observing phenomena that existing theory doesn’t explain well. For instance, Callen Anthony, Mary Tripsas and I started our research project on technology reemergence in the music synthesizer industry because we were puzzled: Why was outdated technology that had been abandoned in the 1980s suddenly the centerpiece of new products? That’s not something that most theories of technology and industry evolution would predict, and our goal was to advance theory accordingly.

2. Breadth of Literatures

Because qualitative work typically “follows the data,” researchers can be forced to dive into entirely new literatures as their projects unfold. Sometimes, this leads qualitative researchers to develop more breadth in the theories they engage and in the scholarly conversations they join. Put differently, qualitative researchers often cannot limit their focus to a dominant lens or theory since their data may lead them elsewhere.

For example, many years ago, I wrote a piece with Jenn Irwin that sought to investigate why librarians were not represented on the founding teams of internet search startups, despite their expertise in information search. We originally conceived of this as a story of competing institutional logics associated with libraries versus startups. But the data pointed to the importance of occupational identity, and our paper became one about how occupational identity and new technologies interact—even though neither of us knew much about the occupational identity literature at the outset.

3. Review Process

The general contours of the review process for qualitative and quantitative work are, of course, very similar. But many scholars are surprised at what may be requested of a qualitative submission, especially early in the process: It’s not unusual for reviewers to ask for additional data, re-coding of data, and the complete rewriting of a paper’s front end. This also means that there may be more uncertainty with qualitative R&Rs (following initial submission) than with much quantitative work. Indeed, recent OrgSci data show that qualitative submissions that are sent for review are slightly more likely to receive an R&R upon first submission, often because the data show potential—but also slightly more likely to be rejected after this first R&R, often because the necessary changes have been (or should have been) more substantial.

4. Time

At Organization Science, we’ve been working hard to reduce the review time in each round and the total number of rounds—for both qualitative and quantitative submissions. But other aspects of the research and publication process can be much slower for qualitative work. Qualitative researchers typically must generate their own data, whether through ethnography, interviews, assembling archival materials, or some other approach. In turn, it takes a long time to identify sites and people, gain access, collect data, and so on. (This is not to deny, of course, that some quantitative data efforts also require a great deal of time.)

Qualitative analysis also takes time—coding, re-coding, re-coding again, and so on; while quantitative studies may require running different models or exploring additional variables, qualitative studies often involve numerous iterations around a study’s most fundamental components—its theory and its data/analysis. And, reflecting points above, if initial analysis suggests that additional data are needed, or that the research question or motivating literature need to change, that takes even more time. I’ve not seen systematic data on the “productivity” of scholars who conduct qualitative versus quantitative research. But my guess is that qualitative projects take much longer from inception to publication, and that researchers who focus on qualitative research produce fewer papers (though perhaps more influential ones).

5. Rigor

I earlier offered the disclaimer that this is not a “how to” guide. But it’s essential to note that that there are better and worse ways to go about the identification, collection and analysis of data. That is, qualitative research, when done well, is systematic and rigorous at every step; it’s not merely “talking to people” or “telling stories.” Given this, as well as the points above, it’s also difficult and it takes a great deal of practice to learn the craft—even if the final published paper makes it seem relatively easy.

6. Diversity

“Rigor” does not equate to “monolithic,” and qualitative approaches vary dramatically. To choose three examples, ethnography, interviews, and content analysis of archival data require different skills, surface different insights, demand different time commitments, and follow somewhat different processes for the collection and analysis of data. Even for the same kind of data—for example, interviews—there are multiple approaches that may be appropriate. (Pro tip: Not all multi-case analyses follow “the Eisenhardt approach,” and not all coding follows “the Gioia method.”)

7. Generalizability

Many observers note that qualitative research is not generalizable. It’s true, of course, that qualitative research is not generalizable in some ways nor does it aim to be—though it’s also true that much quantitative research is not readily generalizable beyond the context of the data. In both cases, a key task is systematic consideration of the boundary conditions for a study. Thus, qualitative scholars typically will use discussion section of a paper to contemplate when, why and how the identified mechanisms may be applicable, or not, in other settings. And in so doing, they’ll very much consider how insights may be transferable.

8. Engagement and Immersion

Finally, as I tell PhD students, one of the treasured aspects of our profession is that we get to choose what we study and how we study it (and whom we study it with!). Much of my work has investigated innovation in music technology. And while there are important questions about this industry that can be assessed quantitatively, there’s undeniable appeal to qualitative approaches that have led me to stand aside Stevie Wonder while observing a music trade show, to review Steve Jobs’ emails contemplating the future of music and computers, and to interview the musicians who created the first digital drum machines. Most qualitative researchers share this same attraction to immersing themselves in a setting. (That’s part of why we’re such a happy bunch!)

What do you think? If you do qualitative research, what do you wish others knew? And just as important, if you do quantitative research, what do you wish qualitative scholars understood about your craft? (A topic for another Substack newsletter?)

1. The Costco box of Oreos seems to be missing.

2. Yes, Beserk Llama Syndrome is a real thing, and yes we have all sorts of weird pets in the Northwest.