Introduction

With the impending 50th anniversary of the first publication of Glaser and Strauss’s The Discovery of Grounded Theory (1967), the time feels right to “talk about what we do in our research and how we do it” (Locke, this issue). This conversation began with submission of a well-attended 2013 Academy of Management panel organized by Isabelle Walsh and Judith Holton including Barney Glaser, Lotte Bailyn, Walter Fernandez, and Natalia Levina. Two reviewers (unknown to the panelists) helped to transform the panel transcript into a more tightly scripted contribution to Organizational Research Methods, after which we invited three expert commentaries (Kevin Corley, Deborah Dougherty, and Karen Locke). The panelists then provided a rejoinder and final comments. In the end, I believe that this conversation clarifies points of agreement as well as surfaces differing assumptions and contemporary considerations related to grounded theory (GT). These articles can be read by novices to grounded theory as well as seasoned GT users. I recommend reading the “conversation” as a package—starting with the initial panel, followed by the expert commentaries and panelist rejoinders and final comments.

There were several areas of agreement across this conversation. First, that grounded theory can accommodate a variety of data is a clear point of agreement. The panel emerged from discussion of Walsh’s question on a listserv, “Whoever said that grounded theory is only a qualitative method?” All panelists and commentators agree grounded theory can include any type of data—numbers, words, and, I would add, images. As Dougherty succinctly states, “Data are data. Period.” Fernandez reiterates this view, “All is data … [but you need] a research problem, with the data offering a good fit to this problem.” The application of the word qualitative to analysis is misleading, according to Bailyn, who argues for identifying data more precisely as verbal or numeric and clarifying whether modes of analysis are confirmatory and explanatory. So, while there is agreement that numeric data can be included in GT, the way in which we refer to research as qualitative or quantitative has created confusion.

Levina extends this agreement on quantitative data in GT by asking: What are we going to do about Big Data? Because Big Data “cannot be reasonably analyzed with qualitative methods alone,” Levina (this issue) calls for inclusion of “inductive data scientists into the grounded theory research community and [to] start using some of the advance analytical techniques available today.” As well, Dougherty (this issue) identifies a need to “develop approaches for ‘data mining’ of big data.” Many involved in this conversation discuss the need to visualize data, see longitudinal patterns, and identify what is interesting in the patterns. Levina points out that tools from “computer science and statistics communities … can help researchers see patterns in data,” but, as she notes, reporting quantitative analyses in journal submissions might be more of a challenge!

A second area of agreement is that we should all read more about grounded theory, but there is less agreement about what to read. Certainly, there is not a lack of books about grounded theory. Locke (this issue) noted over 16,000 in a cursory search of Amazon. She suggests reading a recent book by second-generation grounded theorists (Morse et al., 2009) in order for novice researchers to “make better informed choices about how to navigate and locate themselves within the sizable grounded theory domain.” I have found the 2014 edition of Charmaz’s Constructing Grounded Theory text especially meaningful. Holton emphasizes reading many of Barney Glaser’s contributions after Discovery and argues that reading just GT introductory books is “insufficient.” Fernandez indicates that we all would benefit from GT users reading “the seminal books” about GT in order to enable a “knowledgeable execution of this process.” Further, Barney Glaser urges researchers who want to mix other methods with GT (which he allows as possible) to “read the books!” The references of the commentators and panelists provide rich reading lists, albeit with some decidedly different emphases.

A third theme of agreement relates to the education of doctoral students. Walsh’s original question emerged from the shortcomings in her “instruction received.” Locke (this issue) also notes that “institutional resources available to help our novice researchers develop their research practice in non hypothetico-deductive forms of research is unevenly distributed.” She identifies that some doctoral students may only have a short course sequence on qualitative methods. These comments dovetail with some work I undertook several years ago when I queried PhD directors of top U.S. doctoral programs about qualitative methods in doctoral education. Only 6 of the 17 doctoral directors who responded indicated that a qualitative methods class was required; further, the respondents indicated that over three-quarters of all recent dissertations were quantitative in nature. This trend highlights Corley’s discussion of “trickier” challenges faced in a more exploratory inductive dissertation as compared to deductive research, whereby committee members have to understand that what is achieved is more important than what was proposed.

Just as Barney Glaser and Anselm Strauss diverged in their GT use and writing, the conversation here highlights many differences among this set of GT researchers. From the back and forth in the commentaries and rejoinders, areas of disagreement include: the return to classic grounded theory or embracing contemporary adaptation, whether to be more phenomenon than theory contribution focused, philosophical stances, the inclusion and degree of literature use, and strict adherence to a sequential approach or flexibility in application. Some issues require more work before finding a middle ground, others will be concluded with an “agreement to disagree,” but all benefit from more conversation.

Finally, I highlight some of the vivid images and phrasing and memorable stories that you can look forward to in this conversation: Dougherty’s comparison of “confirmatoids” to “discover-whees!,” Corley’s culinary metaphors for methodological approaches, Bailyn’s exercise from her doctoral course, and Dougherty’s illustrations beyond organizational science (e.g., Higgs boson) and name-that-discipline exercise for the reader! Locke provides a rich description of a recent reviewing experience that led to the rejection of a GT paper with a beautifully crafted core concept. Why? Well, it was not due to the difficulty of getting classic GT published, but rather … well, I won’t spoil the rest of her story. In the conversation across the panel, commentaries, and rejoinders, there are many excellent insights embedded in images, stories, and turns of phrases.

On a personal note, I have immensely enjoyed working closely with panel point person Isabelle Walsh on this project. I appreciate the three commentators’ willingness to sacrifice personal time during the holidays to write their reaction to the panel. They also were willing to provide their viewpoints recognizing that the conversation had to end, however artificially, with rejoinders from the panelists. I am sure that the conversation could have continued across more pages, but I expect to see themes from this set of articles emerge in future Academy panels, animated conference hallway discussions, journal articles, and other formats. For now, we provide these articles as a conversation bracketed in time and space.