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Grounded theory

Author: Dr Simon Moss


Grounded theory refers to a set of data collection and analysis techniques, all ultimately intended to formulate a theory. Usually, the researcher collects data about individuals or events--usually but not always qualitative in nature--and then attempts to develop broader, abstract categories to integrate these data. Finally, researchers attempt to uncover relationships between these broader categories, as a means to understand and explain a specific phenomenon or issue.

Defining features of grounded theory

Grounded theory comprises a series of core principles (see Glaser, 1978, 1992;; Glaser & Strauss, 1967;; Strauss & Corbin, 1990). In particular:

  • Researchers do not formulate hypotheses or construct a literature review before they collect data. Instead, codes and categories emerge from the data.
  • Researchers often switch between data collection and analysis. Indeed, these two phases are not differentiated but integrated. Accordingly, the distinction between research and theory is blurred.
  • Researchers often record memos as they create, clarify, and modify codes and categories. These memos facilitate the develop of theory.
  • Researchers seek individuals, events, or cases that are informative--that could be vital for assessing and refining their categories and theories--rather than representative.
  • Qualitative research is not merely a precursor to quantitative research, intended only to refine quantitative instruments, but a significant endeavor that generates theory rather than simply case studies.


    Grounded theory reconciles and adopts several distinct philosophical underpinnings. First, grounded theory is sympathetic to interpretative analyses (cf., Annells, 1996)--which is the attempt to describe, explain, and understand the subjective experiences of specific individuals. That is, the interpretative approach attempts to represent the thoughts, intentions, beliefs, meanings, interpretations, feelings, sensations, and actions of participants from their own perspective. The subjective experience of participants is deemed as important to appreciate. Grouded theory adopts this approach to the extent that researchers ask questions and seek information that uncovers the subjective experiences of participants.

    Second, grounded theory, however, is also sympathetic to some facets of positivism (van Maanen, 1988)--in which researchers strive to generate broad and abstract laws to describe a predictable world, and research is intended to verify these laws. Grouded theory also adopts this approach to the extent that researchers strives to identify concepts and patterns that characterize the participants from an objective perspective. That is, the researchers constructs theories that are dispassionate and objective rather than personal and subjective.

    Third, grounded theory is also sympathetic to the philosophy of symbolic interactionism (cf., Glaser, 1978). Specifically, according to Herbert Blumer, individuals pursue acts that afford a sense of meaning, and these meanings are derived from interpretations of social interactions (Blumer, 1969). Specifically, when individuals interact with each other, they do not merely respond directly to the actions of another person, as behaviorists had presupposed. Instead, they interpret these actions--ascribing meaning to these behaviors--which in turn shapes their response. Consistent with this perspective, grounded theorists often study how social interactions shape meaning and how individuals conceptualize or define themselves. That is, these researchers in how participants define the context and situation.

    Collecting the data

    Relationship between data collection and analysis

    Researchers collect data from interviews, personal journals, documents, emails, observations, and other sources. While they collect data, researchers immediately begin to analyze this information. They might assign codes to various excerpts or statements, integrate these codes to form broader categories, record notes on the properties of these categories, and reflect upon the relationships between concepts (Strauss & Corbin, 1990).

    This analysis and reflection then influences the data they collect& researchers ask questions that assess their ideas, clarify their categories, and refine their suppositions. In other words, data collection and data analysis often proceed simultaneously. Not only does this approach facilitate analysis, verifying the ideas that emerge, but also ensures that researchers are not overwhelmed with masses of extraneous data.

    Because of this intimate relationship between data collection and analysis, the theorists themselves, and not only an assistant, should participate in the interviews, observations, and examination of information. Many ideas, suppositions, and insights arise while collecting the data. Furthermore, theorists should study their data closely, each night if possible, to generate ideas and insights they might have overlooked while collecting the data.

    Information to collect

    Researchers should attempt to collect rich information--extensive accounts of personal experiences, events, or issues, showing how they unfold over time. When researchers derive data from observations, they maintain detailed records of the sequences of events that culminated in this episode, the setting, the other individuals, and the consequences. When researchers derive data from observations, they record the emotional state of the individual, the atmosphere or rapport, the setting, and other features.

    The researcher strives to collect rich data, not as an end in itself, but as a means to explore key codes, categories, concepts, processes, insights, patterns, and theories. The researcher attempts to describe events superficially as well as derive unspoken meanings, intentions, assumptions, as well as consequences, and then clarifies whether or not their conjectures are correct.

    For example, a researcher might interview senior executives who had been afflicted with depression. One executive might reflect upon a time in which a former subordinate had been assigned the CEO and, since then, had always worked even harder. The researcher might ask whether the CEO "Works hard to avoid the shame they felt that day" to clarify the intentions of this executive.

    Coding the data

    Derive codes from the data, not from preconceptions

    Researchers develop codes as they immerse themselves in the data they have collected. They should not begin with a preconceived list of codes and categories.

    Neverthless, researchers will obviously begin the research process with some preconceptions, which are often implicit. Furthermore, these preconceptions--their assumptions, ideas, and interests--will obviously shape which facets of data they recognize and the codes they formulate. However, the collection and coding of data should not be constrained unduly by these preconceptions. That is, their preconceptions should be conceptualized as a foundation from which they can develop novel codes, categories, concepts, and theories.

    To ensure that preconceptions do not constrain progress, researchers should feel they can pursue any developments or interests that emerge. They should explore any unexpected avenues or surprising insights.

    Initial coding

    Initially, researchers should assign a code to every unit of information--each sentence, argument, or observation, for example. For example, the sentence, uttered by an executive, "I cannot allow my employees to see my anxiety" could be coded as "conceal anxiety". The sentence "My peers culd stab me in the back any day" could be coded as "distrust of peers". These codes should be specific rather than too broad and abstract.

    Coding each sentence or line ensures the researcher remains embedded in the data. They become less likely to apply their own preconceptions to classify these data. Occasionally, researchers will apply codes that are common in their discipline, such as "emotional suppression". However, they should either refrain from these codes or ensure these codes are entirely suitable, to guarantee they are not applying their preconceptions inappropriately.

    These codes should not be regarded as definitive. They should be deemed as merely one of many possible means to classify the data. Indeed, sometimes researchers will apply a code that seems to depart appreciably from the assumptions and perspective of their participant. The participant, for example, might assert "I am ten times more effective than anyone else", and the researcher might apply the code "Exaggerating competence". In these instances, however, the researcher should record their perspective differs from the opinions or position of the participant.

    Focussed coding

    Once researchers have established which codes seem most informative, salient, and prevalent, they will then tend to apply these codes to other data--to interview transcripts, documents, or observations they have yet to analyze. That is, the researcher develops a list of the most vital codes they have unearthed. Next, they attempt to apply these codes to other data.

    This process is undertaken to refine, modify, and understand the codes in more detail. In particular, the researchers will begin to understand some of the common properties and characteristics of this code. In addition, the researcher will understand the antecedents and consequences of this code. Finally, the researcher will uncover the relationship between distinct codes--for example, when they tend to coincide. Accordingly, the definition of each code will evolve to become more concise and precise.

    Identifying categories

    Focussed coding will uncover sets of codes that relate to a common theme or pattern, called categories. For example, codes such as "conceal anxiety" and "exaggerate competence" might be related to the broader category of "enhance reputation". Alternatively, a single code, such as "conceal anxiety", might be rephrased as a more abstract rather than concrete category, such as "hide problems".

    The objective of researchers is to develop categories that are abstract and insightful, emphasizing unobservable but plausible processes or mechanisms, but also related to specific and concrete data.

    To generate categories, researchers, according to Charmaz (2004), should ask themselves questions like:

  • What are the processes or mechanisms that underlie this piece of information. For example, in response to the utternance "I am ten times more effective than anyone else", the researcher might feel the executive is "Attempts to amplify their pride".
  • When does this process or mechanism tend to arise& that is, what are the antecedents or determinants of this process?
  • What are consequences or implications of this process or mechanism?
  • What are the factors that initiate a change in this process or mechanism?
  • What are the thoughts, feelings, sensations, and urges that participants experience when this process is operating?

    Hence, categories emerge from a reflection and refinement of the code. In particular, categories emerge when the researcher compares codes between incidents, times, contexts, and individuals. Furthermore, categories can emerge when the researcher compares different codes and categories with each other (also see Hall & Callery, 2001).


    Memos represent personal insights, ideas, and thoughts that emerge in researchers as they reflect upon the coding process. These insights are intended to be preliminary and rough, rather than definitive and defensible. Researchers should write memos early in the coding process and continue throughout the research program.

    Memos are usually elaborations of the codes and categories that were created--attempts to explore their properties, antecedents, consequences, variations, and complications. In addition, memos include reflections about the coding process, such as records of doubts and uncertainties. Finally, memos include reminders on which sources of data to collect and which ideas or patterns to assess.


    Memos about codes, categories, and concepts are eventually integrated and refined to create a theoretical exposition. That is, the researcher attempts to characterize the concepts that have emerged. In addition, they discuss the processes or mechanisms that shape, maintain, or inhibit these concepts. Furthermore, they consider the consequences of these concepts. Finally, this information demonstrates how the various concepts are related, and an integrated theoretical account of the issues will tend to emerge.

    This theoretical account can then be compared and contrasted to the extant literature--to models, constructs, processes, and frameworks that have been discussed by other writers, This exposition is usually drafted and redrafted several times, and a more abstract, broad, and unified rendering gradually emerges.

    Controversies and criticisms

    Proponents of grounded theory do not all follow the same set of principles. Indeed, controversies abound, especially on whether codes should emerge from pre-existing families. Even the two original authors, Glaser and Strauss, have since 1990 fundamentally disagreed about the principles of grounded theory (Glaser, 1992). Glaserians tend to apply a coding paradigm--in which they consider a set of questions such as antecedents, contexts, strategies, and consequences--to generate codes. Straussians tend to identify codes from a vat store of coding families.

    Furthermore, grounded theory has been criticized frequently, as summarized by Thomas and James (2006). For example, some critics question whether the accounts that emerge from grounded theory are actually theories at all. In addition, in America, qualitiative research is often equated to grounded theory, and proponents of ethnographic and narrative techniques tend to feel their methods have been disregarded.


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    Last Update: 6/1/2016