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Reference this paper as: Lawrence, J and Tar U The use of Grounded Theory Technique as a Practical Tool for Qualitative
Data Collection and Analysis The Electronic Journal of Business Research Methods Volume 11 Issue 1 2013 (pp 29-40),
available online at
www.ejbrm.com
The use of Grounded Theory Technique as a Practical Tool for
Qualitative Data Collection and Analysis
Japhet Lawrence
1
and Usman Tar
2
1
Department of Applied Computing and Information Technology
University of Kurdistan-Hawler
Erbil, Kurdistan Region of Iraq
2
Department of Politics & International Relations
University of Kurdistan-Hawler
Erbil, Kurdistan Region of Iraq
lawrenceje@yahoo.com
usmanatar@gmail.com
Abstract: When encountering qualitative research for the first time, one is confronted with both the number of methods
and the difficulty of collecting, analysing and presenting large amounts of data. In quantitative research, it is possible to
make a clear distinction between gathering and analysing data. However, this distinction is not clear-cut in qualitative
research. The objective of this paper is to provide insight for the novice researcher and the experienced researcher coming
to grounded theory for the first time. For those who already have experience in the use of the method the paper provides
further much needed discussion arising out of I“ In this paper the authors present a
practical application and illustrate how grounded theory method was applied to an interpretive case study research. The
paper discusses grounded theory method and provides guidance for the use of the method in interpretive studies.
Keywords: grounded theory; interpretive; case study; data collection; data analysis; qualitative; quantitative
1. Introduction
One of the main problems of conducting interpretive qualitative research is to decide an appropriate starting point
for the research, and the basic framework within which the data will be collected and analysed. Qualitative
studies tend to produce large amounts of data that are not readily amenable to mechanical manipulation,
analysis and data reduction (Yin, 1984). It not only generates large amount of data, but it generates data in a
non standard format which makes analysis problematic (Turner, 1983). Qualitative analysis provides an
opportunity for the researcher to gain information and gather insights that may be overlooked with traditional
data analysis techniques. The analysis of the case study is done in pursuant to guidance provided by many
scholars in this field, (such as Glaser, 1978; Glaser and Strauss, 1967; Lofland and Lofland, 1984; and Taylor and
Bogdan, 1984).
The process of data analysis in qualitative research involves working with data, organising it, breaking it down,
synthesising it, searching for patterns, discovering what is important and what is to be learned, and deciding
what you will tell others (Bogdan and Biklen, 1982). Spradley (1979) refers to analysis as a systematic
examination of something to determine its parts, the relationship among parts, and their relationship to the
whole. While Miles and Huberman (1984) describe data analysis as consisting of three concurrent activities -
data reduction refers to the process of selecting, simplifying, abstracting and transforming the new case data.
They argue that data collection and data analysis should overlap to allow for flexibility in data collection
procedures so that the researcher remains open to new ideas or patterns which may emerge.
There are many ways of analysing qualitative data and a number of approaches were considered such as
hermeneutics, content analysis and semiotics (Myers, 1997). These approaches come from diverse fields and
all offer the possibility of different insights on the data. These approaches were evaluated from the
perspective of whether the approach draws on all features of case study and whether the philosophy of the
approach imposes any pre-existing theories. Eisenhardt (1989) suggests that theory building research must
begin as close as possible to the ideal of no theory under consideration and no hypotheses to test since
preordained theoretical perspectives may bias and limit the findings.
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The objective of the case study research was the development of a conceptual model that explains the
adoption of Internet in small to medium-sized enterprises (SMEs) and the objective of the study fits well with
the philosophical nature of grounded theory. Accordingly, proponents of the grounded theory advocate that
an approach which concerns itself with the meanings, definitions, and interpretations which are made by the
subjects of the study has greater potential for depicting their world and priorities more accurately than
methods which begin by preconceiving the world and its meaning (De Burca and McLoughlin, 1996). The
researcher did not come to the field with a well-defined set of constructs and instruments with which to
measure the social reality; rather the researcher derives the categories from the field by in-depth examination
and exposure to the phenomenon.
The selection of grounded theory (Glaser and Strauss, 1967; Glaser, 1978; Strauss, 1987; Strauss and Corbin,
1990, 1998) amongst a myriad of other qualitative methods is not arbitrary but rather because it has been a
dominant paradigm for social research (Hughes and Jones, 2003) and its use is increasing in the IS field. This is
evidenced by the growing literature that is either discursive on philosophy and application or detailed about
method (Toraskar, 1991; Orlikowski, 1993; Baskerville and Pries-Heje, 1999; Trauth, 2000; Hughes and
Howcroft, 2000; Urquhart, 2001). Hughes and Jones (2003) note that more researchers are taking up
qualitative studies, it is therefore worth reflecting on lessons learned from the practical application of the
method. The purpose of this paper is to provide insight for the novice researcher and the experienced
researcher coming to grounded theory for the first time. For those who already have experience in the use of
the method the paper provides further much needed discussion arising out of I“
field.
The remainder of the paper is structured as follows. It begins with an overview of the grounded theory
method and a discourse on the use of grounded theory in Information Systems. This will be followed by a
description of the procedures involved in collecting and analyzing data in grounded theory method. Following on
from that is the justification for using grounded theory to collect and analyse the case study data. An illustrative
piece of research is then presented in which grounded theory was used in interpretive, qualitative case studies
and finally, the paper presents some conclusions.
2. The grounded theory method
This section discusses grounded theory (Glaser and Strauss, 1967; Martin and Turner, 1986; Turner, 1983;
Glaser, 1978; Strauss, 1987; Strauss and Corbin, 1990, 1998; Dey, 1999; Charmaz, 2003, 2006, 2008). Grounded
theory originates in the work of Glaser and Strauss (19967) and is a method that has been used extensively
across a variety of social science disciplines. A grounded theory is one that is discovered, developed, and
provisionally verified through systematic data collection and analysis of data pertaining to a particular phenomenon
(Strauss and Corbin, 1990). It is invaluable when conducting empirical research; it has some attraction for a
researcher using qualitative techniques for the first time and it offers well sign-posted procedures. In the method
conceptual
a number of guidelines and procedures. The grounded theory is iterative, requiring a steady movement between
concept and data, as well as comparative, requiring a constant comparison across types of evidence to control the
conceptual level and scope of the emerging theory.
The goal of grounded theory is seeking a theory that is intimately tied with the evidence, so that the resultant theory
is likely to be consistent with empirical data (Orlikowski 1993; Eisenhardt 1989). Data collection, coding rationale,
integration of categories, abstracting from the data and construction of theory are thus guided by theory as it
emerges. Hughes and Wood-Harper (1999) report that the main application areas of grounded theory are most
notably in Glaser and Strauss' own research into status passage, but also in a number of other, usually medical
or nursing related areas such as - experiences with chronic illness (Charmaz, 1980); the management of a
hazardous pregnancy (Corbin, 1992) and homecoming (Hall, 1992). Additionally much work has been done with
respect to guidance on the use of grounded theory method. Most notable amongst them include Turner (1983);
Martin and Turner (1986); Strauss (1987); Strauss and Corbin (1990); Dey (1999); Charmaz (2003, 2006, 2008);
Jones and Alony (2011).
The use of grounded theory has also spread to other disciplines including research in information systems (Torasker,
1991; Pidgeon et al, 1991; Oliphant and Blockley, 1991; Pries-Heje, 1992; Orlikowski, 1993; Pettigrew, 1990;
Calloway and Ariav, 199l; Baskerville and Pries-Heje, 1995, 1998). The most notable use of grounded theory in
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IS research is that by Orlikowski (1993) in which she presents findings of a study into the adoption and use of
CASE tools. In this study the use of grounded t
contextual and processual elements as well as the action of key players associated with organizational change
elements that are often omitted in IS studies. The grounded theory fitted well with the interpretivist rather
than positivst nature of this research. Grounded theory studies in this interpretivist tradition have become
increasingly common in the IS research literature precisely because the method is useful in developing
context-based, process-oriented descriptions and explanations of phenomenon (Myers, 1997; Urquhart,
2001).
Hughes and Howcroft (2000) consider that the individual researcher plays a critical role in an interpretive
study. They maintain that using the grounded theory procedures may be a way for a researcher to deal with
some of the uncertainty that some researchers feel when faced with data collection and analysis in
interpretive studies. Notably they point to the fact that for novice researchers (or experienced researchers
new to interpretive studies) grounded t
factor in the stressful and uncertain nature of conducting qualitative research (Hughes and Jones, 2003).
Grounded theory is a general style of doing analysis that does not depend on any particular disciplinary perspectives
(Strauss 1987) and, therefore, would seem to lend itself to information systems research, which can be described
as a hybrid discipline. The main aspect of grounded theory, which differentiates it from other qualitative research
methods, is its emphasis upon theory development (Strauss and Corbin, 1998). Theory is grounded when it emerges
from and generates explanations of relationships and events that reflect the life experiences of those people and
processes that the researcher is attempting to understand. It also differs from other qualitative approaches,
because traditional qualitative approaches collect data first before commencing the analysis and long after they
have left the research site. In contrast, grounded theory uses the emerging theoretical categories to shape the
data collection while doing the fieldwork (data collection and analysis proceed simultaneously). By analysing
data from the lived experience of the research participants, the researcher can, from the beginning attends to how
they construct their world.
The use of grounded theory is founded on the premise that the generation of theory at various levels is
indispensable for a deep understanding of social phenomena (Glaser and Strauss 1967; Glaser 1978). It requires
that the researcher demonstrates theoretical sensitivity (Glaser and Strauss 1967; Glaser 1978) by being well
grounded in technical literature as well as from personal and professional experience in collection and analysis
of data (Strauss and Corbin 1990). It encourages researchers to steer their thinking out of the confines of technical
literature and avoid standard ways of thinking about the data. The interplay between emergent theory and technical
literature comes to the fore when extending generalisations from the study, which is achieved by either integrating
supplementary or conflicting analysis into the theory by including them as categories or conditions, or criticising
them in terms of what has emerged (Strauss 1987). Grounded theory is particularly suitable for a case study
aimed at exploring the factors that influence the adoption of Internet in Small to Medium-sized Enterprises. It is
useful for understanding contextual elements (Orlikowski 1993) that constituted the main focus of this case study.
One very practical problem with grounded theory is that the method is extremely labour intensive, requiring the
investment of considerable cognitive effort by the researcher. However, the author believes that grounded theory
technique is a suitable approach to use, especially when a researcher needs to analyse large quantities of
unstructured or semi-structured qualitative data. This section has presented and discussed grounded theory as a
practical tool for collecting and analysing qualitative data. The description of the procedures involved in collecting
and analysing data in grounded theory is the topic of the next section.
3. Grounded theory procedures
The previous section explicated grounded theory method. The defining characteristic of grounded theory is
that of a general methodology for discovering theory that is grounded in data systematically gathered and
analysed. The theory evolves during actual research, and it does this through a continuous interplay between
analysis and data collection; data analysis guides future data collection. In this section consideration will be given
to the details of the procedures associated with data collection and analysis in grounded theory method.
Strauss and Corbin (1990) identify three levels of analysis - (a) to present the data without interpretation and
abstraction, the participants tell their own story; (b) to create a rich and believable descriptive narrative using field
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notes, interview transcripts and researcher interpretations; and (c) building a theory using high levels of
interpretation and abstraction. This research combines the second and third approaches, to present rich and
detailed descriptions, which allows the reader to make sufficient contextual judgements to transfer the case study
findings to alternative settings. The concern here is with the multiple constructions of reality as experienced by Small
to Medium-sized Enterprises.
Data analysis in grounded theory involves specific procedures which, when applied appropriately and with
vigilance will result in theory that is rigorous and well grounded in the data. Strauss (1987) points out that the
procedures should be thought of as rules of thumb, rather than hard or fixed rules, and advises researchers to
study these rules of thumb, use them, and modify them in accordance with the requirements of their research. In
addition, Strauss and Corbin (1998) warn researchers that rigid adherence to any procedure can hinder the
analytic process and stifle creativity.
An example application that demonstrates how grounded theory was applied to an interpretive in-depth case
study research is presented in the section titled application of grounded theory. Recording of data may be
thought of as a pre-analytic step of grounded theory method and it is said to be essential to the successful
generation of grounded theory (Hutchinson, 1988). The grounded theory approach involves coding the assignment
of themes and concepts to a selected unit such as sentences taken from an interview transcript. The concepts are
combined into related categories; links between categories are identified and verified against the data, and
selective coding attempts to integrate the categories into a theory, which accounts for the phenomenon being
investigated. The subsection below discusses the process of analysis in grounded theory which is coding data
(that comprises open, axial and selective); memo writing and theoretical sampling.
4. Coding
Codes can take the form of a straight forward category label or a more complex one (example a metaphor)
(Miles and Huberman, 1994). The coding of data such as field notes and interview transcripts poses questions such
as what does this incident indicate? Coding gets the researcher off the empirical level by fracturing the data,
and then conceptually grouping it into codes that then become the theory which explains what is happening in
the data (Glaser, 1978). Researchers use codes to pull together and categorise a series of otherwise discrete events,
statements, and observations which they identify in the data (Charmaz, 1983).
Open coding is the analytic process through which concepts are identified and their properties and dimensions
are discovered in data. It is the part of analysis that pertains specifically to the naming and categorising of
phenomena through close examination of the data. ... During open coding the data are broken down into discrete
parts, closely examined, and compared for similarities and differences, and questions are asked about the
phenomena as reflected in the data (Corbin and Strauss, 1990). The researcher compares incident to incident
with the purpose of establishing the underlying uniformity and its varying conditions (Glaser, 1978). Events,
happenings, objects and actions/ interactions that are found to be conceptually similar in nature or related in
meaning are grouped under more abstract concepts termed "categories" (Strauss and Corbin, 1998).
Glaser (1978) describes a set of three questions that should guide the open coding. What is this data a study of?
This question continually reminds the researcher that his original intents on what he thought were going to study
just might not be. What category does this incident indicate? The continual asking of this question keeps the
analyst from getting lost in the re-experiencing of his data by forcing him to try and generate codes that relate
to other codes. It forces code that earns its way into the theory by its grounding in the data. What is actually
happening in the data? What is the basic social psychological problem(s) faced by the participants in the action
scene? These three types of questions keep the researcher theoretically sensitive and transcending when
analysing, collecting and coding the data. They force the researcher to focus on patterns among incidents,
which yield codes, and to rise conceptually above fascinating experiences. It is important to emphasise that
researchers make codes fit the data, rather than force the data into codes.
Axial coding involves re-building the data (fractured through open coding) in new ways by establishing
relationships between categories and their subcategories. It is termed "axial" because coding occurs around the
axis of a category, linking categories at the level of properties and dimensions (Strauss and Corbin, 1998). Axial
codes typically represent categories that describe the open codes. The researcher continues to code and
compares the concept to more incidents (Glaser, 1978). Comparison enables the identification of variations in
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the patterns to be found in the data. Data coding at this level is intended to elevate the data to higher levels
of abstraction (Hutchinson, 1988). During axial coding, the analyst begins to fit the pieces of the data 'puzzle'
together, which were fractured during open coding. Each piece (e.g., category and subcategory) has its place in
the overall explanatory scheme. When building a puzzle, the analyst might pick up a piece and ask, "Does this
go here or there?" The analyst's first attempts are often trial and error. Later, as he becomes more theoretically
sensitive, making the fit between conceptual indicator and category becomes easier.
Selective coding: the aim of selective coding is to integrate and refine the categories into a theory, which
accounts for the phenomenon being investigated (Darke et al, 1998) and validates the statements of relationships
among concepts, and fills in any categories in need of further refinement. In selective coding the researcher
reduces data from many cases into concepts and sets of relational statements that can be used to explain, in a
general sense, what is going on (Strauss and Corbin, 1998).
5. Memo writing
Memos are devices that depict the relationship among concepts. It is an important ways of keeping records of
analysis. Martin and Turner (1986) and Strauss (1987) discuss the processes involved in detail. Memo writing
takes place throughout the research process starting with the first interview. They serve a dual purpose of
keeping the research grounded and maintaining awareness for the researcher. Memos provide an opportunity
to generate and develop explanations of the emerging concepts, and to discern some of the interrelationships
which exist between them. The memo informs what the code is about and provides the pivotal step of breaking
the categories into components and elaborating the codes. Glaser (1978) considers writing of theoretical memos as
the core stage in the process of generating theory. Glaser defines memo as "the theorising write-up of ideas
about codes and their relationships as they strike the analyst while coding ... memo can be a sentence, a
paragraphs or a few pages ... it exhausts the analyst momentary ideation based on data with perhaps a little
conceptual elaboration". Memos don't just report data; they tie together different pieces of data into a
recognisable cluster, often to show that those data are instances of a general concept.
Memos are one of the most useful and powerful sense-making tools at hand for researchers to use during
analysis. The advice is to 'stop and memo' as coding sparks off ideas. You are writing memos to yourself,
secondarily to colleagues. Memoing helps the analyst move easily from empirical data to conceptual level,
refining and expanding codes further, developing key categories and showing their relationships, and building
towards a more integrated understanding of events, processes, and interactions in the case. Memoing
develops the core category around which the other categories integrate. The core category integrates the
theory according to the emergent perspective of investigation and thereby defines its cut-off points.
However, the core category has earned its relevance through the grounding of the theory in the domain. 'It
must be central, that is related to as many other categories and their properties as possible... and account for
a large portion of the variation in a pattern of behaviour' (Glaser, 1978). It must also occur frequently, be
completely variable, and 'have a clear and grabbing implication for formal theory' (Glaser, 1978). Memos are a
rapid way of capturing thoughts that occur throughout data collection, data reductions, data display,
conclusion drawing and final reporting. It saturates dimensions of the main categories that have emerged
through coding, and constantly generates open questions for further coding and data collection. At the end of
the process memos have to be sorted and integrated. Sorting memos simply means putting those that
elucidate the same category together in order to clarify its dimensions and to distinguish it from the other
categories.
6. Theoretical sampling and comparing
Two analytic processes contribute to raising categories to conceptual categories - constant comparison, which
is central in generating grounded theory and theoretical sampling (Glaser and Strauss, 1967). Both of these
processes are achieved through a process Glaser (1978) calls theoretical sampling and the selective sampling of
the literature. Essentially, the researcher needs to confront the conceptual categories with more data in order
to define them carefully, delineate their properties, explicate their causes, and demonstrate the conditions
under which they operate, and spell out their consequences.
The constant comparative is central to the data analysis in generating grounded theory. The purpose is to
build and clarify a category by examining all the data it covers and variations from it. The researcher takes a