doi:10.1111/j.1365-2575.2009.00328.x
Info Systems J (2010) 20, 357–381
357
Putting the ‘theory’ back into grounded
theory: guidelines for grounded theory
studies in information systems
Cathy Urquhart,* Hans Lehmann† & Michael D. Myers‡
*Department of Information Systems and Operations Management, University of
Auckland, Private Bag 92019, Auckland, New Zealand, email: [email protected],
†
School of Information Management, Victoria University, Wellington, New Zealand, email:
[email protected], and ‡Department of Information Systems and Operations
Management, University of Auckland, Private Bag 92019, Auckland, New Zealand, email:
[email protected]
Abstract. Over the past decade, there has been increasing interest in the use of
grounded theory in information systems research. Grounded theory is a qualitative
research method that seeks to develop theory that is grounded in data systematically gathered and analysed. The purpose of this paper is to suggest guidelines for
grounded theory studies in information systems. Our guidelines are based on a
framework for theorizing in grounded theory studies that focuses on conceptualization and theory scope. Our hope is that the guidelines will help to raise the
quality and aspirations of grounded theory studies in information systems.
Keywords: grounded theory, research methods, theory building, guidelines for
grounded theory
INTRODUCTION
Over the past decade, there has been increasing interest in the use of grounded theory in
information systems research (Howcroft & Hughes, 1999; Hughes & Howcroft, 2000; Urquhart, 2001; 2007; Lundell & Lings, 2003; Bryant et al., 2004; Lings & Lundell, 2005).
Grounded theory is a qualitative research method that seeks to develop theory that is
grounded in data systematically gathered and analysed. According to Martin & Turner
(1986), grounded theory is ‘an inductive, theory discovery methodology that allows the
researcher to develop a theoretical account of the general features of a topic while simultaneously grounding the account in empirical observations or data’. The major difference
between grounded theory and other qualitative research methods is its specific approach to
theory development – grounded theory suggests that there should be a continuous interplay
between data collection and analysis.
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In information systems, grounded theory has proved to be extremely useful in developing
context-based, process-oriented descriptions and explanations of information systems phenomena (Myers, 1997; Goulielmos, 2004). It offers relatively well-signposted procedures for
data analysis, and potentially allows for the emergence of original and rich findings that are
closely tied to the data (Orlikowski, 1993). It is this last feature that provides researchers with
a great deal of confidence, as for each concept produced, the researcher can point to dozens
of instances in the data that relate to it.
However, grounded theory studies in information systems have been criticized for having a
relatively low level of theory development. Many grounded theory studies in information
systems use grounded theory only as a coding method, and, indeed, the term ‘grounded
theory’ itself has almost become a blanket term for a way of coding data (Hughes & Howcroft,
2000; Bryant et al., 2004; Urquhart, 2007). Interestingly, this particular usage of the grounded
theory method is not limited to the field of information systems. Scholars in other fields have
highlighted exactly the same issue, of the grounded theory method being viewed primarily as
a way of coding data rather than a method for generating theory (Becker, 1983; Benoliel, 1996;
Green, 1998; Elliott & Lazenbatt, 2005).
We believe that this use of grounded theory – while appropriate in some cases – is
somewhat limited. Grounded theory is not just a coding technique, but offers a comprehensive method of theory generation. In fact, one of the attractions of grounded theory for
information systems researchers is the promise that it will help us to develop new theories
of information systems phenomena – theories that are firmly grounded in empirical phenomena. Given the calls for information systems researchers to focus more on theory development (Watson, 2001; Weber, 2003), we suggest that grounded theory can be used to help
generate theories in information systems. Hence, a key question that this paper seeks to
address is: ‘How can the grounded theory method be leveraged to build theory in information systems?’
The purpose of this paper, therefore, is to suggest guidelines for conducting and evaluating
grounded theory studies in information systems. Our hope is that the guidelines will help to
raise the quality and aspirations of grounded theory studies in information systems, and, as a
consequence, contribute to theory development in the field. This paper should be of interest to
all information systems researchers using or considering using grounded theory, and to all
other information systems researchers who, while not using grounded theory themselves,
might like to understand its potential contribution.
This paper is organized as follows. In the next section, we clarify the nature of
grounded theory and outline its theoretical and philosophical foundations. In the third
section, we discuss the issue of theory building in information systems, and what
grounded theory can contribute to theory building in the IS discipline. In the fourth section,
we propose a framework for theorizing using grounded theory. In the fifth section, we
discuss our suggested guidelines for the conduct and evaluation of grounded theory studies
based on the framework. In the sixth section, we use these guidelines to analyse three
grounded theory studies in information systems. The final section is the discussion and
conclusions.
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GROUNDED THEORY METHOD – AN OVERVIEW
Barney Glaser and Anselm Strauss published a book entitled ‘The Discovery of Grounded
Theory’ in 1967 (Glaser & Strauss, 1967). This book outlined a research methodology that
aimed at systematically deriving theories of human behaviour from empirical data. It was a
reaction against ‘armchair’ functionalist theories in sociology (Dey, 1999; Kendall, 1999).
Several more books and articles by the co-originators followed, which developed and later
debated the method (Glaser, 1978; 1992; 1995; 1998; 1999; 2001; Strauss, 1987; Strauss &
Corbin, 1990; 1994; 1997).
Following the publication of this seminal work in 1967, grounded theory spread fairly quickly
as a qualitative research method within the social sciences and many other fields. For
example, Benoliel (cited in Dey, 1999, p. 412) says there was a 70-fold increase in published
papers with ‘grounded theory’ as a keyword in the health field over the previous decade. By the
mid-1990s, the methodological procedures of grounded theory had permeated qualitative
research to such an extent that Miles and Huberman labelled it a ‘ “common feature” [of
qualitative] analytic methods’ (Miles & Huberman, 1994, p. 9).
There are various definitions of grounded theory. The earliest, a process definition by the
creators themselves, defines it as ‘the discovery of theory from data – systematically obtained
and analysed in social research’ (Glaser & Strauss, 1967, p. 1). A more detailed definition is
as follows:
The methodological thrust of grounded theory is toward the development of theory, without
any particular commitment to specific kinds of data, lines of research, or theoretical interests . . . Rather it is a style of doing qualitative analysis that includes a number of distinct
features . . . and the use of a coding paradigm to ensure conceptual development and
density (Strauss, 1987).
From these various definitions, we can discern four distinctive characteristics of the grounded
theory method. These are as follows:
1 The main purpose of the grounded theory method is theory building.
2 As a general rule, the researcher should make sure that their prior – often expert –
knowledge of the field does not lead them to preformulated hypotheses that their research then
seeks to verify – or otherwise. Such preconceived theoretical ideas could hinder the emergence of ideas that should be firmly rooted in the data in the first instance.
3 Analysis and conceptualization are engendered through the core process of joint data
collection and constant comparison, where every slice of data is compared with all existing
concepts and constructs to see if it enriches an existing category (i.e. by adding/enhancing its
properties), forms a new one or points to a new relation.
4 ‘Slices of data’ of all kinds are selected by a process of theoretical sampling, where the
researcher decides on analytical grounds where to sample from next.
The first characteristic implies that researchers who use grounded theory only as a way of
coding data are neglecting the main purpose of the method – which is to build theory. Theory
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building is why grounded theory was developed in the first place. In developing theory, the
researcher needs to be capable of theoretical sensitivity. Theoretical sensitivity is based on
being steeped in the field of investigation and associated general ideas, so that a researcher
understands the context in which the theory is developed (Glaser, 1978).
The second characteristic – of no preformulated hypotheses – underscores the first – i.e.
that theory building, not theory verification, is the main and only aim of grounded theory.
However, it is often held to imply that the researcher should not look at the existing literature
before doing the empirical research. This injunction is mainly designed to ensure that the
researcher does not impose ideas from the literature on that coding. If the researcher starts
with an existing theory, then the aim of the grounded theory method is to enhance the theory,
widen its scope or in other ways improve it – but not to verify or falsify it. In a footnote in the
original 1967 book, Glaser and Strauss (1967, p. 3) state that the researcher does not
approach reality as a tabula rasa but must have a perspective that will help him or her abstract
significant categories from the data. Dey (1999) speaks of the difference between an ‘open
mind and an empty head’ – both he and we believe that the founders of grounded theory
inclined to the former position.
The third characteristic requires joint interaction between data collection and comparison.
Although comparative analysis has been a standard method in social research long before
1967, the specific rigour and the level of detail demanded by grounded theory are significantly
greater. Glaser & Strauss (1967, p. 43) emphasize that the data collection, coding and analysis
need to be done together because separating these operations might hinder the development
of theory. They give the example of a fresh analytic idea emerging in the coding that may
redefine the collection but is ignored due to pre-established rules or routine – thus stifling the
generation of theory. The idea of joint interaction between data collection and analysis is
central in grounded theory.
As for the fourth characteristic, the term ‘slices of data’ was coined by Glaser and Strauss
to reflect the fact that different kinds of data give the researcher different views from which to
understand a category or to develop its properties. They say ‘these different views we have
called slices of data’ (Glaser & Strauss, 1967, p. 65). Theoretical sampling is where the
researcher uses the categories, concepts and constructs established so far to direct further
data collection (Glaser, 1978). In the original book, a whole chapter is devoted on how
to select sample groups to aid development of the emerging theory (Glaser & Strauss, 1967).
Philosophical foundations of grounded theory
There is considerable disagreement and debate with regard to the underlying philosophical
assumptions of grounded theory. Grounded theory belongs to the realm of qualitative empiricism and has been variously described as positivist, interpretive or critical. However, Bryant
(2002) is critical of the founders for their phenomenalist approach, which assumes that a theory
is just waiting to be discovered in the data. Clearly, this idea does not take into account the
subjectivism of coding. We tend to see this philosophical uncertainty as simply reflective of the
intellectual climate of the time in which Glaser and Strauss introduced grounded theory. Holton
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(2007) says that Charmaz (2006) identifies the crux of the matter as a lack of clarity in the
seminal work of 1967, and suggests that a search for a position is futile.1
Following Myers (1997), we take the view that grounded theory is primarily a qualitative
research method for gathering and analysing data. As a research method, grounded theory is
independent of the underlying epistemology. This means that grounded theory is itself, as
Glaser describes, ‘paradigmatically neutral’ (Glaser, 2001). It can be used in positivist studies
(Lehmann, 2003), interpretive or critical studies (Annells, 1996; Urquhart, 2001; CecezKecmanovic et al., 2008). Grounded theory’s neutrality also makes it useful for mixedparadigm research (Charmaz, 2005).
A key point we wish to make here is that a researcher’s own ontological and epistemological
position will impact on their coding and analysis of the data and the way in which they use
grounded theory (Madill et al., 2000). Our suggested guidelines, however, apply to all kinds of
grounded theory.
Two strands of grounded theory
In subsequent years the grounded theory method has evolved into two distinct variants, one
favoured by Glaser, the other by Strauss (Melia, 1996). A very public disagreement between
these two co-founders of grounded theory occurred on the publication of Strauss and Corbin’s
book in 1990 (Strauss & Corbin, 1990). This book was written in response to their students’
requests for a ‘how to’ manual of grounded theory, and contains clear guidelines and procedures. In Glaser’s view, this formalization is far too restrictive, to the extent that it may strangle
any emergent conceptualizations and instead force the concepts into a preconceived mould.
Glaser felt so strongly about the Strauss and Corbin book that he requested it to be pulled from
publication, and when it was not, wrote a correctional rejoinder ‘Emergence vs. Forcing: Basics
of Grounded Theory Analysis’ (Glaser, 1992). He sums up his critique as follows:
If you torture the data long enough, it will give up! . . . [In Strauss & Corbin’s method] the data
is not allowed to speak for itself as in grounded theory, and to be heard from, infrequently it
has to scream. Forcing by preconception constantly derails it from relevance (Glaser, 1992,
p. 123).
Glaser disagreed on two fundamental issues. First, Strauss & Corbin (1990) suggested
breaking down the coding process into four prescriptive steps (open, axial, selective and
‘coding for process’), whereas Glaser uses just three: open, selective and theoretical coding,
at incremental levels of abstraction. Second, Glaser objected to the use of a coding paradigm
and the ‘conditional matrix’, which are designed to provide ready-made tools for the conceptualization process. Glaser pointed out that to ‘force’ coding through one paradigm and/or
down one conditional path was not grounded theory, but conceptual description, which ignored
1
For those readers interested in philosophical reinterpretations of grounded theory, we can do no better to point interested
readers to Charmaz (2006) for a constructivist re-rendering of grounded theory, and to Clarke (2005) for a post-modern
view.
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the emergent nature of grounded theory (Glaser, 1992). Also, the coding paradigm used by
Strauss and Corbin – which suggests that the researcher looks at context, conditions, action/
interactional strategies, intervening conditions and consequences for the purposes of establishing categories and relationships – can be further critiqued as a departure from traditional
grounded theory. First, this coding paradigm provides only one particular view of a phenomena. By contrast, Glaser (1978) suggests 18 coding families, which cover ideas like dimensions and elements, mutual effects and reciprocity, social control, recruitment and isolation,
and many other ideas for categories and relationships. Second, we have found that the
insistence on a phase of axial coding, where categories and relationships are considered
simultaneously using the coding paradigm, causes real difficulty for some researchers, especially novices. Selective coding, followed by theoretical coding, in our view, allows for more
abstract theorizing, as has been noted by Kendall (1999).
Given that this is such a well-documented disagreement between the two co-founders of
grounded theory, we believe that information systems researchers need to be aware which
version of grounded theory they are using. The Strauss and Corbin (1990) book is arguably the
most widely known, and regarded as the most accessible. However, it describes only one
version of grounded theory, and has also been described as rather formulaic and overburdened with rules (Melia, 1996; Kendall, 1999).
The generation of grounded theory
The process of generating a grounded theory is summarized in Figure 1. A researcher begins
a grounded theory study with ideational constructs, such as ‘hunches’ (Miles & Huberman,
1984), for investigation. It is important to note that despite the injunction to try to avoid having
any preconceived theoretical ideas before starting the research, these seed concepts or early
hunches ‘can come from sources other than data’ (Glaser & Strauss, 1967, p. 6). These seed
concepts help a researcher to select an area of enquiry and define the topic. The area of
enquiry is called the ‘substantive area’ in grounded theory terminology.
Next, the researcher takes ‘slices of data’ (Glaser & Strauss, 1967) from the area of enquiry
and codes them into conceptual categories. These slices of data can come from many different
sources, and can be collected using many different data collection methods. This of course
provides an opportunity for corroboration or triangulation of the data.
As the first element of a grounded theory, these conceptual categories are first described by
their properties. Using additional slices of data, the categories are further conceptualized into
theoretical constructs by establishing ‘relations’ between them (Glaser & Strauss, 1967, p. 35).
Constant comparison with previous data, categories, concepts and constructs is the key.
Additional data are acquired using theoretical sampling until the existing categories are
‘saturated’ (i.e. there are no more instances of them in the data), and until no more new
conceptual categories or relations emerge. The ‘saturated’ concepts are then reduced as much
as possible to the relationships between core categories, which then form a ‘grounded’ theory.
The grounded theory that is produced is thus firmly anchored in the data that led to its
formulation.
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'Lived' Experience
Anecdotal Evidence
Other Theories
Hunches
Lead to
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Area of Enquiry
First
‘Slices-of-Data
Categories and
Their Properties
Theoretical
Sampling
Adding Further Data
Additional
to Saturate Categories
Additional
Additional
‘Densification’ of the
‘Relations’ between
‘Slices-of-Data
Categories
Grounded Theory
Relationships
between
Categories
Figure 1. Cycle of data collection and analysis in the grounded theory method [after Lehmann (2001) and Fernandez
et al. (2002)].
Grounded theory views the process of theory generation as one of increasing the level of
abstraction, range and scope of the theory.
Generally speaking, there are three levels of theory in the grounded theory method.
Narrow concepts
Seed concepts, which get the theory building process started, are of limited use and have the
least range and scope. They are conceptual constructs themselves, although they are often no
more than hunches, and have little, if any, empirical grounding. For example, Sarker et al.
(2001) say that they started their research project by identifying aspects and concepts from
their own backgrounds that could be brought to bear in their theorizing about virtual collaboration while guarding against becoming captive to any particular literature. They describe this
first stage as one where they informally interacted with the data.
Substantive theories
Theories that have been generated from within a specific area of enquiry using grounded
theory methods are termed ‘substantive’ theories. They apply to the substantive area of
enquiry, but are independent of and beyond the data analysed and the incidents observed
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3. Formal Theories
2. Substantive Theories
Categories
Categories
Relations
Categories
and Their
1. Narrow Properties
Concepts
Figure 2. The progression of theory development in the grounded theory methodology (adapted from Lehmann, 2001).
(Glaser & Strauss, 1967). For example, Orlikowski (1993) developed a substantive theory
relating to the use of CASE (Computer Aided Software Engineering) tools in organizations.
She says that the concepts developed were intimately related to (because they were derived
from) the arena of actual CASE tools adoption and use. At the same time, however, the
theoretical framework was ‘sufficiently general to be applicable to a range of situations’
(Orlikowski, 1993, p. 335).
Formal theories
The highest level of abstraction in grounded theory is called a ‘formal theory’. Formal theories
focus on conceptual entities (Strauss, 1987), such as organizational knowledge, organizational
learning or collaborative work.
Figure 2 depicts this hierarchy of theories. The general idea of using grounded theory is that
as the researcher moves up the level of abstraction, the range and scope of the theory
increases.
Glaser & Strauss (1967) suggest that in order to generate formal theory, a comparative
analysis should be made among different substantive theories that fall within a particular
substantive area and by comparing substantive theoretical ideas from many different cases.
Substantive theory can be used as a springboard towards formal theory by providing initial
direction in developing conceptual categories. Glaser (1978) makes the point that constant
comparative analysis can generate both substantive and formal theory. He further contends
that in any study each type of theory can shade into the other.
BUILDING THEORY IN THE INFORMATION SYSTEMS DISCIPLINE
Having examined the nature of grounded theory, its history, foundations and how a grounded
theory is generated, we now turn our attention to how grounded theory can be applied
specifically in the discipline of information systems.
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The role of theory in information systems has commanded attention in recent years. For
example, Gregor (2006) proposes a taxonomy of theory in information systems that includes
the following categories – theory for analysing, theory for explaining, theory for predicting,
theory for explaining and predicting, and theory for design and action. We suggest that
grounded theory has the capability to generate theory that exists in all these categories
because it contains the essential building blocks of any theory – constructs in the form of
categories and relationships between those constructs in the form of theoretical coding. Dey
(1993) uses the useful analogy of a wall of theory building – the categories are the bricks, the
relationships the mortar between the bricks – but importantly, the emergent theory is informed
by the research objectives. Gregor (2006) bemoans the use of vague terms for causality, like
associated with or linked to, but from our perspective, it all depends for what purpose the
theory is being developed – interpretive researchers find the search for causality limiting. What
is certain is that because grounded theory has an emphasis on constructs and relationships,
it is relatively easy to generate propositions relating to information systems phenomena that
may – or may not – be testable.
One well-known characteristic of the information systems research domain is the use of
many theories borrowed from other disciplines (Baskerville & Myers, 2002). Although importing
theories from outside the discipline is often valuable, we suggest that grounded theory could
be used to build theories from within the field itself. For example, Orlikowski & Iacono (2001)
pointed out the lack of presence of the IT artefact in theorizing in the information systems
discipline. We suggest that grounded theory might well be useful in developing theories about
such phenomena.
Our next section introduces a framework for theorizing in grounded theory studies, and
discusses levels of theory (theory scope), and the degree to which concepts are developed
(theory conceptualization). This framework is then used as a basis for guidelines for information systems researchers using grounded theory.
A FRAMEWORK FOR THEORIZING IN GROUNDED THEORY STUDIES
We have observed in our own grounded theory work and in that of others that two aspects are
important for theorizing. These two aspects are the degree of conceptualization and theory
scope. These two dimensions underline the grounded theory process of theory building –
conceptualization that moves beyond mere description, and also considers relationships
between categories, and pitching the theory scope at the appropriate level. The first axis – the
degree of conceptualization, can be seen as relating to the process of building a grounded
theory, and relates to the degree of analysis carried out. The second axis, theory scope, can
be seen to relate to the outcome of building a grounded theory. A summary of the framework
is shown in Figure 3.
As the main purpose of using grounded theory is theory building, researchers should aim to
develop theories of greater scope. The more the data analysis moves from description to
theory, and the more the scope of the theory increases with the development of formal
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More
Formal
Concepts
Theory
Scope
Substantive
Focus
Bounded
Context
Less
Description Interpretation
Less
Theory
More
Degree of Conceptualisation
Figure 3. A framework for analysing grounded theory studies.
concepts, the better. Generally speaking, grounded theory studies should aim for the top
right-hand corner of the figure. Of course, the framework shown in Figure 3 might also be
useful for other research approaches, but we suggest it is especially applicable to grounded
theory. The axes of the figure will now be explained in more detail.
Degree of conceptualization
The first axis of our framework is the degree of data analysis, corresponding to the horizontal
axis of Figure 3. A key objective of grounded theory research is to aim for greater and greater
depth of analysis of the data (Glaser & Strauss, 1967). In the Glaser variant, the process of
discovering grounded theory has three principal stages that successively increase the depth of
analysis.
Description
The first stage yields descriptions. Descriptions are the most basic of conceptual constructs,
where analysis has not proceeded beyond identifying concepts at the level of ‘categories’.
Categories may have detailed ‘properties’, which are usually arrived at through a process of
open coding.
Interpretation
The second stage is the interpretation of categories and properties. Selective coding is
employed to refine conceptual constructs that can help explain whatever interaction occurs
between the descriptive categories (Glaser, 1978). This clear aetiological focus aims to
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understand and explain one or more specific areas under investigation. At this point, the
research problem becomes more refined, as aspects of the research problem become apparent through selective coding.
Theoretical coding
The third stage, theoretical coding, results in the formulation of a theory. The aim is to create
inferential and/or predictive statements (sometimes in the form of hypotheses) about the
phenomena. This is achieved by stipulating explicit relationships between individual interpretive constructs – these relationships can be associations or influences, or can be causal. The
system of inferences covers the whole of the area under investigation. Without theoretical
coding, there is no theory, as relationships between constructs have not been considered.
Analytic memos, where relationships between categories are considered, are invaluable at this
stage and assist the theoretical coding.
There are a number of options open to the grounded theorist when considering relationships
between categories. Glaser (1978) suggests 18 theoretical coding ‘families’. Strauss & Corbin
(1990) suggest a coding paradigm. Clearly, how much attention is paid to the precise nature
of the association between constructs is critical to theorizing.
Theory scope
The second dimension of the framework is that of theory scope. According to the tenets of
grounded theory, the primary objective of the method is to develop theories of greater and
greater scope (Glaser & Strauss, 1967, e.g. Dey, 1999).
Bounded context
Seed concepts within a ‘bounded context’ represent theory with the narrowest scope. Seed
concepts, bounded by their immediate context within a specific area of inquiry, are often little
more than hunches. These seed concepts have little empirical base; they simply represent
formal postulates of the researcher’s hunches from ‘lived experience’, from anecdotal evidence
that the researcher has about the field of enquiry, or even from limited, exploratory fieldwork.
Substantive focus
Theories with a ‘substantive focus’ are wider than theories within a bounded context. A
substantive theory extends its predictive and explanatory power to the specific set of phenomena from where it was developed. This kind of theory is no longer simply based on seed
concepts but has been developed by the rigorous application of grounded theory procedures.
A substantive theory has significant empirical support.
Formal concepts
The widest form of grounded theory that can be developed is a formal theory that uses formal
concepts. A formal theoretical construct applies to the conceptual area that it has been
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developed for, which usually spans a set or family of several substantive areas. For example,
a formal theory in information systems would apply to many different kinds of situations,
systems and organizations (e.g. a theory regarding the implementation of information systems
in general). While we have not found any instances of formal theories built from the use of the
grounded theory method in the information systems discipline, this has been achieved in the
social sciences – for instance, Biernacki’s (1986) theory of identity transformation. Clarke
(2005) gives some useful strategies for formulating theories at the meso and macro level of
analysis.
For a grounded theorist, there are thus three levels of theory. The promise of grounded
theory is that it can help a researcher to produce theories of greater and greater scope. Indeed,
the main objective of a grounded theorist is to move up along the left axis as much as possible.
Although our framework has two dimensions, we acknowledge that both axes are closely
related to each other. We developed the framework primarily as a device to clarify what good
grounded theory might look like. As we stated earlier, the main objective of grounded theory is
to develop theory that is grounded in data systematically gathered and analysed. Obviously,
the extent to which the data is analysed and conceptualized impacts the scope of the theory
developed. Ideally, a researcher using grounded theory should attempt to move from the
bottom left quadrant to the top right quadrant as much as possible (as per the diagonal arrow
in Figure 3). The next section suggests guidelines for grounded theory studies in information
systems using the two axes of Figure 3.
GUIDELINES FOR GROUNDED THEORY STUDIES IN INFORMATION SYSTEMS
A key question that this paper seeks to address is: ‘How can the grounded theory method be
leveraged to build theory in information systems?’ This section attempts to answer this
question by proposing guidelines for the conduct and evaluation of grounded theory studies in
information systems. These guidelines are oriented towards building theory in our field, and are
summarized in Table 1. The guidelines build on the two axes of the framework identified in the
fourth section, conceptualization and theory scope. The first three guidelines address how the
researcher might achieve the degree of conceptualization necessary to build a good theory
through analytic mechanisms, such as constant comparison. These guidelines can also be
seen as relating to the process of theory building. The final two guidelines give assistance with
the issue of theory scope by giving guidance on the level of theory and how it might be
integrated with the extant literature, an important aspect of theory building. Thus, these last two
guidelines deal with the theory that is the outcome of the first three stages.
Constant comparison
Constant comparison has been described as core to the grounded theory method (Charmaz,
2006). Constant comparison is the process of constantly comparing instances of data that you
have labelled as a particular category with other instances of data in the same category to see
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Table 1. Guidelines for grounded theory studies in information systems
1 Constant comparison
Constant comparison is the process of constantly comparing instances of data
labelled as a particular category with other instances of data in the same category.
Constant comparison contributes to the development of theory by exposing the
analytic properties of the codes and categories to rigorous scrutiny. This guideline for
data analysis encourages researchers to be both rigorous and theoretical (Charmaz,
2006).
2 Iterative conceptualization
This guideline suggests that researchers should increase the level of abstraction and
relate categories to each other through a process of iterative conceptualization. In
grounded theory, this is done using theoretical coding. The relationships between
categories can be of many different types, not just causal. Theoretical coding
contributes to an understanding of relationships between the concepts or factors of a
theory. Theoretical memos are also very important to the development of theoretical
coding and the whole process of iterative conceptualization.
3 Theoretical sampling
This guideline stresses the importance of deciding on analytic grounds where to
sample from next in the study. Theoretical sampling helps to ensure the
comprehensive nature of the theory, and ensures that the developing theory is truly
grounded in the data.
4 Scaling up
This guideline suggests how a researcher might counter what is said to be a common
problem in grounded theory viz. the production of a low level theory, which is then
hard to relate to the broader literature. Scaling up is the process of grouping
higher-level categories into broader themes. Scaling up contributes to the
generalizability of the theory.
5 Theoretical integration
This guideline helps the researcher deal with what we think is an obligation of the
grounded theorist – theoretical integration. Theoretical integration means relating the
theory to other theories in the same or similar field. It is the process of comparing the
substantive theory generated with other, previously developed, theories. This principle
contributes to theoretical integration in the discipline and could help in the generation
of formal theories.
if these categories fit and are workable (Urquhart, 2001). Charmaz (2006) makes two points
about constant comparison. First, making comparisons between data, codes and categories
advances conceptual understanding because of the need to expose analytic properties to
rigorous scrutiny. Second, it makes the analysis more explicitly theoretical by asking ‘What
theoretical category are these data an instance of?’
A legitimate question to be asked here is, should researchers code at the word and sentence
level? Is it necessary to code at such a low level? From our perspective, the answer is a qualified
yes, depending on the phenomena investigated. Such low-level coding is appropriate for
interactional studies, because it means that the data are examined minutely, and just as
importantly, ‘lived with’ for a long time. However, where the unit of analysis is the organization,
word and sentence level coding may not always be as fruitful. That said, the insights that
low-level coding affords cannot be underestimated, for it is in this way that the grounded theory
method provides a chain of evidence like no other approach. The constant comparative method
means that there are always dozens of instances to support the theory that is produced.
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Constant comparison encourages the researcher to be both rigorous and theoretical
(Charmaz, 2006). Both Orlikowski (1993) and Hughes & Howcroft (2000) are good examples
of the use of constant comparison.
Iterative conceptualization
One unique aspect of grounded theory is what we have chosen to call iterative conceptualization – where theory is built in an iterative fashion by using theoretical coding, focusing
particularly on relationships between categories. These relationships can be of many kinds,
causal relationships being one of many options. One of the interesting paradoxes about
grounded theory is that, at first glance, it offers well-signposted procedures for theory building
for the novice (Urquhart, 1997). Yet we notice that many researchers get into difficulties at this
point, as theory building is an essentially creative process and cannot be achieved by following
procedures alone. Hence, the strengths of the method can only be truly leveraged if both
qualities of the method – systematic procedures and an iterative approach to conceptualization
– are fully employed. Iterative conceptualization is the plank on which theory generation is
based. A mechanistic application of coding stages will not yield the desired results in terms of
theory. The researcher using grounded theory needs to be alert to intuition and to think beyond
labels for the data.
In terms of doing iterative conceptualization, researchers have suggested a number of
alternatives. There are the coding stages of Strauss & Corbin (1990) (open coding, axial
coding, selective coding), the coding stages of Glaser (1992) (open coding, selective coding,
theoretical coding) or the coding stages of Charmaz (2006) (open coding, focused coding, axial
coding, theoretical coding). Whichever coding stages are used, the key thing is that all stages
are followed to allow adequate conceptualizations, which are the basis of a formed theory.
Miles & Huberman (1994) give a useful set of characterizations about codes that are of
assistance when assessing the data analysis component of grounded theory studies in
information systems. They describe three types of codes that can be equated to analytic level:
descriptive codes – attributing a class of phenomena to a segment of text, interpretive codes
– where meaning is attributed with reference to context and other data segments, and pattern
(or linked) codes – inferential and explanatory codes that describe a pattern. Clearly, it is
desirable that the researcher reaches the third stage, that of inferential and explanatory codes.
Axial coding (Strauss & Corbin, 1990) or theoretical coding (Glaser, 1978) are essentially
about relationships between categories – the very essence of theory building. Theoretical
coding contributes to an understanding of relationships between the concepts or factors of
a theory.
In our experience, it is in defining the relationships between categories that novice researchers often struggle to really achieve depth of theory. Establishing such relationships can be
assisted by the coding paradigm of Strauss & Corbin (1990) and/or with Glaser’s (1978) coding
families, which give many options for theory building, including causal relationships, and
generation of hypotheses. Other options include considering limit, range, intensity, intent,
aspects, types, dimensions, mutual interactions, ends and goals, clusters, and agreements.
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During this stage, it often becomes clear that some categories are properties of others, and as
thinking sharpens, category names often reflect analytic thinking as opposed to simply describing the phenomenon.
Iterative conceptualization thus helps to answer important theoretical questions concerning
‘what’ and ‘why’. Whetten (1989) says that the ‘what’ in a theory justifies the selection of factors
and the proposed (causal) relationships. The ‘why’ in a theory attempts to explain why the
factors are behaving the way they do. This aspect of a theory supplies the plausible, cogent
explanation for ‘why we should expect certain relationships in the what and how data’
(Whetten, 1989, p. 491).
Theoretical memos (Strauss, 1987; Charmaz, 2006) are a further aid to iterative conceptualization, as the writing of a memo creates a formal space in which the researcher can reflect
on the emerging theory. Examples of theoretical memos are rare in information systems, but
not in the social sciences (Charmaz, 2006). Examples of theoretical memos can be found in
Urquhart (1997; 2001).
Theoretical sampling
Theoretical sampling is deciding on analytic grounds where to sample from next (Glaser &
Strauss, 1967), and is an important aspect of grounded theory. Theoretical sampling can occur
at the group level (considering similar and different data sets) and at the category level through
‘slices of data’ (Glaser & Strauss, 1967). Through successive sampling according to the
emergent theory (Glaser, 1992), the research questions gradually become more refined, as
dimensions of the research problem become clearer through analysis (Dey, 1993). If the
researcher is guided by the emergent theory when collecting data, then there is very little
chance of the researcher imposing preconceived notions on the data. Theoretical sampling
also means that there is a focus on the development of research questions. Orlikowski (1993)
employed theoretical sampling in her study of organizational change and CASE tools.
Charmaz (2006) suggests that theoretical sampling assists delineation of category properties, relationships between categories, to saturate categories, to clarify relationships between
categories, to distinguish between categories, and to follow hunches about categories. Theoretical sampling is one of the foundations of grounded theory method – it enables both a focus
on the developing theory and ensures that the developing theory is truly grounded in the data.
Theoretical sampling can also be used to extend the scope of the generated theory.
Theoretical sampling is a key element of the method and the single most important contributor to the ‘fit’ of a theory. Without theoretical sampling and the constant comparison and
assessment of the contribution achieved by new slices of data, it will be impossible to establish
how ‘saturated’ the theory is. In fact, theoretical sampling is the single most important assurance that a theory ‘works’, i.e. explains ‘what is actually going on’ (Glaser & Strauss, 1967, p.
35). Most of the theoretical sampling in the information systems research literature is rather
weak and seems to have taken the path of ‘more-of-the-same’, which mainly serves to confirm
the properties of existing categories and can freeze the current conceptual level. ‘Same-datagroup’ is, however, but one of several options, some of them explicitly designed to extend
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scope and depth of the theoretical constructs created. Glaser & Strauss (1967, pp. 49–60) and
Glaser (1978, pp. 36–54) provide a detailed discussion of such theoretical sampling strategies.
This sampling for data that could enhance the theory is not only needed during a specific
research project, but also should be carried on even after a first cohesive theoretical construct
has been established. This is for two reasons: first, it enables maximum ‘fit’ of the theory by
keeping it up-to-date with changing circumstances; and second, it facilitates the extension of
the theory’s substantive limits.
Theoretical sampling ensures the comprehensive nature of the theory. Deciding on which
categories are ‘core’ categories and selectively coding until saturation is reached also provides
a comprehensive theory that is well grounded in the data. Because each category needs to be
‘saturated’, that is, well represented by many instances in the data, the theory generated is also
parsimonious. Whetten (1989) suggests that comprehensiveness and parsimony are two
important characteristics of theory.
Scaling up
Our collective experience with the grounded theory method tells us that first-time users tend to
get overwhelmed at the coding level. The attention to word- and sentence-level coding, while
giving rich insights to the researcher, naturally focuses the mind on the detail. However, we
believe it is important for researchers at some stage to try to rise above the detail in order to
consider the bigger picture.
One simple mechanism that we have used successfully is that of grouping high-level
categories into larger, broader themes. It is then much easier to relate these to competing
theories. The desired level of abstraction can be achieved by coding around one or two core
categories or themes (Glaser, 1978; 1992; Strauss, 1987).
In practice, we find that people end up with far more than one or two core categories,
particularly if they start with word- or sentence-level coding. This may be because the phenomenon being studied is not necessarily a process, and may have many different and distinct
elements. A more compelling general reason is that the bottom up derivation of the generated
theory makes it difficult to think abstractly. The very strength of grounded theory – its unique
tie to the data – may also be in fact the Achilles heel of the method. Thus, grouping high-level
categories (which may or not be named core categories) into higher-level core categories (or
themes) is a very useful practice to scale up the substantive theory. A similar tactic is to
generate propositions.
Glaser makes some useful suggestions for scaling up a theory (Glaser, 1978). First, the
rewrite method, where the theory is rewritten to omit specifics – so, for example, instead of
talking about the strategies used by analysts when talking to their clients, one could talk about
the strategies used by professionals when dealing with their clients. While there are no more
data points sampled, it nevertheless provides a starting point for increasing the level of
conceptualization. Second, the level of conceptualization can be raised by comparing it to the
data from other substantive theories.
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Hence, scaling up contributes to answering the ‘who, where and what’ aspects of a theory.
Whetten suggests these aspects are very important in determining the temporal and contextual
factors that set the limit on the theory’s range i.e. determine how generalizable the theory is
(Whetten, 1989).
Theoretical integration
Like any other theory, a grounded theory needs to be put into the context of other theories in
the field. One of the potential advantages of the grounded theory method for information
systems researchers is the obligation (Strauss, 1987, p. 282) to engage with theories outside
the discipline. Weber (2003) suggests more scrutiny of high quality exemplars from other
disciplines. We believe that the use of grounded theory, because of its rigorous approach to
theory building, makes this kind of scrutiny possible. Glaser (1978) suggests that the substantive theory can be analysed by comparing it with other substantive theories in the area. Glaser
also suggests that formal models of process, structure and analysis may be useful guides to
integration. Hence, in the field of information systems, meta-theories such as structuration
theory (Orlikowski & Robey, 1991; Walsham, 2002) or actor–network theory (Walsham, 1997)
may be a useful lens through which to view the emergent theory.
Glaser (1978) also makes the point that context is necessarily stripped away as one moves
toward a formal theory, and that comparative analysis is used to compare conceptual units of
a theory, as well as data.
In the next section, we illustrate how the guidelines of constant comparison, iterative
conceptualization, theoretical sampling, scaling up and theoretical integration can be applied
to grounded theory studies in information systems.
APPLYING THE GUIDELINES
In this section, we illustrate the usefulness of the guidelines by applying them to three
grounded theory studies in information systems. The three studies are as follows:
1 Orlikowski’s (1993) study of the use of CASE tools in two organizations;
2 Urquhart’s (2001) study of the dialogue between a systems analyst and client in one of six
case studies; and
3 Lehmann & Gallupe’s (2005) analysis of the use of information systems in three multinational companies across multiple locations.
Orlikowski (1993)
Orlikowski (1993) investigates the adoption and use of CASE tools in organizations. Most of
the data comes from interviews with people from two organizations. The data analysis was
carried out following the Strauss and Corbin stages of coding – open coding, axial coding
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and selective coding. Orlikowski uses the terms concepts, properties and relations, as used
in Glaser & Strauss (1967). Concepts are grouped in categories, and those categories
related together in a framework. There are six major categories in the framework, substantially more than the one or two core categories suggested by Glaser and Strauss as the
basis of a theory.
Constant comparison was used and is explained as constant comparison across types of
evidence to control the conceptual level and scope of the emerging theory (Orlikowski,
1993).
Orlikowski also used iterative conceptualization to draw out ‘multiple sources of loops of
causation and connectivity’ and to identify patterns in the process of change. Connections
were made between subcategories using the axial coding technique (Strauss & Corbin,
1990). It is not clear whether the Strauss & Corbin (1990) coding paradigm of phenomena,
causal conditions, context, intervening conditions, action and interactional strategies, and
consequences was used to assist the coding. Conditions do appear in the theory, leading us
to wonder if Orlikowski chose to be informed by, rather than apply, the coding paradigm.
The relationships between three categories (Environmental Context, Organizational Context
and Information Systems Context) and two other categories (Conditions for Adopting and
Using CASE Tools and Adopting and Using CASE tools) are very carefully delineated and
discussed in the paper.
It appears that theoretical sampling (deciding on analytical grounds where to sample from
next) was used in the later stages of data collection. Data collection was overlapped with
analysis, and the author cites Eisenhardt (1989) as pointing out that this is useful for theory
building. The author also says that in the site selection, the two cases were chosen for their
similarities, as well as their differences. Glaser & Strauss (1967) say that minimizing differences among comparison groups increases the possibility of collecting similar data, but will
also help in spotting important differences.
Scaling up is also evident in the paper, as eight categories are generated in total. Three are
grouped into the Institutional Context, and three into Strategic Conduct in Adopting and Using
CASE tools. There are also three categories on Systems Developer Reactions to CASE tools
that are not linked to the preceding framework, but discussed separately under the heading of
‘Implications for Systems Development Practice’.
Theoretical integration is achieved by discussing the resultant theory in the context of other
theories on radical change and distinctions in types of innovation, in particular the classification
of incremental and radical types of innovation used in the innovation literature.
Urquhart (2001)
Urquhart (2001) explores three case studies of analyst–client interaction and discusses three
themes from three case studies in the context of Boden’s (1994) theory of organizational
agendas.
Constant comparison is not mentioned in the article, though both the individual characteristics of the analysts and clients and the results from the three cases are explicitly compared.
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The sequence of coding is explained in detail, including how different data sources were
treated in the coding process. Similarly, theoretical sampling is not evident in the paper (though
it did take place at the category level as the author can attest). By contrast, iterative conceptualization and scaling up are clearly evident in the explanation of grouping grounded theory
concepts, via an intermediate unit of analysis, a conversational topic. In terms of iterative
conceptualization, there are a number of different relationships postulated between the themes
Organizational Context, Issues to Be Discussed and Professional Relationships. Scaling up of
the theory is achieved by grouping categories into themes using the aforesaid intermediate unit
of analysis – the conversational topic. Actual categories are not mentioned.
Theoretical integration is achieved by discussing the emergent theory, in particular the
relationships between the three themes, in the light of Boden’s (1994) theory of organizational
agendas arising from interaction. The findings illustrate how an organizational agenda may
start from an interaction. Also, the reflexive nature of this relationship is discussed.
Lehmann & Gallupe (2005)
Lehmann & Gallupe (2005) examine three multinational companies and put forward a theoretical framework concerned with the structure of international information systems. The
constant comparative method is explicitly mentioned, and data collection overlapped with data
analysis and theory building.
Iterative conceptualization was carried out using Weick’s (1979) cause–effect loops between
categories. These cause–effect loops were built on theoretical coding between categories and
are very extensive. There are also relationships posited between Global Standards, Information Systems Initiatives, Strategic Migration, Autonomy and Information Systems by force – all
categories from the grounded theory analysis.
Theoretical sampling was used at the level of text, the case and across cases.
Scaling up of theory is evident – a force-field diagram showing tensions between territorial
forces and functional forces appears to be grounded in the categories.
Theoretical integration is achieved by relating the substantive theory to other theories. The
international information systems architecture model is systematically related to global strategy
literature. Examples of cyclical movements are mentioned from many diverse business
research fields, indicating that the authors are both raising the level of conceptualization by
comparing the theory to data from other substantive theories, and using theoretical sampling
to a great extent.
While the grounded nature of the theory is evident, and relationships between concepts
clearly explained, this paper does not explicitly show the route from categories to larger
concepts. Neither does the paper explicitly discuss the coding, except in general terms. Again,
this illustrates a significant problem for grounded theory studies – in the space afforded by a
journal article, the author may have to make a choice between explaining the theory and
explaining the chain of evidence that led to that theory.
Our overall assessment of all three articles using the five guidelines for grounded theory
studies is shown in Table 2.
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Table 2. Overall assessment of the three grounded theory studies
Lehmann & Gallupe
(2005)
Orlikowski (1993)
Urquhart (2001)
1 Constant comparison
Constant comparison is
explicitly mentioned. The
first case was
systematically contrasted
with the second case
Constant comparison is
not explicitly mentioned in
the paper, but is evident
in cross-case comparison.
Constant comparison is
explicitly mentioned in the
paper.
2 Iterative
conceptualization
Connections were made
between subcategories
using axial coding.
Interactions between 3
key concepts and the
context were carefully
outlined.
Situational links between
themes are made, and
these links are based on
lower level category
relationships
The categories have
correlational and causal
linkages, and hypotheses
are formed
3 Theoretical sampling
Later stages of data
collection were directed by
emerging concepts, and
data collection was
overlapped with analysis.
Sites chosen for
similarities rather than
differences.
Theoretical sampling is
implied, but not explicitly
mentioned. No
overlapping data collection
and analysis.
Theoretical sampling
carried out at the level of
text, case and across
cases. Overlapping data
collection and analysis.
4 Scaling up
Scaling up is evident, as
each key concept contains
a number of categories.
Scaling up is evident as
categories within an
intermediate unit of
analysis, conversational
topic, are grouped into
themes.
Scaling up is not explicit,
but appears to have been
done to some extent.
5 Theoretical integration
The resultant theory is
discussed in the context
of other theories on
radical change.
The resultant theory is
related to Boden’s (1994)
work on organizational
agendas.
The resultant theory is
related to Lewin’s (1952)
force field concept.
As can be seen in the table, in two out of the three papers analysed, constant comparison
was explicitly mentioned. In all three papers, iterative conceptualization was evident. Theoretical sampling was evident in two of the papers – the other paper did a series of ‘one-shot’
case studies so no overlapping data collection and analysis occurred. This is perhaps typical
of grounded theory studies that start out using grounded theory as a method of analysis only.
Scaling up is very obvious in two of the papers, and it may be that in the third paper, it has
occurred but not mentioned explicitly. All three papers relate their emergent theory to larger
theories. Our concluding section discusses the ramifications of our guidelines and their
potential contribution to the use of grounded theory in information systems.
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DISCUSSION AND CONCLUSIONS
Over the past decade, many information systems researchers have started to use the
grounded theory method. While we welcome this growing interest in the method, we believe it
is an opportune time to question whether information systems researchers have been using
this method to its full potential.
It would seem that many information systems researchers, like those in other disciplines,
have used the grounded theory method mostly as a way of coding qualitative data (Becker,
1983; Benoliel, 1996; Bryant et al., 2004; Urquhart, 2007). This use of grounded theory, while
appropriate in some cases, suggests to us that the primary purpose for which grounded theory
was developed – to generate theory – is being neglected. Grounded theory is not just a coding
technique, but offers a comprehensive method of theory generation.
There have been calls for information systems researchers to focus more on theory development (Watson, 2001; Weber, 2003). We have suggested that one possible way to answer
this call is to use grounded theory to help generate theories related to information systems
phenomena. Hence, the key question that this paper has sought to address is: ‘How can the
grounded theory method be leveraged to build theory in information systems?’
We have answered this question by suggesting guidelines for grounded theory studies in
information systems. The guidelines are oriented towards increasing the degree of conceptualization and theory scope in grounded theory studies. Our intention is to raise the bar for
grounded theory studies in information systems, such that all information systems researchers
who use grounded theory might aim to increase the degree of conceptualization and theory
scope in their research as much as possible.
Our suggested guidelines draw attention to a few key features of the grounded theory
method. First, constant comparison is at the heart of the method. Constant comparison helps
to ensure that the categories and the resulting theory are properly grounded. The idea of one
or two core categories or themes helps focus the theory. Iterative conceptualization is also
fundamental to the method. The dynamic interplay between analysis and data collection –
where relationships are built between concepts in an iterative manner – is one of the features
that distinguishes grounded theory from most other qualitative research methods. Theoretical
sampling increases the relevance and density of the theory, while scaling up helps to increase
the level of abstraction. Theoretical integration, where the generated theory is related to other
theories, has the potential to help bring disparate theory building efforts together. While Lee &
Baskerville (2003) counsel against the ‘uniformity of nature assumption’ in information systems
theory building efforts, we would suggest that the utilization of grounded theory for theory
building in information systems would in fact increase our discipline’s engagement with diverse
theories from other fields.
We have suggested that the guidelines, while potentially helping to improve the conduct of
grounded theory studies in information systems, can also be used for post hoc evaluation. We
evaluated three such information systems articles, and found that all three exhibited the five
guidelines for grounded theory studies to some extent, but most guidelines were implicit rather
than explicit. There was some inconsistency in application, and some guidelines were empha-
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sized more than others. For example, constant comparison tended to be a less visible part,
especially in one of the studies. In all of the articles, scaling up was evident, but none of the
authors explained how this was achieved. In fact, in one of the studies, scaling up was not
mentioned at all, although the findings would suggest that it must have been performed to
some extent. All three articles were exemplary in their attempts at theoretical integration with
previously existing theories.
In our opinion, the article by Orlikowski (1993) remains the high-water mark for theorizing in
information systems using grounded theory. All five guidelines are clearly evident in this paper.
The article pays great attention to the relationships between concepts, exhibits iterative
conceptualization and systematically explores those relationships. It also provides more of a
chain of evidence than the other two papers, although the author does not explain how scaling
up was achieved. It is interesting to speculate why this is the best paper of the three. It may be
that a less restrictive word limit for journal articles may be partly responsible for the depth and
excellence of Orlikowski’s theorizing: MIS Quarterly allows for the publication of longer papers
than most other journals.
We believe that our evaluation of these articles using the five guidelines demonstrates how
grounded theory can be leveraged to build theory in information systems. The guidelines
emphasize the key distinguishing features of grounded theory and suggest how theory building
efforts that use grounded theory in information systems might be improved.
One question that can legitimately be asked is whether more use of grounded theory in
information systems would simply result in more unrelated theories. We acknowledge that this
is a possibility, but one way to counter this would be to consider extended use of theoretical
sampling. Extending theoretical sampling points to a way of increasing the explanatory power
of grounded theories: it allows information systems researchers to build on each other’s work
with studies that complement or extend earlier work. These studies can be carefully designed
to extend either the ‘fit’ of the theory, thereby increasing its scope, or to improve the way the
theory ‘works’ by modelling more, and more specific, linkages and relationships between the
‘objects’ (i.e. concepts and constructs of the existing theory). Other possibilities would be
the extension of the theory’s original substantive area.
This brings us to the issue of collaboration. Students of Anselm Strauss were encouraged
to code collaboratively, and it has also been our experience that collaborative coding results
in a stronger theory. Follow-on studies using generated theories could be carried out in
collaborative arrangements, perhaps by forming virtual teams. One of the grounded theorist’s most powerful tools, the theoretical memo, lends itself naturally to email communication. One example of Internet collaboration is the Forum for researchers on Glaser’s
Grounded Theory Institute web page (Glaser, 2008) Collaboration could also be done
through the exchange of data sets from text analysis software applications such as NUDIST,
nVivo or ATLAS ti.
In closing, we caution that the five guidelines we have suggested should not be used
mechanistically. Although the grounded theory method is sometimes seen as rather formulaic
and overburdened with rules (Melia, 1996; Kendall, 1999), we would like to stress that the
application of the guidelines requires considerable creative thought (cf. Klein & Myers, 1999).
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The use of the guidelines does not obviate the need for intellectual effort on the part of the
researcher.
In summary, we have suggested guidelines for grounded theory studies in information
systems. These guidelines are oriented towards increasing the degree of conceptualization
and theory scope in grounded theory research projects. Our hope is that these guidelines will
to help to raise the quality and aspirations of grounded theory studies in information systems.
If grounded theory is used to its full potential, we believe that we may well see much more
theory development in the information systems arena.
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381
MIS Quarterly in 2007. She has a strong interest in qualitative data analysis, especially the use of grounded
theory in information systems. Her current research interest is technology and social inclusion, particularly in
developing countries. She is an Associate Editor for the
Journal of Information Technology and Development and
the International Journal of E-Politics, and is on the editorial board for the International Journal of Learning and
Change. Her home page can be accessed at http://
staff.business.auckland.ac.nz/curquhart.
Cathy Urquhart is a Senior Lecturer in Information
Systems at the Department of Information Systems and
Hans Lehmann is the Associate Professor for Electronic Business at Victoria University of Wellington, New
Zealand. He is a graduate in psychology from the University of Vienna and the University of Natal and in business
administration from the University of South Africa. His PhD
in Information Systems was obtained from the University of
Auckland. Hans looks back on 25 years of business experience with information technology, both in line management in banks and the manufacturing industry and as a
consultant with Deloitte specializing in the management of
information systems for multinational enterprises. In 1991,
Hans changed careers and joined the University of Auckland, New Zealand, where he focused his research on the
strategic management of global information technology. In
2003, he moved to Victoria University, where his current
research interest is in the application of wireless technology in business. His research focuses strongly on qualitative enquiry, with the main emphasis on the use of
grounded theory.
Michael D. Myers is Professor of Information Systems
and Head of the Department of Information Systems and
Operations Management within the University of Auckland
Business School, New Zealand. His research articles have
been published in many journals and books. He won the
Best Paper Award (with Heinz Klein) for the most outstanding paper published in MIS Quarterly (MISQ) in 1999. This
paper has been cited over 1000 times and is the third most
cited paper to appear in MISQ. He also won the Best Paper
Award (with Lynda Harvey) for the best paper published in
Information Technology & People in 1997. He currently
serves as Senior Editor of Information Systems Research
and as Editor of the ISWorld Section on Qualitative
Operations Management at the University of Auckland
Business School, New Zealand. She has a PhD in Infor-
Research. He previously served as Senior Editor of MIS
Quarterly from 2001–2005, as Associate Editor of Informa-
mation Systems from the University of Tasmania, Australia. She was named as one of Australia’s outstanding
tion Systems Research from 2000–2005 and as Associate
Editor of Information Systems Journal from 1995–2000. He
teachers of computing in the Australian Campus Review
in November 1996. She won the Outstanding Paper
also served as President of the Association for Information
Systems in 2006–2007, and as Chair of the International
award in Information Technology and People in 1999.
She won a Developmental Associate Editor Award for
Federation of Information Processing Working Group 8.2
from 2006–2008.
Biographies
© 2009 Blackwell Publishing Ltd, Information Systems Journal 20, 357–381