Putting the 'theory' back into grounded theory: guidelines for grounded theory studies in...

Putting the ‘theory’ back into groundedtheory: guidelines for grounded theorystudies in information systemsCathy Urquhart,* Hans Lehmann† & Michael D. Myers‡

*Department of Information Systems and Operations Management, University ofAuckland, 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 OperationsManagement, 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 ofgrounded theory in information systems research. Grounded theory is a qualitativeresearch method that seeks to develop theory that is grounded in data systemati-cally gathered and analysed. The purpose of this paper is to suggest guidelines forgrounded theory studies in information systems. Our guidelines are based on aframework for theorizing in grounded theory studies that focuses on conceptual-ization and theory scope. Our hope is that the guidelines will help to raise thequality and aspirations of grounded theory studies in information systems.

Keywords: grounded theory, research methods, theory building, guidelines forgrounded theory

INTRODUCTION

Over the past decade, there has been increasing interest in the use of grounded theory ininformation systems research (Howcroft & Hughes, 1999; Hughes & Howcroft, 2000; Urqu-hart, 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 isgrounded in data systematically gathered and analysed. According to Martin & Turner(1986), grounded theory is ‘an inductive, theory discovery methodology that allows theresearcher to develop a theoretical account of the general features of a topic while simul-taneously grounding the account in empirical observations or data’. The major differencebetween grounded theory and other qualitative research methods is its specific approach totheory development – grounded theory suggests that there should be a continuous interplaybetween data collection and analysis.

doi:10.1111/j.1365-2575.2009.00328.x

Info Systems J (2010) 20, 357–381 357

© 2009 Blackwell Publishing Ltd

In information systems, grounded theory has proved to be extremely useful in developingcontext-based, process-oriented descriptions and explanations of information systems phe-nomena (Myers, 1997; Goulielmos, 2004). It offers relatively well-signposted procedures fordata analysis, and potentially allows for the emergence of original and rich findings that areclosely tied to the data (Orlikowski, 1993). It is this last feature that provides researchers witha great deal of confidence, as for each concept produced, the researcher can point to dozensof instances in the data that relate to it.

However, grounded theory studies in information systems have been criticized for having arelatively low level of theory development. Many grounded theory studies in informationsystems use grounded theory only as a coding method, and, indeed, the term ‘groundedtheory’ 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 groundedtheory method is not limited to the field of information systems. Scholars in other fields havehighlighted exactly the same issue, of the grounded theory method being viewed primarily asa 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 – issomewhat limited. Grounded theory is not just a coding technique, but offers a comprehen-sive method of theory generation. In fact, one of the attractions of grounded theory forinformation systems researchers is the promise that it will help us to develop new theoriesof information systems phenomena – theories that are firmly grounded in empirical phenom-ena. Given the calls for information systems researchers to focus more on theory develop-ment (Watson, 2001; Weber, 2003), we suggest that grounded theory can be used to helpgenerate theories in information systems. Hence, a key question that this paper seeks toaddress is: ‘How can the grounded theory method be leveraged to build theory in informa-tion systems?’

The purpose of this paper, therefore, is to suggest guidelines for conducting and evaluatinggrounded theory studies in information systems. Our hope is that the guidelines will help toraise the quality and aspirations of grounded theory studies in information systems, and, as aconsequence, contribute to theory development in the field. This paper should be of interest toall information systems researchers using or considering using grounded theory, and to allother 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 ofgrounded theory and outline its theoretical and philosophical foundations. In the thirdsection, we discuss the issue of theory building in information systems, and whatgrounded 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, wediscuss our suggested guidelines for the conduct and evaluation of grounded theory studiesbased on the framework. In the sixth section, we use these guidelines to analyse threegrounded theory studies in information systems. The final section is the discussion andconclusions.

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GROUNDED THEORY METHOD – AN OVERVIEW

Barney Glaser and Anselm Strauss published a book entitled ‘The Discovery of GroundedTheory’ in 1967 (Glaser & Strauss, 1967). This book outlined a research methodology thataimed at systematically deriving theories of human behaviour from empirical data. It was areaction against ‘armchair’ functionalist theories in sociology (Dey, 1999; Kendall, 1999).Several more books and articles by the co-originators followed, which developed and laterdebated 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 quicklyas a qualitative research method within the social sciences and many other fields. Forexample, Benoliel (cited in Dey, 1999, p. 412) says there was a 70-fold increase in publishedpapers with ‘grounded theory’ as a keyword in the health field over the previous decade. By themid-1990s, the methodological procedures of grounded theory had permeated qualitativeresearch to such an extent that Miles and Huberman labelled it a ‘ “common feature” [ofqualitative] analytic methods’ (Miles & Huberman, 1994, p. 9).

There are various definitions of grounded theory. The earliest, a process definition by thecreators themselves, defines it as ‘the discovery of theory from data – systematically obtainedand analysed in social research’ (Glaser & Strauss, 1967, p. 1). A more detailed definition isas follows:

The methodological thrust of grounded theory is toward the development of theory, withoutany particular commitment to specific kinds of data, lines of research, or theoretical inter-ests . . . Rather it is a style of doing qualitative analysis that includes a number of distinctfeatures . . . and the use of a coding paradigm to ensure conceptual development anddensity (Strauss, 1987).

From these various definitions, we can discern four distinctive characteristics of the groundedtheory 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 thenseeks to verify – or otherwise. Such preconceived theoretical ideas could hinder the emer-gence 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 datacollection and constant comparison, where every slice of data is compared with all existingconcepts and constructs to see if it enriches an existing category (i.e. by adding/enhancing itsproperties), 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 theresearcher decides on analytical grounds where to sample from next.

The first characteristic implies that researchers who use grounded theory only as a way ofcoding data are neglecting the main purpose of the method – which is to build theory. Theory

Guidelines for grounded theory studies in information systems 359


building is why grounded theory was developed in the first place. In developing theory, theresearcher needs to be capable of theoretical sensitivity. Theoretical sensitivity is based onbeing steeped in the field of investigation and associated general ideas, so that a researcherunderstands 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 literaturebefore doing the empirical research. This injunction is mainly designed to ensure that theresearcher does not impose ideas from the literature on that coding. If the researcher startswith 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 theoriginal 1967 book, Glaser and Strauss (1967, p. 3) state that the researcher does notapproach reality as a tabula rasa but must have a perspective that will help him or her abstractsignificant categories from the data. Dey (1999) speaks of the difference between an ‘openmind and an empty head’ – both he and we believe that the founders of grounded theoryinclined 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 before1967, the specific rigour and the level of detail demanded by grounded theory are significantlygreater. Glaser & Strauss (1967, p. 43) emphasize that the data collection, coding and analysisneed to be done together because separating these operations might hinder the developmentof theory. They give the example of a fresh analytic idea emerging in the coding that mayredefine the collection but is ignored due to pre-established rules or routine – thus stifling thegeneration of theory. The idea of joint interaction between data collection and analysis iscentral in grounded theory.

As for the fourth characteristic, the term ‘slices of data’ was coined by Glaser and Straussto reflect the fact that different kinds of data give the researcher different views from which tounderstand a category or to develop its properties. They say ‘these different views we havecalled slices of data’ (Glaser & Strauss, 1967, p. 65). Theoretical sampling is where theresearcher uses the categories, concepts and constructs established so far to direct furtherdata collection (Glaser, 1978). In the original book, a whole chapter is devoted on howto 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 philosophicalassumptions of grounded theory. Grounded theory belongs to the realm of qualitative empiri-cism 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 theoryis just waiting to be discovered in the data. Clearly, this idea does not take into account thesubjectivism of coding. We tend to see this philosophical uncertainty as simply reflective of theintellectual climate of the time in which Glaser and Strauss introduced grounded theory. Holton



(2007) says that Charmaz (2006) identifies the crux of the matter as a lack of clarity in theseminal 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 qualitativeresearch method for gathering and analysing data. As a research method, grounded theory isindependent of the underlying epistemology. This means that grounded theory is itself, asGlaser describes, ‘paradigmatically neutral’ (Glaser, 2001). It can be used in positivist studies(Lehmann, 2003), interpretive or critical studies (Annells, 1996; Urquhart, 2001; Cecez-Kecmanovic et al., 2008). Grounded theory’s neutrality also makes it useful for mixed-paradigm research (Charmaz, 2005).

A key point we wish to make here is that a researcher’s own ontological and epistemologicalposition will impact on their coding and analysis of the data and the way in which they usegrounded theory (Madill et al., 2000). Our suggested guidelines, however, apply to all kinds ofgrounded theory.

Two strands of grounded theory

In subsequent years the grounded theory method has evolved into two distinct variants, onefavoured by Glaser, the other by Strauss (Melia, 1996). A very public disagreement betweenthese two co-founders of grounded theory occurred on the publication of Strauss and Corbin’sbook 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 proce-dures. In Glaser’s view, this formalization is far too restrictive, to the extent that it may strangleany 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 frompublication, and when it was not, wrote a correctional rejoinder ‘Emergence vs. Forcing: Basicsof 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 datais not allowed to speak for itself as in grounded theory, and to be heard from, infrequently ithas to scream. Forcing by preconception constantly derails it from relevance (Glaser, 1992,p. 123).

Glaser disagreed on two fundamental issues. First, Strauss & Corbin (1990) suggestedbreaking 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 paradigmand the ‘conditional matrix’, which are designed to provide ready-made tools for the concep-tualization process. Glaser pointed out that to ‘force’ coding through one paradigm and/ordown one conditional path was not grounded theory, but conceptual description, which ignored

1For 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.



the emergent nature of grounded theory (Glaser, 1992). Also, the coding paradigm used byStrauss and Corbin – which suggests that the researcher looks at context, conditions, action/interactional strategies, intervening conditions and consequences for the purposes of estab-lishing categories and relationships – can be further critiqued as a departure from traditionalgrounded theory. First, this coding paradigm provides only one particular view of a phenom-ena. By contrast, Glaser (1978) suggests 18 coding families, which cover ideas like dimen-sions and elements, mutual effects and reciprocity, social control, recruitment and isolation,and many other ideas for categories and relationships. Second, we have found that theinsistence on a phase of axial coding, where categories and relationships are consideredsimultaneously using the coding paradigm, causes real difficulty for some researchers, espe-cially novices. Selective coding, followed by theoretical coding, in our view, allows for moreabstract theorizing, as has been noted by Kendall (1999).

Given that this is such a well-documented disagreement between the two co-founders ofgrounded theory, we believe that information systems researchers need to be aware whichversion of grounded theory they are using. The Strauss and Corbin (1990) book is arguably themost widely known, and regarded as the most accessible. However, it describes only oneversion of grounded theory, and has also been described as rather formulaic and overbur-dened 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 beginsa 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 havingany preconceived theoretical ideas before starting the research, these seed concepts or earlyhunches ‘can come from sources other than data’ (Glaser & Strauss, 1967, p. 6). These seedconcepts help a researcher to select an area of enquiry and define the topic. The area ofenquiry is called the ‘substantive area’ in grounded theory terminology.

Next, the researcher takes ‘slices of data’ (Glaser & Strauss, 1967) from the area of enquiryand codes them into conceptual categories. These slices of data can come from many differentsources, and can be collected using many different data collection methods. This of courseprovides an opportunity for corroboration or triangulation of the data.

As the first element of a grounded theory, these conceptual categories are first described bytheir properties. Using additional slices of data, the categories are further conceptualized intotheoretical 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 newconceptual categories or relations emerge. The ‘saturated’ concepts are then reduced as muchas 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 itsformulation.



Grounded theory views the process of theory generation as one of increasing the level ofabstraction, 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 theleast range and scope. They are conceptual constructs themselves, although they are often nomore 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 fromtheir own backgrounds that could be brought to bear in their theorizing about virtual collabo-ration while guarding against becoming captive to any particular literature. They describe thisfirst 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 groundedtheory methods are termed ‘substantive’ theories. They apply to the substantive area ofenquiry, but are independent of and beyond the data analysed and the incidents observed

Additional

'Lived' Experience

Anecdotal Evidence

Other Theories

Hunches

Area of Enquiry

First

‘Slices-of-Data

Categories and

Their PropertiesTheoretical

Sampling

Grounded Theory

Relationships

between

Categories

‘Densification’ of the

‘Relations’ between

Categories

Additional

Additional ‘Slices-of-Data

Adding Further Data

to Saturate Categories

Lead to

Figure 1. Cycle of data collection and analysis in the grounded theory method [after Lehmann (2001) and Fernandez

et al. (2002)].



(Glaser & Strauss, 1967). For example, Orlikowski (1993) developed a substantive theoryrelating 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 derivedfrom) the arena of actual CASE tools adoption and use. At the same time, however, thetheoretical 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 theoriesfocus on conceptual entities (Strauss, 1987), such as organizational knowledge, organizationallearning or collaborative work.

Figure 2 depicts this hierarchy of theories. The general idea of using grounded theory is thatas the researcher moves up the level of abstraction, the range and scope of the theoryincreases.

Glaser & Strauss (1967) suggest that in order to generate formal theory, a comparativeanalysis should be made among different substantive theories that fall within a particularsubstantive area and by comparing substantive theoretical ideas from many different cases.Substantive theory can be used as a springboard towards formal theory by providing initialdirection in developing conceptual categories. Glaser (1978) makes the point that constantcomparative analysis can generate both substantive and formal theory. He further contendsthat 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 groundedtheory is generated, we now turn our attention to how grounded theory can be appliedspecifically in the discipline of information systems.

2. Substantive Theories

3. Formal Theories

Categories

and Their

Properties

RelationsCategoriesCategories

1. NarrowConcepts

Figure 2. The progression of theory development in the grounded theory methodology (adapted from Lehmann, 2001).



The role of theory in information systems has commanded attention in recent years. Forexample, Gregor (2006) proposes a taxonomy of theory in information systems that includesthe following categories – theory for analysing, theory for explaining, theory for predicting,theory for explaining and predicting, and theory for design and action. We suggest thatgrounded theory has the capability to generate theory that exists in all these categoriesbecause it contains the essential building blocks of any theory – constructs in the form ofcategories 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, therelationships the mortar between the bricks – but importantly, the emergent theory is informedby the research objectives. Gregor (2006) bemoans the use of vague terms for causality, likeassociated with or linked to, but from our perspective, it all depends for what purpose thetheory is being developed – interpretive researchers find the search for causality limiting. Whatis 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 thatmay – or may not – be testable.

One well-known characteristic of the information systems research domain is the use ofmany theories borrowed from other disciplines (Baskerville & Myers, 2002). Although importingtheories from outside the discipline is often valuable, we suggest that grounded theory couldbe 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 systemsdiscipline. We suggest that grounded theory might well be useful in developing theories aboutsuch phenomena.

Our next section introduces a framework for theorizing in grounded theory studies, anddiscusses 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 informa-tion 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 areimportant for theorizing. These two aspects are the degree of conceptualization and theoryscope. These two dimensions underline the grounded theory process of theory building –conceptualization that moves beyond mere description, and also considers relationshipsbetween categories, and pitching the theory scope at the appropriate level. The first axis – thedegree of conceptualization, can be seen as relating to the process of building a groundedtheory, and relates to the degree of analysis carried out. The second axis, theory scope, canbe seen to relate to the outcome of building a grounded theory. A summary of the frameworkis shown in Figure 3.

As the main purpose of using grounded theory is theory building, researchers should aim todevelop theories of greater scope. The more the data analysis moves from description totheory, and the more the scope of the theory increases with the development of formal



concepts, the better. Generally speaking, grounded theory studies should aim for the topright-hand corner of the figure. Of course, the framework shown in Figure 3 might also beuseful for other research approaches, but we suggest it is especially applicable to groundedtheory. 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 horizontalaxis of Figure 3. A key objective of grounded theory research is to aim for greater and greaterdepth of analysis of the data (Glaser & Strauss, 1967). In the Glaser variant, the process ofdiscovering grounded theory has three principal stages that successively increase the depth ofanalysis.

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 ofopen coding.

Interpretation

The second stage is the interpretation of categories and properties. Selective coding isemployed to refine conceptual constructs that can help explain whatever interaction occursbetween the descriptive categories (Glaser, 1978). This clear aetiological focus aims to

BoundedContext

SubstantiveFocus

Formal

Concepts

TheoryInterpretationDescription

Theory

Scope

Degree of ConceptualisationMore

More

Less

Less

Figure 3. A framework for analysing grounded theory studies.



understand and explain one or more specific areas under investigation. At this point, theresearch problem becomes more refined, as aspects of the research problem become appar-ent through selective coding.

Theoretical coding

The third stage, theoretical coding, results in the formulation of a theory. The aim is to createinferential and/or predictive statements (sometimes in the form of hypotheses) about thephenomena. This is achieved by stipulating explicit relationships between individual interpre-tive constructs – these relationships can be associations or influences, or can be causal. Thesystem of inferences covers the whole of the area under investigation. Without theoreticalcoding, there is no theory, as relationships between constructs have not been considered.Analytic memos, where relationships between categories are considered, are invaluable at thisstage and assist the theoretical coding.

There are a number of options open to the grounded theorist when considering relationshipsbetween categories. Glaser (1978) suggests 18 theoretical coding ‘families’. Strauss & Corbin(1990) suggest a coding paradigm. Clearly, how much attention is paid to the precise natureof 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 ofgrounded theory, the primary objective of the method is to develop theories of greater andgreater scope (Glaser & Strauss, 1967, e.g. Dey, 1999).

Bounded context

Seed concepts within a ‘bounded context’ represent theory with the narrowest scope. Seedconcepts, bounded by their immediate context within a specific area of inquiry, are often littlemore than hunches. These seed concepts have little empirical base; they simply representformal postulates of the researcher’s hunches from ‘lived experience’, from anecdotal evidencethat 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. Asubstantive theory extends its predictive and explanatory power to the specific set of phenom-ena from where it was developed. This kind of theory is no longer simply based on seedconcepts 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 formalconcepts. A formal theoretical construct applies to the conceptual area that it has been



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 systemsin general). While we have not found any instances of formal theories built from the use of thegrounded theory method in the information systems discipline, this has been achieved in thesocial 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 ofanalysis.

For a grounded theorist, there are thus three levels of theory. The promise of groundedtheory 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 closelyrelated to each other. We developed the framework primarily as a device to clarify what goodgrounded theory might look like. As we stated earlier, the main objective of grounded theory isto 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 theorydeveloped. Ideally, a researcher using grounded theory should attempt to move from thebottom left quadrant to the top right quadrant as much as possible (as per the diagonal arrowin Figure 3). The next section suggests guidelines for grounded theory studies in informationsystems 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 beleveraged to build theory in information systems?’ This section attempts to answer thisquestion by proposing guidelines for the conduct and evaluation of grounded theory studies ininformation systems. These guidelines are oriented towards building theory in our field, and aresummarized in Table 1. The guidelines build on the two axes of the framework identified in thefourth section, conceptualization and theory scope. The first three guidelines address how theresearcher might achieve the degree of conceptualization necessary to build a good theorythrough analytic mechanisms, such as constant comparison. These guidelines can also beseen as relating to the process of theory building. The final two guidelines give assistance withthe issue of theory scope by giving guidance on the level of theory and how it might beintegrated with the extant literature, an important aspect of theory building. Thus, these last twoguidelines 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 youhave labelled as a particular category with other instances of data in the same category to see



if these categories fit and are workable (Urquhart, 2001). Charmaz (2006) makes two pointsabout constant comparison. First, making comparisons between data, codes and categoriesadvances conceptual understanding because of the need to expose analytic properties torigorous scrutiny. Second, it makes the analysis more explicitly theoretical by asking ‘Whattheoretical category are these data an instance of?’

A legitimate question to be asked here is, should researchers code at the word and sentencelevel? Is it necessary to code at such a low level? From our perspective, the answer is a qualifiedyes, depending on the phenomena investigated. Such low-level coding is appropriate forinteractional studies, because it means that the data are examined minutely, and just asimportantly, ‘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 thatlow-level coding affords cannot be underestimated, for it is in this way that the grounded theorymethod provides a chain of evidence like no other approach. The constant comparative methodmeans that there are always dozens of instances to support the theory that is produced.

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.



Constant comparison encourages the researcher to be both rigorous and theoretical(Charmaz, 2006). Both Orlikowski (1993) and Hughes & Howcroft (2000) are good examplesof the use of constant comparison.

Iterative conceptualization

One unique aspect of grounded theory is what we have chosen to call iterative conceptual-ization – where theory is built in an iterative fashion by using theoretical coding, focusingparticularly on relationships between categories. These relationships can be of many kinds,causal relationships being one of many options. One of the interesting paradoxes aboutgrounded theory is that, at first glance, it offers well-signposted procedures for theory buildingfor the novice (Urquhart, 1997). Yet we notice that many researchers get into difficulties at thispoint, as theory building is an essentially creative process and cannot be achieved by followingprocedures alone. Hence, the strengths of the method can only be truly leveraged if bothqualities of the method – systematic procedures and an iterative approach to conceptualization– are fully employed. Iterative conceptualization is the plank on which theory generation isbased. A mechanistic application of coding stages will not yield the desired results in terms oftheory. The researcher using grounded theory needs to be alert to intuition and to think beyondlabels for the data.

In terms of doing iterative conceptualization, researchers have suggested a number ofalternatives. There are the coding stages of Strauss & Corbin (1990) (open coding, axialcoding, 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, axialcoding, theoretical coding). Whichever coding stages are used, the key thing is that all stagesare 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 ofassistance when assessing the data analysis component of grounded theory studies ininformation 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 isdesirable that the researcher reaches the third stage, that of inferential and explanatory codes.Axial coding (Strauss & Corbin, 1990) or theoretical coding (Glaser, 1978) are essentiallyabout relationships between categories – the very essence of theory building. Theoreticalcoding contributes to an understanding of relationships between the concepts or factors ofa theory.

In our experience, it is in defining the relationships between categories that novice research-ers often struggle to really achieve depth of theory. Establishing such relationships can beassisted by the coding paradigm of Strauss & Corbin (1990) and/or with Glaser’s (1978) codingfamilies, which give many options for theory building, including causal relationships, andgeneration of hypotheses. Other options include considering limit, range, intensity, intent,aspects, types, dimensions, mutual interactions, ends and goals, clusters, and agreements.



During this stage, it often becomes clear that some categories are properties of others, and asthinking sharpens, category names often reflect analytic thinking as opposed to simply describ-ing 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 factorsand the proposed (causal) relationships. The ‘why’ in a theory attempts to explain why thefactors are behaving the way they do. This aspect of a theory supplies the plausible, cogentexplanation 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 conceptu-alization, as the writing of a memo creates a formal space in which the researcher can reflecton the emerging theory. Examples of theoretical memos are rare in information systems, butnot in the social sciences (Charmaz, 2006). Examples of theoretical memos can be found inUrquhart (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 occurat 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 theemergent theory (Glaser, 1992), the research questions gradually become more refined, asdimensions of the research problem become clearer through analysis (Dey, 1993). If theresearcher is guided by the emergent theory when collecting data, then there is very littlechance of the researcher imposing preconceived notions on the data. Theoretical samplingalso 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 proper-ties, relationships between categories, to saturate categories, to clarify relationships betweencategories, to distinguish between categories, and to follow hunches about categories. Theo-retical sampling is one of the foundations of grounded theory method – it enables both a focuson 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 con-tributor to the ‘fit’ of a theory. Without theoretical sampling and the constant comparison andassessment of the contribution achieved by new slices of data, it will be impossible to establishhow ‘saturated’ the theory is. In fact, theoretical sampling is the single most important assur-ance 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 ratherweak and seems to have taken the path of ‘more-of-the-same’, which mainly serves to confirmthe properties of existing categories and can freeze the current conceptual level. ‘Same-data-group’ is, however, but one of several options, some of them explicitly designed to extend



scope and depth of the theoretical constructs created. Glaser & Strauss (1967, pp. 49–60) andGlaser (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 specificresearch project, but also should be carried on even after a first cohesive theoretical constructhas been established. This is for two reasons: first, it enables maximum ‘fit’ of the theory bykeeping it up-to-date with changing circumstances; and second, it facilitates the extension ofthe theory’s substantive limits.

Theoretical sampling ensures the comprehensive nature of the theory. Deciding on whichcategories are ‘core’ categories and selectively coding until saturation is reached also providesa 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 alsoparsimonious. Whetten (1989) suggests that comprehensiveness and parsimony are twoimportant characteristics of theory.

Scaling up

Our collective experience with the grounded theory method tells us that first-time users tend toget overwhelmed at the coding level. The attention to word- and sentence-level coding, whilegiving rich insights to the researcher, naturally focuses the mind on the detail. However, webelieve it is important for researchers at some stage to try to rise above the detail in order toconsider the bigger picture.

One simple mechanism that we have used successfully is that of grouping high-levelcategories into larger, broader themes. It is then much easier to relate these to competingtheories. The desired level of abstraction can be achieved by coding around one or two corecategories 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 phe-nomenon being studied is not necessarily a process, and may have many different and distinctelements. A more compelling general reason is that the bottom up derivation of the generatedtheory makes it difficult to think abstractly. The very strength of grounded theory – its uniquetie to the data – may also be in fact the Achilles heel of the method. Thus, grouping high-levelcategories (which may or not be named core categories) into higher-level core categories (orthemes) is a very useful practice to scale up the substantive theory. A similar tactic is togenerate propositions.

Glaser makes some useful suggestions for scaling up a theory (Glaser, 1978). First, therewrite method, where the theory is rewritten to omit specifics – so, for example, instead oftalking about the strategies used by analysts when talking to their clients, one could talk aboutthe strategies used by professionals when dealing with their clients. While there are no moredata points sampled, it nevertheless provides a starting point for increasing the level ofconceptualization. Second, the level of conceptualization can be raised by comparing it to thedata from other substantive theories.



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 contextualfactors 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 inthe field. One of the potential advantages of the grounded theory method for informationsystems researchers is the obligation (Strauss, 1987, p. 282) to engage with theories outsidethe discipline. Weber (2003) suggests more scrutiny of high quality exemplars from otherdisciplines. We believe that the use of grounded theory, because of its rigorous approach totheory building, makes this kind of scrutiny possible. Glaser (1978) suggests that the substan-tive theory can be analysed by comparing it with other substantive theories in the area. Glaseralso suggests that formal models of process, structure and analysis may be useful guides tointegration. Hence, in the field of information systems, meta-theories such as structurationtheory (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 movestoward a formal theory, and that comparative analysis is used to compare conceptual units ofa theory, as well as data.

In the next section, we illustrate how the guidelines of constant comparison, iterativeconceptualization, theoretical sampling, scaling up and theoretical integration can be appliedto grounded theory studies in information systems.

APPLYING THE GUIDELINES

In this section, we illustrate the usefulness of the guidelines by applying them to threegrounded 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 sixcase studies; and3 Lehmann & Gallupe’s (2005) analysis of the use of information systems in three multina-tional companies across multiple locations.

Orlikowski (1993)

Orlikowski (1993) investigates the adoption and use of CASE tools in organizations. Most ofthe data comes from interviews with people from two organizations. The data analysis wascarried out following the Strauss and Corbin stages of coding – open coding, axial coding



and selective coding. Orlikowski uses the terms concepts, properties and relations, as usedin Glaser & Strauss (1967). Concepts are grouped in categories, and those categoriesrelated together in a framework. There are six major categories in the framework, substan-tially more than the one or two core categories suggested by Glaser and Strauss as thebasis of a theory.

Constant comparison was used and is explained as constant comparison across types ofevidence 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 ofcausation and connectivity’ and to identify patterns in the process of change. Connectionswere 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, andconsequences was used to assist the coding. Conditions do appear in the theory, leading usto wonder if Orlikowski chose to be informed by, rather than apply, the coding paradigm.The relationships between three categories (Environmental Context, Organizational Contextand Information Systems Context) and two other categories (Conditions for Adopting andUsing CASE Tools and Adopting and Using CASE tools) are very carefully delineated anddiscussed in the paper.

It appears that theoretical sampling (deciding on analytical grounds where to sample fromnext) was used in the later stages of data collection. Data collection was overlapped withanalysis, and the author cites Eisenhardt (1989) as pointing out that this is useful for theorybuilding. The author also says that in the site selection, the two cases were chosen for theirsimilarities, as well as their differences. Glaser & Strauss (1967) say that minimizing differ-ences among comparison groups increases the possibility of collecting similar data, but willalso help in spotting important differences.

Scaling up is also evident in the paper, as eight categories are generated in total. Three aregrouped into the Institutional Context, and three into Strategic Conduct in Adopting and UsingCASE tools. There are also three categories on Systems Developer Reactions to CASE toolsthat 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 othertheories on radical change and distinctions in types of innovation, in particular the classificationof 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 threethemes from three case studies in the context of Boden’s (1994) theory of organizationalagendas.

Constant comparison is not mentioned in the article, though both the individual character-istics of the analysts and clients and the results from the three cases are explicitly compared.



The sequence of coding is explained in detail, including how different data sources weretreated in the coding process. Similarly, theoretical sampling is not evident in the paper (thoughit did take place at the category level as the author can attest). By contrast, iterative concep-tualization and scaling up are clearly evident in the explanation of grouping grounded theoryconcepts, via an intermediate unit of analysis, a conversational topic. In terms of iterativeconceptualization, there are a number of different relationships postulated between the themesOrganizational Context, Issues to Be Discussed and Professional Relationships. Scaling up ofthe theory is achieved by grouping categories into themes using the aforesaid intermediate unitof analysis – the conversational topic. Actual categories are not mentioned.

Theoretical integration is achieved by discussing the emergent theory, in particular therelationships between the three themes, in the light of Boden’s (1994) theory of organizationalagendas arising from interaction. The findings illustrate how an organizational agenda maystart 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 theo-retical framework concerned with the structure of international information systems. Theconstant comparative method is explicitly mentioned, and data collection overlapped with dataanalysis and theory building.

Iterative conceptualization was carried out using Weick’s (1979) cause–effect loops betweencategories. These cause–effect loops were built on theoretical coding between categories andare very extensive. There are also relationships posited between Global Standards, Informa-tion Systems Initiatives, Strategic Migration, Autonomy and Information Systems by force – allcategories 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 strategyliterature. Examples of cyclical movements are mentioned from many diverse businessresearch fields, indicating that the authors are both raising the level of conceptualization bycomparing the theory to data from other substantive theories, and using theoretical samplingto a great extent.

While the grounded nature of the theory is evident, and relationships between conceptsclearly explained, this paper does not explicitly show the route from categories to largerconcepts. 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 ajournal article, the author may have to make a choice between explaining the theory andexplaining the chain of evidence that led to that theory.

Our overall assessment of all three articles using the five guidelines for grounded theorystudies is shown in Table 2.



As can be seen in the table, in two out of the three papers analysed, constant comparisonwas explicitly mentioned. In all three papers, iterative conceptualization was evident. Theo-retical 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 typicalof 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 hasoccurred but not mentioned explicitly. All three papers relate their emergent theory to largertheories. Our concluding section discusses the ramifications of our guidelines and theirpotential contribution to the use of grounded theory in information systems.

Table 2. Overall assessment of the three grounded theory studies

Orlikowski (1993) Urquhart (2001)

Lehmann & Gallupe

(2005)

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.



DISCUSSION AND CONCLUSIONS

Over the past decade, many information systems researchers have started to use thegrounded theory method. While we welcome this growing interest in the method, we believe itis an opportune time to question whether information systems researchers have been usingthis 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, whileappropriate in some cases, suggests to us that the primary purpose for which grounded theorywas developed – to generate theory – is being neglected. Grounded theory is not just a codingtechnique, but offers a comprehensive method of theory generation.

There have been calls for information systems researchers to focus more on theory devel-opment (Watson, 2001; Weber, 2003). We have suggested that one possible way to answerthis call is to use grounded theory to help generate theories related to information systemsphenomena. Hence, the key question that this paper has sought to address is: ‘How can thegrounded theory method be leveraged to build theory in information systems?’

We have answered this question by suggesting guidelines for grounded theory studies ininformation systems. The guidelines are oriented towards increasing the degree of conceptu-alization and theory scope in grounded theory studies. Our intention is to raise the bar forgrounded theory studies in information systems, such that all information systems researcherswho use grounded theory might aim to increase the degree of conceptualization and theoryscope in their research as much as possible.

Our suggested guidelines draw attention to a few key features of the grounded theorymethod. First, constant comparison is at the heart of the method. Constant comparison helpsto ensure that the categories and the resulting theory are properly grounded. The idea of oneor two core categories or themes helps focus the theory. Iterative conceptualization is alsofundamental 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 featuresthat distinguishes grounded theory from most other qualitative research methods. Theoreticalsampling increases the relevance and density of the theory, while scaling up helps to increasethe level of abstraction. Theoretical integration, where the generated theory is related to othertheories, has the potential to help bring disparate theory building efforts together. While Lee &Baskerville (2003) counsel against the ‘uniformity of nature assumption’ in information systemstheory building efforts, we would suggest that the utilization of grounded theory for theorybuilding in information systems would in fact increase our discipline’s engagement with diversetheories from other fields.

We have suggested that the guidelines, while potentially helping to improve the conduct ofgrounded theory studies in information systems, can also be used for post hoc evaluation. Weevaluated three such information systems articles, and found that all three exhibited the fiveguidelines for grounded theory studies to some extent, but most guidelines were implicit ratherthan explicit. There was some inconsistency in application, and some guidelines were empha-



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 theauthors explained how this was achieved. In fact, in one of the studies, scaling up was notmentioned at all, although the findings would suggest that it must have been performed tosome extent. All three articles were exemplary in their attempts at theoretical integration withpreviously existing theories.

In our opinion, the article by Orlikowski (1993) remains the high-water mark for theorizing ininformation systems using grounded theory. All five guidelines are clearly evident in this paper.The article pays great attention to the relationships between concepts, exhibits iterativeconceptualization and systematically explores those relationships. It also provides more of achain of evidence than the other two papers, although the author does not explain how scalingup was achieved. It is interesting to speculate why this is the best paper of the three. It may bethat a less restrictive word limit for journal articles may be partly responsible for the depth andexcellence of Orlikowski’s theorizing: MIS Quarterly allows for the publication of longer papersthan most other journals.

We believe that our evaluation of these articles using the five guidelines demonstrates howgrounded theory can be leveraged to build theory in information systems. The guidelinesemphasize the key distinguishing features of grounded theory and suggest how theory buildingefforts that use grounded theory in information systems might be improved.

One question that can legitimately be asked is whether more use of grounded theory ininformation systems would simply result in more unrelated theories. We acknowledge that thisis a possibility, but one way to counter this would be to consider extended use of theoreticalsampling. Extending theoretical sampling points to a way of increasing the explanatory powerof grounded theories: it allows information systems researchers to build on each other’s workwith studies that complement or extend earlier work. These studies can be carefully designedto extend either the ‘fit’ of the theory, thereby increasing its scope, or to improve the way thetheory ‘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 bethe extension of the theory’s original substantive area.

This brings us to the issue of collaboration. Students of Anselm Strauss were encouragedto code collaboratively, and it has also been our experience that collaborative coding resultsin a stronger theory. Follow-on studies using generated theories could be carried out incollaborative arrangements, perhaps by forming virtual teams. One of the grounded theo-rist’s most powerful tools, the theoretical memo, lends itself naturally to email communica-tion. One example of Internet collaboration is the Forum for researchers on Glaser’sGrounded Theory Institute web page (Glaser, 2008) Collaboration could also be donethrough 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 usedmechanistically. Although the grounded theory method is sometimes seen as rather formulaicand overburdened with rules (Melia, 1996; Kendall, 1999), we would like to stress that theapplication of the guidelines requires considerable creative thought (cf. Klein & Myers, 1999).



The use of the guidelines does not obviate the need for intellectual effort on the part of theresearcher.

In summary, we have suggested guidelines for grounded theory studies in informationsystems. These guidelines are oriented towards increasing the degree of conceptualizationand theory scope in grounded theory research projects. Our hope is that these guidelines willto 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 moretheory development in the information systems arena.

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Biographies

Cathy Urquhart is a Senior Lecturer in Information

Systems at the Department of Information Systems and

Operations Management at the University of Auckland

Business School, New Zealand. She has a PhD in Infor-

mation Systems from the University of Tasmania, Austra-

lia. She was named as one of Australia’s outstanding

teachers of computing in the Australian Campus Review

in November 1996. She won the Outstanding Paper

award in Information Technology and People in 1999.

She won a Developmental Associate Editor Award for

MIS Quarterly in 2007. She has a strong interest in quali-

tative data analysis, especially the use of grounded

theory in information systems. Her current research inter-

est 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 edi-

torial board for the International Journal of Learning and

Change. Her home page can be accessed at http://

staff.business.auckland.ac.nz/curquhart.

Hans Lehmann is the Associate Professor for Elec-

tronic Business at Victoria University of Wellington, New

Zealand. He is a graduate in psychology from the Univer-

sity 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 expe-

rience with information technology, both in line manage-

ment 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 Auck-

land, 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 technol-

ogy in business. His research focuses strongly on qualita-

tive 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 outstand-

ing 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

Research. He previously served as Senior Editor of MIS

Quarterly from 2001–2005, as Associate Editor of Informa-

tion Systems Research from 2000–2005 and as Associate

Editor of Information Systems Journal from 1995–2000. He

also served as President of the Association for Information

Systems in 2006–2007, and as Chair of the International

Federation of Information Processing Working Group 8.2

from 2006–2008.



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