The intent of grounded theory is to generate or discover a theory – an abstract
analytical schema of a philosophy, that relates to a particular situation. This
situation could be one in which individuals interact, take actions, or engage in a
process in response to a phenomenon (Creswell, 1998).
Procedures Involved In Conducting A Study:
In open coding, the researcher forms initial categories of information about
the phenomenon being studied by segmenting information. Within each
category (a category represents a unit of information composed of events,
happenings and instances), the researcher finds several properties, or
subcategories, and looks for data to dimensionalize, or show the extreme
possibilities on a continuum of, the property.
In axial coding, the researcher assembles the data in new ways after open
coding. The researcher presents this using a coding paradigm or logic
diagram in which he/she identifies a central phenomenon, explores causal
conditions (i.e., categories of conditions that influence the phenomenon),
specifies strategies (i.e., the actions or interactions that result from the central
phenomenon), identifies the content and intervening conditions (i.e., the narrow
and broad conditions that influence the strategies), and delineates the
consequences (i.e., the outcomes of the strategies) for this phenomenon.
In selective coding, the researcher identifies a “story line” and writes a story
that integrates the categories in the axial coding model. In this phase,
conditional propositions (or hypotheses) are typically presented.
Finally, the researcher develops and visually portrays a conditional matrix
that elucidates the social, historical, and economic conditions influencing the
This process results in a theory, written by the researchers close to a specific
problem or population of people.
The researcher needs to set aside, as much as possible, theoretical ideas or
notions so that the analytical, substantive theory can emerge.
Despite the evolving, inductive nature of this form of a qualitative
inquiry, the researcher must recognize that this is a systematic approach to
research with specific steps in data analysis.
The researcher needs faces the difficulty of determining when the
categories are saturated or when the theory is sufficiently detailed.
An ethnography is a description and interpretation of a cultural or social group
or system (Creswell, 1998). In such a study, the researcher examines the group’s
observable and learned patterns of behavior, customs, and ways of life (Harris,
1968). Here, the researcher becomes a participant observer, and gets immersed
in the day-to-day lives of the people or through one-on-one interviews with
members of the group. The researcher focuses on the meanings of behavior,
language, and inter-actions of the culture-sharing group.
Procedures Involved In Conducting A Study:
The research begins with the researcher looking at people in interaction in
ordinary settings and attempting to discern pervasive patterns such as life
cycles, events, and cultural themes.
To establish patterns, the ethnographer engages in extensive work in the
field (field work), gathering information through observations, interviews,
and materials helpful inn developing a portrait and establishing “cultural
rules” of the culture-sharing group.
The researcher is sensitive to gaining assess to the field through
gatekeepers. The ethnographer locates key informants, i.e., individuals who
provide useful insights into the group and can steer the researcher to
information and contacts. The researcher is also sensitive about reciprocity
between the investigator and the subjects being studied, so that something
will be returned to the subjects being studied in exchange for their
information. Lastly, the researcher is also sensitive to reactivity, the impact of
the researcher on the site and the people being studied. The researcher also
makes every effort to make his/her intent known from the start to avoid any
trace of deception.
The researcher then does a detailed description of the culture-sharing
group or individual, an analysis by themes or perspectives and some
interpretation for meanings of social interaction and generalizations about
human social life.
The researcher needs to have a grounding in cultural anthropology and
the meanings of social-cultural systems as well as the concepts typically
explored by ethnographers.
The time to collect data is extensive, involving prolonged time in the field.
The style of writing, literary (almost story telling approach), may limit
audience and may be challenging for some authors who are used to
traditional approaches of writing social science research.
There is the possibility that the researcher would “go native” and be
unable to complete the study or be compromised in the study.
Creswell (1998) defines a case study as an exploration of a “bounded system” or
a case (or multiple cases) over time through detailed, in-depth data collection
involving multiple sources of information rich in context. Some consider “the
case” as an object of study (e.g., Stake, 1995) while others consider it a
methodology (e.g., Merriam, 1998). According to Creswell, the bounded system
is bounded by time and place, and it is the case being studied – a program, an
event, an activity, or individuals.
Procedures Involved In Conducting A Study:
The researcher needs to situate the case in a context or setting. The
setting may be a physical, social, historical, and/or economic.
The researcher needs to identify the focus of the study. It could be
either on the case (intrinsic study), because of its uniqueness, or it may be on
an issue or issues (instrumental study), with the case used instrumentally to
illustrate the issue. A case study could involve more than one case (collective
In choosing what case to study, a researcher may choose a case because
it shows different perspectives on the problem, process, or event of interest,
or it may be just an ordinary case, accessible, or unusual.
The data collection is extensive, drawing on multiple sources of
information such as observations, interviews, documents, and audio-visual
The data analysis can be either a holistic analysis of the entire case or an
embedded analysis of a specific aspect of the case.
From the data collection, a detailed description of the case is done.
Themes or issues are formulated and then the researcher makes an
interpretation or assertions about the case.
When multiple cases are chosen, a typical format is to provide a detailed
description of each case and themes within the case (called within-case
analysis), followed by a thematic analysis across the cases (called a cross-case
analysis), as well as assertions or an interpretation of the meaning of the case.
In the final stage, the researcher reports the “lessons learned” from the
case (Lincoln and Guba, 1985).
The researcher needs to identify his/her case among a host of possible
The researcher needs to decide whether to study a single case or
multiple cases. The motivation for considering many cases is the issue of
generalizability, which is not so much of a pressing issue in qualitative
inquiry. Studying more than one case runs the risk of a diluted study, lacking
the “depth” compared to a single case. “How many” cases becomes a
Getting enough information to get a good depth for the case is a
Deciding on the boundaries in terms of time, events and processes may
be challenging. Some cases have no clean beginning and ending points.
The Creation of Theory:
A Recent Application of the Grounded Theory Method
Naresh R. Pandit *
The Qualitative Report, Volume 2, Number 4, December, 1996
This paper outlines a particular approach to building theory that was employed in a recent
doctoral research project (Pandit, 1995). Three aspects used in conjunction indicate the
project's novelty: firstly, the systematic and rigorous application of the grounded theory
method; secondly, the use of on-line computerised databases as a primary source of data;
and, thirdly, the use of a qualitative data analysis software package to aid the process of
grounded theory building.
The principal objective of this paper is to reveal how the style of qualitative research
known as the 'grounded theory approach' was applied in a research project (Pandit, 1995)
which attempted to generate a theoretical framework of corporate turnaround. Two lesser
auxiliary objectives are firstly, to assess the utility of on-line computerised databases as a
primary source of data for this type of research; and secondly, to assess the extent to
which computer-based qualitative data analysis (QDA) software can aid this type of
In the next section the elements of grounded theory are recalled. This is followed by a
detailed account of the procedures and rationale of grounded theory building as employed
in the project. Next, the generated theory of corporate turnaround is overviewed and
finally, a reflexive account of the research experience is given.
The Elements Of Grounded Theory
The three basic elements of grounded theory are concepts, categories and propositions.
Concepts are the basic units of analysis since it is from conceptualisation of data, not the
actual data per se, that theory is developed. Corbin and Strauss (1990, p. 7) state:
Theories can't be built with actual incidents or activities as observed or reported; that is,
from "raw data." The incidents, events, happenings are taken as, or analysed as, potential
indicators of phenomena, which are thereby given conceptual labels. If a respondent says
to the researcher, "Each day I spread my activities over the morning, resting between
shaving and bathing," then the researcher might label this phenomenon as "pacing." As
the researcher encounters other incidents, and when after comparison to the first, they
appear to resemble the same phenomena, then these, too, can be labelled as "pacing."
Only by comparing incidents and naming like phenomena with the same term can the
theorist accumulate the basic units for theory.
The second element of grounded theory, categories, are defined by Corbin and Strauss
(1990, p. 7) thus:
Categories are higher in level and more abstract than the concepts they represent. They
are generated through the same analytic process of making comparisons to highlight
similarities and differences that is used to produce lower level concepts. Categories are
the "cornerstones" of developing theory. They provide the means by which the theory can
be integrated. We can show how the grouping of concepts forms categories by continuing
with the example presented above. In addition to the concept of "pacing," the analyst
might generate the concepts of "self-medicating," "resting," and "watching one's diet."
While coding, the analyst may note that, although these concepts are different in form,
they seem to represent activities directed toward a similar process: keeping an illness
under control. They could be grouped under a more abstract heading, the category: "Self
Strategies for Controlling Illness."
The third element of grounded theory are propositions which indicate generalised
relationships between a category and its concepts and between discrete categories. This
third element was originally termed 'hypotheses' by Glaser and Strauss (1967). It is felt
that the term 'propositions' is more appropriate since, as Whetten (1989, p. 492) correctly
points out, propositions involve conceptual relationships whereas hypotheses require
measured relationships. Since the grounded approach produces conceptual and not
measured relationships, the former term is preferred.
The generation and development of concepts, categories and propositions is an iterative
process. Grounded theory is not generated a priori and then subsequently tested. Rather,
... inductively derived from the study of the phenomenon it represents. That is,
discovered, developed, and provisionally verified through systematic data collection and
analysis of data pertaining to that phenomenon. Therefore, data collection, analysis, and
theory should stand in reciprocal relationship with each other. One does not begin with a
theory, then prove it. Rather, one begins with an area of study and what is relevant to that
area is allowed to emerge. (Strauss and Corbin, 1990, p. 23. Emphasis added.)
The Process Of Grounded Theory Building
Five analytic (and not strictly sequential) phases of grounded theory building were
identified: research design, data collection, data ordering, data analysis and literature
comparison. Within these phases, nine procedures or steps were followed. These phases
and steps were evaluated against four research quality criteria: construct validity, internal
validity, external validity and reliability. Briefly, construct validity is enhanced by
establishing clearly specified operational procedures. Internal validity is enhanced by
establishing causal relationships whereby certain conditions are shown to lead to other
conditions, as distinguished from spurious relationships. In this sense, internal validity
addresses the credibility or "truth value" of the study's findings. External validity requires
establishing clearly the domain to which the study's findings can be generalised. Here,
reference is made to analytic and not statistical generalisation and requires generalising a
particular set of findings to some broader theory and not broader population. Finally,
reliability requires demonstrating that the operations of a study - such as data collection
procedures - can be repeated with the same results.
Table 1 provides an overview of these phases, steps and tests and forms the template for
the subsequent discussion which moves from a normative or prescriptive account of
recommended activities to a descriptive account of how these prescriptions were applied
in the study.
Table 1: The Process of Building Grounded Theory
PHASE ACTIVITY RATIONALE
Step Review of technical Definition of research Focuses
1 literature question efforts
Definition of a priori Constrains irrelevant variation and
constructs sharpens external validity
Step Selecting cases Theoretical, not random, Focuses efforts on theoretically useful cases
2 sampling (e.g., those that test and/or extend theory)
Step Develop rigorous data Create case study Increases reliability Increases construct
3 collection protocol database validity
Employ multiple Strengthens grounding of theory by
data collection triangulation of evidence. Enhances
methods internal validity
Qualitative and Synergistic view of evidence
Step Entering the field Overlap data Speeds analysis and reveals
4 collection helpful adjustments to data collection
Allows investigators to take advantage of
Flexible and opportunistic emergent themes and unique case features
data collection methods
DATA ORDERING PHASE
Step Data ordering Arraying events Facilitates easier data analysis. Allows
5 chronologically examination of processes
DATA ANALYSIS PHASE
Step Analysing Use open Develop concepts, categories and properties
6 data relating to coding
the first case Develop connections between a category
Use axial and its sub-categories
Integrate categories to build theoretical
Use selective framework
All forms of coding enhance internal
Step Theoretical sampling Literal and theoretical Confirms, extends, and sharpens theoretical
7 replication across cases framework
(go to step 2 until
Step Reaching closure Theoretical saturation Ends process when marginal improvement
8 when possible becomes small
Step Compare emergent Comparisons with Improves construct definitions, and
9 theory with extant conflicting frameworks therefore internal validity
Comparisons with similar Also improves external validity by
frameworks establishing the domain to which the
study's findings can be generalised
Research Design Phase
Research design is defined by Easterby-Smith et al. (1990, p. 21) as,
... the overall configuration of a piece of research: what kind of evidence is gathered from
where, and how such evidence is interpreted in order to provide good answers to the basic
It follows logically that the first step is to define the basic research questions. These
should be defined narrowly enough so that the research is focused and broad enough to
allow for flexibility and serendipity.
A good source of research questions in grounded theory studies is the 'technical literature'
(i.e., reports of research studies and theoretical and philosophical papers characteristic of
professional and disciplinary writing) on the general problem area (Strauss and Corbin,
1990, p. 52).
Once basic research questions have been generated and the research is focused, the next
aspect of research design and the second step is to select the first case. Cases (the
principal units of data in this research) should be selected according to the principle of
The process of data collection for generating theory whereby the analyst jointly collects,
codes, and analyses his data and decides what data to collect next and where to find them,
in order to develop his theory as it emerges. (Glaser and Strauss, 1967, p. 45.)
Unlike the sampling done in quantitative investigations, theoretical sampling cannot be
planned before embarking on a grounded theory study. The specific sampling decisions
evolve during the research process itself. (Strauss and Corbin, 1990, p. 192)
During initial data collection, when the main categories are emerging, a full 'deep'
coverage of the data is necessary. Subsequently, theoretical sampling requires only
collecting data on categories, for the development of properties and propositions. The
criterion for judging when to stop theoretical sampling is the category's or theory's
'theoretical saturation'. By this term Glaser and Strauss refer to the situation in which:
... no additional data are being found whereby the (researcher) can develop properties of
the category. As he sees similar instances over and over again, the researcher becomes
empirically confident that a category is saturated ... when one category is saturated,
nothing remains but to go on to new groups for data on other categories, and attempt to
saturate these categories also. (1967, p. 65.)
A qualification springs from the fact that not all categories are equally relevant, and
accordingly the depth of enquiry into each one should not be the same. As a general rule,
core categories, those with the greatest explanatory power, should be saturated as
completely as possible. A theory is saturated when it is stable in the face of new data and
rich in detail.
Theoretical sampling translates in practical terms into two sampling events. An initial
case is selected and, on the basis of the data analysis pertaining to that case and hence the
emerging theory, additional cases are selected.
The initial case (unit of data) in this study was the technical literature on the subject of
corporate turnaround. Strauss and Corbin support this approach and state:
The literature can be used as secondary sources of data. Research publications often
include quoted materials from interviews and field notes and these quotations can be used
as secondary sources of data for your own purposes. The publications may also include
descriptive materials concerning events, actions, settings, and actors' perspectives, that
can be used as data using the methods described. (1990, p. 52.)
The grounded analysis of the first ('literature') case led to the generation of the initial
theoretical framework of corporate turnaround. Additional ('empirical') cases were then
selected, one at a time, to test and extend this framework.
To recall, according to the principle of theoretical sampling, each additional case should
serve specific purposes within the overall scope of enquiry. Three options are identified
by Yin (1989, p. 53-54):
choose a case to fill theoretical categories, to extend the emerging theory; and/or,
choose a case to replicate previous case(s) to test the emerging theory; or,
choose a case that is a polar opposite to extend the emerging theory.
Logically, this implies that each additional case must be carefully selected so that it
produces similar results (a literal replication - options (a) and (b) above ); or, produces
contrary results but for predictable reasons (a theoretical replication - option (c) above).
The second case or unit of data, Fisons plc which experienced a turnaround during the
period 1975-84, was selected for the purpose of literal replication, that is, to fill
theoretical categories and to test the emerging theory. The third case, British Steel
Corporation (BSC) which experienced a turnaround during the period 1975-89 was again
chosen for the purposes of literal replication.
After the analysis of the three cases, the marginal improvement to the theoretical
framework was small. Theoretical saturation via literal replication had been approached
and the decision to conclude the research was taken. This experience is corroborated by
Martin and Turner (1986, p. 149) who state:
By the time three or four sets of data have been analysed, the majority of useful concepts
will have been discovered.
Data Collection Phase
The grounded approach advocates the use of multiple data sources converging on the
same phenomenon and terms these 'slices of data.' Glaser and Strauss (1967, p. 65) state,
In theoretical sampling, no one kind of data on a category nor technique for data
collection is necessarily appropriate. Different kinds of data give the analyst different
views or vantage points from which to understand a category and to develop its
properties; these different views we have called slices of data. While the [researcher] may
use one technique of data collection primarily, theoretical sampling for saturation of a
category allows a multifaceted investigation, in which there are no limits to the
techniques of data collection, the way they are used, or the types of data acquired.
(Emphasis in original.)
Similarly, Eisenhardt (1989, p. 538) states:
... case study research can involve qualitative data only, quantitative only, or both..
Moreover, the combination of data types can be highly synergistic.
The synergy (or 'data triangulation') referred to works as follows: quantitative data can
indicate directly observable relationships and corroborate the findings from qualitative
data. Qualitative data can help understand the rationale of the theory and underlying
The use of multiple data sources thus enhances construct validity and reliability. The
latter is further enhanced through the preparation of a case study database which is a
formal assembly of evidence distinct from the case study report. Yin (1989, pp. 98-99)
Every case study project should strive to develop a formal, retrievable database, so that in
principle, other investigators can review the evidence directly and not be limited to the
written reports. In this manner, the database will increase markedly the reliability of an
entire case study. (Emphasis added.)
To summarise, the third step is to develop a rigorous data collection protocol by
employing multiple data collection methods using both qualitative and quantitative data
and systematically establishing a case study database.
The principal data source in this study for the two 'empirical' cases (i.e., Fisons and BSC)
was archival material in the form of reports in newspapers, trade journals, business
journals, government publications, broker reviews, annual company documents and press
releases. These data were extracted in computerised form (i.e., ASCII files) from the
Reuter Textline and Predicasts PROMT (Predicasts Overview of Markets and
Technology) databases. There are over 600 active information sources contributing to
Reuter Textline, of which approximately 200 are primary sources and over 400 are
associated sources provided by third party contributors. The earliest material on Reuter
Textline dates from 1980. Predicasts is the largest on-line source of business information
of its kind. The Predicasts family of complimentary databases contains more than
5,000,000 article abstracts, forecasts, statistical series and full text records from a broad
range of business, industry and government sources. The earliest material on PROMT
dates from 1975.
It was whilst reading a paper by Turner (1983) that the idea of developing grounded
theory based on this type of data was formed. In that research project,
... documentary sources were treated like sets of field notes. Analysis and category
generation was commenced at the first paragraph of the report, and a theoretical
framework generated which would handle the aspects perceived to be of interest to each
paragraph. (1983, p. 342.)
Case study databases were constructed within the qualitative data analysis software
package ATLAS. A full discussion of the procedures followed is provided in the data
analysis section below.
The fourth step was thus to ensure that data was collected and analysed simultaneously
and flexibility is maintained. This overlap allows adjustments to be made to the data
collection process in light of the emerging findings. Eisenhardt describes such flexibility
as 'controlled opportunism'.
Data Ordering Phase
The fifth step was data ordering. Following Yin (1989, p. 119) data for the two 'empirical'
cases were ordered chronologically:
The arraying of events into a chronology permits the investigator to determine causal
events over time, because the basic sequence of a cause and its effect cannot be
temporally inverted. However, unlike the more general time-series approaches, the
chronology is likely to cover many different types of variables and not be limited to a
single independent or dependent variable.
Data Analysis Phase
Once data were ordered, the sixth step was to analyse the data. Data analysis is central to
grounded theory building research. For the study as a whole, data collection, data
ordering, and data analysis were interrelated as depicted in figure 1 (the attached
numbers indicate the activity's analytic sequence).
Figure 1: The Interrelated Processes of Data Collection,
Data Ordering, and Data Analysis to Build Grounded Theory
Data Analysis (4)
Theory Development (5)
Data Ordering (3)
Theory Saturation ? Yes
Data Collection (2)
Theoretical Sampling (1)
Within this general framework, data analysis for each case involved generating concepts
through the process of coding which,
... represents the operations by which data are broken down, conceptualised, and put back
together in new ways. It is the central process by which theories are built from data.
(Strauss and Corbin, 1990, p. 57.)
There are three types of coding: open coding, axial coding, and selective coding. These
are analytic types and it does not necessarily follow that the researcher moves from open
through axial to selective coding in a strict, consecutive manner.
Open coding refers to that part of analysis that deals with the labelling and categorising
of phenomena as indicated by the data. The product of labelling and categorising are
concepts - the basic building blocks in grounded theory construction.
Open coding requires application of what is referred to as 'the comparative method', that
is, the asking of questions and the making of comparisons. Data are initially broken down
by asking simple questions such as what, where, how, when, how much, etc.
Subsequently, data are compared and similar incidents are grouped together and given the
same conceptual label. The process of grouping concepts at a higher, more abstract, level
is termed categorising.
Whereas open coding fractures the data into concepts and categories, axial coding puts
those data back together in new ways by making connections between a category and its
sub-categories (i.e., not between discrete categories which is done in selective coding).
Thus, axial coding refers to the process of developing main categories and their sub-
Selective coding involves the integration of the categories that have been developed to
form the initial theoretical framework.
Firstly, a story line is either generated or made explicit. A story is simply a descriptive
narrative about the central phenomenon of study and the story line is the
conceptualisation of this story (abstracting). When analysed, the story line becomes the
The core category must be the sun, standing in orderly systematic relationships to its
planets. (Strauss and Corbin, 1990, p. 124.)
Subsidiary categories are related to the core category according to the paradigm model,
the basic purpose of which is to enable the researcher to think systematically about data
and relate them in complex ways. The basic idea is to propose linkages and look to the
data for validation (move between asking questions, generating propositions and making
comparisons). The basic features of this model are depicted in figure 2 below.
Figure 2: The Paradigm Model
Action / Interaction Strategies
The core category (i.e., the central idea, event or happening) is defined as the
phenomenon. Other categories are then related to this core category according to the
schema. Causal conditions are the events that lead to the development of the
phenomenon. Context refers to the particular set of conditions and intervening conditions,
the broader set of conditions, in which the phenomenon is couched. Action/interaction
strategies refer to the actions and responses that occur as the result of the phenomenon
and finally, the outcomes, both intended and unintended, of these actions and responses
are referred to as consequences.
An important activity during coding is the writing of memos. Corbin and Strauss (1990,
p. 10) maintain that,
Writing theoretical memos is an integral part of doing grounded theory. Since the analyst
cannot readily keep track of all the categories, properties, hypotheses, and generative
questions that evolve from the analytical process, there must be a system for doing so.
The use of memos constitutes such a system. Memos are not simply "ideas." They are
involved in the formulation and revision of theory during the research process.
At least three types of memo may be distinguished: code memos, theoretical memos and
operational memos. Code memos relate to open coding and thus focus on conceptual
labelling. Theoretical memos relate to axial and selective coding and thus focus on
paradigm features and indications of process. Finally, operational memos contain
directions relating to the evolving research design.
In the past, the tools used to aid the type of data analysis elucidated above were simply
scissors, a copier and piles of blank paper. In this research project, data were analysed
using the qualitative data analysis software package ATLAS which also facilitated the
construction of case study databases. The use of computer programs to aid the analysis of
qualitative data is a recent innovation:
... there has been considerable progress in the analysis of qualitative data using a variety
of specially written computer programs ... There are at present around a dozen programs
on the market or under development, each with different characteristics and facilities.
(Lee and Fielding, 1991, p. 1.)
The principal advantage of using a program is that it simplifies and speeds the
mechanical aspects of data analysis without sacrificing flexibility thereby freeing the
researcher to concentrate to a greater extent on the more creative aspects of theory
The thinking, judging, deciding, interpreting, etc., are still done by the researcher. The
computer does not make conceptual decisions, such as which words or themes are
important to focus on, or which analytical step to take next. These analytical tasks are
still left entirely to the researcher. (Tesch, 1991, pp. 25-26.)
Lee and Fielding summarise:
It is likely that computers will bring real benefits to qualitative researchers, making their
work easier, more productive and potentially more thorough. (1991, p. 6.)
There are two modes of data analysis within ATLAS: firstly, the 'textual level' which
focuses on the raw data and includes activities such as text segmentation and, coding and
memo writing; and secondly, the 'conceptual level' which focuses on framework building
activities such as interrelating codes, concepts and categories to form theoretical
networks. In general, we found the procedures within ATLAS to be both efficient and
firmly based on the principles of grounded theory generation.
Once a theoretical framework relating to the first case has been generated, the next and
seventh step in theory building case research is to test and develop this framework by
selecting additional cases according to the principle of theoretical sampling, that is, with
the aim to extend and/or sharpen the emerging theory by filling in categories that may
need further refinement and/or development. The eighth step, reaching closure, is taken
according to the principle of theoretical saturation, that is, when the marginal value of
the new data is minimal.
Literature Comparison Phase
The ninth and final step is to compare the emerged theory with the extant literature and
examine what is similar, what is different, and why. Eisenhardt (1989, p. 545) states:
Overall, tying the emergent theory to existing literature enhances the internal validity,
generalisability, and theoretical level of the theory building from case study research ...
because the findings often rest on a very limited number of cases.
The emergent theory of corporate turnaround was compared with the extant theories in
the broader field of strategic management. This revealed the discovered theory to
resemble in many ways Pettigrew's "content-context-process" model of strategic change
An Overview of a Grounded Theory of Corporate Turnaround
Through the process of open and axial coding in ATLAS/ti a number of concepts and
categories were generated and developed. During selective coding (i.e., the integration of
categories) the core category was defined and labelled 'recovery strategy content'. The
other major categories were then related to this category. The content of appropriate
recovery strategies were found to be contingent upon six sets of contextual factors: the
causes of decline; the severity of the crisis; the attitude of stakeholders; industry
characteristics; changes in the macroeconomic environment; and, the firm's historical
strategy. The content of recovery strategies was usefully decomposed into operational
level actions (management change, improved controls, reduction in production costs,
investment in plant and machinery, decentralisation, improved marketing, and
restructuring finances) and strategic level actions (asset reduction/divestiture and
product/market reorientation). An implementation or process dimension was also
discovered. Successful actions to effect recovery fall into four distinct (but overlapping)
stages (the management change stage, the retrenchment stage, the stabilisation stage, and
the growth stage). A diagrammatical depiction of this framework is given in figure 3 (see
Pandit, 1995 for a fuller discussion).
Figure 3: A Theoretical Framework of Corporate Turnaround
The causes of decline
The severity of the crisis
The attitude of the stakeholders
Changes in the macroeconomic
The firm's historical strategy
IMPLEMENTATION / PROCESS OF RECOVERY
Management change stage
Retrenchment stage Operational level:
Stabilisation stage Management change
Growth stage Improved controls
Reduction in production costs
Investment in plant and machinery
53 propositions linking the concepts and categories within the framework were generated
and tested. Table 2 lists a sample of five (see Pandit, 1995, pp. 277-278 for the full list).
Table 2: A Sample of Propositions Generated by the Literature Case and
Supported by the Cases of Fisons and BSC
Proposition Generated by Explicitly Implicitly Explicitly Implicitly
the Literature Case Supported Supported Supported Supported
A sustained deterioration in
performance is the result of
both internal and external
Successful turnaround firms
are more severely affected in
terms of financial
performance in the
downturn phase than
If the causes of decline are
primarily internal in origin,
actions that improve
efficiency at the operational
level should be emphasised
to effect successful recovery.
If the causes of decline are
primarily external in origin,
strategic level actions should X X
be emphasised to effect
actions vary according to X X
With respect to the two lesser auxiliary objectives of this study I found firstly, that the
data available from the on-line databases Reuters Textline and Predicasts PROMT to be
extremely appropriate for this type of research. The hundreds of articles extracted
provided a rich and diverse source of information for the two 'empirical' cases. Events
were easily traced over time, differing viewpoints provided much intellectual stimulation,
and reported interviews with key people at the time rather than retrospectively provided
valuable insights and served as an efficient and effective substitute for conducting similar
interviews ourselves. Ultimately, my assessment of the quality of the data is a tribute to
the quality of business journalism in the UK, the USA and continental Europe (where
most of the reports we analysed originated).
My second auxiliary objective was to assess the utility of computer-based qualitative data
analysis software packages when used in conjunction with on-line data in grounded
theory research. In general, I found the packages to be of limited use (rather than easing
the process they tend to overcomplicate it) with much development required before they
can make a significant impact on the conduct and quality of qualitative research.
However, I found the package that I chose (ATLAS) to be very much the exception to the
rule. A number of attributes distinguished it from the alternatives. Firstly, it is very 'user-
friendly' and operates in a similar manner to the more widely used Windows package
developed by Microsoft. Secondly, it is powerful. Given the immense volume of data to
be analysed, problems were expected but thankfully never materialised. Finally, it is
thoroughly based on the principles of grounded theory generation and therefore few
compromises had to be made.
Five problems were encountered in this study. Four relate to the research process and
one, more fundamentally, to the research approach. Firstly, the process of grounded
theory research is extremely time-consuming. The sheer volume and complexity of data
generated for this study was quite daunting, although the use of ATLAS aided matters
considerably. Secondly, grounded theory research involves long periods of uncertainty.
Without a priori hypotheses to test and established protocol to follow, much of the first
half of the study period required a good measure of faith and hope. Thankfully, there did
come a time after much patience, persistence, and perspiration when things become
clearer. Thirdly, the data extracted from the two on-line databases was sometimes found
to be incomplete. Often, and particularly with long articles, only summaries and not the
full text was available. This was particularly disappointing given that longer articles are
usually the most informative and, therefore, potentially of most use. I estimate that about
10 per cent of the data extracted was shortened in this way. Also, any graphs related to an
article are not reproduced in computerised form within the databases. Once again,
valuable information is lost. Fourthly, collecting data from on-line databases is
expensive. Fortunately, my access to Reuters Textline was at a preferential rate (used for
promotional purposes) and my access to Predicasts PROMT was free of charge owing to
the fact that it was on a limited trial period. Without these two contingencies our runs
(which amounted to well over 100 hours of on-line time) would have cost many
thousands of pounds sterling.
Let us now turn to the fifth and more fundamental problem with the overall approach of
this study. Grounded theory research requires certain qualities of the researcher. In
particular, confidence, creativity and experience (both of doing research and of the
context(s) being researched) are of great benefit. Accordingly, the approach does not
favour the novice researcher who may be just beginning to develop these qualities. This
is not to say that novice researchers should not embark upon grounded theory studies;
rather, I imply that (a) they are likely to find the approach more difficult than more
conventional methodologies; and, (b) the more experienced (probably postdoctoral)
researcher is likely to produce better theory.
Grounded theory begins with a research situation. Within that situation, your
task as researcher is to understand what is happening there, and how the
players manage their roles. You will mostly do this through observation,
conversation and interview. After each bout of data collection you note down
the key issues: this I have labelled "note-taking".
Constant comparison is the heart of the process. At first you compare
interview (or other data) to interview (or other data). Theory emerges
quickly. When it has begun to emerge you compare data to theory.
The results of this comparison are written in the margin of the note-taking as
coding. Your task is to identify categories (roughly equivalent to themes or
variables) and their properties (in effect their sub-categories).
If this is all a bit abstract, some examples later will help.
As you code, certain theoretical propositions will occur to you. These may be
about links between categories, or about a core category: a category which
appears central to the study. As the categories and properties emerge, they
and their links to the core category provide the theory. You write yourself
notes about it -- memoing.
As the data collection and coding proceeds the codes and the memos
You add to your sample through theoretical sampling. This is purposive
sampling which increases the diversity of your sample, searching for different
properties. If your core category and its linked categories saturate; you no
longer add to them or their properties. This is a sign that it is time to move
to sorting. You group your memos, like with like, and sequence them in
whatever order will make your theory clearest.
The literature is accessed as it becomes relevant. It is not given special
treatment. Glaser makes the point that most research including qualitative
research is hypothesis-testing.
The order of your sorted memos provides you with the skeleton, and many of
the words, of your thesis. You begin writing.
To summarise graphically ...
Over time, a grounded theory study works through the following mostly-
In short, data collection, note-taking, coding and memoing occur
simultaneously from the beginning. Sorting occurs when all categories are
saturated -- this is explained in more detail later, as are the elements of this
diagram. Writing occurs after sorting.
For ease of explanation, what follows may seem a bit prescriptive. Feel free
to experiment with it until you find something that works for you. The theory
is emergent -- discovered in the data, Glaser will say. The methods can be
This is an important issue, worth more attention.
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Hypothesis testing versus emergence
What most differentiates grounded theory from much other research is that it
is explicitly emergent. It does not test a hypothesis. It sets out to find what
theory accounts for the research situation as it is. In this respect it is like
action research: the aim is to understand the research situation. The aim, as
Glaser in particular states it, is to discover the theory implicit in the data.
This distinction between "emergence and forcing", as Glaser frames it, is
fundamental to understanding the methodology. Most of you, whatever your
discipline, will have been exposed more to hypothesis-testing research than
to emergent research. The research processes you have learned and the
thesis structures you have internalised are those of hypothesis testing, not of
emergence. Doing grounded theory well is partly a matter of unlearning
some of what you have been taught or have acquired through your reading.
If you judge grounded theory by the criteria you have learned to use for
hypothesis testing research you will likely misjudge it, perhaps badly. In
particular, the place of literature is quite different. So is the way in which
both methodology and theory develop gradually as data and interpretations
In particular, judgments about the rigour of research are often based on
narrow criteria: criteria which make sense only for the methodology for which
they were developed. Grounded theory has its own sources of rigour. It is
responsive to the situation in which the research is done. There is a
continuing search for evidence which disconfirms the emerging theory. It is
driven by the data in such a way that the final shape of the theory is likely to
provide a good fit to the situation.
In fact, Glaser suggests two main criteria for judging the adequacy of the
emerging theory: that it fits the situation; and that it works -- that it helps
the people in the situation to make sense of their experience and to manage
the situation better.
Elsewhere, I’ve offered similar arguments in favour of action research. In
particular, I draw your attention to my 1999 paper to the AQR conference,
and the recent paper on data driven research.
Now, the elements in more detail ...
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You will of course keep your eyes open. There is a lot to be learned just by
observing, some of it evident within minutes of entering a situation.
Interviews are frequently the main source of the information you will develop
your theory from. But any data collection methods can be used. Focus
groups are not uncommon in other qualitative research, and are suited to
grounded theory. So is informal conversation, group feedback analysis, or
any other individual or group activity which yields data.
I’ve included some references in the bibliography. For interviewing I like
Minichiello, Aroni, Timewell and Alexander (1990) or Kvale (1996), and of
course my own Convergent interviewing. For focus groups you might try
some of the recent work: Bader and Rossi (1998) I like, and also Barbour and
Kitzinger (1999). For both interviews and focus groups I’ve also listed some
others. For group feedback analysis, try Heller and Brown (1995).
I won’t go into further detail here. I will say two further things. First, I
assume that you will touch base with the literature on your chosen method.
Second, I presume you’ll continue to fine tune it as you develop more
experience in its use. I encourage you to experiment.
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Glaser recommends against recording or taking notes during an interview of
other data collection session. Speaking for myself, I agree with his avoidance
of tape recordings and word-by-word transcripts. I think you’ll get more
understanding from the extra interviews you could do in the time it would
take you to listen to and transcribe a tape recording.
However, I think he is vulnerable on that point, and especially for thesis
purposes. My suggestion is that you take key-word notes during the
interviews and convert them to themes afterwards. I also suggest that you
tape-record the interviews and check your notes against the tape recording.
This won’t be as time consuming (or alternatively as costly) as full transcripts
and in my experience it will do the job well.
If it’s not for thesis purposes I think you can make your own choices. I
neither take notes during interviews nor use a tape recorder. I find rapport
develops more rapidly and effectively if I don’t. However, I do have a
memory system which allows me to memorise up to 20 distinct themes (more
if it’s necessary) and recall them in order.
The coding (which follows) will be much easier if you do it adjacent to the
interview notes. You can leave wide margins (as much as a third of the page,
perhaps) for that purpose.
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So -- in reality or in imagination -- you have in front of you a set of interview
notes. They are written in the left hand two-thirds of the page, let’s say.
You’ve identified any important bio-data about the person interviewed at the
head of the notes (this may later help to identify properties).
Have some other pieces of paper, or preferably cards, for memoing. The
benefits of that will become evident soon.
You begin to code. You take a sentence at a time and examine it.
[ index ]
o Constant comparison
For the first interview you are merely asking yourself: What is going on here?
What is the situation? How is the person managing that situation? Therefore,
what categories (plural) are suggested by that sentence?
Code the second interview with the first interview in mind. Code subsequent
interviews (or data from other sources) with the emerging theory in mind.
That’s constant comparison: initially comparing data set to data set; later
comparing data set to theory.
o For instance, suppose you were to ask the postgraduates in the
coursework higher degrees at Griffith University about the course, as I
did recently. The first two people might mention (as they did) having
to organise time or organise work. You may tentatively code these
sentences as "organising" (perhaps among other codes).
As you do this, be aware of any theoretical ideas that come to mind. If any
do, note them down immediately. For easier sorting later, I use 125 mm x 75
mm systems cards. They fit in my pocket and are very convenient. I carry a
pocketful around with me most of the time.
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o Categories and properties
In effect, a category is a theme or variable which makes sense of what your
informant has said. It is interpreted in the light of the situation you’re
studying, and other interviews, and the emerging theory.
o In the two sentences considered above, I’ve already mentioned
"organising" as a tentative category. What is different between the
two sentences is this: one is about organising time, one about
organising work. Perhaps this will be a property, a sub-category, of
[ index ]
o Core category
After a time one category (occasionally more) will be found to emerge with
high frequency of mention, and to be connected to many of the other
categories which are emerging. This is your core category. It is hazardous to
choose a core category too early in the data collection. However, when it is
clear that one category is mentioned with high frequency and is well
connected to other categories, it is safe to adopt this as the core category.
(If more than one core category emerges, Glaser recommends focussing at
one time on one only. You can recode for the second of them later, if you
o All five of the postgraduates I talked to in my miniature example
mentioned the use they were making or would make of what they
were learning. If became evident before long that this one category
(titled "application") fitted the two criteria of frequency of mention and
When a core category has been identified, you cease coding any sentences
which do not relate to it. You will find that in most instances your coding
rapidly becomes more efficient as the study progresses. You now code for
the core category, other connected categories, and properties of both.
You record any identified connections between categories in memos. You
continue doing this, adding to your sample as necessary (see sampling,
below), until you achieve saturation.
[ index ]
In collecting and interpreting data about a particular category, in time you
reach a point of diminishing returns. Eventually your interviews add nothing
to what you already know about a category, its properties, and its relationship
to the core category.
When this occurs you cease coding for that category.
[ index ]
Your initial sample is likely to be defined by your choice of research situation.
If there are many people associated with the situation, you might begin by
putting together as diverse a sample as you are able. (I don’t recall
anywhere that Glaser offers a clear description of the beginning sample,
though I may be mistaken there.)
As categories emerge from your data, you then seek to add to your sample in
such a way that you further increase diversity in useful ways. Your purpose is
to strengthen the emerging theory by defining the properties of the
categories, and how those mediate the relationship of category to category.
Glaser and Strauss refer to this as theoretical sampling. The sample is
emergent, as is the theory and the method generally.
o The small group of postgraduates I talked to were either studying
part-time and working, or had worked at some stage. One might
expect a category such as "application" to be influenced by work
experience. I could therefore have added usefully to the sample by
identifying and talking to people from the program who had never
[ index ]
I have mentioned already that memoing continues in parallel with data
collection, note-taking and coding. In effect, a memo is a note to yourself
about some hypothesis you have about a category or property, and
particularly about relationships between categories.
Glaser makes the point, and I agree, that memoing is given high priority. As
an idea occurs to you, pause in what you are doing and write a memo to
yourself. I carry a pocket full of 125 mm x 75 mm system cards in my pocket
most of the time, for jotting down memos.
In time your core category and the categories related to it will have
saturated. By the time this happens you will have accumulated a large
number of memos. Between them they will capture the different aspects of
the theory which has emerged from your data.
o In the example, early memos might record hypotheses that
"organisation" and "application" were categories. Another memo
might question if "present application to work" and "future application
to work" might be properties of application. A further memo might
hypothesise that application is a core category. Another memo might
query if organisation is important at least in part because it may lead
to better application.
In short, in using grounded theory methodology you assume that the theory
is concealed in your data for you to discover. Coding makes visible some of
its components. Memoing adds the relationships which link the categories to
The next task is to decide how you will structure the report to communicate
your theory to others. That is the purpose of sorting.
[ index ]
My reason for using cards for memoing is twofold. They are easier to carry,
so I can jot down ideas whenever they occur to me. They are easier to sort.
For the actual sorting I work on a large table or on the floor. First I group
them on the basis of the similar categories or properties they address. I then
arrange the groups to reflect on the sorting surface their relationship. The
intention is that their layout in two-dimensional space will capture the
structure of the eventual report or thesis.
I then gather the cards in the sequence which will allow the structure to be
described. This provides the basis for the writing up, which follows.
[ index ]
Having done all this -- coding, memoing, sorting -- the writing is less a chore
than it might otherwise be. The sort structure is the report structure. It is
often just a matter of preparing a first draft by typing up the cards in
sequence and integrating them into a coherent argument.
[ index ]
The place of literature
There are two important points to be made about the literature. The first is
that, in an emergent study, you probably won’t know at the beginning which
literature will later turn out to be relevant. This has implications both for the
place of reading in your own research process and for your report. The
second is that the literature is not given a position of privilege when
compared to the data. It is treated as data, with the same status as other
[ index ]
o Literature as emergent
Most people embarking on a research project will first examine the relevant
literature. Thesis candidates often do not begin data collection until well into
their candidature. In an emergent study you can begin collecting data as
soon as you have a research situation. You can then access literature as it
Glaser (especially 1978) makes much of the prior background reading which
provides the models to help make sense of the data. He recommends reading
widely while avoiding the literature most closely related to what you are
researching. His fear, which I share, is that your reading may otherwise
constrain your coding and memoing.
At the same time, I think this approach may leave you vulnerable to criticism
from examiners or referees or colleagues. The defence is to take special
pains to be responsive to the data, to seek disconfirming evidence
assiduously, and to defend by careful argument your decision to do so.
Reading later is less an issue for Glaser. My own view is that it makes sense
to access relevant literature as it becomes relevant. Most examiners and
colleagues will expect you to locate your study within the relevant fields of
literature. You can also reach a wider sample, in effect, by refining your
findings in the light of the literature in slightly different but related fields.
In short, a progressive accessing and reading of relevant literature can
become a part of your data collection procedures.
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o Literature as data
Constant comparison remains your core process. Your aim as you read is to
compare literature to the emerging theory in the same way that you compare
data to the emerging theory. For instance you might follow the same
procedure of data-collection (in this instance reading) overlapping with note-
taking, coding and memoing.
Whether or not you do precisely this, the key issue is how you treat apparent
disagreement between your emerging theory and the literature. You don’t
assume that your theory must be wrong. After all, you have been concerned
throughout with its fit to the data and its ability to make sense of actual
experience. You seek to extend the theory so that it makes sense of both the
data from your study and the data from the literature.
This issue -- of treating disagreement appropriately -- has been a focus of
some of my own work on rigour in action research. It is in fact possible to
substitute some action research procedures for some of all of data-collection,
note-taking, coding, memoing and sorting.
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A variation based on action research
I research my own practice as educator, facilitator and consultant. The
methods I use were developed until recently entirely independently of
grounded theory. I wasn’t familiar with its literature. When I did eventually
start to read that literature I was pleased at the obvious parallels between the
Let me illustrate this by describing how I approach ... let’s say,
organisational diagnosis, using interviewing. I’ll do this in such a way that
the parallels are evident. I think you will find that the parallels are such that
you can substitute parts of one for parts of the other.
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o Convergent interviewing
In diagnostic interviewing (see my 1990 monograph) I begin in a very open-
ended way. For instance I may often say "Tell me about this organisation" or
whatever it is. I then keep the person talking for somewhere about 45
minutes without asking specific questions. This increases the likelihood that
the data come from the informant's experience, not from the questions I ask.
I memorise the themes they mention (some of my colleagues instead take
key-word notes, which serve the same purpose).
I prefer to work with a colleague who at the same time interviews a different
informant. After each pair of interviews we compare notes. We identify those
themes which both informants mention.
Sometimes those themes are mentioned in the same way by both
informants. Sometimes they mention the same theme, but with
o I was evaluating an action learning program with Karyn Healy, a
colleague. Many informants mentioned that they weren’t provided
resources which allowed them to pay someone to do their work, to
free them up for their action learning.
An example of agreement might be two informants saying words to
the effect that their action learning was done in their own time, which
they both resented. A disagreement would be when both mentioned
doing it in their own time, but one of them mentioned this with
satisfaction, not dissatisfaction.
When we identify an agreement we devise probe questions to seek exceptions
to the agreement.
o For example, we might ask if there were people who didn’t resent the
intrusions on their own time. We might ask if there were advantages
to being able to devote their own time to the action learning projects.
When we identify a disagreement we devise probe questions which seek
explanations for the difference.
o For instance we might say something like this ... "Many people have
mentioned taking part in the action learning in their own time. To
what extent was this your experience? How did you feel about that?
Some have mentioned this with substantial resentment. Others seem
not to mind. Can you help us understand how this difference might
As with grounded theory the explanations emerge gradually from the data as
the study proceeds. All interviews begin open-ended. In the later interviews
there are more probe questions. And more of those probes are specific. The
theory emerges from the data, from the informants. In the early stages it
consists primarily of themes. These become more elaborated as the study
This is depicted diagrammatically below.
I suggest that, in deciding your own methods, you choose those which will be
easiest for you to defend to examiners, readers or colleagues. What you do is
probably less important than how well you justify it.
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This is for those attempting to use grounded theory in psychology. Many of
you will barely have heard of qualitative methodology, let alone learned how
to use them. However, there is a growing, if small, band of people exploring
the application of qualitative methods in psychology. I’ve included some of
them in the bibliography below. It may help you with your supervisors,
committee or examiners if you can demonstrate that there is an alternative
tradition to which your studies are a contribution.
[ index ]
Contribution to knowledge
I have no doubt, by the way, that you will have a contribution to knowledge
at the end of it all. The theory will arise more quickly than you imagine.
You’ll enjoy doing it (Glaser calls it the "drugless trip"). There is a good
chance it will be an addition to the literature because most psychological
research builds on what has gone before. You, on the other hand, are going
to be responsive to the research situation as it is. You are going to find out
what is really happening there.
By some chance you may discover a theory only to find someone else has
come up with the same theory using more traditional methods. You still have
a contribution to knowledge, and a valuable one. You have cross-validated,
using a very different methodology, the theory previously offered.