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Solved by verified expert:please answer the question in ch 9 p 93 and 94 (last two page)step to answer:1. read the book ch 82. read the three research3. answer each question (each research has own answer)
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The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1176-6093.htm
Mixed methods research
in accounting
Mixed methods
research in
accounting
Jennifer Grafton and Anne M. Lillis
Department of Accounting and BIS, The University of Melbourne,
Melbourne, Australia, and
5
Habib Mahama
School of Accounting and BIS, The Australian National University,
Canberra, Australia
Abstract
Purpose – The purpose of this paper is to set the scene for this special issue by synthesising the vast
array of literature to examine what constitutes mixed methods research, and the associated strengths
and risks attributed to this approach.
Design/methodology/approach – This paper takes the form of a literature review. The authors
draw on extensive methods research from a diverse range of social science disciplines to identify and
explore key definitions, opportunities and risks in mixed methods studies. They review a number of
accounting studies that adopt mixed methods research approaches. This allows the authors to analyse
variance in how mixed methods research is conceptualised across these studies and evaluate the
perceived strengths and limitations of specific mixed methods design choices.
Findings – The authors identify a range of opportunities and challenges in the conduct of mixed
methods research and illustrate these by reference to both published studies and the other contributions
to this special issue.
Originality/value – With the exception of Modell’s work, there is sparse discussion of the application
and potential of mixed methods research in the extant accounting literature.
Keywords Research methods, Accounting
Paper type Literature review
1. Introduction
Mixed methods research has a long history in the social sciences (Creswell, 2009; Jick,
1979; Johnson et al., 2007). The management literature abounds with studies that adopt a
mixed methods approach and methodological papers that examine the properties of this
research strategy (Greene, 2008; Tashakkori and Creswell, 2007b). Despite the
development of mixed methods research designs in the social sciences over several
decades and the recent growth in the popularity of mixed methods research as a “third
methodology” (Hall and Howard, 2008) or “third paradigm” (Denscombe, 2008), there is
still little evidence or sustained discussion of mixed methods research in the accounting
literature (see Modell, 2005, 2009, 2010, for an exception). This is particularly notable in
the management accounting context, given the wide acceptance that qualitative
methods already enjoy in this arena. Several calls in the literature acknowledge this
potential to complement positivist/functionalist paradigms with aspects of case-based
research (Ferreira and Merchant, 1992; Ittner and Larcker, 2001; Modell, 2005; Shields,
1997). Thus, in this paper, we review literature on mixed methods research originating
The authors are grateful to Deryl Northcott for helpful comments on this paper.
Qualitative Research in Accounting &
Management
Vol. 8 No. 1, 2011
pp. 5-21
q Emerald Group Publishing Limited
1176-6093
DOI 10.1108/11766091111124676
QRAM
8,1
6
from diverse social sciences and consider a range of definitions, opportunities and risks
associated with mixed methods research in accounting in general and management
accounting in particular.
“Mixed methods research” recently has gained popular acceptance as the term to define
research designs that combine qualitative and quantitative methods in a single study
(Johnson et al., 2007); but this method is variously referred to throughout the literature as
convergent methodology, multiple/multi-method/multitrait research, convergent
validation, between or across method triangulation, multiple operationalism, blended
research, integrative research, and mixed research (Denzin, 1978; Jick, 1979; Johnson et al.,
2007). An extensive literature considers the nature of mixed methods research, how the use
of mixed methods within a single study can both extend and strengthen potential findings,
and the potential pitfalls of integrating methods (Bryman, 2007; Johnson et al., 2007;
Modell, 2005; Teddlie and Tashakkori, 2009; Yin, 2006).
In this paper, we set the scene for this special issue by synthesising the vast array of
literature to examine what constitutes mixed methods research, and the associated
strengths and risks attributed to this approach. We illustrate the application of mixed
methods with three published management accounting studies (Davila and Foster, 2007;
Modell and Lee, 2001; Wouters and Wilderom, 2008) and one financial accounting study
(Graham et al., 2005). We examine these published studies for what they tell us about the
strengths of mixed method designs as well as the tensions and trade-offs in execution.
Similar themes of relative strengths, tensions and trade-offs are evident in the other
papers in this special issue that reflect on applications of mixed methods design (see the
papers by Malina, Nørreklit and Selto, Murphy and Maguire, and De Silva).
At the outset, we draw a “soft” distinction between mixed methods and mixed
methodologies. To the extent that mixed methods rely on the joint exploitation of
qualitative and quantitative methods, this can occur within either a positivist/functionalist
or interpretive paradigm. However, we refer to this as a soft distinction because the
definitions we draw on frequently refer to elements of mixing methods and methodologies.
Furthermore, many scholars argue that moving between quantitative and qualitative
methods by definition implies a methodological shift, whether acknowledged or not. While
recognising that the boundary is “fuzzy”, we initially eschew questions of mixing
methodologies to focus on issues associated with the more straightforward application of
mixed methods, largely from a positivist/functionalist perspective. We then return to the
question of mixing methodologies. In particular, we pay attention to ongoing debates
regarding the compatibility of quantitative and qualitative methodologies within a single
study and the perceived possibilities for successfully combining methods with such
distinct epistemological and ontological positions (see also De Loo and Lowe in this special
issue for elaborated discussion on the contention of mixing methodologies).
It is not our intention in the paper to prescribe how to perform the mixing of methods
(see instead Creswell and Plano-Clark, 2007, or Teddlie and Tashakkori, 2009). Nor do
we introduce or discuss strategies to assess the quality (reliability and validity) of mixed
methods studies (see instead Dellinger and Leech, 2007, and Kihn and Ihantola in this
issue).
Section 2 defines and introduces mixed methods research. We then turn to the
contentious question of mixing methodologies (Section 3). Sections 4 and 5 explore the
question of why researchers mix methods and the risks in doing so, respectively.
In Section 6, we draw on four published examples of mixed methods research
in the accounting literature. We then conclude the paper by drawing together the
literature on mixed methods and the “reality” observed in the examples discussed.
Ultimately, we consider the future potential for mixed methods research in accounting.
2. What is mixed methods research?
Mixed methods research is now widely accepted across diverse social science disciplines
as a separate research strategy with its own distinct worldview, vocabulary and
techniques (Denscombe, 2008; Hall and Howard, 2008; Johnson et al., 2007; Tashakkori
and Creswell, 2007b; Teddlie and Tashakkori, 2003). Despite this, as evidenced by the
responses of 19 leaders in the field solicited by Johnson et al. (2007), there is significant
variation in the definition of mixed methods research. However, the majority of the
definitions provided, and popular opinion in the discipline at large, seem to suggest that
mixed methods designs include both a quantitative and qualitative component. Where
inconsistencies and disagreements seem to originate is in the consideration of how these
quantitative and qualitative components are related, and whether these components
reflect quantitative and qualitative data collection and analysis techniques (i.e. methods)
and/or quantitative and qualitative approaches to research (i.e. methodologies)
(Denscombe, 2008; Tashakkori and Creswell, 2007b). Further points of contention relate
to the focus placed on the quantitative and qualitative components of the study
(the weighting decision), at what stages of the study quantitative and qualitative
components are mixed (the mixing decision) and in which order quantitative and
qualitative methods are used (the timing decision) (Creswell and Plano-Clark, 2007; Hall
and Howard, 2008; Jick, 1979). As Johnson et al. (2007) note, it is perhaps not surprising
that a fixed definition of mixed methods research remains elusive as definitions can and
usually will continue to evolve over time as a method grows. However, this looseness in
definition is not necessarily fatal (Creswell and Tashakkori, 2007) as “having the term
not cast in stone is intellectually useful and allows for reshaping understandings” (Guba,
1990, p. 17).
In the social sciences, the concept of methods “triangulation” dates to the work of
Campbell and Fiske (1959) who propose the use of more than one research method as part
of a validation strategy to ensure the explained variance is the result of the underlying
phenomenon and not an artefact of the research method adopted. Subsequent
researchers elaborate on the nature of methods triangulation, distinguishing
within-methods triangulation (the use of multiple quantitative or multiple qualitative
elements) from between-methods (the use of both quantitative and qualitative
elements)[1] and delineating method triangulation from data, investigator and theory
triangulation[2] (Webb et al., 1966). Studies have been considered mixed on the basis of:
addressing two types of research questions; the manner in which research questions are
developed; adopting two types of sampling procedures, data-collection techniques, types
of data or data analysis; and presenting two types of conclusions (Tashakkori and
Creswell, 2007b).
In this section, we analyse the concept of what is seen to constitute mixed methods
research from the platform of a broad definition provided by Tashakkori and Creswell
(2007b, p. 4) wherein mixed methods research is considered to be:
[. . .] research in which the investigator collects and analyses data, integrates the findings, and
draws inferences using both qualitative and quantitative approaches or methods in a single
study or program of inquiry.
Mixed methods
research in
accounting
7
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8,1
We select this definition as it makes prominent what we consider to be two essential
aspects of a study that combines quantitative and qualitative elements:
(1) the notion of “integration” between quantitative and qualitative elements[3];
and
(2) the importance of developing a “single study or program of inquiry”.
8
Further, rather than considering mixed methods in a narrow or “pure” sense, this
definition is inclusive in allowing for the possibility of mixing encompassing both
method and methodology, and permitting variation in the weighting, mixing and timing
decisions of researchers (Johnson et al., 2007).
Integration of methods
The attribute of integration between qualitative and quantitative elements of a mixed
method study is evident primarily in the way interdependencies between the multiple
strands of the study are embedded in the research design, and managed in the analysis.
Complementary or sequenced quantitative and qualitative components of a study that
do not involve reciprocal interdependencies between these research strands may not be
considered to be mixed methods (Bazeley, 2009; Bryman, 2007). Integration “might occur
through iteration, blending, nesting or embedding” (Bazeley, 2009, p. 204). Examples of
these forms of integration across the research process provided by Bazeley (2009, p. 205)
include: using the results of one analysis employed to approach the analysis of another
form of data; the synthesis of data from a variety of sources for joint interpretation; the
comparison of coded qualitative data across groups defined by categorical or scaled
variables; the conversion of qualitative to quantitative coding to allow for descriptive,
inferential or exploratory statistical analyses; the creation of “blended” variables to
facilitate further analysis; flexible, iterative analyses involving multiple, sequenced
phases where the conduct of each phase arises out of or draws on the analysis of the
preceding phase.
Yin (2006) notes that the integration of quantitative and qualitative strands of mixed
methods studies can occur in many ways. The articulation of research questions, the
identification of samples and units of analysis, the data collection methods used and the
analytic strategies employed are all implicated in the integrative quality of mixed
method design. Yin (2006) proposes that the more the quantitative and qualitative
elements are integrated into research procedures, the stronger the “mix” of methods that
results. Creswell and Tashakkori (2007), further note that “strong mixed methods”
studies integrate the quantitative and qualitative results of the study into coherent
conclusions or inferences. Bazeley (2009) considers the integration of quantitative and
qualitative results the minimum requirement for a study to qualify as mixed methods in
design, and observes that blending data and meshing analyses is far less frequent in
practice. A critical foundation for integration may be the development of an overarching
mixed methods research question (Mertens, 2007; Tashakkori and Creswell, 2007a).
Mixed methods studies that struggle to integrate findings are usually those that develop
either qualitative or quantitative research questions and then use mixed methods solely
for data collection. The inference drawn from the study by Mertens (2007) is that
developing an overarching mixed methods question is a design necessity in mixed
methods studies if mixed methods researchers are to present integrated and coherent
research results.
Single program of inquiry
Importantly, mixed methods designs must also ensure that the integrity of the single
study focus is maintained and the study does not inadvertently devolve into two or more
parallel studies (Yin, 2006). While there is potential to integrate qualitative and
quantitative findings either within or across studies, we restrict our definition of mixed
method studies to those that integrate qualitative and quantitative findings within a
single study. We do this for several reasons. First, the importance of a mixed methods
research question and research design as an antecedent to effective integration of
findings is premised on the notion that integration is occurring in a single study
(Mertens, 2007; Tashakkori and Creswell, 2007a). Second, authors are really only able to
assess the extent to which two sets of data converge, contradict or extend one another
with a clear understanding of the construct definitions and the domain of observables
that govern the collection of both datasets. This is generally only evident in a single
study. It is possible that multiple sequential studies by the same author may go some
way to achieving the required consistency in definitions to integrate data across studies.
Malina et al. (in this issue) present such a possibility. It is notable, however, that
while their reflections refer to sequential studies, they rely on repeat analysis of a single
dataset to produce the primary mixed methods contribution that they describe. Multiple
studies by different authors are much less likely to satisfy the need for consistency in
definitions and domain of observables. In such cases, the integration of findings relies on
meta-analyses that address the added complications of variability caused by time, study
design, sampling and definitional differences (Johnson and Onwuegbuzie, 2004; Yin,
2006).
In summary, mixed methods research designs are characterized by the use of both
qualitative and quantitative methods within a single study, with a focus on the
integration of these multiple strands in both study design and data analysis. While such
a definition emphasises the mixing of methods, it implicitly embraces the potential to
mix methodologies, as does the literature from which we draw our definition. However,
the question of mixing methodologies emerges as somewhat more contentious than the
mixing of methods. In the next section, we consider competing views on the viability or
authenticity of mixed methodologies.
3. Mixing methodologies
A comprehensive review of the mixed methods literature shows that there are two
dominant views about the mixing of methodologies: the incompatibility thesis and the
pragmatists’ view. Researchers who articulate an incompatibility thesis about mixing
methodologies argue that qualitative and quantitative methodologies draw from
different epistemological assumptions and have different research cultures that work
against the convergence of research methodologies (Brannen, 2005; Sale et al., 2002; Scott
and Briggs, 2009). This argument is premised on the idea that qualitative research
methodology is based on inductive logic of enquiry, which is considered to be
diametrically opposed to the hypothetic-deductive logic that underpins quantitative
methodology. Accordingly, these two methodologies speak to different ways of knowing
reality and thus have different implications for deriving research questions and require
different research processes, suggesting that any attempt to mix them will create tension
and lead to difficulties in interpreting results. For instance, the hypothetic-deductive
logic requires more structured protocols, representativeness of a sample
Mixed methods
research in
accounting
9
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8,1
10
and, by implication, the generalisability of results requires a much larger sample. In
contrast, inductive logic does not require large, representative samples. For Sale et al.
(2002), these two different methodological approaches are incommensurate and should
therefore not be mixed in any mixed methods studies.
Some researchers extend the incompatibility thesis to argue that mixing
methodologies can create argumentative incoherence by attempting to “blend
paradigms with incommensurable epistemic and ontological foundations” (Scott and
Briggs, 2009, p. 230; Johnson and Onwuegbuzie, 2004; Sale et al., 2002). They contend
that qualitative and quantitative methodologies draw on incompatible paradigmatic
assumptions that work against any attempt at mixing the two methodologies.
Qualitative methodologies are said to derive from interpretivism and constructivism
where it is generally assumed that reality has no existence prior to the activity of
investigation and where the focus is on shared meanings rather than causal relations
(Sale et al., 2002). In contrast, quantitative methodology is based on positivism and its
assumption of an objective reality that can be studied without researcher influence
(Sale et al., 2002). Given these different paradigmatic assumptions, Sale et al. (2002) argue
that qualitative and quantitative methodologies do not study the same phenomenon and
should not therefore be mixed in any way. They argue further that even when the same
phenomenon is explored through these two methodologies, the definitions of these
phenomena will differ and the approach to knowing the phenomena will also differ, thus
making it impractical to mix the two methodologies.
The conclusion drawn from the incompatibility thesis is that the mixing of
methodologies in mixed methods research is not a reasonable proposition and should
therefore be discouraged. I …
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