Management Accounting Research 31 (2016) 45–62
Contents lists available at ScienceDirect
Management Accounting Research
journal homepage: www.elsevier.com/locate/mar
The contingency theory of management accounting and control:
1980–2014
David Otley
Lancaster University Management School, Lancaster LA1 4YX, UK
a r t i c l e i n f o
Article history:
Available online 12 February 2016
Keywords:
Management control package
Contingency theory
Management control system
Middle range theory
Knowledge in management accounting
a b s t r a c t
This article reviews the literature on the contingency theory of management accounting since the 1980
review by the author. It traces the expansion of this literature and critically outlines some of the major
themes explored over this period. It argues that a mechanistic approach that will develop into a predictive
mechanism for the design of optimal control systems is misguided. Rather the existence of management
control‘packages’thatarecontinuallychanginganddevelopingrequiresstudiesthatfollowthesechanges
over time and seek to explain the mechanisms that are observed to be deployed. The ‘package’ concept
has not yet been taken seriously in the design of most empirical studies although this is fundamental to
the design of future studies. That is, different elements of control system packages are developed quasi
independently by different actors at different times and are only loosely co-ordinated. Full coordination is
precluded for several reasons, most notably the rapid pace of change and the addition of new or amended
systems at a faster rate than the coordination process can develop. It is suggested that the narrow view
of contingency that relies on responses to generally applicable questionnaires needs to be replaced by a
more tailored approach that takes into account the context of specific organizations.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
This paper provides an overview of the research on management
accounting and control which has used a contingent perspective. It
starts from my 1980 review of the topic (Otley, 1980) and seeks to
bring this up to the present day.1 However, there are a number of
features that require clarification to define the scope of this review.
First,thetopichasbroadenedinitsscopeoverthelastthreedecades
and it seems sensible to include aspects of management control
systems (MCSs) which are used in conjunction with management
accounting information rather than focussing solely on management accounting techniques. Second, management accounting has
itself changed with a variety of ‘new’ techniques being developed
and popularized, particularly in the 1980s and 1990s. Third, organizations have changed with traditional hierarchical forms being
modified into flatter forms, and strategies which emphasize concentrating on a core business rather than attempting to encompass
the whole supply chain within a single legal entity. Thus control
systems are increasingly required to operate across organizational boundaries. Finally, the idea of contingency requires further
E-mail address: [email protected]
1 From this point on I will refer to my own papers in the third person and put any
personal comments in a footnote.
clarification, as it can be argued that all research on these topics
has to take a ‘contingency’ approach as it becomes recognized that
universal solutions to problems in organizational control generally
do not exist.
In the 1970s management accounting formed the centrepiece
of many organizational decision-making and control approaches.
Budgetary control was the dominant technique used and most of
the early contingency-based research studies concentrated on the
deployment and use of budgets. Indeed many of the early studies
exposedtheflawsthatbudgetaryinformationpossessedwhenused
in a manner that did not acknowledge its limitations. More recently
non-financial performance measures have increased in popularity and are seen as part of an overall control system, together
with a variety of other control approaches which have little to do
with traditional management accounting. For this paper it seems
most appropriate to concentrate on the over-arching area of management control systems where much of the research takes an
organizational approach. Decision-making, by contrast, tends to
take an individual approach informed predominantly by psychology and this is covered in a separate review by Hall (2016) in this
issue. However, the boundary is not always clear as some studies
use both individual and organizational level variables, and focus on
topics which include both decision-making and control, so there is
some overlap.
http://dx.doi.org/10.1016/j.mar.2016.02.001
1044-5005/© 2016 Elsevier Ltd. All rights reserved.
46 D. Otley / Management Accounting Research 31 (2016) 45–62
The developments in management accounting began with the
introduction of activity-based costing (ABC) in the early 1980s,
although this concentrated on generating information for improved
decision-making rather than control. However, it was rapidly
followed by other techniques often lumped together under the
general heading of strategic management accounting. Although
this can be interpreted as an attempt by management accountants to maintain their presence at the centre of both organizational
decision-making and control, it is also a convenient label to encapsulate the approaches that were developed during this decade.
However, the dominance of accounting control was challenged in
the early 1990s by the codification of what has become the most
widely adopted technique in modern organizations, the Balanced
Scorecard (BSC), which combined both financial and non-financial
performance measures into a single integrated framework. The
scope of management control increasingly began to include issues
of both strategic and operational control that had been specifically
excluded (for reasons of simplicity and convenience) by Anthony
(1965) in his seminal definition of the field.
The context in which management accounting and control is
practised has also undergone substantial change. Organizations
have become less hierarchical and many have restructured themselves to focus on their ‘core businesses’, leaving more peripheral
activities to be outsourced. Thus organizations now tend to be
embedded into supply chains and new forms of control need to be
developed in this situation (Anderson and Dekker, 2014).2 These
supply chains span several different legal entities with no hierarchical oversight, although there is often one large organization
that dominates the other participants. These developments were
reviewed in Otley (1994) but have continued to change subsequently. In particular, the general business environment has shown
an increasing rate of change and competition, both locally and globally, which has caused a greater degree of uncertainty to become
apparent. Finally, technological developments continue to drive
change at an increasing rate, not least in the changes to business
practice which have been made available by modern computer
technology and the internet. At the very least this has led to
increased environmental uncertainty and a breakdown in the (often
implicit) predictive models on which control was based.
The idea of the role of contingency theory is also beginning to
change. Whereas initially it developed from the idea that no universal solution to the problems of control was feasible, it hoped
that empirical work would establish the key contingencies from
which prescriptions to suit different sets of circumstance could
be developed. However, research over the past four decades has
come up with an extended list of possibly significant contingencies
that are faced by organizations, many of which suggest conflicting recommendations. Even if research could be progressed on a
much greater scale than in the past, it is unlikely that an overall
contingency model could be developed to suggest optimal control
configurations in all possible combinations of circumstances. And
even if was to prove possible, the world would have moved on by
the time the results were available. Contingency therefore has to be
considered in a much more dynamic context than previously, which
leads to the need to use more process-based models which examine the mechanisms of change and the implementation of modified
forms of management and control.
This paper will therefore not attempt to perform a comprehensive review of all previous ‘contingency’ studies, of which there
have been a number, most notably that by Chenhall (2007) which
updates his 2003 review and this paper will not attempt to duplicate the detailed work he performs in that comprehensive chapter.
2 See also Dekker, 2016.
Chenhall noted that “the term contingency means that something
is true only under specified conditions. As such there is no ‘contingency theory’, rather a variety of theories may be used to explain and
predict the conditions under which particular MCSs will be found or
whether they will be associated with enhanced performance.” (p. 191).
He goes on to suggest that a much wider range of theories may
prove useful, encompassing economics (both agency approaches
and behavioural economics), psychology, sociology and information science. He also suggests that prior work has concentrated
on traditional, functionalist theories and should move on to use
more interpretive and critical views in future. This paper will analyze a number of practical and conceptual issues that appear to
make it likely that traditional approaches to contingent theorizations have run their course and to argue that it will require different
approaches to provide insightful and useful explanations of this
complex subject.
2. What is contingency theory?
The idea of a contingency theory of management accounting
began to develop in the 1970s in an attempt to explain the varieties of management accounting practice that were apparent at that
time. It drew heavily on the contingency theory of organizational
structure which had been developed over the previous twenty
years to codify which forms of organizational structure were most
appropriate to specific circumstances. The independent variables
used to explain organizational structure were often transferred
wholesale into the emerging theory of management accounting to
explain the design and use of management accounting systems,
with additional variables being added as the years progressed.3 As
Hopwood (1974b) had pointed out earlier, the design of a (management accounting) system and the design of an organizational
structure are really inseparable and interdependent, although this
important observation has tended to be neglected over the years
that followed.
In his overview of the contingency theory of management
accounting, Otley (1980) specifies that “a contingency theory must
identify specific aspects of an accounting system which are associated
with certain defined circumstances and demonstrate an appropriate
matching.” (p.413). This indicates three areas to which attention
needs to be paid. First, what are the aspects of the management
accounting system that are to be explained? In particular, are we
concerned just with the existence of specific techniques in an organization, or also with the extent and manner of their use? Studies
have tended to be rather arbitrary in their selection of the techniques they focus on, with little consistency between one study
and another both in selection and measurement of variables connected with the accounting control system. Second, how are the
defined circumstances to be selected? Again, although the contingent variables used by organization theorists have been extensively
used here, often only a subset are used in any one study making
comparability difficult. Finally, the definition of what constitutes
an appropriate matching has caused significant difficulty over the
years. At its most simple, existence has been taken as indicating
such a matching, although this assumes that a long-run equilibrium has been achieved. More sophisticated studies have used some
variant of firm performance to indicate whether an appropriate
matching has been found, despite the likelihood that MCSs have
only a small impact on performance, although the measures used
3 This led to an ambiguity in the role of organizational structure which was the
dependent variable in the organizational theory, but an independent variable in
the management accounting theory, if it was included. Evidently a risk of multicollinearity could exist if it was used together with the common list of explanatory
variables.
D. Otley / Management Accounting Research 31 (2016) 45–62 47
vary. In addition, use of performance in this way is potentially problematic as it can be argued that performance is also an independent
contingent variable in its own right which can explain the extent to
which reliance is placed on accounting systems in an organization.
However, the totality of these extended approaches implies a
very broad definition of contingency theory, which led to Chenhall’s
(2007) previously quoted comment that there are inevitably a range
of contingency theories. Indeed, it might be suggested that all
research in management accounting is essentially contingent, in
that it seeks to discover when specific techniques might be most
appropriate for particular organizations in their specific circumstances. Clearly, given this possibility a overall review needs to be
bounded, and initially a simple approach to what is included and
excluded was taken to indicate some of the broad trends that have
occurred over the period since 1980,4 but confined to those studies
which make a specific reference to ‘contingency’, or which can be
clearly seen as having such a focus.
3. Survey 1980–2014
An initial literature search was conducted using three steps.
Firstly, a preliminary list was generated by searching keywords in
the online versions of seven major accounting journals. Secondly,
a further search was conducted using major electronic databases
which provide access to most of the other important journals.
Finally, the list was further supplemented by examining the reference lists of the key articles already identified. This was intended to
generate a list of relevant articles that was as complete as possible
in the area of contingent approaches to management accounting
and control.
The literature research began by searching articles from major
relevant journals, namely the following nine major accounting
journals: Accounting, Organizations and Society, British Accounting Review, European Accounting Review, Management Accounting
Research, Journal of Management Accounting Research, Accounting
Auditing and Accountability Journal, The Accounting Review, Journal of
Accounting Research, and Accounting and Business Research. As all of
these journals provide online resources, articles were collected by
keyword searches of the supporting online platform. The key words
used were “contingency”; “contingent”; “management”; “management accounting” “relation”; “relationship”; “impact”; “effect”; and
“influence”. The last five words are searched in order to include
those essentially contingency studies which do not directly claim
to be such. The time specified in the search filter spanned from
1980 to mid-2014. The articles generated were reviewed by title
and abstract to ensure that they were appropriate. As some crossdisciplinary studies may be published in the journals of other fields
a more general search with similar filter conditions was conducted
on the seven major platforms which provide access to a multidisciplinary collection of online resources; namely Science Direct
Freedom Collection; Business Source Premier; ProQuest; Wiley
Online Library; SwetsWise; JSTOR and Taylor & Francis Social Science and Humanities Library. In the final step; the reference lists
in the review articles identified and the most cited articles thus
listed were used to add to the overall list; although this generated only a small number of additions, it gave some confidence in
the completeness of the list. This process generated an extensive
list which was only lightly edited to exclude items which seemed
clearly inappropriate. The final list may therefore include some
items of peripheral relevance; but it was considered more useful
to err on the side of inclusion rather than exclusion.
4 But see Specklé and Kruis (2014) for an up to date review of recent developments
in the management control literature more widely.
Table 1
Number of articles by journal.
Name of the journal Number
Accounting, Organizations and Society 66
Management Accounting Research 57
British Accounting Review 22
Journal of Management Accounting Research 13
Accounting, Auditing and Accountability Journal 9
European Accounting Review 9
Accounting and Business Research 7
Subtotal 183
Information and Management 4
Strategic Management Journal 4
Administrative Science Quarterly 3
Journal of Management 3
Subtotal 14
Others 39
Total 236
In summary, the number of articles from each journal is shown
in Table 1, with only the accounting journals which contain more
than four articles being included.5 It is notable that, although
a reasonable number of authors were located in the USA, the
main journals in which this work was published are European- or
Australasian-based, rather than US-based. This probably indicates
the US journal preference for quantitative work using substantial
(often publicly available) data sets and the use of sophisticated
quantitative models. Most work in the contingency field requires
data to be collected individually (rather than there being any publicly available datasets) which restricts samples to quite a small
size (rarely more than the low hundreds), and thus precludes the
extensive use of the more data hungry statistical techniques.6
The total number of articles included in the bibliography
amounted to 236. Of these 157 could be categorized as being empirical and using quantitative methods7; the remainder were either
theoretical (39), review (20), qualitative (10), or methodological
(10), although several articles could have been included in more
than one category. In the 1980s, less than 5 relevant articles were
published each year although this figure increased to around 10 in
the late 1990s. Despite a brief drop of publications in years 2000
and 2001, the statistics show a generally upward trend, as shown
in Fig. 1 below, and indicate the steadily growing amount of work
on this topic over the period. However, this increase may be partly
due to the increased number of journals available, most notably the
launch of Management Accounting Research in 1990.
4. Initial overview
There are a number of features that characterize the bulk of the
work reviewed. First, it is generally not systematic, and the variables (or measures) selected for analysis in any particular study
generally do not exactly correspond to those used in prior work.
Thus, cumulative results are rare. Second, viewing this feature from
a more positive stance, it has clearly seemed better to researchers
to extend their work to a wider range of areas in order to map out
the boundaries of the field rather than to concentrate further on
those topics which happen to have been studied in the past. How-
5 Just four relevant articles were found in each of The Accounting Review and the
Journal of Accounting Research in the period covered.
6 Recent developments in statistical techniques now permit smaller sample sizes
to generate reliable results, and may allow more useful statistical work to be conducted in this field in future.
7 The majority of the quantitative empirical studies involved data collection by
mail questionnaire across a single or a number of different organizations.
48 D. Otley / Management Accounting Research 31 (2016) 45–62
Fig. 1. Number of articles on the contingency theory of management accounting by year.
ever, these extensions have tended to concentrate on increasing the
number of independent variables studied rather than on the dependent variables of MCS design and use, with only a few exceptions.
This is connected with the almost complete absence of replication studies, perhaps accentuated because journals may have been
unwilling to publish them. If such studies were to find null results
it is less likely that they would be seen in print, although journal
editors tend to dispute this interpretation despite the empirical
evidence. Third, limited attention has been paid to the characterization of the management control system itself. The initial focus
was often on budgetary control, reflecting its widespread use in
the 1980s, but has been extended to examine a wider range of performance measures and control techniques, but only on a sporadic
basis. Finally, the predominant research method has been the use of
survey questionnaires (often at arm’s length) with quite limited use
made of combining this work with more interpretative or critical
qualitative methods. This seems to have been excessively limiting
at what is still an early and exploratory stage of this field.
4.1. Independent variables
More and more variables continue to be examined. Major
independent variables can be grouped into external variables
and internal variables.8 The most commonly examined external
variables include technology, market competition or hostility, environmental uncertainty and national culture. The major internal
variables are organizational size, structure, strategy, compensation systems, information systems, psychological variables (e.g.,
tolerance for ambiguity), employees’ participation in the control
systems, market position, product life-cycle stage, and systems
change.
In the early stage of contingency research, many studies examined the relationship of just one independent variable with one
dependent variable. However, Fisher (1995) argued that it is essential to understand the interactions between multiple contingent
and control factors in determining the effectiveness of control
system design. In other words, the understanding of the interrelationship between multiple contingent independent variables may
lead to a better framework for dependent variables determinant
analysis. He also classified contingency studies on management
control by the level of analysis complexity. The work on the contingency theory of management accounting can be classified into
3 levels of analysis on this basis. At the first level of analysis, one
contingent independent variable is correlated with one dependent
variable. At the second level of analysis, the joint effect of multiple
8 The view of the author(s) has been accepted in this regard, although there is a
debate as to whether an internal variable which can be affected by the firm itself
should be treated as a contingent variable or as a dependent variable, most notably
concerning organizational structure and strategy.
contingent variables on one dependent variable is examined. Some
of these variables may be moderating or mediating variables rather
than independent variables. The third level of analysis examines
the effect of the fit of multiple independent variables on several
dependent variables, although this has been relatively rare. There
is a trend in this stream of research for more variables to be examined in any one study with increasing attention being paid to their
interrelationships.
4.2. Dependent variables
The most widely examined dependent variables are performance, performance measures, budgeting behaviour, management
control system design and its use, effectiveness, job satisfaction,
change in practices, and product innovation. Performance, effectiveness and design of systems are the major dependent variables
used with financial performance being the most commonly used
outcome variable. One of the major reasons is that financial performance is a widely used measure in most organizations. Moreover,
most variable compensation systems use a measure of financial
performance as the indicator for incentive payments. However, the
over-reliance of performance measure on financial performance
may produce biased results. The study by Coates et al. (1992)
indicates that different countries have different preferences for performance measurement systems which may result from varying
emphases on financial stability. Specifically, the employment of
non-financial performance measures was more prevalent in U.S.
companies at that time. Many of the performance measurements
which are highly valued and of significant impact are non-financial
measurements such as production process measures, defect rates,
cycle time and customer service measures; or qualitative measurement, such as customers’ perception, attitude of employees
towards jobs, and product innovation. (Otley, 1999). Despite of the
importance of non-financial and qualitative performance measurement, these variables have been relatively neglected in the studies
reviewed here.
These mainly quantitative studies form the core of what has
become known as the contingency approach and have formed the
foundation of our knowledge about the major variables thought to
affect the design and use of MCSs. They have also increasingly paid
attention to the interactions between both the independent and
the dependent variables, a topic further discussed in Sections 5.5
and 5.6. However, it is perhaps unfortunate that the term ‘contingency’ has now become associated only with the methods typically
employed in this strand of research when a wider range of research
approaches are likely to give additional insights. Whilst recognizing the knowledge that has been gained from these studies it
seems likely that further progress is most likely to be obtained from
deploying a much wider range of research approaches, given the
complex nature of the phenomena being studied.
D. Otley / Management Accounting Research 31 (2016) 45–62 49
Qualitative studies have emerged more recently and are more
difficult to categorize, ranging from detailed analyses of very specific and small scale operations, through to overviews of whole
areas, often with a theoretical component. The empirical techniques involved were usually interviews as the main evidence
gathering technique, although this was sometimes supplemented
by documentary evidence and questionnaire responses from managers. These will not be reviewed separately in detail as they are
few in number and difficult to compare and aggregate, although
they have yielded some significant insights into MCS development,
modification and use.9 The work reviewed here does not do full justice to the number of contributions already made to management
control research using qualitative methods, as many of the studies
would not describe themselves as being within the ‘contingency’
tradition. It may well be that the use of this label is now becoming obsolete as studies focus on how MCSs occur in the forms that
are observed and the effects that different configurations have on
managerial and organizational behaviour.
Rather than trying to impose what would likely be an artificial
order of the range of work being considered, this review will take
a topic-based approach and examine the areas where significant
amounts of work have been conducted, with a view to drawing
out some lessons which can be learned for the conduct of future
research. This is inevitably selective, but has been done in the hope
that an overview of a few areas will prove more insightful than
a more comprehensive yet inevitably more superficial review of a
large number of widely varied studies. This section will also include
a discussion of some methodological issues which have been discussed. It will conclude by suggesting issues that future work might
usefully consider. A full bibliography of all the articles considered
is attached in Appendix A, with the reference list at the end of this
article containing only those references not included there.
5. Review of some selected bodies of work
As has been observed above, the empirical work which has been
undertaken is difficult to categorize neatly, with little cumulative
progress having been made, due to successive authors designing
their studies with only limited connections to previous work. It is
also worth noting that the context within which many of the earlier
studies were conducted has changed substantially since that time,
and that their results may not be applicable to today’s organizations. However, a number of major themes have emerged which
will now be discussed in more detail.
5.1. Reliance on accounting performance measures (RAPM)
Early work on contingency theory tended to be based on prior
findings from organizational behaviour, but one important stream
developed from conflicting empirical observations that required
explanation. This started with the work of Hopwood (1972, 1974a)
who examined the effect of senior managers giving a high priority to
accounting performance measures in evaluating the performance
of their subordinates, a style later characterized as RAPM. The main
result was that where accounting performance measures (in particular, meeting the budget for the unit) were given higher significance
than other criteria, such as long-run effectiveness, then a variety of
undesirable consequences followed. A subsequent study by Otley
(1978) deliberately chose a situation where he believed this result
would not hold (i.e., where operating units were largely independent of each other, in contrast to Hopwood’s highly interdependent
units), and found the conflicting results he predicted. He argued
9 But see Section 5.6 for further discussion.
that this was therefore a contingent result dependent upon the contingency of sub-unit interdependence. However, this proved to be
a contentious conclusion as there were several other differences
between the two studies (e.g., US versus UK organization; private
versus public sector; cost centres versus profit centres; size of organizational unit etc.) and subsequent work sought to explicate some
of these possible differences and what their consequences might
be.
The work which followed, despite being described as “the only
organized critical mass of work in management accounting at present”
(Brownell and Dunk (1991) (p.703)) had a major deficiency in that
very different measures of the central concept (RAPM) were used
in different studies. These difference were outlined and reviewed
in Otley and Fakiolis (2000) which concluded that many of the
studies were not comparable with each other due to these differences in measurement. Significantly, both Hopwood’s and Otley’s
studies made significant use of interviews in developing their
questionnaire-based measures and in interpreting their results,
whereas later studies tended to use arm’s length general purpose
questionnaires, sometimes used across a variety of different organizations. Using the over-arching term of RAPM was itself misleading
as it covered the use of several different measures which each
focussed on different aspects of the underlying phenomena. Further, the appropriateness of the questionnaire items to the specific
organizations being studied is unclear as validation through fieldwork was usually absent.
In addition, the world had moved on from the situation that
existed in the early 1970s (see Otley (1994)) for an analysis
at that date). Budgetary control had reduced in significance as
a performance measure, with non-financial measures increasing
in importance. Organizational structures had become flatter and
inter-organizational relationships had increased in importance as
out-sourcing had become more prevalent. These trends have continued to the present day and it seems unlikely that results which
were found in the past can be relied upon to hold in the present
day. At the very least, this needs to be investigated rather than
reliance being placed on work conducted long ago. The one major
attempt to construct a broader framework was Simons (1995) work
on Levers of Control which was based on a large number of case
studies conducted in US companies, generally involving data from
CEOs and other senior managers. He focussed on a much wider set
of controls than most previous studies (categorized into diagnostic,
interactive, beliefs and boundary controls) although his formulation has proved to be somewhat problematic as identified and then
improved by Tessier and Otley (2012). But subsequent research
focussed almost entirely on his distinction between diagnostic and
interactive uses of controls, and the ambiguity in the definition of
interactive use has also led to the term being used to cover a variety of different measures. Indeed, Bisbe et al.’s (2007) review of this
concept identified five different dimensions of the concept which
had been aggregated in a variety of ways. The consequence is that,
when the literature refers to the use of interactive controls, very
different concepts may be found within this single label because of
the different measurement instruments being used.
However, the underlying idea behind the early studies does
appear to have a continuing significance in a world which is becoming increasingly dominated by performance targets of all types. That
is, managers who place reliance on motivating appropriate subordinate behaviour by setting quantitative performance targets and
emphasizing these above all else, should not be surprised if such
targets are attained by a variety of (often unobserved) behaviours
that are often dysfunctional to the achievement of overall organizational objectives. There is overwhelming empirical and anecdotal
evidence to this effect from both the private sector (e.g., call centre operatives cutting off calls before they reach the target time
for dealing with enquires) and the public sector (e.g., school teach
50 D. Otley / Management Accounting Research 31 (2016) 45–62
ers concentrating on those pupils whose results will most affect
the performance target; hospital ambulances being made to wait
outside A&E departments so as not to start the time clock for target treatment times etc.). Even university academics have been
affected by the Research Assessment Exercise in the UK where
administrators have converted the subjective rules involving peer
judgement to quantitative targets of achieving a given number of
articles in journals believed to have a high quality rating.
It is therefore a pity that this stream of research seems to
have dried up because of the measurement difficulties associated
with a particular set of measures designed to measure RAPM. The
underlying concept still seems sound and very relevant to modern organizations, particularly if modified to include non-financial
as well as financial performance measures and targets. In particular, RAPM focussed on the ways in which line managers actually
used the accounting (and other) information supplied to them in
the process of holding their subordinates accountable for their performance. This is still a key area that is deserving of continuing
attention.
5.2. Environmental uncertainty and hostility
Of all the variables used in the original studies of the contingency theory of organizational structure, the one that has gained
by far the widest attention in the area of management accounting
is that of environmental uncertainty. This seems to be for several
reasons. First, it produced some of the strongest results in early
studies, in a similar way to the ground breaking work of Burns and
Stalker (1961) in the organizational literature. If an organization or
unit is faced by high levels of uncertainty it requires flexible and
adaptable systems to manage activities when unexpected events
occur. Second, it can be argued that environmental uncertainty has
increased over the years, in part due to the emergence of the global
economy and more extensive competition. But it is also caused by
organizations ceasing to attempt to control all aspects of the value
chain within one overall (holding) organization and the relative
demise of the divisionalized organization. This exposes the smaller
and more focussed organizational units to more uncertainty that, in
the past, may well have been buffered by the overarching organization. Third, there is also the issue of measurement. Here the most
commonly used variable is a measure of perceived environmental uncertainty which can easily be incorporated into interviews
or questionnaires administered to individual managers. Although
this may be seen as using a very subjective measure, it can also be
argued that this is the most relevant aspect of uncertainty—it is the
uncertainty perceived by individuals that will most directly affect
their behaviour. However, it is only indirectly connected with more
objective measures of risk and uncertainty and the factors which
cause some individuals to perceive greater uncertainty than others
are not specified.10
Associated with, but distinct from uncertainty are other aspects
of the environment, including hostility, particularly that related
to intense competition. Although hostility may produce a significant degree of uncertainty, the findings of most studies indicate
that the two features have diametrically opposed impacts on
MCS design and use. Hostility has been shown to be associated
with a greater reliance on accounting controls (especially budgets)
whereas uncertainty is associated with a more flexible style of control that is open and externally focussed. As Chenhall (2007) has
pointed out, it is an open question how the tension between these
two factors should be managed in an MCS given they may often
occur simultaneously. This is indicative of a common problem with
10 A useful review of the impact of uncertainty on performance measurement and
compensation systems can be found in Abernethy and Mundy (2014).
contingency studies in determining how multiple contingencies
having conflicting recommendations should be combined. It also
draws attention to the common issue of distinguishing between
the existence of formal controls and the ways in which they are
used by managers.
5.3. Strategy
Strategy has been hypothesized to affect control systems design
in a number of straightforward ways, depending on which categorization of strategy is used. Following Miles and Snow (1978)
who described four organizational types (defenders, prospectors,
analyzers, and reactors), it has been suggested that defenders
undertake little product innovation, whereas prospectors are continually searching for new market opportunities, either for existing
or new products. The former type therefore concentrate on finance,
production and engineering, compared with an emphasis on marketing and R&D in the latter. Analyzers are thought to combine the
strongest characteristics of both defenders and prospectors, whilst
reactors are seen as an unsuccessful type and are rarely examined.
In a similar vein, Porter (1980) distinguished three generic
strategies—cost leadership, differentiation and focus. The competitive advantage of cost leaders is focussed on the economies of scale,
the operation of efficient procurement and efficient production
technology. By contrast, a differentiation strategy seeks to focus on
providing products that are highly valued by customers who are
thus prepared to pay premium prices. Finally, a focus strategy dedicates itself to catering for a segment of the market that is poorly
served by competitors. Here again the control system focus will be
on either cost control or on product qualities based on customer
satisfaction.
Finally, Gupta and Govindarajan (1984) developed a life cycle
approach based on the sequence of strategic missions from build,
hold, harvest and divest. In the early stages the focus is on building a market share and strategic position, with lesser emphasis on
short-term earnings or cash flow. As the business moves to a harvest strategy a firm ceases to invest except where strictly necessary
and seeks to achieve short-term profit and cash flow rather than
increasing market share. A hold strategy is intermediate to these
two, where a firm seeks to protect market share and strategic position whilst obtaining reasonable returns. Finally, the divest strategy
occurs when a business decides to exit from a specific area of activity. Each strategy again tends to be associated with a specific group
of controls.
Although these different characterizations of strategy share
some similar control system attributes, there does not seem to have
been any coherent comparison between them. Rather, the empirical studies on the impact of strategy on MCS design and use tend
to select one typology to work with, and to follow the implications
of this for MCS characteristics, although again focussing on different MCS features in different studies. However, the stream of work
by Simons11 focuses on the choice companies make between the
diagnostic and interactive use of controls to support their strategic intent. Unlike previous empirical studies, in Simons’ work the
content of the strategy is not seen as critical to understanding
the nature of the interaction between controls and strategy, using
his typology of diagnostic and interactive use, belief systems and
boundary systems.
A good review of the earlier work on strategy and control can
be found in Langfield-Smith (1997) although the topic seems to
have waned somewhat in interest since that time and no further
11 These are summarized in Simons (1995). Interestingly his individual studies
were not identified in the literature search, despite being reported in journal articles,
as they make no specific reference to ideas of contingency.
D. Otley / Management Accounting Research 31 (2016) 45–62 51
overview articles were found. More usefully perhaps, there have
been some more detailed, qualitative studies that have tried to capture the details of actual strategies adopted and the ways in which
these have influenced the use of control systems. One of these
by Adler and Chen (2011) indicated the existence of a confrontation strategy (as distinct from cost leadership or differentiation)
which was associated with collaborative organizational cultures,
lean organizational structures and practices, and training and
development programes that focussed on developing empowered,
multi-skilled teams of self-governing and coordinating employees.
Thus the contingency work on the relationship between strategy and MCS design and use is fragmented in several ways. First,
there is a reliance on simple generic strategy characterizations that
may fail to capture the complexity of real organizational strategies.
In addition, it is not always clear whether what is being measured is
an espoused or a realized strategy, or even whether an overall organizational strategy is being assumed to apply in an organizational
sub-unit that may be responding to different local circumstances.
Second, the dimensions of the control systems examined are varied
with no agreed structure or content, leading to piecemeal results,
although Simons’ work represents a distinct approach grounded
in case-based research. However, it has not achieved any great
popularity in contingency work, except for his distinction between
diagnostic and interactive uses, perhaps partly because it does not
connect easily with any other established framework. Although
serious attempts have been made to achieve a greater degree of
coherence in framework specification by Malmi and Brown (2008)
and by Ferreira and Otley (2009) there is much still to be done to
develop a useful general framework that will allow the results of
future studies to be validly compared.
One recent piece of work by Klassen (2014) has suggested
that there may be an underlying variable that is logically prior to
strategy, namely value logic. Essentially, a value logic is the basic
business model adopted by an organization and has been categorized into three types: value chain, value network and value shop
(Stabell and Fjeldstad, 1998). A value chain is the traditional structure occupying one position in a chain of activities stretching from
raw material through to final products or services (e.g., a manufacturing company); a value network relies on the connections that
an organization has with other organizations to provide an overall service to clients (e.g., a bank); a value shop is an organization
that contains within it a range of specialized resources that can
be mobilized to provide a personalized bespoke service for clients
(e.g., a professional services firm). Klassen has shown that the differences between the control systems of value chains and value
shops are quite distinct, and value logic may thus be more fundamental to MCS design than strategic positioning. His results are
less clear for value networks (which are generally in an intermediate position) perhaps because these take several forms and a more
precise definition of their characteristics may need to be developed.
The contingency work on the impact of strategy on MCS is thus
fragmented and it is difficult to find cumulative contributions. This
is partly due to arbitrary classifications of strategy, which although
necessary for survey work, may categorize actual strategies too
simplistically. Here the pursuit of work that focusses on the underlying variable of value logic may provide a route to further progress
at the more general level, with more interpretative studies, which
will inevitably focus on small samples of organizations, providing
more specific detail. The lack of cumulative progress is also due to
a lack of consensus on the characterization of the MCS itself, which
will be dealt with in Section 6.
5.4. Culture
There has been a significant amount of work which examines
the effect of culture (usually national culture) on the design and
operation of control systems with some 25 articles in the bibliography being on this topic. Much of the work has been conducted
by US-based authors studying Chinese (or Taiwanese) culture and
many articles rely upon Hofstede’s early work on the topic which
was reported most fully in 1980. It is relevant to note that the
database for his work consisted of IBM employees working in
many different locations, so may give a biased representation of
employees in other organizations despite its impressive national
coverage. Hofstede (1980) initially identified four major dimensions on which national cultures could be distinguished: power
distance, individualism, masculinity and uncertainty avoidance. He
later added short-term vs. long-term emphasis, and Hofstede et al.
(2010) added pragmatism and indulgence based on World Values Survey data. Essentially, these studies depended upon forms
of statistical analysis such as factor analysis to identify underlying
clusters of variables which were then given the above labels.
What is notable about the MCS work is that differences in
national cultures are often merely assumed to be different in studies, rather than being measured by them, and they are also assumed
to accord with the results of Hofstede’s early studies, despite the
age of his work. In a few cases an instrument based on Hofstede’s
work is used to construct a measure of some cultural values for
a specific sample. The outcome is that studies are rarely comparable even on how culture is defined or assumed to be, let alone
with its effects on control systems. Here the extant work studies
different aspects of control systems, with many finding that apparently intuitive hypotheses are not substantiated. So it proves almost
impossible to generalize about even the major effects of (national)
culture on MCS design and use.
This is probably mainly due to two effects. First, national culture, even if captured by the measurement instruments used, is
an average within which there is almost certainly a wide range of
variation between individuals and groups within a country. The
employees of a particular company may well differ significantly
from the stereotypical behaviour that an overall average provides.
Second, it is likely that organizational culture will also have a significant influence on attitudes and behaviour within an organization.
Unless some attempt is made to measure the cultural values and
assumptions of the particular employees in question, then it is likely
that any results will contain significant amounts of noise. Again,
there is likely to be considerable variation between individuals and,
in addition, in these days of global employment, many employees
in a single location may well have been brought up in different
national cultures. But organizational culture can also be managed
to an important extent and significant examples exist of training
regimes that have changed the behaviours of key employees in
certain organizations (e.g., airline pilots in a Korean airline who
previously tended to have such a high level of hierarchical respect
that they failed to question the decisions of a senior pilot even
when these were thought to be clearly inappropriate, and in some
cases led to major accidents). Organizational culture is probably
best seen as a mediating variable through which national culture
acts in influencing behaviour in organizations.
These comments should not diminish the importance of studying organizational culture and its impact on employee behaviour as
organizational culture is an important control mechanism (Ouchi,
1979). According to Fisher (1995) organizational culture implies a
set of social norms, values and beliefs that are shared by the members of the organization and influence their actions. He argues that
a strong internal culture can decrease the need for other control
mechanisms, and may thus affect the overall design of an MCS.
This is therefore an important area for continued work, despite the
difficulties that will need to be overcome to obtain results of any
generality.
52 D. Otley / Management Accounting Research 31 (2016) 45–62
5.5. Effectiveness
The idea of a contingency fit requires some measure of effectiveness to act as a criterion variable. That is, a good contingent fit can be
defined as achieving higher effectiveness than a poor fit. But how
effectiveness is defined and measured varies considerably across
studies. Initially some studies merely assumed that existence was
itself a measure of effectiveness, generally on the (often unstated)
grounds that in the long-run equilibrium considerations would lead
to observed occurrences stemming from a good fit, whereas cases of
a poor fit would have gone out of existence. Not only is this implausible in modern conditions, but empirical studies which analyze a
large dataset require some variable to act as a criterion, so each
such study requires a measure of effectiveness. These vary depending on the topic of the study; for example product innovation has
been used in studies where the focus is on MCS design and use
that support innovation (see Bisbe and Otley (2004)). But the most
commonly used measure of effectiveness, by far, has been financial
performance, usually profit or return on investment.
There are two major problems with using profitability as a criterion variable to determine contingency fit. Firstly, profitability is
affected by a huge range of factors other than MCS design or use.
Thus a great deal of random noise can be expected. Additionally,
the unit whose profitability is used should ideally be different for
each of the managers included in the study (or issues about the
appropriate unit of analysis will be raised). Secondly, financial performance has been argued to be a contingent variable in its own
right. For example, an organization facing poor financial performance is highly likely to pay more attention to financial control
techniques such as budgeting. If this is the case, then the apparently
perverse result that the extensive use of budgeting is positively
associated with poorer financial performance can be expected. Certainly, it is not possible to use financial performance as a criterion
variable if it is wished to study its role as a contingent variable,
which is perhaps why few studies have undertaken such an investigation. Nevertheless, it is possible to avoid this issue by either using
a different measure of organizational effectiveness, or by using a
managerial estimate of control systems effectiveness, despite the
issues raised by using data from the same manager to report both
on the nature of the system and on its effectiveness (particularly if
that person has been involved in the design of the system).
There are also wider issues in determining how ‘fit’ can be
assessed. These are well set out in Gerdin and Greve (2004) who
identify a number of different types of fit (Cartesian vs. configuration; congruence vs. contingency; and mediating vs. moderating)
each of which is appropriate to different types of hypothesis. They
also consider whether it is the form of a relationship that is being
hypothesized, or its strength. They then analyze a number of major
studies which use strategy as a contingent variable and conclude
that there is widespread confusion in the way ‘fit’ has been conceptualized in different studies (and sometimes within the same
study). This was followed by a later article (Gerdin and Greve, 2008)
which attempts to set out the appropriate statistical tests to assess
whether a given type of fit has been achieved or not.
Where several contingent variables are used there are difficulties in analyzing and understanding the results obtained in studies.
A popular early method was to use an interaction effect in a regression equation, where the interaction term is the multiplication of
the two independent variables involved. This is not problematic
(provided the regression model is appropriate to the hypothesis
being tested (see above)) but becomes more complicated when
the number of independent variables increases. Three variables
seems to have been the practical limit, but even here the interpretation of a three-way interaction is complicated and a clear
explanation often requires it to be broken down into sub-parts,
usually by dichotomizing one variable into two levels (e.g., high and
low with respect to its mean) and examining each sub-sample so
formed separately, despite the information loss in such a process.12
This process also draws attention to the common practice, often
also implicit in the statistical techniques used, of referring to levels
of a variable being high or low by reference only to other values
in the sample rather than to some external benchmark, making
comparability between studies difficult.
There has also been extensive debate on the role of appropriate statistical methods when testing for the existence of mediating
or moderating variables in contingent relationships. Hartmann and
Moers (2003) argued that there were many cases in the literature
where the theoretical reasoning led to the prediction of one of these
hypothesized relationships being true, but that the statistical test
used actually tested the other hypothesis. This provoked a debate
on the topic which is well summarized in Burkert et al. (2014) which
outlines several different forms of fit (some of which had not previously been discussed). They assess the best statistical techniques
that can be used in various circumstances and thus provide a useful guide for researchers developing large-scale empirical studies in
this area. However, many of these techniques are still data hungry
and may not prove feasible in many contexts, although statistical
techniques such as structural equation modeling and path analysis
can require less data to give statistically significant results.
There are thus practical limitations to understanding the complex interactions that may exist between more than a very few
contingent variables at a time. It is unlikely that there could ever
be a time when we would be able to predict the best MCS in a situation where there were more than a small number of important
contingent variables, particularly where different variables pointed
in conflicting directions. However, this narrow definition of what
comprises a ‘contingency study’ is unnecessarily constraining, as
pointed out by Chapman (1997), although he focusses specifically
on accounting rather than MCSs more generally. In an important
sense, all research on this topic can be seen as contingent, as we
seek to understand the appropriate matching between the use
of an accounting technique and the circumstances in which it is
used, whatever types of research methods are used. Chapman also
points out a confusion in the literature between complexity and
uncertainty, with some scales purporting to measure uncertainty
actually focussing on complexity. He argues for a dialogue between
traditional, quantitative research approaches increasingly adopted
in traditional contingency studies (even seen as defining them)
and more qualitative, interpretative field studies aimed at gaining insight into the complicated processes by which accounting
is mobilized and used within organizations. Although more of the
latter type of studies have occurred in the period after his article was published, the movement towards the study of MCS and
performance management systems (rather than just accounting
systems) has also taken place, which has made the studies necessarily even more complex, and his plea for more field-based work
is still very relevant. Given the dominance of non-US journals in
reporting research in this field, it is perhaps surprising that qualitative work has been so relatively slow in developing, although
there is evidence that this is beginning to change.
5.6. MCS: systems or packages?
There has been recent discussion as to whether a set of control
devices used by an organization are better regarded as a system
or a package, although the distinction between these terms is not
always made clear. The concept goes back to the use of the term
‘package’ by Otley (1980) where he uses it to refer to the separate
12 This is an important area where more modern statistical techniques are proving
to be very helpful in isolating the effects of a larger number of independent variables.
D. Otley / Management Accounting Research 31 (2016) 45–62 53
parts of an overall management control system, but without any
definition.13 The fullest discussion of the topic has been given by
Malmi and Brown (2008) in their introduction to a Special Issue of
MAR. Here they state that there are several reasons for considering
an MCS as a package. First, the components of an MCS do not operate
in isolation and the effect of any one needs to be considered in the
context of the other components being used at the same time. Second, it seems necessary to consider an overall package of controls if
the use and impact of a new MCS element is related to the functioning of the existing MCS package. Third, only some MCS elements are
accounting-based and consideration needs to be given as to how
these relate to broader controls (such as administrative or cultural
controls) and whether or how these complement or substitute for
each other in different contexts. They conclude by stating that “by
taking a broader package approach to the study of MCS, researchers
will be able to develop better theory of the real impact of innovations
such as the BSC, and how to design MCS packages.” (p. 288).
Included in the same Special Issue is also an article by Sandelin
(2008) which compares the development of control systems in a
single organization at two different points in time. He argues that,
although the external context is very similar in the two ‘cases’, the
control systems observed are very different. This is used, following
Gerdin (2005a), to support an argument for ‘equifinality’, namely
the fact that two different systems may actually produce equivalent
(or equally good) outcomes, and that there is no ‘one best way’ even
if this is considered in contingent terms.
Malmi and Brown seem however to go only part way down
the path they have identified, as they pay limited attention to the
phenomena often observed in practice that the elements of an overall control system may not be well-integrated or coordinated. The
fuller idea of a package should perhaps incorporate this idea, which
is sometimes referred to as ‘loose coupling’, although it is often not
clear whether this is regarded as intentionally designed or accidently achieved! This idea was developed by Orton and Weick
(1990) and Malmi and Brown suggest that it might be fruitful to
follow a similar approach in characterizing the linkages between
the elements in an MCS package.
The main contribution of the Malmi and Brown article seems
rather to be the typology they give of the various categories of
control that form an overall package. These are seen as falling
into five different categories, most centrally Planning and Cybernetic Controls (essential ex post and ex ante control), together with
Reward and Compensation. These are supplemented by Administrative Controls (which include both governance and organizational
structure) and all are included within a wider set of Cultural Controls. This provides a valuable supplement to the twelve questions
suggested by Ferreira and Otley (2009) in their proposed framework for the study of overall control systems, although they make
little reference to the idea of packages except in their question
about coordination between controls.
A limited conceptualization of an MCS and its components permeates the literature. Most articles select just one component of
an overall system for study (such as budgeting, use of a BSC, or
compensation system) and proceed without any reference to the
other components that surround it. It is rare for an attempt to be
made to capture the totality of an overall system, although some
of the users of the Ferreira and Otley (2009) framework have tried
to move in this direction. This is gratifying to me as the framework
was put forward in order to make it more feasible for researchers
to attempt such a task. Some use has also begun to take place of the
13 My recollection is that I felt unhappy with using the term ‘system’ because it
seemed to imply a designed system of well-coordinated parts, and many overall
MCSs did not seem to possess this property. I used the term ‘package’ to imply a set
of pieces that were put together without ensuring that they were fully coordinated.
Malmi and Brown (2008) categorization, but these studies comprise just a small part of extant work. Grabner and Moers (2013)
have also tackled the problem of more precisely defining the idea
of internal consistency which has been used to define an optimal
(perhaps closely coupled) MCS package. However, their work is
primarily analytic and is mainly concerned with the conceptualization of ‘internal consistency’ based on a number of assumptions,
before addressing some implications for empirical studies. There
is therefore scope for this issue to be examined from an empirical
perspective to complement their analytic approach. One example
of such work is Gong and Ferreira (2014) which seeks to examine whether consistency in management control systems design
choices affects firm performance, with their results showing a positive relationship.
The importance of overall context had also been emphasized
by Nixon and Burns (2005) in their introduction to an earlier Special Issue of MAR. They drew particular attention to the idea that
change had itself changed by becoming much more rapid. The idea
that periods of change are punctuated by periods of equilibrium
has become outdated. They also drew attention to the continued
existence of two gaps: first, that between extant management control literatures and management practice, and second, between the
management control literature and other literatures. They argue
that these issues “increase the persuasiveness of longstanding criticisms of the theoretical foundations of management control” (p.262).
This view is strongly reflected in one article in that Special Issue
by Collier (2005) which provides an interesting perspective on
several control issues, namely the changes that occur in management control over an organizational life cycle, the degree of
consistency among different controls, and the interaction between
formal, systems-based controls and informal controls. In addition,
he argues that both the frameworks of Ferreira and Otley (2009)
and Simons (1995) pay too little attention to beliefs controls, and
concludes that modern organizations will have to develop controls which allow them both to compete today and to prepare for
tomorrow.
Finally, Mundy (2015) has developed the idea of loose coupling in MCSs following earlier work by Demartini (2011). Although
developed in both organization theory and economics, this idea
has yet to be fully applied to MCSs. Mundy takes the view that
MCSs within many organizations constitute a package of distinct
management control elements that have been separately designed
and implemented without an overall intention or coordination, but
where each element aims to facilitate the attainment of different
aspects of organizational goals. She applies this to examine the patterns of interaction observed within a MCS package in a single
organization, and interprets these as an exemplar of loose coupling. Of particular interest is her documentation of management
‘workarounds’, that is, informal practices that enable the overall
package of control to function better than observation of just the
formal systems might imply. She characterizes the coupled nature
of interrelations within an MCS package using four dimensions:
mode, directness, directionality, and frequency, and demonstrates
the actual functionality of a specific package of controls despite
its parts having been implemented at different times, by different
individuals and for different purposes.
These studies indicate an emerging view that overall MCSs are
influenced by their content and trajectory of development as well as
by traditional contingent factors. As external change occurs, control
systems are adapted, often by the addition of additional features or
systems (and perhaps less by the removal of practices which have
become outdated, as these tend to fall into disuse rather than being
removed). Rather than moving from one equilibrium to another,
such systems resemble packages which are constantly being modified and developed with the ever-present danger that they become
internally inconsistent and incoherent. Although this can be (and
54 D. Otley / Management Accounting Research 31 (2016) 45–62
perhaps should be) tackled as part of their development process, in
practice MCS packages will inevitably contain inconsistent and contradictory elements. It appears that informal processes are likely
to play an increasingly important role in helping preserve their
continuing functionality.
6. A characterization of MCSs and their context
The above critiques have concentrated on the specification of
different contingent (independent) variables that have been frequently used in the literature. It is surprising that a similar amount
of attention has not been devoted to the dependent variable of the
MCS and aspects of its design and use. By contrast, this has generally
been treated in a fragmentary manner with just one or two aspects
selected by each reported study, with very little work attempting to
gain a holistic view of the overall systems in use by an organization.
Admittedly, this is a significant task to attempt, particularly with
the lack of frameworks to assist in categorizing such MCS components. For example, Ferreira and Otley (2009) focus primarily on
the purposes served by the components of such systems, whereas
Malmi and Brown (2008) attempt a basic classification of tools and
techniques, but again concentrate on their use (e.g., planning, control etc.). It seems likely that more useful progress will now be
gained by a greater focus on the MCS itself, how its elements may
most usefully be conceptualized, and how they are inter-related.
This requires a richer conception of the reality of the actual control
systems extant in organizations, and an attempt to characterize this
is set out below.
Organizations exist in an environment of considerable
uncertainty.14 Business organizations, in particular, working
in a competitive environment can never totally predict the actions
of their competitors or what technological innovation may occur
and on what time scale. They also depend upon other organizations as either suppliers, customers, service providers or network
partners, and these relationships are subject to ongoing change.
The overall economic environment is now global and increasingly
unpredictable as no sector is immune to changes happening far
away. Even the public sector is subject to some of these features
and also by the vagaries of public policy, changes in which can
sometimes be quite sudden and unpredictable. In addition, the
internal organizational environment is also subject to considerable
uncertainties about how employees will communicate, coordinate
and generally behave in ways conducive to efficient operations.15
Of course, different types and amounts of uncertainty exist in
different environments, and these differences have been the focus
of one major contingent variable. But it needs to be recognized that
substantial uncertainty is present in all organizations and that they
need to cope with this, as argued in Otley (2014). Thus MCSs need to
be able to operate in such an uncertain environment and may need
to be adapted to cope with this ever more common circumstance.
For example, the Beyond Budgeting movement has claimed that
in this ‘new’ environment budgeting is fundamentally past its sellby date and needs to be replaced with a better system (Hope and
Fraser, 2003), although it now seems to have modified its claims of
being an alternative system to the more modest suggestion that it
comprises a set of useful tools (see Hansen et al., 2003). Nevertheless the majority of organizations of any size still have budgetary
14 See Otley and Soin (2014) for a set of essays on how uncertainty affects the
design and operation of MCSs.
15 I well remember as a PhD student being ‘reprimanded’ by my teacher of organizational behaviour for concentrating excessively on dysfunctional behaviour. “Isn’t
what is really surprising, he suggested, is that organizations actually work as well
as they do, and shouldn’t we concentrate on trying to understand how they achieve
such remarkable consistency and regularity?”
systems, although these may have been adapted in a variety of ways
(e.g., more frequent updating; shorter time-spans; rolling budget
systems etc.; different patterns of budget use for different purposes
etc.). What is evident is that budgetary control has been displaced
from the central place it occupied forty years ago and supplemented by other systems, most notably Balanced Scorecard-type
systems containing a variety of non-financial measures of performance. In addition, these performance measurement systems are
often complemented by performance-related pay systems which
rely on further (and sometimes different) performance measures,
and which are usually different at successive hierarchical levels.
A central feature of the elements (sub-systems) of an overall
MCS is that they comprise of largely independent systems in their
own right. For example, we still have budgetary control systems
(although the ways in which these are used may have changed
markedly), but also non-financial performance measures, perhaps
integrated into a dashboard or scorecard, risk management systems, incentive payment systems, corporate governance systems
and strategic control systems as well as many others. These have
generally been developed by different (groups of) people at different times, often with a particular and limited purpose in mind at
the time of their implementation. In addition, they may impinge
differently within each organizational function, and at different
hierarchical levels. Thus it often seems to make more sense to think
of an organizational control ‘package’ as the different elements are
likely not to be perfectly coordinated with each other. For example, the performance measures driving a senior management bonus
scheme may not be those specified in the top-level BSC (a real
example!).
This process is dynamic. Changes may be made from time
to time, often with the purpose of aligning disparate systems
with each other. These will often be successful in their own
right, although there are often significant lags in alignment being
achieved (payment systems being particularly ‘sticky’ in this
respect as they often require renegotiation with groups of employees; and computer systems are invariably slow to get updated).
However, other new systems may also be introduced that have
their own differences from the extant package, and the speed of
improvement often lags the rate of introduction of new elements.
The ways in which employees use the elements available to
them often changes over time, sometimes quite rapidly. When
Mundy (2015) documented the ‘workarounds’ that were adopted in
the organization she observed, these could be generally described
as functional in that they allowed ill-coordinated systems to be
made workable by these informal changes. Additionally, in multinational organizations another layer of complexity often arises in
that systems which operate well in one national environment may
work very differently in another national culture. Mergers and
acquisitions also often display instances of systems change which
proves ineffective because of the differing organizational cultures
of the combining organizations.
Finally, more organizations have become part of a value chain
that covers several independent organizations, which have no common ownership or superior authority, yet still need to coordinate
their operations. Many of these seem to have one organization in
a dominant position, either because it is significantly larger than
the others, or it has a monopoly over the route to the ultimate consumer, and here its systems will tend to be imposed. For example,
most cases of open book accounting seem to display this characteristic. But others are comprised of more equal partners who need
to devise arrangements to achieve better coordination and control,
and are often in a continuing process to adapt their arrangements.
It has become usual for such partly co-ordinated combinations
of elements into an overall system to be labelled as ‘looselycoupled’ although this term seems to cover both intentional design
and accidental outcomes. It seems probable that most of the loose
D. Otley / Management Accounting Research 31 (2016) 45–62 55
ness of coupling in MCSs is accidental rather than intentional,
although this is an empirical question which would be interesting
to investigate. However, the overall context and design of an overall
MCS requires us to recognize the type of environment in which it
operates, both in terms of specific factors and general overall trends.
In particular, researchers need to view the systems they are studying from the above perspective, and to adopt research designs and
methods that can cope with this complexity. Although ‘snapshot’
pictures of the type generated by arm’s length quantitative studies have their place and can cover a range of organizations, their
design needs to standardize and control for, as far as possible, the
variables that they are not able to measure, so that the results are
not contaminated by unknown random variation. More insight will
probably be gained, especially in what are early days in studying
complete control systems in their entirety, by field studies of a small
number of organizations in some depth and preferably over time.
We understand relatively little of the development of MCSs over
time and the complex ways in which the technical components of
these complex systems, their interactions, and the ways in which
managers use them, are important aspects for study.
Such studies may well not follow a formal, contingent approach,
but they rest on the important information that previous studies have provided. However, it is important to recognize that it
is likely that these previous results are neither universal nor constant. That is, a specific study will have taken place in particular
conditions, many of which have not been documented or even measured; even if valid in that situation, the passage of time may well
have changed other relevant factors as well. So the result is perhaps usefully indicative of the types of system that can exist, but it
is unlikely to have the predictive power to predict what will be
found even in other apparently similar circumstances. The type
of knowledge we have obtained is not that of a hard, scientific
nature, where experiments can be conducted on phenomena which
have constant properties at different times and in different places.
It is knowledge about how processes and interactions between
processes occur, so that we are in a position to understand the generalities of behaviour that occur in such systems, rather than being
able to predict the outcomes in any set of specific circumstances
without further investigation.
7. Conclusion
The work conducted under the banner of contingency theory has
been one of the success stories of research in management accounting and control over the past forty years. It has given insights
into how different configurations and uses of control systems have
resulted in a variety of different consequences. However, it has also
been tantalisingly inconclusive and has produced little cumulative
knowledge. This is perhaps because it has (implicitly) set out to produce knowledge of a type which may not exist in the complex and
changing world of organizational control. As Saulpic and Zarlowski
(2014) point out, we need to recognize that in this field “research
does not often lead to establishing what does or does not work in a
specific organizational context.” (p.215). We are unlikely ever to be
able to produce knowledge of the type that is generated by the
physical sciences as our subject matter does not have the stability
and uniformity of physical matter, nor is it amenable to controlled
experimentation.
In this context, one way forward can be found in the deployment
of what has been termed Middle Range Thinking (MRT) by Richard
Laughlin and well expounded in Broadbent and Laughlin (2014).
They argue that “a research approach using MRT provides important
insights into the nature and functioning of MCSs, particularly in conditions of uncertainty” (p.255). They view the social world not as rule
governed but rather as interpretively constructed, which implies
that it cannot usefully be characterized solely by tight theoretical
descriptions. Yet this social interaction is also embedded in the context of existing yet dynamic social structures and institutions. This
is not to suggest that researchers should go into the field free of theory (an impossibility in any case), but the theories that are being
assumed should be made explicit and remain open to adaptation.
Such an approach represents a middle ground between taking a
firm initial theoretical position and the attempt to build interpretations uncontaminated by prior beliefs, as is sometimes suggested
by the proponents of grounded theory. It suggests that such theories
cannot be ‘tested’ in the ways that positivistic research approaches
might demand, but still allows them to be open to change in the
light of new interpretations. The underlying theories can be seen
as a ‘skeleton’ that give researchers a language to discuss the empirical situation and which are given meaning by the empirical ‘flesh’.
As they summarize their position “Just as the theoretical ‘skeleton’
needs empirical ‘flesh’ to give it meaning, so the empirical flesh is given
shape by the theoretical frame.” (p.257).
The MRT approach therefore gives theory a different role than
that taken by the positivist approaches used in the natural sciences. In the social sciences theories will be less all-encompassing
and will possess a much more limited predictive ability, yet
remain important for codifying the common understandings of
researchers working in a particular field. Yet these understandings
will inevitably be partial and subject to continual modification and
change. As they conclude “MRT accepts that we can derive generic
theories . . . but that such theories will always be ‘skeletal’ in nature as
the nature of understanding is uncertain and changing.” (p.267). This
implies that all theoretical structures in this field require empirical
‘flesh’ to provide an adequate explanation of observed behaviours.
But whatever theoretical approach is adopted it needs to take seriously the inherent uncertainty in the world we are studying and
the types of knowledge that it will be possible to discover.
In particular, a major deficiency of much prior work has been the
lack of attention paid to the conceptualization of the overall MCS.
Although many elements of an overall MCS have been studied, these
have been seen in isolation from the context of the other elements
which surround them. The idea of a ‘package’ of control systems has
been in existence since at least 1980 but has only recently begun
to be taken seriously. At the very least, researchers need to take
pains to set out and report the context (both external and internal)
in which their data has been gathered in order that the limitations to its generalization can be made apparent. In addition, few
studies have yet attempted to take an overview of the overall package of controls being deployed in an organization and to study the
dynamics of how these develop and the outcomes that result. MCSs
are deployed in an environment of considerable uncertainty where
even responsible managers may have an incomplete understanding
of how outcomes will result from their decisions. The limitations
of knowledge and the types of theory that are possible need to be
more explicitly acknowledged.
But this is a vitally important topic where researchers can
develop insights which can both help to establish theoretical propositions and also have practical impact in the world of organizations.
The work of Simons (1995) and the case studies on which it is based
give one exemplar as to how this can be done. But the task has
only just begun, and there is a multitude of opportunities open to
researchers working in this area. I look forward to seeing the results
of their endeavors in the pages of future issues of Management
Accounting Research.
Acknowledgments
The author would like to acknowledge the help given by Yahui
Dong and Ying Sun, two M.Sc. students at Lancaster University who
56 D. Otley / Management Accounting Research 31 (2016) 45–62
helped compile and categorize the bibliography. Also to participants at the Management Accounting Research conference held
at the LSE in April 2015, and to Professor Bob Scapens, Professor
Michael Bromwich and an anonymous reviewer for their helpful
comments.
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