BEHAVIORAL RESEARCH IN ACCOUNTING American Accounting AssociationVol. 25, No. 1 DOI: 10.2308/bria-503332013pp. 89–114
The Effect of Managers’ Enabling Perceptionson Costing System Use, PsychologicalEmpowerment, and Task Performance
Habib Mahama
Australian National University
Mandy M. Cheng
The University of New South Wales
ABSTRACT: This study investigates whether and how managers’ enabling perceptions
of their costing systems affect task performance. We propose that managers who
perceive their costing system as more enabling will have higher levels of task
performance, and that this relationship occurs through the intensity with which the
costing system is used and the level of psychological empowerment experienced by the
managers. To test these propositions, we conduct a survey of middle-level managers
and analyze the responses using a PLS model. Our results generally support our
propositions. Specifically, we find a positive relationship between managers’ enabling
perceptions and the intensity with which the costing system is used. The intensity of use
is further associated with all four dimensions of psychological empowerment (meaning,
competence, self-determination, and impact). Finally, the intensity of use also has an
indirect impact on task performance via the competence dimension of psychological
empowerment. The present study extends prior research on costing systems, and adds
to our understanding of the role managers’ perceptions play in improving costing system
effectiveness.
Keywords: enabling perception; costing system; pyschological empowerment; task
performance.
Data Availability: Data available upon request.
INTRODUCTION
Costing systems are part of wider management information systems used in organizations to
improve performance. As information systems, costing systems have the potential to
deepen managers’ understanding of the organizational decision context, improve
managerial judgment and decision making, and enhance productivity. While in principle, these
The authors acknowledge the helpful comments from participants at the 2008 EIASM Conference, 2009 AAA AnnualMeeting, and 2009 AFAANZ Conference.
Steve G. Sutton, Associate Editor.
Published Online: October 2012
89
benefits are possible, in practice, organizations have difficulty realizing these benefits (Bhimani
1996; Innes et al. 2000; Anderson et al. 2002; Chenhall 2004). Consequently, management
accounting researchers have sought to understand how, and the extent to which, these systems are
successful in achieving these benefits for organizations.
Much of the prior research in this area has focused on the technical design aspects of these
systems (e.g., sophistication of the costing system, selection of cost drivers and cost pools) as a
variable for explaining the success of costing systems in improving the quality/relevance of cost
information for decision making and enhancing organizational performance (Christensen and
Demski 1997; Anderson and Young 1999; Bromwich and Hong 1999; Ittner et al. 2002). Other
researchers have criticized the over-emphasis on the technical design of costing systems, and have
highlighted the need for studies that examine the effect of behavioral implementation factors on
costing system success (Shields and Young 1989; Shields 1995; Foster and Swenson 1997;
McGowan and Klammer 1997; McGowan 1998; Anderson et al. 2002; Chenhall 2004). In this
study, we aim to extend prior research in this area by focusing on the impact of psychological/
behavioral factors on the post-implementation use of costing systems. Specifically, we aim to
provide evidence on how managers’ perceptions of a costing system as enabling (‘‘enabling
perceptions’’) influence their usage of the system, their psychological empowerment, and task
performance.
Adler and Borys (1996) develop the concept of ‘‘enabling’’ to describe an organizational
technology that helps workers to deal effectively with work contingencies, rather than one designed
to fool-proof work processes. Subsequently, accounting studies have shown that the principles
underlying an enabling system are relevant to understanding the design of performance
measurement, information system integration, and management control (e.g., Ahrens and Chapman
2004; Wouters and Wilderon 2008; Chapman and Kihn 2009). Our study extends the prior research
by focusing on managers’ enabling perceptions in relation to their costing systems.
The importance of focusing on managers’ perception derives mainly from psychology
literature that suggests that perception is an important factor affecting the attitudes and behavior of
organizational members. This literature argues that individuals actively perceive their work
environments, and that their reactions to those environments are shaped by their perceptions and
interpretations that go beyond the verifiable reality of those environments (Thomas and Velthouse
1990; Spreitzer 1996). More specifically, Spreitzer (1996) argues that rather than the ‘‘objective’’work environment determining behavior in organizations, individuals’ perceptions of those
environments influence behavior. As costing systems are part of the work environment of managers
and following from the above, we argue that the perceptions managers hold about the enabling
property of these systems will play significant roles in determining their behavioral reactions toward
those systems.
Consistent with the psychology literature, the information systems (IS) and accounting
literatures have also recognized the need to understand the behavioral and performance
consequences of the psychological properties associated with an information system. In the IS
literature, DeLone and McLean (2003) argue that evaluating the success of any information system
requires an examination of factors not only at the technical level (i.e., factors in relation to the
accuracy/efficiency of the system), but also factors at the semantic level, which concerns how the
meaning and the purpose of the information produced by the system is perceived by its users.1
Further, as users experience features of the system, it becomes important to also assess system
successes at the influence level; that is, how the system influences the way individual users conduct
1 Other well-established models in the IS literature, such as the Technology Acceptance Model (TAM), also arguethat users’ perceptions of an information system drive their behavioral responses, such as their willingness to usethe information system.
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their work. Similarly, in the accounting literature, managers’ behavioral responses to management
accounting practices and systems are significantly influenced by their perceptions, including
perceived fairness and justice (e.g., Lau and Moser 2008; Burney et al. 2009). Here, we argue that
managers’ enabling perceptions can explain the benefits they derive from their costing systems;
namely, improved task performance.2
Prior research also suggests that perception is linked to use (behavior) and feelings of
psychological empowerment (Spreitzer 1996; Seddon 1997). ‘‘Use’’ is a conduit through which
information systems generate organization and individual effects (Davis 1993; Straub et al. 1995;
Chenhall 2003); hence, we expect that the performance impact of managers’ enabling perceptions
will be realized through increasing the intensity with which the system is used. Psychological
empowerment has also been established by recent accounting research as a key factor that mediates
the relationship between management accounting practices and individual-level performance
(Drake et al. 2007; Hall 2008). Spreitzer (1996, 486) argues that ‘‘[f]or individuals to feel
empowered, they must perceive a role environment to be liberating rather than constraining.’’ This
suggests psychological empowerment is also an important variable through which managers’
perceptions of costing systems can affect their task performance. These potentially important
linkages between enabling perception, use, psychological empowerment, and task performance
form the basis of the proposed conceptual model and the hypothesis developed for the present
study.
We test our proposed hypothesis by conducting a cross-sectional survey of middle-level
managers in Australia. We hypothesize and show that the intensity with which a costing system is
used is positively associated with managers’ enabling perceptions. Following from Spreitzer
(1995), we model psychological empowerment as a four-dimensional construct (meaning,
competence, self-determination, and impact), and predict that the intensity of use is positively
associated with all four dimensions, and the results support this prediction. We also find that
managers’ enabling perceptions are indirectly related to three of the dimensions of psychological
empowerment (meaning, competence, and impact) through the intensity of use. In addition, we
hypothesize that psychological empowerment and the intensity of use are positively associated with
task performance. We find support for two dimensions of psychological empowerment (competenceand self-determination) and task performance. There is no direct relationship between intensity of
use and task performance; however, the intensity of use is indirectly related to task performance
through the competence dimension of psychological empowerment.
Our study makes a number of contributions to the literature. First, prior literature has found
mixed evidence on the benefits of sophisticated costing systems such as activity-based costing
(ABC) systems (Bhimani 1996; Innes et al. 2000; Chenhall 2004). Our study contributes to this
literature by highlighting the importance of examining the enabling property of a costing system as
perceived by the managers. Although past studies in the costing system research literature have
investigated the impact behavioral implementation factors have on costing system effectiveness
(e.g., McGowan and Klammer 1997; Chenhall 2004), our study is one of the first to show that the
behavioral issues associated with the usage of these systems are also significant factors to be
considered. From the practitioners’ point of view, the findings from the present study suggest that in
addition to the technical design, costing systems designers should consider user perceptions.
Second, we provide further support to the concept of enabling as an important accounting system
attribute, and show that enabling perception is an antecedent to important behavioral variables such
as psychological empowerment and costing system usage.
2 In this study, we use the term ‘‘task performance’’ to refer to individual managers’ performance with respect totheir work tasks. We view task performance as a subset of individual performance, with a focus specifically onhow well individuals perform on their work tasks.
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Third, Chenhall (2003) argues that the positive link between the usefulness of management
control systems, their subsequent use, and enhanced organizational outcomes is a ‘‘broad leap in
logic’’ that is not supported by compelling empirical evidence. Our study shows that while an
enabling perception of a costing system has a direct positive impact on its usage, the subsequent
link from use to task performance is indirect, via elements of psychological empowerment. The
result, thus, illustrates the importance of identifying intervening variables in explaining the benefits
of costing systems. Although our study does not extend to performance at the organizational level,
understanding the positive effects of costing system on task performance is the first step toward
improving organization-level outcomes. Finally, while prior studies have established that
psychological empowerment is important in designing management accounting systems (Drake
et al. 2007; Hall 2008; Marginson and Bui 2009), its role is still under-researched (Drake et al.
2007). We add to the literature by showing that psychological empowerment is indirectly
influenced by the extent to which managers perceive their costing systems as enabling.
The rest of the paper is organized as follows. First, we present the overall proposed model.
Next, the relationship between managers’ enabling perceptions and their behavioral responses
(namely, psychological empowerment and intensity of use) are discussed. We then explain the task
performance effect of managers’ intensive usage of the costing system. This is followed by an
outline of our research method, result analysis (including both the measurement model and the
structural model of our PLS analysis) and, finally, discussions and conclusions.
THEORY AND HYPOTHESIS DEVELOPMENT
Costing Systems
Costing systems are interrelated manual and computer parts used to gather, analyze, and
manage cost and activity data to provide information for internal users estimating the cost of cost
objects, better cost management, strategy development and management, enhanced product
planning decisions, and improved managerial judgment. Since the 1980s, there has been growing
interest in costing systems, and this interest is driven by changes in the corporate landscape,
including changes in manufacturing technology, global competition, and shorter product life cycle
(Al-Omiri and Drury 2007).
Despite this growing interest, there has been mixed evidence on the ability of costing systems
to deliver benefits. A review of recent literature in this area suggests that some researchers have
approached this issue by focusing on costing system design, exploring specific technical attributes
of these systems (e.g., system sophistication, cost behavioral classifications) and/or the interaction
of these technical attributes with the organization’s external environment and internal
characteristics to deliver positive results (e.g., Abernathy et al. 2001; Ittner et al. 2002; Pizzini
2006; Al-Omiri and Drury 2007). Others adopt a different approach and focus their attention on the
implementation process (e.g., Anderson and Young 1999; Anderson et al. 2002; Chenhall 2004),
exploring both behavioral factors (e.g., cognitive conflict) and technical attributes (e.g., the size of
the implementation team and the use of external consultants).
We seek to contribute to the existing literature by examining the psychological/behavioral
factors associated with costing systems use and the consequences of that for task performance. We
propose a model linking the costing system users’ enabling perceptions of their systems to their
experience of psychological empowerment and task performance via the intensity with which these
systems are used. DeLone and McLean (1992) argue that in examining systems use, it is important
to consider the nature and intensity of use. Following from this, we focus on the intensity with
which costing systems are used for cost management practices. The hypothesized relationships in
our conceptual model are shown in Figure 1.
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Enabling Perceptions of Costing Systems and the Intensity of Use of These Systems
The concept of enabling formalization was initially introduced to the accounting literature by
Ahrens and Chapman (2004), and subsequent studies have applied it to the study of accounting
phenomena (Naranjo-Gil and Hartmann 2006; Wouters and Wilderon 2008; Chapman and Kihn
2009). The core aim of this concept is to provide a useful framework for understanding how
employees distinguish good (positive) administrative rules and systems from bad (negative) ones
(Adler and Borys 1996). Specifically, the notion of enabling formalization describes rules and
systems that are designed to facilitate how employees structure, refine, and conduct their work
processes with no necessary hierarchical implications. That is, they are rules and systems designed
to support rather than control the employee (Ahrens and Chapman 2004). In contrast, rules and
systems that are designed to force ‘‘reluctant compliance’’ and, thus, seek to police adherence to
pre-specified standards, are said to be less enabling and rather coercive (Adler and Borys 1996;
Ahrens and Chapman 2004).
Recently, Chapman and Kihn (2009) have shown that the positive effect of integrated IS such
as enterprise resource planning (ERP) systems on organizational outcomes can be explained by the
association between IS integration and the design characteristics of enabling management control.
In this study, we focus our attention on the perceptions managers hold about the enabling property
of costing systems, and the impact of such perceptions on managers’ behavioral responses to these
systems. Perception has long been held as an important factor affecting the attitudes and behavior of
organizational members (Agarwal and Prasad 1998; Pierce and O’Dea 2003; Jarrar et al. 2007).
Perception is an internal representation whose functional role is to ‘‘stand in’’ for features of the
percept (i.e., the events or objects being perceived) (Knill and Richards 1996; Warren 2006). More
FIGURE 1Theoretical Model
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specifically, it is a process through which individuals acquire information about events and objects
in their environment, and by which individuals construct representations of their worlds. Such
representations are said to be sufficiently rich to provide the basis for behavior or conduct (Warren
2006). That is, perceptions about events and objects influence behavior. Generally, positive
perceptions are associated with more desirable behavior toward the percept, and negative
perceptions lead to less desirable reactions.
To develop positive or negative perceptions of a costing system, individual managers need a
conceptual base. Following from Shields (1995), we conceptualize costing systems as
administrative innovations. This then allows us to draw on the concept of enabling formalization
to understand the conceptual basis of individual managers’ perceptions of costing systems. Our
premise is that individual managers will perceive costing systems as more or less enabling of their
work processes. We argue that systems that are thought to support, rather than control, managers’
work processes will be perceived more positively than those that are less enabling. We further posit
that this variation in enabling perceptions influences managers’ behaviors, and as use is considered
to be a type of behavior (see Seddon 1997), we argue that a manager’s perceptions of how enabling
a costing system is will be significantly and positively related to the degree to which he or she will
use the costing system for cost management.3 Following prior literature, we use the term ‘‘intensity
of use’’ to describe the extent users draw on the system to support their work (e.g., Teng and
Calhoun 1996; Schoute 2009). More formally, we hypothesize the following:
H1: There is a positive direct relationship between individual managers’ enabling perceptions
of their costing systems and the intensity with which individual managers use a costing
system for cost management
Enabling Perceptions of Costing Systems, Intensity of Use, and Psychological Empowerment
Psychological empowerment refers to an individual’s intrinsic motivation toward, or
psychological reaction to, his or her work environment (Spreitzer 1995; Spreitzer et al. 1997;
Kraimer et al. 1999). It reflects an individual’s feelings about his or her ability to influence his or
her work roles. Spreitzer (1995) argues that an individual’s psychological empowerment is manifest
in a set of four cognitions: meaning, competence, self-determination, and impact. Meaning refers to
the value placed on work goals relative to an individual’s own standards. It reflects a fit between an
individual’s work role requirements and their personal beliefs, values, and behavior (Spreitzer
1996; Carless 2004). Competence relates to an individual’s belief that he or she has the capability to
accomplish specific activities skillfully. It reflects ‘‘an individual’s belief about mastery over
behavior’’ (Carless 2004, 407). Self-determination is similar to Bandura’s (1997) notion of self-
efficacy, and refers to an individual’s belief that he or she has the autonomy to initiate and regulate
their work behaviors. Impact denotes an individual’s beliefs that he or she can influence work
outcomes.
Psychology research suggests that an individual’s perception and interpretation of his or her
work environment is an important determinant of his or her level of psychological empowerment
(Thomas and Velthouse 1990; Spreitzer 1995, 1996; Burney et al. 2009). Spreitzer (1995) contends
that there is a positive relationship between an individual’s work context and psychological
empowerment, and that the direction of the influence in this relationship flows from the work
environment to empowerment. She notes, ‘‘[e]xcept in contexts like organizations undergoing
3 Consistent with Chenhall (2004), we view cost management practices as using cost information to make a rangeof decisions, including cost reductions and modeling, reengineering and improvement, budgeting, andperformance measurement.
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metamorphic change or entrepreneurial start-up firms, where individuals can have considerable
leverage, the environment will generally tend to have a more powerful effect on individuals than the
converse’’ (Spreitzer 1996, 486). Support for this direction of influence can also be found in
Martinko and Gardner (1982), Ashforth (1989), and Carless (2004). Overall, the literature suggests
that the work environment influences psychological empowerment.
An important part of the work environment is information. Empirical research suggests that
managers’ access to information is associated with their feelings of empowerment (Drake et al.
2007; Spreitzer 1996 [cited in Hall 2008]). Costing systems are an integral part of the information
systems of organizations and, thus, an important part of the work environment. We contend that
managers’ perceptions of their costing systems as enabling will significantly and positively
influence their feeling of empowerment.
More specifically, we expect that managers’ enabling perceptions of their costing system will
influence each of the four cognitions of psychological empowerment. For instance, individuals are
said to feel a sense of meaning when an activity or event ‘‘counts’’ in their value systems (Hackman
and Oldham 1980; Carless 2004). A costing system that is perceived as enabling or supportive of
work roles will ‘‘count’’ as something meaningful to their task requirements and, thus, influence
their feeling of empowerment. Also, when individuals perceive a costing system to be enabling,
they are more likely to feel confident that it will support them to competently execute work tasks
and, thus, improve the competence dimension of their psychological empowerment (Carless 2004).
We also argue that in considering the enabling property of a costing system, individuals will
evaluate how the system will support them in the decision-making (choice) processes about how
and what task to undertake. A perception that the system will be supportive of the decision-making
processes will, thus, positively influence individuals’ belief in their self-determination (Bandura
1997). Finally, a costing system perceived to be enabling will invoke a feeling of support in an
individual’s quest to influence work outcomes and, thus, affect the impact dimension of
psychological empowerment. This leads to our second hypothesis:
H2: There is a positive direct relationship between individual managers’ enabling perceptions
of their costing systems and individual managers’ psychological empowerment.
Further, we expect that the intensity with which the costing system is used is associated with a
greater sense of psychological empowerment. Using costing systems for cost management involves
modeling the information to account for the relevant decision variables. Such modeling generally
involves classifying, categorizing, and structuring cost information in a manner that enables
managers to establish relationships between problems, decision variables, and task goals. Prior
research suggests that the structuring or modeling of information has both cognitive effects (allows
a complex set of information to be dealt with as one element) and motivational effects (improves
the meaningfulness of the information and related task) (van Merrienboer and Sweller 2005).
Models that emerge from the structuring of information also serve as useful sources for explaining
and justifying decisions and actions (Sweller 1994). Given that the use of costing systems for cost
management involves the structuring of information through cost modeling, we expect that such use
will have effects on psychological empowerment.
More specifically, we argue that the structuring of information that occurs when costing
systems are used for cost management will improve the meaningfulness of a manager’s work role
by allowing the manager to actively engage in the relevant work tasks. This expectation is based on
Paas et al.’s (2004) findings that the structuring of information helps to align (fit) decision variables
with one’s cognitive architecture, and such alignment improves the meaningfulness of work
processes. We, therefore, expect that when costing systems are used intensively for a variety of cost
management decisions, such as budgeting and performance measurement, it will increase
managers’ feelings that there is a fit between the requirements of the work role (to manage costs)
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and their behaviors (using costing systems to support relevant cost management initiatives); this, in
turn, heightens the meaningfulness of their job (Spreitzer 1995).
We also expect the intensity with which costing systems are used in cost management will be
positively associated with competence. This is because the structuring/modeling of information in
cost management practices involves establishing problem categories and relating these categories to
possible solutions. Categorizing information helps people to determine how to deal with problems
and, thus, solve problems they would otherwise have difficulty solving (Sweller 1994). As cost
modeling in cost management processes involves categorizing, we expect that the intensity of using
costing systems for cost management will increase the confidence of a manager in his or her
capability to carry out specific tasks successfully. In this respect, the competence dimension of the
manager’s psychological empowerment is expected to be positively associated with the intensity
with which costing systems are used.
Similarly, a manager’s self-determination can be enhanced through an intensive use of a
costing system. By intensively using the costing system for cost management, individual managers
will be able to assess the outcomes of different behaviors or task strategies, and make choices
relating to their work process based on these assessments (Spreitzer et al. 1997). Also, using the
costing system to model the impact of task strategies can provide a manager with an internal
justification to make autonomous decisions, thereby improving the manager’s self-determination(Spreitzer et al. 1997). Furthermore, the intensity of costing systems use is expected to enable
individuals to model the effect of their work behaviors on organizational outcomes, and through
such modeling, the manager is able to provide justification for effects arising from his or her
actions, thus enhancing the impact dimension of his or her psychological empowerment. For
example, using costing systems for process improvement allows managers to see how their work
and their decisions affect organization outcomes. We, therefore, predict that high intensity of
costing systems use will be associated with high levels of psychological empowerment:
H3a: There is a positive direct relationship between the intensity with which individual
managers use a costing system for cost management and individual managers’
psychological empowerment.
In addition, as system usage allows users to experience the features of a system (DeLone and
McLean 1992; Seddon 1997), we propose that the enabling perception of a costing system will
indirectly flow through to psychological empowerment via intensity of use. That is, as a manager’s
enabling perception of a costing system increases the intensity with which the system is used, this
usage will increase the manager’s feeling of psychological empowerment. More formally, we
hypothesize the following:
H3b: There is a positive indirect relationship between individual managers’ enabling
perception of their costing systems and their psychological empowerment through the
intensity with which individual managers use a costing system for cost management.
The Performance Impacts of Costing System Use
Next, we consider the task performance impacts associated with the perception and use of
costing systems. Prior IS research suggests that system use is an important conduit through which
these systems generate both individual and organizational outcomes (Davis 1993; Straub et al.
1995; Seddon 1997). DeLone and McLean (1992, 2003), in particular, argue that without use, there
can be no observable consequences. In extending their model, Seddon (1997) also suggests that use
is not an indicator of information system success in itself, but an important variable that leads to
individual and organizational impacts. Similarly, accounting researchers argue that the success of
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accounting information systems is associated with usage (McGowan and Klammer 1997;
McGowan 1998; Chenhall 2004). Although prior research has not directly examined the
relationship between the use of accounting information systems and task performance, based on
these prior findings on the positive relationships between system usage and individual-level
impacts, we predict that the intensity of costing systems use will be associated with task
performance:
H4a: There is a direct positive relationship between the intensity with which individual
managers use a costing system for cost management and their task performance.
Prior research also suggests that an individual’s level of psychological empowerment resulting
from costing system use will be associated with task performance. Existing research on
psychological empowerment indicates that because empowered managers see themselves as
competent and able to influence their work processes in meaningful ways, they are more likely to be
proactive in the execution of their task responsibilities (Spreitzer 1995; Spreitzer et al. 1997).
Spreitzer (1995) argues that psychological empowerment increases concentration, initiative, and
resilience, and these translate into effective task performance. In particular, each of the four
dimensions of psychological empowerment has been related to a number of conditions for effective
task performance.
Meaning is said to be associated with high commitment and the concentration of energy on task
(Kanter 1983; Spreitzer 1995; Liden et al. 2000). Competence is found to be related to greater effort
exertion, high goal expectations, and persistence in challenging situations (Ozer and Bandura 1990;
Gist and Mitchell 1992; Spreitzer 1995). Self-determination has been found to result in learning,
interest in activity, and resilience (Spreitzer 1995). Impact has also been found to be associated with
absence of withdrawal from difficult situations and high task performance (Ashforth 1989; Spreitzer
1995). Consistent with these studies, we predict that the individual manager’s psychological
empowerment will be associated with task performance:
H4b: There is a direct positive relationship between individual managers’ psychological
empowerment and their task performance.
Based on our arguments underlying H3a, that costing system usage increases psychological
empowerment (Spreitzer 1995; Spreitzer et al. 1997), and the literature supporting a relationship
between psychological empowerment and task performance, as discussed earlier, we also predict
that the intensity of use will be indirectly associated with task performance through psychological
empowerment. More formally:
H4c: There is an indirect positive relationship between the intensity with which individual
managers use a costing system for cost management and their task performance, through
psychological empowerment.
RESEARCH METHODS
Sample Selection and Data Collection
The sample for this study was composed of middle-level managers. Our choice of middle-level
managers was based on prior research findings that this level of managers is interesting
theoretically, as their work varies from relatively structured to unstructured and they have access to
more resources and information (Johnson and Frohman 1989; Spreitzer et al. 1997). Given that our
study focuses on the information generated from costing systems, we felt that a sample of middle-
level managers was most appropriate. However, due to the fact that the study focuses on the
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intensity of use of costing systems, we excluded managers from accounting and finance
departments from our sample, since they are considered to be designers/preparers of cost
information.
Potential middle-level managers who were targeted for this study were drawn from a cross-
section of companies listed on the Australian Stock Exchange (ASX) and the Business ReviewWeekly (BRW) directory of the top 500 Australian private companies. Consistent with Hoque and
James’ (2000) findings that large companies are those that are likely to have adequate costing
systems, we ensured that the companies sampled in this study were sufficiently large.4 An initial
sample of 500 companies (400 listed and 100 private) was compiled. We then conducted Internet
searches to identify specific middle-level managers in those companies and the relevant postal
addresses. The Internet searches yielded a list of 474 managers out of the 500 companies initially
identified. These middle-level managers were across different functional areas, including
production managers, marketing managers, sales managers, branch/divisional managers, inventory
controllers, supply chain managers, general managers, contracts managers, commercial managers,
logistics managers, publications managers, and operations managers.
A self-administered survey instrument (including a reply paid envelop) was mailed to each of
the 474 managers in the sample. The managers were assured of anonymity and confidentiality, and
were also encouraged to complete and return the instrument within one week of receiving it. Of the
mailed survey instruments, 122 were returned undelivered because the address changed, the address
was incorrect, or the manager no longer worked for the company. In part, this is explained by the
target companies not updating staff information on their website. This left us with 352 potential
respondents. Reminder letters were sent to these 352 potential respondents four weeks after the
initial mail-out to encourage those who had not responded to do so and to thank those who had
already responded. Of the 352 managers, 74 (21 percent) responded. The 74 responses came from
across the range of middle-level managers in our target sample. Out of the 74 responses, three had
missing data and were, therefore, excluded.5 A useable sample of 71 (20.2 percent) was, therefore,
used in our analysis. These 71 respondents had a mean of 10.56 years (standard deviation¼ 7.702
years) working with their respective companies, and a mean of 2.20 years (standard deviation ¼1.879 years) working in their current roles. We compared the means of the first ten responses and
the last ten responses as a proxy for non-response bias, and there were no statistically significant
differences between the two groups across all measures (p-values range from 0.105 to 0.912, one-
tailed).6
Measurement of Variables
The constructs in this study were measured using multi-item scales (see Appendix A for the
measures used for each construct). With the exception of measures for the perception of costing
systems construct, measures for all the constructs were adapted from previous studies. Each
measure was anchored on a seven-point scale. The survey instrument resulting from these measures
was pilot tested on ten accounting academics, and they were generally satisfied with the wording
4 The Australian Securities and Investments Commission (ASIC) guidelines suggest that a corporation shouldhave at least 50 employees to be considered large. The respondents in our study all work for companies withemployee numbers greater than 50.
5 Excluding these three responses was necessary as they had data missing for a substantial number of the surveyquestions (hence, replacing these data using a statistical approach is not meaningful). Nonetheless, we repeatedour PLS analysis by replacing the missing data using the serial mean approach in SPSS. The inclusions of thereplacement data did not have any significant effect on our results.
6 In this study, we used the traditional ‘‘first-last’’ comparison to proxy for non-response bias because we are notable to identify the non-respondents and their characteristics.
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and the clarity of the questions. To be sure that we adapted these measures in a way consistent with
the spirit of the original instrument, we performed preliminary factor analysis of the items before
including them in our PLS model. The measures for each construct and the results of the
preliminary factor are discussed below.
Enabling Perception
A six-item scale was developed from Adler and Borys (1996) and Ahrens and Chapman
(2004) to measure the extent to which managers perceived their organizational costing systems as
enabling (see Appendix A).7 Cronbach’s alpha for this scale was 0.81. A principal component
analysis of the measures yielded a single factor solution with eigenvalues exceeding 1 and factor
loadings ranging from 0.622 to 0.823. This factor explained 51.65 percent of the total variance.
Intensity of Use of Costing Systems for Cost Management
A four-item scale was adapted from Chenhall (2004) to measure the intensity with which
costing systems were used for cost management (see Appendix A). Cronbach’s alpha for this scale
was 0.76. A principal component analysis of the measure revealed a single factor with eigenvalues
exceeding 1 and factor loadings ranging from 0.741 to 0.776. This factor explained 58.28 percent of
the total variance.
Psychological Empowerment
The psychological empowerment construct has four dimensions: meaning, competence, self-
determination, and impact (Spreitzer 1995). Hulland (1999) argues that when a construct is multi-
dimensional in nature, it is more appropriate to represent each dimension separately in a statistical
model. Consistent with this, we used separate scales to measure each of the four dimensions of this
construct. Three item-scales, adapted from Spreitzer (1995), were used to measure each dimension.
Cronbach’s alphas for the four dimensions of psychological empowerment range from 0.76 to 0.95.
We conducted a principal components analysis of all the measures and they loaded strongly on the
various dimensions they were meant to represent, with eigenvalues exceeding 1. The four factor
solution accounted for 86.1 percent of the total variance with meaning (with factor loadings from
0.856 to 0.910) contributing 29.0 percent, competence (with factor loadings from 0.613 to 0.833)
accounting for 13.5 percent, self-determination (with factor loadings from 0.814 to 0.889)
contributing 20.5 percent, and impact (with factor loadings from 0.860 to 0.903) accounting for
23.1 percent.
Task Performance
We measured task performance using a six-item scale adapted from Kathuria and Davis (2001).
We used a subjective measure of task performance for two main reasons. First, prior research has
established that accurate estimates of ‘‘objective measures’’ are difficult to obtain in survey research
due to the confidential nature of the data and variance among firms with regard to accounting
procedures (Dess and Robinson 1984). Second, prior accounting research suggests that subjective
measures are not worse than objective measures in survey studies (Abernethy and Stoelwinder
1991). Cronbach’s alpha for this construct was 0.83. A principal component analysis of these
measures yielded a single factor solution with eigenvalues exceeding 1 and factor loadings ranging
from 0.538 to 0.805. This factor accounted for 55.55 percent of the total variance.
7 We modeled this as a single construct because we are interested in the overall perception of enabling, which is incontrast to Chapman and Kihn (2009), who were concerned with the design principles of the system.
The Effect of Managers’ Enabling Perceptions on Costing System Use 99
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Descriptive Statistics and Control Variables
In addition to the primary constructs of interest to this study, we collected information about
the industry groupings of the respondents’ companies, the relative size of their companies, and the
respondents’ experience (with the company and also in their current role). We included these
variables in our statistical model to partial out their effects on our dependent variables. For the
industry grouping factor, construction/property development, manufacturing, and wholesale, retail,
and distribution had the highest representation among the survey respondents. Table 1 shows the
industry groupings of the 71 respondents. To include the industry grouping variable in our
statistical model, we coded construction/property development as 2, and all other industry groups as
1. The data were split between construction/property development and all other industry groups
because construction represented one of the largest groups represented in our sample (with 12
respondents), and we wanted to be sure that the results were not driven by that industry. We
repeated this grouping by replacing the construction/property industry with the other industries with
more than ten respondents and ran separate models for each grouping, and the results were
unchanged.
We used number of employees as proxy for size. The respondents’ years of experience with the
company and their years of experience in their current role were also included as proxies for
experience. The statistical results show that none of these control variables were significantly
related to our dependent variables.8
RESULTS
We analyzed the data gathered using the partial least squares (PLS) approach to structural
equation modeling (SEM). PLS is a component-based modeling approach that seeks to maximize
TABLE 1
Industry Groupings
Industry Frequency Percentage
Construction/Property Development 12 16.9%
Engineering 2 2.8%
Financial Services 9 12.7%
Health Care 3 4.2%
Hospitality 3 4.2%
Logistics/Transportation 3 4.2%
Manufacturing 11 15.5%
Media 3 4.2%
Mining 7 9.9%
Utilities 3 4.2%
Wholesale, Retail, Distribution 12 16.9%
Other 3 4.2%
Total 71 100.0%
8 To improve the clarity of our model presentation, we did not include these control variables in our diagram inFigure 2. The control variables were, however, included in our statistical model, and their relationships with ourprimary variables of interest were not statistically significant.
100 Mahama and Cheng
Behavioral Research In AccountingVolume 25, Number 1, 2013
the variance explained and to minimize error. It is able to examine theory (structural model) and
measures (measurement model) simultaneously. The benefit of using PLS is its ability to handle
small sample size, as it does not make any distributional assumptions about the data. Given our
useable sample of 71, we considered PLS to be the most suitable approach. Chin and Newsted
(1999) argue that the minimum sample size for PLS modeling should be ten times of the part of the
model that requires the largest multiple regression. In our model, the largest multiple regression has
six independent variables, which implies a minimum sample size of 60. Our sample size of 71 is,
therefore, adequate for PLS modeling.
Since PLS makes no distributional assumptions about the data being analyzed, fit indices
generally associated with covariance-based structural equation modeling are not appropriate (Chin
1998; Hulland 1999). Rather, the R2 is considered adequate in assessing the stability of the model.
Also, because of the distribution-free assumption of PLS, parametric-based approaches to
significant testing are not possible. Instead, bootstrapping resampling is used to test the significance
of factor loadings and path coefficients. In this study, we used PLS-Graph software (version 3.0) to
simultaneously estimate the measurement and structural models. The results are discussed below.
Discussion of the Measurement Model
The measurement model estimates the relationship between scale measures (manifest variables)
and the constructs they represent (latent variables). This involves the estimation and evaluation of
the reliability (individual item and composite reliabilities) and validity (convergent and
discriminant validities) of the measurement model. The individual item reliability, composite
reliability, convergent validity, and descriptive statistics of our final measurement model are
summarized in Table 2.
Individual item reliability is assessed by examining the factor loading of each scale item to the
construct to which it relates. While factor loadings of 0.70 and above are recommended in the PLS
literature, Hair et al. (2010) argue for sample size to be taken into account in the interpretation of the
significance of factor loadings. For our sample size of 71, minimum factor loading of 0.65 is
required to obtain a power level of 80 percent and 0.05 significance level. In our measurement
model, all items loaded significantly (p , 0.001, one-tailed) to the respective constructs except
CS2.9 CS2 (with loadings of�0.6102, p . 0.1, one-tailed) was, therefore, excluded from the final
measurement model. Nunnally (1978) suggests that composite reliability should be 0.7 or higher for
a construct to demonstrate adequate composite reliability. The composite reliability for all the
constructs in our model ranges from 0.848 to 0.970, indicating adequate composite reliability.
Convergent validity measures the extent to which scale items for each construct are correlated.
This is assessed using the average variance extracted (AVE). Adequate convergent validity is
demonstrated by AVE measure of 0.5 or more (Chin 1998; Hulland 1999). As reported in Table 2,
the AVEs for all the constructs in our model were more than 0.5, which provides evidence of
adequate convergent validity. Finally, we assessed discriminant validity by comparing the square
roots of the AVEs of the constructs to the correlation coefficient between constructs (Chin 1998;
Hulland 1999). Table 3 reports the correlation coefficients in the off-diagonal, and the square roots
of the AVEs in the diagonal. All the square roots of the AVEs are greater than the correlation
coefficients, and that indicates adequate discriminant validity. The above analyses and evaluations
indicate that our measurement model is satisfactorily reliable and valid.
9 CS2 asks the following question: ‘‘I feel that the costing system is designed with the aim of monitoring how Icomply with company procedures (R).’’ The failure of CS2 (which focuses on monitoring) to load significantlysupports our view that the costing system is an information system.
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Common Method Bias
Given that we collected data through self-reported survey, there is the potential for the
responses to be affected by common method bias. While our research design did not have adequate
procedural remedies for minimizing the effects of this bias, we performed three statistical analyses
to assess whether common method bias was likely to be a serious concern. First, we performed
Harman’s single-factor test, in which measures representing the constructs in our model were
entered into an unrotated exploratory factor analysis (Podsakoff et al. 2003). Results from the factor
TABLE 2
Reliability and Convergent Validity (AVE)
Latent Variable Mean SD Loading t-statistics
Enabling Perception of Costing Systems (composite reliability ¼ 0.853; AVE ¼ 0.539)
CS1 4.718 1.416 0.7406 4.3096
CS3 3.113 1.508 0.6910 5.1383
CS4 4.789 1.548 0.8872 9.4090
CS5 3.697 1.443 0.6850 3.9546
CS6 4.296 1.616 0.6441 3.4929
Intensity of Use (composite reliability ¼ 0.848; AVE ¼ 0.583)
CMAN1 5.239 1.497 0.7548 8.7056
CMAN2 4.634 1.684 0.7664 12.1667
CMAN3 5.535 1.350 0.7542 7.9761
CMAN4 5.366 1.417 0.7774 7.9227
Meaning (composite reliability ¼ 0.961; AVE ¼ 0.890)
MEAN1 6.197 0.821 0.9051 24.9228
MEAN2 6.141 0.816 0.9542 56.4020
MEAN3 6.183 0.780 0.9701 87.1064
Competence (composite reliability ¼ 0.884; AVE ¼ 0.723)
COMP1 6.324 0.713 0.9178 27.3853
COMP2 6.183 0.743 0.9416 37.8444
COMP3 5.507 1.054 0.6623 6.7017
Self-Determination (composite reliability ¼ 0.918; AVE ¼ 0.789)
SELF1 5.803 1.023 0.8587 17.8500
SELF2 5.690 1.022 0.8908 25.7556
SELF3 5.704 1.020 0.9155 24.1572
Impact (composite reliability ¼ 0.970; AVE ¼ 0.916)
IMPACT1 6.028 0.985 0.9627 55.3168
IMPACT2 5.746 1.105 0.9352 22.6404
IMPACT3 5.915 1.105 0.9726 67.2285
Task Performance (composite reliability ¼ 0.879; AVE ¼ 0.549)
PERF1 5.451 0.824 0.7611 9.6736
PERF2 5.549 0.968 0.6233 5.4557
PERF3 5.563 0.857 0.8311 19.0270
PERF4 5.113 1.090 0.7340 8.2885
PERF5 5.380 1.100 0.7884 13.9832
PERF6 5.211 1.206 0.6914 7.2616
All item loadings are statistically significant (p , 0.001, one-tailed).
102 Mahama and Cheng
Behavioral Research In AccountingVolume 25, Number 1, 2013
analysis yielded a seven-factor solution (corresponding to the seven constructs in our model), and
the most covariance explained by one factor was 27.85 percent, indicating that common method
bias is unlikely to be a serious concern.
Second, we followed the procedures outlined in Liang et al. (2007) to implement the single
unmeasured method factor design in our PLS model. This approach focuses on partialing out the
error variance at the indicator level in order to eliminate their effects on the structural model (Chin
et al. 2012). We created a common method factor from all the measures for our substantive (main)
constructs in our model and included in our PLS model (see Liang et al. [2007] for detail
procedure). To include the common method factor, we modeled each measure as a single-indicator
latent variable (first-order construct), and the substantive construct as a second-order construct of
their respective single-indicator variables. We then included the common method factor in the PLS
model with links to all the single-indicator variables in the model. The path coefficient between the
single-indicator variables and the constructs (substantive constructs and the common method factor)
are interpreted as the factor loadings. We assessed the results of the PLS test by (1) examining the
statistical significance of factor loadings on both the substantive constructs and the common method
factor, and (2) comparing the percentage variance of each single-indicator variable explained by its
substantive construct and by the method factor.
As shown in Table 4, loadings on the method factor are insignificant (except for two items),
and the percentage of the variances of the indictor variables explained by the substantive construct
(average variance ¼ 0.679) is substantially greater than the percentage variances explained by the
common method factor (average ¼ 0.013), thus providing evidence that common method bias is
unlikely to be a serious concern for this study (Liang et al. 2007). Also, the results of the PLS
structural model (when the common method factor is included) are similar to those of the base
model (see Appendix B).
Third, we implemented the marker variable method suggested by Chin et al. (2012). While
the single unmeasured method factor design focuses on partialing out the effect of common
method bias at the indicator level, Chin et al. (2012) call for controlling for this bias at the level of
the structural model. This approach requires measured indicators for the marker variables to be
included in the PLS model, and these indicators should not be correlated with the indicators
measuring the substantive constructs of the study except for the correlation caused by common
method bias. Our research instrument had some additional indicators that were not measuring the
substantive constructs of our study, so we assessed the correlation between these indicators and
TABLE 3
Discriminant Validity
EnablingPerception
Intensityof Use Meaning Competence
Self-Determi-
nation ImpactTask
Performance
Enabling Perception 0.734
Intensity of Use 0.506 0.764
Meaning 0.126 0.243 0.943
Competence 0.032 0.202 0.609 0.850
Self-Determination �0.023 0.143 0.288 0.398 0.888
Impact 0.106 0.365 0.544 0.427 0.469 0.957
Task Performance 0.117 0.135 0.399 0.512 0.353 0.240 0.741
Diagonal elements are square roots of AVE; off-diagonal elements are correlations between constructs.
The Effect of Managers’ Enabling Perceptions on Costing System Use 103
Behavioral Research In AccountingVolume 25, Number 1, 2013
those measuring our substantive constructs. Three of the indicators were minimally correlated
with the indicators of our substantive constructs; hence, we used these three indicators to form our
marker variable. We included the marker variable in our PLS model as an independent variable
predicting each of our dependent variables. We then compared the results of the model with the
marker variable (see Appendix C) with our base model to determine whether the path coefficients
that were significant in our base model will become insignificant after the inclusion of the marker
variables. All the paths that were significant in the base model remained after including the
marker variable, thus providing further evidence that common method bias is not a serious
concern for this study.
As the three analyses we performed suggest that common method bias is not likely to be a
serious concern, we proceed to discuss only the PLS structural model results for our base model.
TABLE 4
Common Method Bias Analysis
Construct Indicator
SubstantiveFactor Loading
(R1) R12
MethodFactor Loading
(R2) R22
Enabling Perception of Costing Systems CS1 0.646*** 0.417 0.170 0.029
CS3 0.768*** 0.590 �0.121 0.015
CS4 0.834*** 0.695 0.058 0.003
CS5 0.756*** 0.571 �0.021 0.000
CS6 0.688*** 0.473 �0.099 0.010
Intensity of Use CMAN1 0.763*** 0.581 0.005 0.000
CMAN2 0.768*** 0.591 0.012 0.000
CMAN3 0.719*** 0.517 0.054 0.003
CMAN4 0.803*** 0.644 �0.069 0.005
Meaning MEAN1 0.906*** 0.821 0.003 0.000
MEAN2 0.993*** 0.987 �0.051 0.003
MEAN3 0.931*** 0.867 0.047 0.002
Competence COMP1 0.814*** 0.662 0.132 0.017
COMP2 0.893*** 0.797 0.061 0.004
COMP3 0.875*** 0.766 �0.269 0.072
Self-Determination SELF1 0.849*** 0.721 0.030 0.001
SELF2 0.935*** 0.873 �0.082 0.007
SELF3 0.883*** 0.780 0.051 0.003
Impact IMPACT1 0.881*** 0.777 0.099** 0.010
IMPACT2 0.928*** 0.861 �0.112 0.013
IMPACT3 0.965*** 0.932 0.009 0.000
Task Performance PERF1 0.919*** 0.845 �0.207 0.043
PERF2 0.372*** 0.138 0.265** 0.070
PERF3 0.747*** 0.557 0.093 0.009
PERF4 0.859*** 0.738 �0.134 0.018
PERF5 0.731*** 0.534 0.094 0.009
PERF6 0.773*** 0.598 �0.052 0.003
Average 0.815 0.679 �0.001 0.013
**, *** p , 0.05 and p , 0.01, respectively.
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Behavioral Research In AccountingVolume 25, Number 1, 2013
Discussion of the Structural Model
We used the PLS structural model to test the hypothesized relationships between the
constructs in our theoretical model. Table 5 and Figure 2 provide summaries of results for the
structural model. In Table 5, direct relationships are shown in Panel A and indirect relationships
are shown in Panel B.
TABLE 5
PLS Results
Panel A: Path Coefficient, t-statistics (in parentheses), and R2 PLS Results
Latent Variable
Path to:
R2Intensity
of Use Meaning CompetenceSelf-
Determination ImpactTask
Performance
Enabling
Perception
0.506 0.004 �0.093 �0.128 �0.105 —
(3.8268)*** (0.0215) (0.5311) (0.6700) (0.6480)
Intensity
of Use
0.241 0.249 0.207 0.417 �0.051 0.26
(1.6471)* (1.7761)** (1.3306)* (4.0329)*** (0.3787)
Meaning 0.197 0.06
(1.2823)
Competence 0.363 0.05
(2.8757)***
Self-
Determination
0.228 0.03
(1.7287)**
Impact �0.121 0.14
(0.6974)
Task
Performance
0.34
Panel B: Indirect Effects and Bootstrap Confidence Intervals (in parentheses)a
Latent Variable Linkages
Path to:
Meaning CompetenceSelf-
Determination ImpactTask
Performance
Enabling
Perception
Intensity
of Use
0.122 0.126 0.105 0.212
(0.0027 �0.2846)*
(0.0066 �0.2703)*
ns (0.0621 �0.3813)**
Intensity
of Use
Competence 0.10
(0.0047 �0.2087)*
Self-
Determination
0.05
ns
*, **, *** p , 0.10, p , 0.05, and p , 0.01, respectively, one-tailed.n ¼ 71a We used the bootstrap confidence level as proposed in Hayes (2009) to determine the significance of indirect effects.
The Effect of Managers’ Enabling Perceptions on Costing System Use 105
Behavioral Research In AccountingVolume 25, Number 1, 2013
H1 predicted a positive relationship between managers’ enabling perceptions of their costing
systems and the intensity with which costing systems are used for cost management. The PLS
structural path coefficient for this was significant (p , 0.01) and in the hypothesized direction.
This suggests that managers who perceive their organizations’ costing systems to be enabling are
more likely to use the system more intensively in their cost management practices. The highly
significant result and the relatively large coefficient (0.506) are consistent with our expectation
that managers’ enabling perceptions have important impacts on their behaviors. Thus, H1 is
supported.
We also predicted that enabling perception has both a direct impact and an indirect impact (via
intensity of use) on managers’ psychological empowerment (H2 and H3b, respectively). The
structural paths between enabling perception and all four dimensions of psychological
empowerment were not significant, suggesting that there is no direct relationship between enabling
perception and psychological empowerment. Thus, H2 is not supported. However, we found that
enabling perception was significantly indirectly related to one dimension of psychological
empowerment (impact ¼ 0.212, p , 0.05), and marginally indirectly related to two dimensions
(meaning¼ 0.122, p , 0.10, and competence¼ 0.126, p , 0.10) through the intensity with which
these managers use their organizations’ costing systems for cost management (see Panel B, Table
5), providing support for H3b.
The intensity with which costing systems are used for cost management was hypothesized to be
positively related to managers’ psychological empowerment (H3a). The structural path coefficients
between intensity of use and the meaning (0.241) and competence (0.249) dimensions were
FIGURE 2PLS Structural Model with Path Coefficients
*,**,*** p , 0.10, p , 0.05, and p , 0.01, respectively, one-tailed.
n¼ 71.
106 Mahama and Cheng
Behavioral Research In AccountingVolume 25, Number 1, 2013
significant at the 0.05 level. The path coefficient between intensity of use and self-determination(0.207) was only marginally significant at the 0.10 level, while the path leading from intensity of use
to impact (0.417) was significant at the 0.01 level. H3a is, therefore, supported. Taken together, the
insignificant result for H2 and the significant support for H3a and H3b are consistent with DeLone
and McLean’s (1992) argument that usage is an important conduit through which the effect of an
information system can be experienced by individuals. In our study, psychological empowerment
only increases when managers experience their costing systems through intensive usage.
Next, we examine the performance impact of the costing system. Our model predicted that
psychological empowerment is positively associated with task performance (H4b), and that the
intensity of use has an indirect effect on task performance (via psychological empowerment, H4c).
As shown in Table 5 (Panel A) and Figure 2, H4b was partially supported. The paths leading from
competence (0.363, p , 0.01) and self-determination (0.228, p , 0.05) to task performance were
significant. However, the paths from meaning and impact were not significant.
Drawing conclusions on insignificant paths is difficult, but prior findings by Hall (2008)
allow us to speculate on the reasons for the partial support we find for H4b. As noted earlier,
Spreitzer (1995) contends that an individual’s work context influences psychological
empowerment. Our results for the paths linking psychological empowerment to performance
and the results from Hall (2008) suggest that the differences in contexts of use and purposes for
accounting systems may explain which dimension of psychological empowerment will be salient
in explaining performance. While we find that paths leading from competence and self-determination are significantly related to task performance in the context of costing systems use,
Hall (2008) found only the meaning dimension to be significantly related to managerial
performance in the context where comprehensive performance measurement systems (CPMS) are
used. We speculate that in the context of costing systems, the emphasis is on using cost
information for actions and decision making (e.g., using cost information for budgeting); this
could be a possible explanation underlying the strength of the relationship between the
competence and self-determination dimensions of psychological empowerment and task
performance. In contrast, the significant emphasis on providing performance feedback in CPMS
and the stronger link between CPMS and strategy could be reasonable explanations of the
importance of the meaning dimension in explaining managerial performance in Hall (2008).10
Neither Hall (2008) nor our study find significant results for the impact dimension; again, we can
only speculate that the performance effects of the impact dimension may be less salient when it
comes to certain accounting information systems. These speculations are worth examining in an
empirical setting.
While there was no significant direct relationship between the intensity of use of costing
systems for cost management and task performance (H4a), we found a significant indirect
relationship through the competence dimension of psychological empowerment (see Panel B, Table
5). Our results, thus, provide support for H4c, which suggests that intensity of use does not impact
directly on task performance, but rather, it acts through the psychological empowerment
experienced by the managers. Also, competence, which relates to an individual’s beliefs about
his or her capabilities in performing an activity, appears to play a particularly important role in the
model. The empirical results provide partial support for our theoretical model. The empirics suggest
that enabling perceptions strengthen managers’ beliefs about their own abilities via increased usage
of the system and, in doing so, allow managers’ enabling perceptions to ultimately influence their
task performance.
10 We should also note that Hall’s (2008) model focuses on managerial performance rather than taskperformance.
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DISCUSSION AND CONCLUSION
In this study, we aim to provide an understanding of how the enabling perceptions managers
hold about their costing systems affect the intensity of use of the system for cost management,
psychological empowerment, and task performance. Our focus is on the end users, rather than the
designers of costing systems. Although managers’ enabling perceptions are likely the result of
specific system design features,11 the direct examination of the role of managerial perception is
important because individuals’ behavior is largely based on how they perceive a system (Burney et
al. 2009). We found that the extent to which a costing system is viewed as enabling is positively
associated with the intensity with which the system is used by managers. The intensity of use, in
turn, is associated with all four dimensions of psychological empowerment experienced by the
managers and, finally, through an increased feeling of competence, indirectly related to task
performance.
Our findings have a number of theoretical implications. First, while prior literature has investigated
the technical factors associated with costing system design choices and the behavioral implications of
the implementation process, our study takes a different perspective and explores the psychological
properties of a costing system associated with its usage. We show that managers’ perceptions of a
costing system as enabling have a significant, but indirect, impact on task performance. In doing so, we
highlight that an understanding of costing system effectiveness can be achieved by considering its
characteristics as perceived by the user managers, in addition to its technical characteristics. Further,
these results also help clarify the ‘‘broad leaps of logic’’ (Chenhall 2003, 132) from positive perceptions
of an enabling costing system to positive task performance implications, via its usage. The implications
of this finding go beyond costing system design. The impact of enabling perception likely extends to
other accounting information systems, such as performance management systems, budgeting and
forecasting systems, and nonfinancial reporting systems.
Second, prior literature has demonstrated that both the intensity of use and psychological
empowerment are important considerations when implementing accounting information systems
(e.g., Chenhall 2004; Drake et al. 2007; Hall 2008). In the present study, we show that enabling
perception of a costing system is an antecedent to these variables. Our findings are consistent with
Delone and McLean’s (1992, 2003) model, which argues for the importance of meaning of an IS
system to the users (semantic level variables) when examining system successes, and how such
perceptions then flow through to impact on individuals’ task performance.
Third, in our model, competence stands out as a critical dimension of employee empowerment.
While enabling perception indirectly affects three out of the four empowerment dimensions via
intensity of use (meaning, competence, and impact), the competence dimension is the main
dimension through which the intensity of use affects task performance. Our result, therefore,
indicates the importance of studying the concept of employee empowerment as four distinctive, but
related, dimensions.
Our study also has practical implications. Our findings demonstrate that building managers’
enabling perceptions is important given its effects on costing system usage, psychological
empowerment, and task performance. Although the enabling perception relates to how a system is
used rather than the technical characteristic of a system (Ahrens and Chapman 2004), there are a
number of ways in which designers of costing systems can influence managers’ enabling
perceptions. Prior literature has suggested that designers of an accounting system can generate an
11 Although managers’ perception of a system as enabling is likely the result of the design principles behind thecosting system, the current study focuses on managers’ perceptions. Consistent with prior literature, we arguethat, ultimately, it is how the managers view their work environment that is critical to organizationalconsequences (Spreitzer 1996; Leigh et al. 1988).
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Behavioral Research In AccountingVolume 25, Number 1, 2013
enabling perception by ‘‘unlocking’’ the system; for example, through communicating the logic of
the costing system to the user managers, or incorporating functions that allow user managers to
update the formula, information, and measures contained in the costing system as the operation
environment changes (Ahrens and Chapman 2004). Designers of costing systems can also enhance
the enabling perception of a costing system by improving the internal transparency of the work
processes, allowing managers broader access and linkages to other departments’ systems, and
allowing users more flexibility with respect to customizing their reports from the costing systems
(Ahrens and Chapman 2004).
Our findings should be interpreted in the light of four limitations. First, while our response rate
and sample size are considered acceptable, our study would have benefited from a stronger response
from the intended survey participants. While the sample size is adequate for testing our hypotheses, it
limits the extent to which our results can be generalized to the larger population. Second, the research
design would have benefited from an explicit definition of what we meant by costing systems and to
determine how relevant these systems were to the roles performed by the respondents. While this can
be a potential concern, the additional comments provided as part of responses to our survey questions
provide us with confidence that the respondents’ understanding of costing systems is consistent with
what we intended, and that they encounter these systems in their specific roles. Third, the present
study focuses on examining the impact of managers’ enabling perceptions of the costing system,
rather than its technical aspects. However, an interaction may possibly exist between managers’
perceptions about the costing system and its technical design. For example, managers may be more
willing to use a costing system that is seen as enabling if it is technically sound (i.e., provides more
accurate and relevant information in a timely manner) than if the costing system is technically
deficient. Nonetheless, past literature suggests that, ultimately, the subjective perception of the users
of information systems, such as costing systems, may impact behavior (Spreitzer 1996; Burney et al.
2009). Finally, our paper would have benefited from using more than three item-measures for each of
the dimensions of psychological empowerment. While we do not consider this as a serious concern
(given that our ultimate dependent variable and almost half of the constructs in our model have a
sufficient number of items), we believe that future research will benefit from a sufficiently large
number of items to measure each of the dimensions of the construct.
Further research can extend our study in a number of ways. First, as discussed earlier, we have
focused our attention on managers’ perceptions of the costing system, rather than its technical
functions. Future research can explore the interactive nature of the technical, semantic, and
influence levels of costing system designs. For example, researchers can investigate whether the
effect of the enabling perception may be moderated by the sophistication of the costing system. In
addition, future research can also extend our proposed framework to examine other individual-level
and organizational-level impact variables.
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APPENDIX A
MEASURES FOR SUBSTANTIVE CONSTRUCTS
1. Enabling Perception of Costing Systems
The following scale items ranged from 1 (strongly disagree) to 7 (strongly agree):
CS1: I feel that the costing system is designed with the aim of enabling me to work more efficiently.
CS2: I feel that the costing system is designed with the aim of monitoring how I comply with
company procedures (R).
CS3: I feel that the costing system is designed with the aim of facilitating how I deal with
unanticipated work problems.
CS4: I feel that the costing system is designed with the aim of improving the visibility I have over
the work I am responsible for.
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CS5: I feel that the costing system is designed with the aim of enhancing the flexibility with which I
perform my job.
CS6: I feel that the costing system is designed with the aim of allowing me to understand the
broader processes within my company.
2. Intensity of Use of Costing Systems for Cost Management
To what extent do you use your organization’s costing system to facilitate the following (the
following scale items ranged from 1 [lesser extent] to 7 [greater extent]):
CMAN1: Cost reduction and modeling
CMAN2: Reengineering and improvement
CMAN3: Budgeting
CMAN4: Performance measurement
3. Psychological Empowerment
The following scale items ranged from 1 (strongly disagree) to 7 (strongly agree):
3.1. Meaning
MEAN1: The work I do is very important to me.
MEAN2: My job activities are personally meaningful to me.
MEAN3: The work I do is meaningful to me.
3.2. Competence
COMP1: I am confident about my ability to do my job.
COMP2: I am self-assured about my capabilities to perform my work activities.
COMP3: I have mastered the skills necessary for my job.
3.3. Self-Determination
SELF1: I have significant autonomy in determining how I do my job.
SELF2: I can decide on my own how to go about doing my work.
SELF3: I have considerable independence and freedom in how I do my job.
3.4. Impact
IMPACT1: I have a large impact on what happens in my department.
IMPACT2: I have a great deal of control over what happens in my department.
IMPACT3: I have significant influence over what happens in my department.
4. Task Performance
How satisfied are you with your performance on the following (the following scale items
ranged from 1 [not satisfied] to 7 [very satisfied]):
PERF1: Accuracy of work performed
PERF2: Quantity of work performed
PERF3: Quality of work performed
PERF4: Operating efficiency
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PERF5: Customer satisfaction
PERF6: Timeliness in meeting delivery schedules
APPENDIX B
PLS Structural Model (with Latent Common Method Factor Included) Results
Latent Variable
Path to:Path Coefficient and t-statistics (in parentheses)
R2Intensity of
Use Meaning CompetenceSelf-
Determination ImpactTask
Performance
Enabling
perception
0.480 0.0276 �0.108 �0.125 �0.122
(4.5364)*** (0.1979) (0.8235) (0.7468) (1.0065)
Intensity
of Use
0.256 0.251 0.203 0.419 0.044 0.23
(1.8553)** (1.8524)** (1.3748)* (4.0444)*** (0.3529)
Meaning 0.216 0.06
(1.2467)
Competence 0.331 0.05
(2.6003)***
Self-
Determination
0.232 0.03
(1.8128)**
Impact �0.127 0.14
(0.7800)
Task
Performance
0.32
*, **, *** p , 0.1, p , 0.05, and p , 0.01, respectively.
APPENDIX C
PLS Structural Model (with Marker Variable Included) Results
Latent Variable
Path to:Path Coefficient and t-statistics (in parentheses)
R2Intensity
of Use Meaning CompetenceSelf-
Determination ImpactTask
Performance
Enabling
Perception
0.429 0.017 �0.082 �0.144 �0.111 —
(3.0592)*** (0.0905) (0.4942) (0.7604) (0.7294)
Intensity
of Use
0.282 0.264 0.172 0.373 0.036 0.27
(1.9072)** (1.7665)** (1.3848)* (3.3803)*** (0.2768)
Meaning 0.259 0.06
(1.2670)
Competence 0.375 0.06
(3.0323)***
Self-
Determination
0.222 0.08
(1.6513)**
Impact �0.174 0.17
(0.9915)
Task
Performance
— 0.34
*, **, *** p , 0.1, p , 0.05, and p , 0.01, respectively.
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