2. 1. Introduction
The purpose of this study is to examine the enablers of top management team (TMT) members' support
for integrated management control systems (MSC) innovations. Since Johnson and Kaplan's (1987)
publication of “Relevance Lost: the Rise and Fall of Management Accounting”, there has been significant
attempts at innovating management accounting techniques and controls with the view to regaining practical
relevance. More recently, management control innovations have focused on leveraging existing controls by
taking advantage of the generative, analytical, and integrative capacity of information technology (IT) to
develop integrated management control systems (Rom and Rohde, 2006; Williams and Williams, 2007;
Grabski et al., 2011). The focus on “integrated” MCS rather than isolated MCS stems from the well-established
view in management accounting literature that the management control systems of organisations do not
operate in isolation; rather they are interrelated and work as a package (Otley, 1980; Dent, 1990; Chenhall,
2003; Malmi and Brown, 2008). The central issue in packaging controls through IT-based innovations is their
ability to provide useful information through combining complementary management controls as a package.
While in principle these innovations offer significant transformative capacities in the management control of
organisations, research indicates that there is lower than expected adoption and implementation of these
innovations (Granlund, 2011). The existing literature suggests that the lower uptake of these innovations is
due to lack of top management team (TMT) support. Consequently, this paper focuses on examining the
factors that drive TMT support for integrated MCS innovations.
Prior studies indicate that the role of TMT support is crucial for the successful adoption, implementation
and use of MCS innovations. For instance, in contingency-based research, TMT leadership and support is one
of the important organisational contingencies that determine the design and use of various MCS innovations
(see for example, Cotton et al., 2003; Cavalluzzo and Ittner, 2004; Chenhall, 2004). Similarly, the strategic
management literature highlights the important role that TMT plays in the design and use of MCS (Carpenter
et al., 2004; Wilkin and Chenhall, 2010).2
This line of research attributes the positive relationship between
TMT support and the deployment of MCS to the authority and power inherent in TMT (Hambrick and Mason,
1984; Abernethy et al., 2010). Support by TMT is crucial as that determines the sufficiency of resources (such
as finances, time, information and human resources) committed to MCS innovations (Anderson and Young,
1999; Chenhall, 2004; Naranjo-Gil and Hartmann, 2007) and also signals to organisational members what top
managers consider strategically important to delivering outcomes.
Given the importance of TMT support for MCS innovation, most prior studies assume that such support
will flow naturally and almost certainly for MCS innovation in all cases. Contrary to this, some existing
research suggests that the nature and form of TMT support for MCS innovations are built over time and
depend on several cognitive, psychological, and contextual factors (Hambrick et al., 1993; Lewis et al., 2003).
Recent studies also show that the level of TMT support for MCS innovations varies across organisations
(Anderson and Young, 1999; Liang et al., 2007). This evidence implies that rather than taking TMT support for
MCS innovations as a given, it is essential to investigate and understand the enablers of the support. In doing
so, this will enhance the theoretical and empirical links between their assumed reasons of existence and their
impact on MCS innovations (Shields and Shields, 1998; Chenhall, 2003; Luft and Shields, 2003). Identifying
the enablers of TMT support for MCS innovation will also help future research to build and test richer research
models that link the antecedents of TMT support for MCS to organisational choices and outcomes.
This study makes several contributions to the current MCS literature. The study opens the black box of
TMT support for MCS innovations by building and testing a richer model of the drivers of TMT support for MCS
innovations. From a pragmatic standpoint, this study informs practitioners and consultants on how to
generate TMT support for MCS innovations. By knowing these factors, organisations will be able to enhance
them and achieve higher TMT support for integrated MCS innovation.
The structure of the remainder of the paper is as follows. The following section presents the theoretical
development of the research model and hypotheses. An overview of the methodology, operationalization of
constructs, data analysis, and discussion of results follow. We conclude with a discussion of limitations and
implications of the findings for practice and future research.
2
Upper echelon literature argues that organisations do not make choices but they are the reflection of its top managers who make
those choices and decisions (Hambrick and Mason, 1984).
2 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
3. 2. Literature review and hypotheses development
2.1. The concept of TMT support
MCS have evolved over time since Johnson and Kaplan's (1987) book entitled “Relevance Lost: the Rise
and Fall of Management Accounting”. Johnson and Kaplan (1987) recognised that traditional management
accounting procedures used at that time had lost their relevance to manager's planning, control, and decision
making as management accounting had failed to keep pace with changes in the organisational landscape, and
were often “too late, too aggregated and too distorted to be relevant for planning, decision making and
control” (Johnson and Kaplan, 1987, p. 1). For management accounting to be relevant and applicable for
management control in organisations, management accounting processes need to keep pace with the
changing and evolving information and control needs of organisations (Johnson and Kaplan, 1987). Johnson
and Kaplan (1987) argued that the relevance of management accounting and control systems should be
regained by capitalising on significant developments in information technology, which can enable an
expansion of organisational information gathering and processing capabilities. These technological
developments have granted management accounting researchers and practitioners the foundation to explore
possibilities for improving the relevance of management control systems.
The combination of Johnson and Kaplan's (1987) call for relevance and advances in information
technology has led to the development of a number of MCS innovations; including activity-based cost
management (ABC/M), performance measurement systems (PMS), activity-based budgeting (ABB) and
beyond budgeting (Kaplan and Norton, 1992; Anderson and Young, 1999). A more recent innovation is the
integrated MCS which employs information technology (IT) paradigms to combine several standalone MCS
innovations to generate reports for cybernetic controls (Elbashir et al., 2011). By facilitating such integration
and allowing organisations to use them as a multifarious package, integrated MCS innovations further amplify
the capabilities of these MCS innovations (Williams, 2004, 2008). Once integrated MCS innovations are
connected to the organisational central databases, they can draw on broad-scale data to deliver an expanded
set of relevant, accurate and timely management accounting information (Howard, 2003; Brignall and
Ballantine, 2004; Williams, 2004, 2008). For instance, information generated by ABC/M can be fed into ABB, and
be used as an input for BSC simultaneously. As such, integrated MCS innovations are able to deliver an extensive
set of business analytics, key performance indicators, and pre-built management metrics and reports (Howard,
2003; Williams, 2004, 2008).3
Thus, integrated MCS innovations are increasingly valued for their provision of
management control reports and information, which improves management decision making across the value
chain and enhances the performance of a range of business processes (Elbashir et al., 2008).
While in principle the benefits of various MCS innovations are obvious, studies over the past ten years have
found that in practice the adoption rates of various MCS innovations are relatively low (Chenhall, 2004; Nixon
and Burns, 2012). For instance, Hendricks et al. (2012) show that only 23.5% of Canadian firms across a range of
industries adopted the balanced scorecard (BSC). These findings are inconsistent with the value-enhancing
evidence cited in the MCS innovation literature. Consequently, this line of research has prompted researchers
to examine the drivers of successful adoption, implementation and use of MCS innovations. In doing so,
TMT support is often identified as one of the, if not the most, important success factors for MCS innovations
(e.g., Shields, 1995; Anderson and Young, 1999; McGowan and Klammer, 1997; Krumwiede, 1998).
Top management team (TMT) is defined in prior literature as a group of the most influential senior
executives, such as the Chief Executive Officer (CEO), Chief Operating Officer (COO), and Chief Financial
Officer (CFO), with an overall responsibility for the organisation (Hambrick and Mason, 1984; Armstrong and
Sambamurthy, 1999; Henri, 2006). TMT are heavily involved in the strategic decision making of organisations
(Simons et al., 1999; Collins and Clark, 2003), and plays a significant role in influencing the organisational
strategies, choices and outcomes (Hambrick and Mason, 1984; Carpenter et al., 2004). It is partly the
influential role of TMT that leads researchers to argue that the support TMT offers is crucial to adoption,
implementation and use of MCS innovations. Despite the overwhelming evidence on the role of TMT in MCS
innovation success, their level of support varies across organisations. It is unclear why TMT in some
organisations fail to provide the support required for MCS innovations. Existing research suggests that the
3
Davila and Foster (2007) identified 46 specific categories of MCS, all of which are supported by the extensive set of pre-built
reports and metrics included in most BI-enabled MCS innovations (Howard, 2003).
3J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
4. nature and form of TMT support is built over time and depends on several contextual factors (Lewis et al.,
2003). Building on the knowledge management and innovation literature, the current study develops and
tests a model of TMT support for integrated MCS innovation and the enablers of such support.
While TMT support is said to be crucial, there is inconsistency in the way researchers conceptualise it
(Anderson, 1995; Shields, 1995; Anderson and Young, 1999). For instance, one group of studies refer to TMT
support as TMT participation, including their contribution in physical activities related to MCS innovations
(Norris, 2002). This includes providing adequate resources, such as time, money and personnel by TMT to
support MCS innovations (e.g., Shields, 1995; Foster and Swenson, 1997; Krumwiede, 1998; Brown et al.,
2004; Chenhall, 2004). Another group of studies refer to TMT support as TMT beliefs, that is, the psychological
state of TMT towards MCS innovations (e.g., Powell, 1995; Liu and Pan, 2007; Sartorius, 2007). For instance,
Liu and Pan (2007) refer to TMT support as TMT's enthusiasm for encouraging innovative ideas. The view
followed in this study is consistent with the innovation literature that TMT support is not either/or but is both
participation (physical activities) and belief (psychological state) and that theoretical models of TMT support
should encompass both TMT participation and TMT beliefs (Chatterjee et al., 2002).
Our research focuses on examining these two dimensions of TMT support for integrated MCS innovation.
Specifically, we propose that TMT support is built in two stages (belief and participation) and show the path
dependence between these two stages. We build and test a research model that depicts the factors that drive
these two stages of TMT support. In particular, the research model suggests that TMT's strategic IT knowledge,
TMT knowledge creation modes, CIO business and IT knowledge, and the level of interaction between CIO and
TMT members will drive TMT support for integrated MCS innovation. Fig. 1 depicts the conceptual model tested
in this study.
2.2. TMT beliefs and TMT participation in integrated MCS innovation
TMT participation in integrated MCS innovations refers to a set of physical activities performed by senior
executives in the management of MCS innovations (Chatterjee et al., 2002). TMT participates by playing
active roles in planning activities related to MCS innovations (Chatterjee et al., 2002). This can range from the
articulation of a vision for the organisational use of MCS innovations, to the formulation of plans and
strategies to translate such visions into reality. TMT are also responsible for establishing appropriate goals and
standards to monitor MCS innovations (Chatterjee et al., 2002). It may also involve either shaping the
organisational context to make it more adaptive to the MCS or facilitating the adoption of the MCS innovation
to the characteristics of the organisation (Sharma and Yetton, 2003). Engaging in these activities require
substantial commitment of costly human and material resources. As the resources available to TMT are
limited, they can and will only direct resources to these activities if they are convinced about the value of the
MCS innovation to the organisation (Chenhall, 2004).
Fig. 1. Research model and hypotheses.
4 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
5. We argue that TMT belief in MCS innovation is an important factor that explains TMT participation. TMT
beliefs in MCS innovations refer to the subjective psychological state and probability estimates of TMT,
reflecting the degree of importance and significance TMT accord to MCS innovations in organisations
(Chatterjee et al., 2002). As stated by Chatterjee et al. (2002), TMT beliefs encompass the extent to which
senior executives believe that MCS innovations have the potential of providing significant business benefits
and competitive advantages, as well as the extent to which TMT believe that MCS innovations are able to
support the business activities and strategies of the organisation. We expect such beliefs to be positively
associated with the level of TMT participation in integrated MCS innovation. This expectation is supported by
the Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975; Ajzen and Fishbein, 1980) and the related
Technology Acceptance Model (TAM) (Davis, 1989; Davis et al., 1989). According to TRA, TMT will participate
in MCS innovations-related activities if they believe that MCS innovations are valuable and relevant to the
organisation. Likewise, according to the TAM literature TMT will increase their participation in activities that
will enhance the MCS innovations if they believe the innovations to be useful in enhancing their performance
as decision makers. The above discussion leads to the following hypothesis:
H1. TMT's belief in an integrated MCS innovation has a positive effect on TMT's participation in the
innovation.
2.3. Enablers of TMT belief in integrated MCS innovation
TMT beliefs are subjective probability estimates about the consequences of an action (Lewis et al., 2003).
Lewis et al. (2003) suggest that TMT develop beliefs about innovation after incorporating their assessments of
various outcomes associated with the organisational use of such innovation. Such assessments are results of
the process through which TMT gather, synthesise and assess information about innovations (Lewis et al.,
2003). Similarly, Agarwal (2000) suggests that TMT's beliefs are formed as a result of their cognitive
evaluations of information relating to the consequences of accepting or using innovation. As such, knowledge
and information serve as the basis for TMT beliefs about innovation.
2.4. TMT's strategic IT knowledge and TMT beliefs in integrated MCS innovations
TMT's strategic IT knowledge refers to TMT's understanding of the merits, opportunities and advantages of
IT in supporting the organisation business strategy (Anderson et al., 2002; Elbashir et al., 2011). It also
encompasses TMT's awareness of the organisational needs of IT and TMT's attentiveness to the organisational
impacts of IT (Argyris and Kaplan, 1994).
As integrated MCS innovations draw heavily on IT, TMT's strategic IT knowledge is expected to form the
basis upon which TMT come to identify the benefits, relevance and value of this innovation (Walsh, 1988;
Thomas and McDaniel, 1990). Strategic IT knowledge will enable TMT to form their opinion about and assess
the value of integrated MCS innovations for the organisation (Walsh, 1988).
The absorptive capacity literature also suggests that TMT's prior related knowledge influences their ability
to recognise the benefits of MCS innovations. That is, in order to engage in the process of collecting,
synthesising and assessing information related to integrated MCS innovation, TMT must have prior related IT
knowledge (Thomas and McDaniel, 1990). Strategic IT knowledge will enable TMT to form beliefs about
integrated MCS innovation. This leads to the following hypothesis:
H2. TMT's strategic IT knowledge has a positive effect on TMT belief in integrated MCS innovations.
2.5. TMT knowledge creation process and TMT beliefs in integrated MCS innovations
TMT's knowledge creation process captures the action and interaction modes that enable TMT to generate
new knowledge and renew existing knowledge (Nonaka, 1994; Nonaka and Takeuchi, 1995; Nonaka et al.,
2000). According to the knowledge creation framework, TMT are exposed to new information about MCS
innovations through knowledge creation activities including socialising with other individuals and
experimenting with new innovative ideas and managerial techniques. IT people are a key source through
which TMT gathers information about MCS innovations (Lewis et al., 2003). Such information may come in
5J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
6. different forms of modality, such as oral, written or observation. Through processing of information received
from internal and external sources, TMT will be able to create new knowledge (Nonaka, 1994; Nonaka and
Takeuchi, 1995; Nonaka et al., 2000). This new knowledge will enable TMT to draw on it as a reference in
forming their estimates of the organisational benefits of MCS innovations (Wyer and Radvansky, 1999).
Therefore, the process of knowledge creation enlarges the cognitive resources available for TMT to draw on as
reference knowledge, thereby solidifying TMT's belief in an integrated MCS innovation. This leads to the
following hypothesis:
H3. TMT's knowledge creation process has a positive effect on TMT's belief in integrated MCS innovations.
2.6. CIO's strategic business and IT knowledge and TMT belief in integrated MCS innovations
CIO's strategic business and IT knowledge encompasses the CIO's understanding of the organisation's
overall business domain, competitive forces, core capabilities, strategic goals, products and services, and
related IT innovations (Armstrong and Sambamurthy, 1999; Bassellier and Benbasat, 2004). It also reflects
CIO's awareness of TMT's strategic and tactical thinking, and the ability to perceive organisational needs for IT
innovations (Watson, 1990). CIOs with strategic business and IT knowledge are expected to positively
influence TMT's estimates of the organisational benefits of integrated MCS innovations (Agarwal, 2000).
As integrated MCS innovations are based on IT, TMT rely heavily on CIOs who possess greater relevant
expertise (Enns et al., 2003a,b, 2007). CIOs with strategic business and IT knowledge are able to “organise key
arguments, assemble supporting data, (and) carefully think through the context of the delivery” to influence
TMT's estimates of likelihood that MCS innovations are able to provide organisational benefits (Enns et al.,
2007, p. 34). They are able to argue a compelling and rational case for how MCS innovations are important and
relevant to the organisation (Enns et al., 2003a,b, 2007).
Strategic business and IT knowledge enables CIOs to recognise and communicate the organisational needs
for MCS innovations. These CIOs are also able to capture the kernel of success stories of integrated MCS
innovations from elsewhere, and conceptualise the potential relevance of these opportunities and benefits to
the organisation (Smalts et al., 2006). In addition, CIOs with strategic business and IT knowledge are able to use
non-technical business language to communicate and interact with other TMT members (Bassellier and
Benbasat, 2004; Enns et al., 2007) and are able to translate the language of IT into the language of business (and
vice versa). They are also able to develop MCS innovations measures based on business effectiveness criteria,
such as cost reduction, inventory reduction and business process productivity (Applegate and Elam, 1992).
Moreover, with strategic business and IT knowledge, CIOs are able to align MCS innovations with the
overall strategic direction of the organisation. Such knowledge enables CIOs to recognise and identify
innovative ways of blending the capabilities of MCS innovations with the organisational needs, priorities and
opportunities (Smalts et al., 2006). By having MCS innovations which are consistent with the overall strategic
direction of the organisation, CIOs are able to positively influence TMT's estimates of the organisational
benefits of MCS innovations (Enns et al., 2003a,b; Bassellier and Benbasat, 2004). In addition, with strategic
business and IT knowledge, CIOs are perceived to be an executive, rather than a mere functional manager
(Enns et al., 2001, 2007). This is important as TMT's information processing capacity may be saturated at
times. In such cases, the ability of TMT to make subjective estimates of the benefits of integrated MCS
innovation is impaired. This may cause TMT to rely and endorse CIO's recommendation that integrated MCS
innovations are important and relevant to the organisation (Agarwal, 2000; Lewis et al., 2003). Therefore,
CIOs with strategic business and IT knowledge are able to positively influence TMT's subjective estimates of
the benefits of integrated MCS innovations to the organisation, increasing their beliefs in the MCS innovations.
This leads to the following hypothesis:
H4. CIO's strategic business and IT knowledge have a positive effect on TMT's belief in integrated MCS
innovations.
2.7. TMT/CIO interactions and TMT belief in integrated MCS innovations
As indicated earlier, TMT belief in integrated MCS innovations is a function of the subjective probability
estimates about the organisational value of the innovations. An important factor in these probability
6 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
7. estimates is the extent of strategic alignment of the innovation. That is, the alignment between business
strategy and the various dimensions of integrated MCS innovation and the shared cognition of CIOs and
TMT about the business value of this innovation (Preston and Karahanna, 2009). Preston and Karahanna
(2009) argue that the nature of interaction between CIOs and TMT is vital to facilitating strategic
alignment and shared cognition of the business value of MCS innovation.
TMT/CIO interactions create a platform or a mechanism for TMT to infuse strategic thinking into MCS
innovation processes by communicating the information processing and control requirements to CIOs. This
provides the CIOs the opportunity to improve their knowledge about organisational needs for MCS innovation
and to tailor MCS innovation activities towards meeting those needs (Doll, 1985). TMT/CIO interaction also
allows CIOs to articulate the strategic relevance of MCS innovation by highlighting both the tangible and
intangible values of MCS innovation directly with TMT. The question and answer approach that generally guides
such interactive settings also creates opportunities for TMT to seek clarification on the nature of MCS
innovations; the strategic, operational and resource implications of such innovation; and the way the innovation
process is to be managed. Seeking such clarification allows CIOs to better explain how MCS innovations are
aligned to organisational strategy and the value that will emanate from such strategic alignment.
In addition, the Upper Echelons theory suggests that TMT beliefs and strategic choices reflect the cognitive
basis of TMT members (Preston and Karahanna, 2009), hence shared cognition between TMT and CIOs has the
propensity to influence TMT belief in MCS innovation. Shared cognition is an important basis for effectively
integrating strategic business knowledge with integrated MCS innovation and thus allows for better
communication of the meaning and relevance of such innovations to value creation within the organisation.
We argue that the exchange of knowledge and information that takes place when TMT and CIOs interact
facilitates the development of shared cognition among them about how MCS innovation can be used to
enhance organisational capabilities and leverage organisational value (Armstrong and Sambamurthy, 1999;
Preston and Karahanna, 2009). As such, it is theorized that the interaction between TMT and the CIO will
influence TMT belief about integrated MCS innovations. This leads to the following hypothesis:
H5. The level of interaction between TMT and the CIO has a positive effect on TMT's belief in integrated
MCS innovations.
3. Research method
Data was collected through a large field survey of customers from an international BI software vendor. The
BI vendor distributes BI software that combines multiple cybernetic control tools (such as activity-costing and
management, balanced scorecard, KPIs, etc.) as a package of integrated MCS. This integrated MCS provides
access to over 200 different pre-built reports based on more than 500 KPIs and analytics designed to answer
over 2900 business critical questions.
The use of clients from a single vendor controls for potential variations in capabilities of BI software
provided by different BI vendors. The vendor provided a contact list of their clients under a written
non-disclosure agreement. Where possible, multiple respondents from each organisation were selected from
the vendor's contact list. For organisations which had one contact person on the list, the organisation was only
selected if the contact person was a senior manager such as a CEO, CFO, or CIO. A multiple respondent strategy
was preferred as it enables collection of rich data, mitigates potential bias, and enhances accuracy (Huber and
Power, 1985; Sethi and King, 1994).
The survey was conducted in accordance with the guidance of Dillman et al. (2009). Survey packets
containing a printed copy of the survey, along with a cover letter and reply-paid envelope were posted to
participants. After four weeks, a reminder was emailed to all participants. A second survey package was
mailed to the non-respondents four weeks after the first reminder. Two weeks later, a third and final
reminder along with a link to the online version of the survey was emailed to those who had not responded to
the second survey package. On average, three respondents from each targeted organisation received the
survey. The survey was sent to 1873 managers in 612 organisations. A total of 419 usable responses were
received from 220 organisations. This resulted in response rate of 22% for individual responses.4
Respondents
4
An ANOVA test was performed to compare the paper-based responses with the on-line responses. No significant differences are
found on any of the main variables of the study, which indicates that the different data collection modes that have been used in the
study did not create a response bias.
7J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
8. were given the option to respond for the organisation as a whole or for the strategic business unit (SBU) in
which they worked. This option allowed for the possibility that in the case of very large organisations it could
be difficult for an individual to assess the entire company. Using the responses for SBUs as unique
organisational responses, the responses represent 347 organisations.
The consistency of responses from multiple respondents of the same organisation is examined using
two tests: (1) computing the correlation between multiple responses (Armstrong and Sambamurthy,
1999), and (2) the co-efficient of the inter-class correlation (ICC) (Shrout and Fleiss, 1979). All correlations
between multiple respondents of the same organisation were found to be highly significant. The ICC
coefficients for all the raters (between 2 and 5 responses per organisation) range from 0.76 to 0.94. The
results of the two tests provide strong evidence of consistency between multiple responses from a single
organisation. In such cases, the average score from multiple respondents was used as the response of the
TMT as a whole. On the other hand, for firms with a single respondent, the individual response was used to
represent TMT.
To test for non-response bias, early and late responses on the main variables of the study were compared
in paired samples of 150, 100, 50, and 40 responses using an ANOVA test. Responses that we received
following the second reminder were also compared with those received before the reminder. The results
reveal no significant differences on the responses across these paired samples indicating an absence of
response bias. Out of the respondents indicating they were unable to complete the survey, 70 noted company
policy precluded their completion of the survey. Moreover, 37 respondents indicated other members from
their company had responded on their behalf, 11 had left their company, and 8 indicated that the survey was
not relevant to them.
Exploratory Factor Analysis (EFA) was used to perform Harman's one-factor test that examines
whether a common method variance problem exists (Podsakoff and Organ, 1986). The results of the
analysis show that there are at least seven “unrotated” factors that account for 70% of the variance in the
measurement items used. We also performed additional tests for common method variance as suggested
in prior literature (Podsakoff and Organ, 1986; Podsakoff et al., 2003). We added a marker variable that is
not relevant to the TMT support construct tested in the study and we examined the research model both
with and without the marker variables. The results show that the results do not change and the marker
variable is not significant. We also added the highest factor from the unrotated explanatory factor
analysis to the PLS model as a control variable. The findings also show that the results of the original
model are not affected by the control “general factor” variable. The results from all these tests indicate
that there is no significant common method variance that threatens the quality of the data (Zhuang and
Lederer, 2003).
3.2. Demographics
Information was collected from the respondents on their organisations (see Table 1). Responses are
predominantly from large organisations with an average of 663 employees and gross revenue of over A
$2 billion per year. About half (50.7%) of the organisations in the survey sample had at least 1000
employees; about a quarter (25.9%) had gross revenue ranging from $100 million to below $500 million.
The largest industry grouping was manufacturing, accounting for 18.7% of all survey respondents. This was
followed by retail, wholesale, and distribution (14.4%), and then banking, finance, and insurance (12.4%).
Hospitality, travel and tourism received the least representation in the sample (1.7%).
The respondents also provided personal demographic data (see Table 2). The average age of respondents
was 41.1 years with 16.5 years of work experience, and 80% of respondents being male. 54% of respondents
classified themselves as executives/managers, 46% as IT executives/managers, and 13% held both business
and IT jobs.
3.3. Operationalization of constructs
TMT's participation in integrated MCS innovations refers to a set of physical activities performed by the
senior executives in the management of MCS innovations as they pertain to BI in this study. TMT's
participation in integrated MCS innovations is measured in this study by using a three-item scale adapted
from Chatterjee et al. (2002). The items measure the extent to which TMT actively participates in three
8 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
9. types of formal BI activities. These activities are the: (1) articulation of vision, (2) formulation of strategy,
and (3) establishment of goals and standards to monitor the organisational use of integrated MCS
innovations (i.e., BI).
TMT's belief in integrated MCS innovations refers to the subjective psychological state of the TMT,
reflecting the degree of importance and significance that TMT places on BI innovation in the organisation.
The measures for TMT's beliefs were based on Chatterjee et al. (2002) and consists of five measures that
capture the extent to which TMT believe that BI: (1) has the potential to provide business benefits to the
organisation, (2) creates competitive advantage for the organisation, (3) is accessible to the relevant
managers of the organisation, (4) is important to support business activities/strategies of the organisation,
and (5) is a secure technology to support the business activities/strategies of the organisation.
TMT's strategic IT knowledge refers to TMT's understanding of the merits, opportunities and advantages
presented in IT, the awareness of the TMT of the organisational needs for IT, and attentiveness to the
organisational impacts of IT. The measures for TMT's strategic IT knowledge were developed by Armstrong
and Sambamurthy (1999) and uses three items that captures the extent to which TMT are knowledgeable
about: (1) the potential and limitations of the organisation's current information and communication
technologies, (2) the potential and limitations of emerging information technologies, and (3) how
competitors are applying information technologies.
TMT's knowledge creation process refers to the process through which TMT creates new knowledge and
renews their existing knowledge. The measures of TMT's knowledge creation process was developed by
adapting Nonaka et al. (2000)'s measure. The final list of measures consists of 26 items that capture four
Table 1
Demographic information on organisations.
Frequency Percentage
Industry categories
Agricultural/mining/construction 12 3.50%
Banking/finance/insurance 43 12.40%
Consulting/professional service 34 9.80%
Health care 35 10.10%
Hospitality/travel/tourism 6 1.70%
Manufacturing 65 18.70%
Media/entertainment/publishing 11 3.20%
Retail/wholesale/distribution 50 14.40%
Telecommunications 21 6.10%
Transport/logistics 12 3.50%
Others 36 10.40%
Missing (did not specify industry) 22 6.30%
Number of employees
Less than 50 35 10.1%
50 to below 200 45 13.0%
200 to below 500 57 16.4%
500 to below 1000 34 9.8%
1000 or more 176 50.7%
Average number of employees = 663
Estimated gross revenue in 2004
Less than $50 million 50 14.4%
$50 million to below $100 million 48 13.8%
$100 million to below $500 million 90 25.9%
$500 million to below $1 billion 42 12.1%
$1 billion to below $5 billion 60 17.3%
$5 billion to below $10 billion 19 5.5%
$10 billion or more 33 9.5%
Missing 5 1.4%
Average gross revenue = $2.1 billion
9J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
10. modes of knowledge creation. Seven of the items measure socialisation, six items measure externalisation,
six items measure combination, and seven items measure internalisation.
CIO's strategic business and IT knowledge is adapted from Armstrong and Sambamuthy (1999) and consists of
six measures that capture CIO's knowledge regarding: (1) the IT infrastructure required to support the
organisation's BI needs, (2) the potential and limitations of relevant emerging information technologies, (3)
how competitors are using BI technologies, (4) the timing and investment strategies in emerging technologies,
(5) the organisation's present and future products and services, (6) best practices in the organisation's industry,
and (7) the business activities of the organisation's competitors.
Table 2
Demographic information on informants.
Frequency Percentage
Age
b25 years 6 1.7%
25–30 years 28 8.1%
31–40 years 124 35.7%
41–50 years 131 37.8%
51–60 years 54 15.6%
61+ years 4 1.2%
Average age = 41.1 years
Years of experience
5 years to below 10 years 86 24.8%
10 years to below 15 years 84 24.2%
15 years to below 20 years 70 20.2%
20 years to below 25 years 46 13.3%
25 years to below 30 years 33 9.5%
Above 30 years 28 8.1%
Average years of experience = 16.5 years
Business Executive
Managing Director 7 2.6%
Chief Executive Officer 2 0.8%
General Manager 17 6.4%
Chief Financial Officer 19 7.1%
Chief Operating Officer 6 2.3%
Business Development Manager 27 10.2%
Branch/Division Manager 29 10.9%
Business Analyst 81 30.5%
Team Leader 28 10.5%
Others 45 16.9%
IT Executive
Director of MIS 4 1.8%
Chief Information Officer 18 8.1%
Manager of MIS 33 14.9%
Business Intelligence Manager 32 14.5%
Senior Systems Analyst 31 14.0%
Project Manager 24 10.9%
Business Intelligence Consultant 32 14.5%
Applications Development Manager 14 6.3%
Applications Support Leader 6 2.7%
Others 21 9.5%
Dual job
Hold both business and IT jobs 56 13%
Missing (did not specify titles) 5 1.9%
Gender Percentage
Male 80%
Female 20%
10 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
11. The level of TMT/CIO interaction consists of two measures adapted from Armstrong and Sambamurthy
(1999) and uses two items capturing: (1) extent to which the CIO is involved with TMT members, and
(2) number of hierarchical levels between CIO and TMT.
3.4. Control variables
Time since adoption is included in the model to control for whether TMT support is built overtime while
TMT becomes familiar with the integrated MCS innovation and experiences the advantages to the
organisation. The longer the organisation uses an integrated MCS innovation, the greater TMT support is
likely to be (Purvis et al., 2000). The measure of time since adoption is the number of years since the
integrated MCS innovations were adopted by the organisation.
Organisational size is included in the research model to control for the organisational support that is
driven by the size of resources that the organisation possesses (Zhu and Kraemer, 2002; Subramani, 2004).
Prior studies suggest that larger organisations have greater ability to provide support for MCS innovations.
CIO as member of TMT controls for the possibility that TMT support for MCS innovations is influenced by a
TMT design which includes the CIO as a member of the TMT. Existing literature suggests that CIOs are able to
provide more support for IT projects when they form part of TMT (Applegate and Elam, 1992; Armstrong and
Sambamurthy, 1999).
4. Data analysis
We use Smart PLS (Ringle et al., 2005), a component-based structural equation modelling technique to
test both the measurement and structural models.5
The bootstrapping resampling approach was used to
generate 1000 random samples of observations from the original data set. The paths' coefficients were
re-estimated using each of these random sample observations. This approach computes the t-statistics and
provides a valid estimate of the significance of the path coefficients (Chin, 1998b).
4.1. Discussion of the measurement model
The test of the measurement model includes examining the internal consistency and convergent and
discriminant validity of the instrument items. All composite reliability scores of the latent constructs
(reported in Table 3) are well above the recommended level of .70, thus indicating adequate reliability of
the reflective item measures for each such construct (Nunnally and Bernstein, 1978). Item loadings
together with the average variance extracted (AVE) were used to examine the convergent validity of each
construct's measure (Van den Bosch et al., 1999). Table 3 shows that all the reflective constructs have
items loading of above 0.70 which indicates their significant contribution to the measured construct.
Moreover, the average variance extracted (AVE) for all constructs was above 0.50, demonstrating the
convergent validity of the measurement items (Fornell and Larcker, 1981). This also indicates that each
measured construct explains more than 0.50 of the variation in the observed variables.
Table 4 shows that the values of the square root of the AVE (on the diagonal) are all greater than the
inter-construct correlations (off the diagonal). This demonstrates that the measures exhibit satisfactory
discriminant validity.6
An additional test of discriminant validity was conducted where each measurement
item is assessed to ensure that it has a higher loading on its assigned factor than on any other factors (Chin,
1998b; Gefen et al., 2000); and the results are shown in Table 5. Each of the measurement items loaded
higher on the appropriate construct than on any other construct providing further support for the
discriminant validity of the measures used in the study.
5
PLS is more appropriate than other SEM techniques such as covariance-based SEM because (1) the data used lacks the
multivariate distribution, and (2) one of the constructs tested in the research model utilizes measurement models that are formative
(interaction between CIO and TMT members). The use of covariance-based SEM to model the construct as formative can result in an
unidentified model (Kline, 2006).
6
For satisfactory discriminant validity, the square root of AVE of the construct should be greater than the variance shared between
the construct and other constructs in the research model (Chin, 1998a).
11J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
12. Table 3
Measurement model statistics.
Panel A: Reflective constructs
Individual item loadings, t-statistics, composite reliability, and average variance extracted (AVE)
Latent variable Loadings t-Statistics
TMT strategic IT knowledge (composite reliability = 0.92; AVE = 0.80)
BEK1: The potential and limitations of the organisation's current information and communication
technologies
0.884 44.37
BEK2: The potential and limitations of emerging information technologies 0.933 107.86
BEK3: How competitors are applying information technologies 0.870 40.51
TMT knowledge creation process (socialisation) (composite reliability = 0.86; AVE = 0.60)
KCS1: Share ideas/experiences with clients and suppliers 0.824 37.24
KCS2: Share ideas/experiences with external experts 0.786 23.65
KCS3: Gather information/ideas from competitors 0.750 23.86
KCS13: Engage in dialogue with subordinates to exchange various ideas and knowledge 0.744 24.88
TMT knowledge creation process (externalisation) (composite reliability = 0.91; AVE = 0.66)
KCS6 Develop new strategies/business opportunities by… 0.809 38.05
KCS7 Make regular contacts with each other through… 0.729 24.50
KCS8 Share information/ideas/experiences with… 0.851 46.65
KCS9 Demonstrate and model their expertise to other… 0.860 44.55
KCS10 Engage in dialogue with subordinates to exchange… 0.807 41.01
TMT knowledge creation process (combination) (composite reliability = 0.91; AVE = 0.66)
KCS15 Plan strategies by using computer simulation and… 0.751 26.61
KCS16 Gather and summarize information from different… 0.841 44.42
KCS17 Build databases on products/services by gathering… 0.799 31.42
KCS18 Convene meetings where new concepts and… 0.820 41.64
KCS19 Use information technologies to collect/transmit… 0.842 46.05
TMT knowledge creation process (internalisation) (composite reliability = 0.91; AVE = 0.66)
KCS22 Experiment with new management practices to… 0.812 38.13
KCS23 Are keen to understand different groups' visions… 0.856 54.13
KCS24 Read business/IT publications 0.727 19.23
KCS25 Use “learning by involvement” in different projects… 0.868 53.84
KCS26 Foster a work environment that is supportive of… 0.798 31.47
CIO strategic business and IT knowledge (composite reliability = 0.93; AVE = 0.65)
CIOK1: The IT infrastructure required to support the organisation's business intelligence needs 0.786 28.69
CIOK2: The potential and limitations of relevant emerging information technologies 0.807 31.40
CIOK3: How competitors are using business intelligence technologies 0.801 36.89
CIOK4: Timing and investment strategies in emerging technologies 0.867 65.04
CIOK5: The organisation's present and future products and service 0.791 30.12
CIOK6: What is considered best practice in the organisation's industry 0.837 40.94
CIOK7: The business activities of the organisation's competitors 0.758 26.23
TMT's beliefs in MCS innovations (composite reliability = 0.96; AVE = 0.83)
TMSB1: Business Intelligence Systems have the potential to provide business benefits to
the organisation.
0.922 93.06
TMSB2: Business Intelligence Systems create competitive advantages for the organisation. 0.910 87.04
TMSB3: Business Intelligence Systems are accessible to the relevant managers of the organisation. 0.873 55.52
TMSB4: Business Intelligence Systems are important to support business activities/strategies of
the organisation.
0.942 141.76
TMSB5: Business Intelligence Systems are secure technologies to support business activities/strategies
of the organisation.
0.912 83.99
TMT's participation in MCS innovations (composite reliability = 0.97; AVE = 0.92)
TMSP1: Articulating the vision for organisational use of Business Intelligence Systems 0.957 167.62
TMSP2: Formulating the strategy for the organisational use of Business Intelligence Systems 0.965 186.59
TMSP3: Establishing goals and standards to monitor Business Intelligence Systems projects 0.951 151.28
12 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
13. 4.2. Discussion of the structural model
Table 6 and Fig. 2 present the overall results of the PLS structural model. Substantial support is provided for
the overall model. The results also indicates that all three control variables—time since adoption, firm size,
and CIO's membership in TMT—have no significant effect on TMT belief in MCS innovations. The total of the
variance of TMT belief and participation in MCS innovations explained by the model are 0.43 and 0.48,
respectively. H1 predicted a positive relationship between TMT beliefs in integrated MCS innovations and
TMT participation in integrated MCS innovations. As shown in Table 6 (Panel A), the path coefficient between
TMT belief and TMT participation in integrated MCS innovations is statistically significant and in the
hypothesised direction (β = 0.680; p b 0.001). The result supports H1. This result is consistent with prior
literature that has suggested that if TMT believes that MCS innovations are worthwhile and able to produce
significant organisational benefits, they will formally, directly and actively participate in MCS
innovations-related activities (see for instance, Fishbein and Ajzen, 1975; Davis, 1989; Davis et al., 1989;
Ajzen, 1991; Lewis et al., 2003). This finding suggests that for TMT to participate in integrated MCS
innovations, they must first be convinced that such innovations provide organisational benefits.
H2 predicted a positive relationship between TMT's strategic IT knowledge and TMT belief in an
integrated MCS innovation. However, as shown in Table 6 (Panel A), the structural path leading from
TMT's strategic IT knowledge to TMT belief in an integrated MCS innovation is in a direction opposite to
the hypothesis (β = −0.002), and is not statistically significant. Hence, contrary to expectations, TMT's
strategic IT knowledge does not have a positive effect on TMT belief in integrated MCS innovations.
H3 predicted a positive relationship between TMT's knowledge creation process and TMT belief in an
integrated MCS innovation. The results shown in Table 6 (Panel A) support the hypothesis with a strong and
significant relationship (β = 0.396; p b 0.001), indicating that TMT's knowledge creation is positively related
to TMT belief in an integrated MCS innovation. This finding supports Elbashir et al.'s (2011) conjecture that
Table 3 (continued)
Panel B: Formative constructs
Indicator weights t-Statistics VIF
TMT/CIO interactions
CIOTMT1 0.993 33.67 1.007
CIOTMT2 0.230 1.84 1.007
Dimensions of TMT knowledge creation: (2nd order construct)
TMT socialisation —N TMT knowledge creation 0.191 17.62
TMT Externalisation —N TMT knowledge creation 0.325 29.35
TMT combination —N TMT knowledge creation 0.327 24.82
TMT internalisation —N TMT knowledge creation 0.322 27.40
All indicator loadings are statistically significant (p b 0.001, one tailed).
Table 4
Correlation matrix with AVE statistics.
1 2 3 4 5 6 7 8
1. TMT strategic IT knowledge 0.894
2. TMT socialisation 0.354 0.927
3. TMT externalisation 0.485 0.603 0.812
4. TMT combination 0.486 0.539 0.683 0.812
5. TMT internalisation 0.584 0.533 0.717 0.677 0.812
6. CIO strategic knowledge 0.557 0.304 0.466 0.450 0.456 0.806
7. TMT belief 0.413 0.371 0.507 0.551 0.497 0.497 0.911
8. TMT participation 0.515 0.291 0.457 0.549 0.540 0.470 0.689 0.959
13J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
14. TMT's knowledge creation process is a potential determinant of TMT belief in MCS innovations. It is also
consistent with Nonaka and Takeuchi (1995), and Nonaka and von Krogh (2009), who reported that the
process of knowledge creation positively influenced the innovativeness of organisations.
The finding of H3 also provides possible explanations for the unexpected results found in H2. The
adaptability to innovations (i.e., the ability to form new knowledge and develop new approaches to existing
problems) is likely to be a greater contributing factor to TMT's belief in MCS innovations than their
pre-existing strategic IT knowledge stock. This idea is further supported by the age demographic of TMT. As
can be seen in Table 2, TMT members are typically somewhat older, with an average age in this study of
41.1 years. Given this trend, it is likely that TMT members underwent their training and studies many years
ago, before MCS innovations became significant. Thus, their strategic IT knowledge stock, no matter how
great, is likely to become obsolete over time. Because of this, TMT's strategic IT knowledge would be much less
significant as a factor in influencing TMT's belief in MCS innovations than TMT's knowledge creation process.
H2 and H3 therefore suggest that the ability of TMT to adapt to new techniques and incorporate them into the
operations of an organisation is more important in influencing their belief in MCS innovations than their static
IT knowledge stock.
H4 predicted a positive relationship between CIO's strategic business and IT knowledge and TMT belief
in an integrated MCS innovation. Table 6 (Panel A) shows that the path leading from CIO's strategic
Table 5
Item loadings and cross loadings.
TMT
knowledge
Socialisation Externalisation Combination Internalisation CIO
knowledge
Belief Participation
BEK1 0.884 0.299 0.444 0.425 0.540 0.510 0.332 0.428
BEK2 0.933 0.255 0.438 0.462 0.536 0.535 0.401 0.508
BEK3 0.870 0.402 0.423 0.417 0.498 0.452 0.372 0.442
KCS1 0.268 0.824 0.473 0.439 0.491 0.221 0.311 0.305
KCS2 0.223 0.786 0.405 0.450 0.367 0.288 0.279 0.183
KCS3 0.273 0.750 0.523 0.440 0.363 0.203 0.314 0.160
KCS13 0.339 0.744 0.468 0.342 0.428 0.237 0.244 0.250
KCS4 0.418 0.560 0.809 0.535 0.589 0.352 0.425 0.397
KCS5 0.246 0.489 0.729 0.468 0.426 0.298 0.290 0.226
KCS7 0.415 0.467 0.851 0.521 0.570 0.394 0.431 0.381
KCS8 0.427 0.461 0.860 0.634 0.648 0.402 0.465 0.433
KCS12 0.440 0.477 0.807 0.603 0.655 0.434 0.429 0.396
KCS15 0.429 0.377 0.508 0.751 0.478 0.405 0.402 0.434
KCS16 0.395 0.497 0.591 0.841 0.540 0.399 0.472 0.425
KCS17 0.322 0.389 0.425 0.799 0.504 0.325 0.466 0.474
KCS18 0.392 0.492 0.677 0.820 0.611 0.373 0.446 0.422
KCS19 0.431 0.416 0.545 0.842 0.601 0.324 0.450 0.482
KCS22 0.485 0.456 0.566 0.536 0.812 0.390 0.388 0.396
KCS23 0.540 0.481 0.690 0.609 0.856 0.429 0.410 0.476
KCS24 0.434 0.399 0.395 0.443 0.727 0.333 0.344 0.386
KCS25 0.485 0.420 0.628 0.597 0.868 0.350 0.419 0.445
KCS26 0.427 0.410 0.603 0.552 0.798 0.346 0.457 0.487
CIOK1 0.354 0.114 0.299 0.296 0.297 0.786 0.316 0.305
CIOK2 0.394 0.140 0.301 0.264 0.275 0.807 0.337 0.296
CIOK3 0.501 0.321 0.363 0.365 0.374 0.801 0.444 0.474
CIOK4 0.521 0.268 0.375 0.391 0.426 0.867 0.461 0.438
CIOK5 0.391 0.262 0.453 0.404 0.370 0.791 0.426 0.347
CIOK6 0.517 0.266 0.452 0.429 0.441 0.837 0.426 0.398
CIOK7 0.430 0.302 0.359 0.359 0.354 0.758 0.360 0.358
TMSB1 0.366 0.365 0.475 0.502 0.486 0.468 0.922 0.626
TMSB2 0.383 0.390 0.475 0.498 0.474 0.459 0.910 0.616
TMSB3 0.331 0.278 0.408 0.495 0.421 0.411 0.873 0.593
TMSB4 0.395 0.351 0.500 0.526 0.467 0.453 0.942 0.647
TMSB5 0.405 0.304 0.449 0.492 0.418 0.475 0.912 0.657
TMSP1 0.496 0.286 0.470 0.531 0.516 0.466 0.691 0.957
TMSP2 0.505 0.291 0.449 0.534 0.529 0.425 0.663 0.965
TMSP3 0.477982 0.259112 0.390915 0.512978 0.505261 0.461313 0.622494 0.951
14 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
15. business and IT knowledge to TMT belief in MCS innovations is statistically significant and in the direction
predicted (β = 0.231; p b 0.001). The results provide evidence supporting CIO's strategic business and IT
knowledge plays an important role in influencing TMT belief in an integrated MCS innovation. This result
is consistent with prior literature that has indicated that CIO's strategic business and IT knowledge are
positively correlated with TMT belief in IT innovations (see for example, Armstrong and Sambamurthy,
1999; Enns et al., 2001, 2003a,b; Bassellier and Benbasat, 2004; Smalts et al., 2006).
H5 predicted a positive relationship between TMT/CIO interactions and TMT belief in integrated MCS
innovations. The results, as shown in Table 6 (Panel A), support the hypothesis (β = 0.159; p b 0.001). This
finding highlights the key role of TMT/CIO interactions in driving TMT's belief in integrated MCS innovations.
This result supports prior research indicating that frequent interactions between TMT and CIOs positively
influence TMT belief in IT innovations (Raghunathan and Raghunathan, 1989; Applegate and Elam, 1992).
Table 6
PLS structural model results.
Panel A: Path coefficient, t-statistics (in parentheses) and R2
Latent variable Path to:
TMT belief in MCS innovation TMT participation in MCS innovation
TMT belief in MCS innovation 0.680 (21.48) ⁎⁎⁎
TMT strategic IT knowledge −0.002 (0.06)
TMT knowledge creation 0.396 (7.11) ⁎⁎⁎
CIO's strategic business knowledge 0.231 (4.33) ⁎⁎⁎
TMT/CIO interactions 0.159 (3.2) ⁎⁎⁎
R2
0.43 0.48
Panel B: Indirect EFFECTS and 99% bootstrap confidence intervalsa
(in parenthesis)
Latent variable Path to:
Through: TMT participation in MCS innovation
TMT knowledge creation TMT belief in MCS innovation 0.269 (0.167–0.372)
CIO's strategic business knowledge TMT belief in MCS innovation 0.157 (0.070–0.262)
TMT/CIO interactions TMT belief in MCS innovation 0.108 (0.011–0.201)
a
All statistically significant at the 0.01 level.
⁎⁎⁎ p b 0.001.
Fig. 2. The results of the PLS analysis. *, **, and *** indicate that the coefficient is significant at the p b 0.05, p b 0.01, and p b 0.001
levels, respectively.
15J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
16. We also conducted an additional post hoc analysis to determine whether TMT belief in integrated
MCS fully mediates the relationships between the antecedent variables and TMT participation in an
integrated MCS innovation. To test this mediation, we follow Baron and Kenny's (1986) step-wise
approach. We first tested a model involving the direct relationship of the antecedent variables on TMT
participation and all the relationships were significant at the 0.05 level. In the second step, we tested the
direct relationship between the antecedent variables and TMT belief in an integrated MCS innovation.
All the relationships were significant at the 0.001 level except the path leading from TMT knowledge to
TMT belief in integrated MCS which was insignificant. In the third step, we include the direct
relationship between TMT belief in an integrated MCS innovation and TMT participation while
controlling for the effects of our antecedent variables on TMT participation. The path was significant at
the 0.001 level.
In the final step, we tested the full model involving all the relationships in the above three steps. When
TMT belief in integrated MCS is included in the model, the direct paths leading from two antecedents (CIO
knowledge and CIO/TMT interaction) to TMT participation in integrated MCS become insignificant. This
confirms that TMT belief in an integrated MCS innovation fully mediates the relationships between the
two antecedents (CIO knowledge and CIO/TMT interaction) and TMT participation in integrated MCS
innovation. Also, the significant direct relationship between knowledge creation and TMT participation is
reduced when TMT belief in an integrated MCS innovation is included; thus providing support for partial
mediation. Following Baron and Kenny (1986), TMT knowledge was excluded from the mediation test as
the direct relationship between this variable and TMT belief in integrated MCS is insignificant. The results
from the post hoc analyses provide strong support for the research model including TMT belief as an
important antecedent to TMT participation in an integrated MCS innovation.
Following the mediation test, we estimated the indirect effects of the antecedents of TMT support on
TMT participation in integrated MCS innovation through TMT belief. The results (Table 6; Panel B) show
that at the 0.01 significance level, TMT knowledge creation, CIO strategic business and IT knowledge and
TMT/CIO interactions have significant indirect effects (β = 0.269, β = 0.157, and β = 0.108 respectively)
on TMT participation through TMT belief in MCS innovation. These significant indirect effects provide
further evidence of the importance of these antecedents to TMT support for TMT participation in an
integrated MCS innovation.
5. Conclusion
This study examines the enablers of TMT support for integrated MCS innovations. The results provide
evidence that TMT support can be conceptualised in a two-stage model that combines TMT belief and
participation in an integrated MCS innovation. The results confirm that TMT participation in MCS
innovations is driven by their belief in the innovations. This result is consistent with calls made in recent
literature which suggest opening the “black box” of TMT support and treating it as a dualistic construct
rather than a monolithic construct (Chatterjee et al., 2002; Liang et al., 2007). The results also show that
TMT's knowledge creation process, CIO's strategic business and IT knowledge, and TMT/CIO interactions
influence the level of TMT belief in integrated MCS innovations. However, TMT's strategic IT knowledge is
found to be insignificantly related to TMT belief in an integrated MCS innovation.
The findings reported in this study have important implications for theory and practice. It is clear that
the lack of TMT's knowledge limits their level of involvement in MCS innovation projects. This suggests
that TMT members need to make the effort to engage in activities that enable them to gain the strategic
knowledge necessary for performing their managerial roles including making decisions that relate to
strategic planning that involves MCS innovations.
The results confirm the importance of CIO's business and IT knowledge in generating TMT support for
MCS innovations. The strong linkage between the CIO knowledge and TMT belief in an integrated MCS
innovation suggests that CIOs play major roles in making TMT aware of the value of MCS innovations in
supporting business strategies and the competitiveness of the organisation. The findings also imply that
the level of interaction between TMT members and CIO, whether by working closely in teams or through
accountability of the CIO including whether the CIO directly or indirectly is reporting to TMT, will have a
significant impact on enhancing TMT belief in MCS innovations.
16 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
17. Examining the antecedents of TMT support for MCS innovations answers the call made by prior
researchers. For instance, Shields and Shields (1998) argue that it is not sufficient to merely investigate the
relationship between an independent variable and a dependent variable. Understanding the antecedents
of the independent variables will enrich theoretical and empirical models (Shields and Shields, 1998). This
study addresses this call by examining the key enablers of TMT support for integrated MCS innovations
which are likely to have an indirect effect on the phenomenon tested in prior management accounting
literature as one of the outcomes of TMT support. The findings of this study will enable future researchers
to build and test more comprehensive models that involve TMT support.
The statistical analysis did not support the conjecture that TMT's strategic IT knowledge as an
antecedent of TMT support for MCS innovations. A plausible explanation for this could be the arguments of
the dynamic view of knowledge management which suggests that dynamic knowledge creation processes
are more effective for organisations than the static knowledge stock that people possess (Nonaka, 1994;
Cook and Brown, 1999). This is simply because static knowledge stocks become obsolete over time and die
quickly. Therefore, the ability of TMT to recognise new knowledge and renew their existing knowledge is
more important for enhancing the level of support for integrated MCS innovations than the level of
strategic IT knowledge that those senior managers possess. Moreover, this study contributes to the current
literature on MCS innovations by answering a call made in prior studies to investigate the factors that might
influence the decisions of TMT to adopt, implement and use MCS innovations.
An investigation into the antecedents of TMT support for integrated MCS innovations has great
practical significance. TMT support is strongly linked to the positive organisational effects of the adoption,
implementation and use of MCS innovations. If organisational performance is to be enhanced then it is
vital to understand the factors that drive TMT to support integrated MCS innovations. Deliberate
engagement of TMT in the process of knowledge creation should be encouraged within organisations as
ongoing processes rather than purposeful and directed short-term knowledge acquisition and renewal.
Moreover, organisations that are willing to promote the adoption, implementation and use of such
innovations should seek to employ CIOs with both strategic business and IT knowledge and activate the
processes and channels that allow an effective interactions between TMT members and the CIO. This could
be through allowing CIOs to attend key executive meetings and reducing the intermediaries between TMT
and the CIO.
The results of this research should be interpreted in light of certain limitations. There are inherent
limitations associated with survey studies that apply. For instance, surveys which attempt to capture
perceptions are always susceptible to misinterpretation or a lack of knowledge and truthfulness by the
respondents. However, techniques used in this study help alleviate some of these concerns. These include
providing respondents with a ‘No Basis for Answering’ option in the survey, capturing the same data from
multiple respondents, and testing for discriminant validity. All of these strategies provide evidence
suggesting that such concerns do not threaten the validity of the results.
The test of the two-stage modelling of TMT support requires longitudinal data. However, the data used
to test the model is cross-sectional. Additionally, several researchers suggest that TMT support is driven by
different factors depending on the life cycle of the innovations (Agarwal and Prasad, 1997; Carlson and
Zmud, 1999; Karahanna et al., 1999). Future researchers should adopt a longitudinal study approach to
examine the stage factors of TMT support as well as the other factors which may impact TMT support for
MCS innovations at different stages of their life cycle.
Furthermore, this study concentrated its analysis on four antecedents of TMT support for MCS
innovations. Future studies should consider other variables that may drive TMT support for MCS
innovations, such as industry-related pressure, competitors' behaviour with MCS innovations, and the
type of business strategy adopted by organisations. Consideration should also be given to concurrently
investigating the antecedents and consequences of TMT support for MCS innovations within a nomological
network.
The conceptual model of this study provides a framework for future researchers wishing to build and
test a nomological network examining the antecedents and consequences of TMT support for integrated
MCS innovations. The results indicate that TMT support for an integrated MCS innovation arises from a
complex set of factors that simultaneously influence TMT behaviour towards integrated MCS innovations.
Understanding this complexity is important to both researchers and practitioners in understanding how
organisations successfully adopt, implement, and use IT-driven MCS innovations.
17J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
18. Appendix A. Survey
A.1. Part 1: Management practices at the level of top management in your organisation
The questions in this part focus exclusively on the strategic level management within your organisation.
They relate to processes, actions and collaborations among top management team members. Top
management team members (TMT) refer to the Chief Executive Officer (CEO), Chief Operational Officer
(COO), Chief Financial Officer (CFO), and other senior executives responsible for the various functions and
business groups. TMT could also include the Senior Information Systems executive (for example the Chief
Information Officer “CIO”).
Please indicate the extent to which you agree or disagree with each of the following statements by
circling the relevant number:
A.1.1. Top management team members in my organisation are knowledgeable about…
A.1.2. Top management team members in my organisation…
No basis for
answering
Strongly
disagree
Neutral Strongly
agree
BEK1 The potential and limitations of the
organisation's current information
and communication technologies.
0 1 2 3 4 5 6 7
BEK2 The potential and limitations of
emerging information technologies.
0 1 2 3 4 5 6 7
BEK3 How competitors are applying
information technologies.
0 1 2 3 4 5 6 7
No basis for
answering
Strongly
disagree
Neutral Strongly
agree
KSC1 Share ideas/experiences with clients and suppliers. 0 1 2 3 4 5 6 7
KSC2 Share ideas/experiences with external experts. 0 1 2 3 4 5 6 7
KSC3 Gather information/ideas from competitors. 0 1 2 3 4 5 6 7
KSC4 Develop new strategies/business opportunities by
doing their rounds.
0 1 2 3 4 5 6 7
KSC5 Make regular contacts with each other through
scheduled meetings/social events.
0 1 2 3 4 5 6 7
KSC6 Attend business conferences/tradeshows. 0 1 2 3 4 5 6 7
KSC7 Share information/ideas/experiences with operational
level managers.
0 1 2 3 4 5 6 7
KSC8 Demonstrate and model their expertise to other
members within the team.
0 1 2 3 4 5 6 7
KSC9 Use collaborative technologies (such as decision
support systems, online discussion, and email) to
share knowledge and expertise with other members
within the team.
0 1 2 3 4 5 6 7
KSC10 Engage in creative and useful conversations
with information technology managers to
share knowledge and expertise.
0 1 2 3 4 5 6 7
KSC11 Use metaphors and analogies in conversations
for strategy development, strategy articulation, and
concept creation.
0 1 2 3 4 5 6 7
18 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
19. A.1.3. The CIO (or most senior IT manager) in my organisation is knowledgeable about…
(continued)
No basis for
answering
Strongly
disagree
Neutral Strongly
agree
KSC12 Engage in dialogue with subordinates to
exchange various ideas and knowledge.
0 1 2 3 4 5 6 7
KSC13 Converse with competitors to gather
information/ideas which can be used in the
organisation.
0 1 2 3 4 5 6 7
KSC14 Plan strategies by using academic/practice-related
literature.
0 1 2 3 4 5 6 7
KSC15 Plan strategies by using computer simulation
and forecasting.
0 1 2 3 4 5 6 7
KSC16 Gather and summarize information from different
department/business units and make it available for
distribution to other people in the organisation.
0 1 2 3 4 5 6 7
KSC17 Build databases on products/services by gathering
management and technical information.
0 1 2 3 4 5 6 7
KSC18 Convene meetings where new concepts and
knowledge are discussed, refined, and documented
in order to be shared with other people within the
organisation.
0 1 2 3 4 5 6 7
KSC19 Use information technologies to collect/transmit
newly created concepts.
0 1 2 3 4 5 6 7
KSC20 Attend business/technology-related events
(such as workshops and seminars).
0 1 2 3 4 5 6 7
KSC21 Engage/liaise with peers and subordinates. 0 1 2 3 4 5 6 7
KSC22 Experiment with new management practices to
improve their knowledge.
0 1 2 3 4 5 6 7
KSC23 Are keen to understand different groups' visions
(such as IT executives, functional managers, etc.).
0 1 2 3 4 5 6 7
KSC24 Read business/IT publications. 0 1 2 3 4 5 6 7
KSC25 Use “learning by involvement” in different projects
to increase their knowledge and expertise.
0 1 2 3 4 5 6 7
KSC26 Foster a work environment that is supportive of
“learning-by-doing” and risk-taking.
0 1 2 3 4 5 6 7
No basis for
answering
Strongly
disagree
Neutral strongly
agree
CIOK1 The IT infrastructure required to
support the organisation's business
intelligence needs.
0 1 2 3 4 5 6 7
CIOK2 The potential and limitations
of relevant emerging information
technologies.
0 1 2 3 4 5 6 7
CIOK3 How competitors are using business
intelligence technologies.
0 1 2 3 4 5 6 7
CIOK4 Timing and investment strategies in
emerging technologies.
0 1 2 3 4 5 6 7
CIOK5The organisation's present and future
products and services.
0 1 2 3 4 5 6 7
CIOK6 What is considered best practice in
the organisation's industry.
0 1 2 3 4 5 6 7
CIOK7 The business activities of the
organisation's competitors.
0 1 2 3 4 5 6 7
A.1.2 (continued)
19J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
20. A.1.4. CIO (or most senior IT manager) involvement with other business executives
A.2. Part 2: Top management support
A.2.1. Please indicate the extent to which the top management team of your organisation believes that:
A.2.2. Please indicate the extent to which top management team of your organisation actively participates in:
No basis for
answering
Not at all To some extent To a great
extent
CIOTMT1: To what extent is the CIO
(or most senior IT manager) in
your organisation involved with
top management team members?
0 1 2 3 4 5 6 7
CIOTMT2: In the hierarchical structure
of your organisation, how many
management layers are there
between the CIO (or most senior
IT manager) and top management
team members?
………….. Layers
No basis for
answering
Not at
all
To some
extent
To a
great
extent
TMSB1 Business Intelligence Systems have the
potential to provide business benefits to the
organisation.
0 1 2 3 4 5 6 7
TMSB2 Business Intelligence Systems create
competitive advantages for the organisation.
0 1 2 3 4 5 6 7
TMSB3 Business Intelligence Systems are
accessible to the relevant managers
of the organisation.
0 1 2 3 4 5 6 7
TMSB4 Business Intelligence Systems are important
to support business activities/strategies of the
organisation.
0 1 2 3 4 5 6 7
TMSB5 Business Intelligence Systems are secure
technologies to support the business
activities/strategies of the organisation.
0 1 2 3 4 5 6 7
No basis for
answering
Not at
all
To some
extent
To a
great
extent
TMSP1 Articulating the vision for organisational use of
Business Intelligence Systems.
0 1 2 3 4 5 6 7
TMSP2 Formulating the strategy for the organisational
use of Business Intelligence Systems.
0 1 2 3 4 5 6 7
TMSP3 Establishing goals and standards to monitor
Business Intelligence Systems projects.
0 1 2 3 4 5 6 7
20 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
21. A.3. Part 3: Demographic information
Please tick the appropriate box in each of the following tables that best describe your organisation:
A.4. Organisation size
A.4.1. Organisation profile
(a) Number of employees ✓
Less than 50
50 to below 200
200 to below 500
500 to below 1000
1000 or more
(b) Estimated gross revenue in 2004 ✓
Less than $50 million
$50 million to below $100 million
$100 million to below $500 million
$500 million to below $1 billion
$1 billion to below $5 billion
$5 billion to below $10 billion
$10 billion or more
Industry type ✓
Agricultural/mining/construction
Banking/finance/insurance
Consulting/professional service
Education/research
Government
Health care
Hospitality/travel/tourism
Manufacturing
Media/entertainment/publishing
Real estate
Retail/wholesale/distribution
Telecommunications
Transportation/logistics
Others (Please specify)
21J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
22. A.5. Respondent profile
A.5.1. Please select one from the following that best describes your current job title
A.5.2. Which of the following categories describes………
A.5.3. Gender
Thank you for your time and co-operation in completing this survey.
Business Executive/Manager ✓
Managing Director
Chief Executive Officer
General Manager
Chief Financial Officer
Chief Operating Officer
Business Development Manager
Branch/Division Manager
Business Analyst
Team Leader
Others (Please specify)
IT executive/manager ✓
Director of MIS
Chief Information Officer
Manager of MIS
Business Intelligence Manager
Senior Systems Analyst
Project Manager
Business Intelligence Consultant
Applications Development Manager
Applications Support Leader
Others (Please specify)
Your years of experience ✓
5 years to below 10 years
10 years to below 15 years
15 years to below 20 years
20 years to below 25 years
25 years to below 30 years
30 years or more
Your age ✓
b25 years
25–30 years
31–40 years
41–50 years
51–60 years
61+ years
1. Male □ 2. Female □
22 J. Lee et al. / International Journal of Accounting Information Systems 15 (2014) 1–25
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