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CONCEPTUAL MODEL FOR EXAMINING THE FACTORS THAT
INFLUENCE THE LIKELIHOOD OF COMPUTERISED ACCOUNTING
INFORMATION SYSTEM (CAIS) ADOPTION AMONG MALAYSIAN
SMES
Wan Nur Syahida Wan Ismail ¹, Azwadi Ali ²
¹² Department of Accounting and Finance, Universiti Malaysia Terengganu, Malaysia.
[email protected] , [email protected]
Abstract
The purpose of this study is to propose and discuss a conceptual model for investigating the influential
factors of computerised accounting information systems (CAIS) adoption in Malaysian SMEs. This study
examines the existing empirical studies in information technology (IT) and information systems (IS) adoption
research related to adoption at organizational level. In particular, the Technological-Organizational-
Environmental (TOE) framework has been widely used in examining the factors influencing IT adoption.
However, studies attempted to use this framework to measure CAIS adoption are limited. In contrast to other
theories commonly used for explaining innovation adoption, TOE framework does not only cover the
technological aspects but more importantly also explores their organizational and environmental contexts.
Hence, this model provides a complete analysis of the possible aspects to be considered. The inclusion of
Diffusion of Innovation (DOI) theory in the technological context and the application of Thong’s SME model
make the proposed model more robust. A summary and conclusion along with research contribution,
limitations, and the direction for future research are also presented in this paper.
Keywords: Computerised Accounting Information System, Information technology, TOE framework, DOI
theory, Thong’s Model, Small-and medium enterprises.
1.0 INTRODUCTION
Small- and Medium-sized
Enterprises (SMEs) have grown in
importance in the global economy (Ang &
Hussin, 2012). They also have high
potential to expand to a larger scale.
Previous research repeatedly showed that
financial management is crucial for the
continuity of SMEs (e.g., Halabi et al.,
2010; Fadhil & Fadhil, 2010; Ahmad &
Seet, 2009; Dyt & Halabi, 2007; McMahon,
2001; Peel & Wilson, 1996). According to
McMahon (2001), financial management in
SMEs could be improved through upgrading
of their financial reporting systems. As
such, SMEs’ owner-managers need a good
record-keeping system that allows them to
maintain control of their finance, and the
most important use is to aid the owner-
managers in making decisions about the
firms (Davis et al., 2009). This accounting
report also provides financial information
which could inform owners of the
consequences of their firms’ operations and
the effects of their past decisions. Therefore,
it serves as a good basis for realistic future
plans (Butkevicius, 2009). The system that
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records all the financial transactions of a
business or organizations is known as
accounting information systems (AIS).
Information technology (IT) offers
many benefits in order to keep the financial
information sharp, clean and well organized.
The important question raise from this issue
is whether firms ready to implement changes
in order to have effective financial
management that will enable them to
analyze results, to interpret, to forecast
future performance and improve their
business decisions. Therefore this study is
conducted to examine the factors that
influence the SMEs in Malaysia to adopt IT
in their accounting processes since effective
financial management could easily be
obtained today with the help of related IT
such as computerized accounting
information systems (CAIS).
The previous studies on AIS are
mainly focused on issues of CAIS
effectiveness (Kouser et al., 2011; Ismail
2009), CAIS threats (Abu-Musa, 2005),
selection of CAIS software (Adhikari et al.,
2004; Adhikari & Zhang 2003) and user
satisfaction (Illias et al., 2009; Nazem
1990). Only a handful of studies (Fowzia &
Nasrin, 2011; Breen et al., 2003) explore the
factors that influence the CAIS adoption.
However, none of them have empirically
validated a conceptual framework that can
consider all the aspects of the organizational
level to represent the case of CAIS adoption
in general and SMEs in particular.
Therefore, the basis for selection of
the hypotheses for this research was based
on previous IT and information system (IS)
adoption literature at the organizational
level. The justification and formulation of
subsequent hypotheses have been made on
adequate evidence of the significance of the
relationships in prior studies with a
probability that they will be proven
significant when implementing the adoption
of CAIS.
2.0 THEORIES USED IN
IT/IS ADOPTION
Information technology is a key
driver of many technological innovation and
organizational evolution including CAIS
(Liang et al., 2010). Liang et al. (2010) has
listed several theories that have been
proposed to explain the widespread issues of
IT such as Resource-based View (RBV),
Transaction Costs, Media Richness Theory
and Coordination Theory. Each theory has
different applicable research domains.
Regarding IT adoption, many
theoretical models have been used to
examine the adoption of IT/IS innovations
such as Technology Acceptance Model
(TAM) (e.g. Li et al., 2011; Vance et al.,
2008; Grandon and Pearson, 2004; Igbaria et
al., 1997), Theory of Planned Behaviour
(TPB) (e.g. Grandon et al., 2011; Harrison
et al., 1997), Combined TAM and TPB (e.g.
Riemenschneider et al. 2003; Chatzoglou et
al., 2010); TAM2 (e.g. Venkatesh 2000),
Diffusion of Innovation Theory (DOI)
(e.g.Premkumar 2003), Resource-Based
View (RBV) (e.g. Ramanathan et al., 2012;
Jacks et al., 2011; Mehrtens et al. 2001),
Stage Theory (e.g. Poon & Swatman, 1999),
and Unified Theory of Acceptance and Use
of Technology (UTAUT)(e.g. Kijsanayotin
et al., 2009; Fowzia & Nasrin, 2011;
Anderson & Schwager, 2003).
However, according to Alam
(2009) and Alatawi et al. (2012), the
literature on technology adoption by
businesses suggests that most research are
based on the Theory of Planned Behaviour
(TPB) (Ajzen, 1991), Technology
Acceptance Model (TAM) (Davis, 1989),
The diffusion of Innovation (DOI) (Rogers,
1995), The Technology-Organization-
Environment Model (TOE) (Tornatzky &
Fleischer, 1990) and the Resource-based
Theory (RBV) (Wernerfelt, 1984). The
DOI, TPB, TAM and TOE theory are highly
applicable in predicting adoption behaviour
of the firm in considering new technology
while RBV has been used to provide the
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theoretical underpinning to understand how
the adoption of innovation is linked to firm
performance (Ramanathan et al., 2012).
As TAM and TPB only focus on
technological perspective which based on
perceptions and attitudes, they have
commonly been used as groundwork for IT
research at the individual level (Salleh and
Rohde, 2005). As the purpose of this study
is to examine the CAIS adoption among
SMEs, the theories and models at the
organizational level are more applicable.
After carefully reviewing the literatures, this
study found that the TOE framework is a
suitable framework for the study of factors
influencing the adoption of IT/IS in any
stages as it allows us to evaluate the
importance of different factors which affect
the propensity to adopt IT (Lin & Lin,
2008). The TOE framework also is
consistent with Rogers’ (1983) theory
(Orturk, 2010) which is one of the dominant
theory used to examine organizational
adoption of IT over the prior two decades
(Yoon, 2009).
2.1 Technological-Organizational-
Environmental (TOE ) framework
Tornatzky and Fleischer (1990) are
credited with being the first to develop the
TOE framework to study the adoption of
technological innovations. Tornatzky and
Fleischer (1990) developed a framework for
organizational adoption based on
Contingency Theory of Organizations
(Arpaci et al., 2012). According to Arpaci
et al. (2012), the former theory postulates
that an effective organization should have a
structure which is consistent with its
environmental needs. The effectiveness of
an organization is based upon its fitness
towards both internal and external factors.
Tornatzky and Fleischer (1990) believed
that the adoption and assimilation of new
technologies in a company were under the
influence of three major dimensions –
Technological-Organizational-
Environmental. Therefore they developed
the TOE framework to determine what
factors influence a firm’s adoption decision.
The TOE framework identifies three aspects
of a firm’s contexts that influence the
adoption and implementation of a
technological innovation, namely
technological, organizational and
environmental aspects.
The technological context describes
both the existing technologies in use and
new technologies relevant to the firm; the
organizational context refers to
characteristics of the organization; and the
environmental context is the arena in which
a firm conducts its business, referring to its
industry, competitors, and dealings with the
government (Oliveira & Martins, 2010).
These three groups of contextual factors
influence a firm’s intent to adopt an
innovation, effect the assimilation process
and eventually the impacts of the innovation
on organizational performance (Zhu et al.,
2004) and therefore has been the choice of
many prior studies in technological
adoption.
Many researchers also agreed that
TOE provide an excellent theoretical
foundation for exploring IS adoption
behaviour within SMEs. For example,
Mehrtens et al. (2001) adopt TOE
framework for investigating the adoption of
internet in seven SMEs. Lertwongsatien and
Wongpinunwatana (2003) show the
suitability of the TOE framework for
studying the e-commerce adoption study in
Thailand SMEs. Ramdani et al. (2009)
adopt the TOE framework for predicting the
potential enterprise systems adopters in
SMEs in England. Drawing upon the
empirical evidence detailed above, the TOE
framework is an appropriate theoretical
foundation for investigating CAIS adoption
in Malaysian SMEs.
TOE does, however, not aim to
offer a concrete model describing the factors
that influence the adoption process; it is
rather taxonomy for classifying factors in
their respective context (Ven & Verelst,
2011). The main contribution of this
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framework is that it encourages the
researcher to take into account the broader
context in which the adoption takes place
(Ven & Verelst, 2011). The constructs
used under each context usually were
selected from previous studies which were
found suitable with the condition of the
technology that was studied. However some
researchers suggested that to identify
specific technological, organizational and
environmental factors and to establish the
causal relationships needed for hypothesis
development, the TOE framework should be
combined with other theories (Awa et al.,
2011; Henderson et al., 2012; Chong &
Chan, 2012; Alatawi et al., 2012).
According to Awa et al. (2011), integrating
TOE with other models offering larger
number of constructs than the original and
provides richer theoretical lenses to the
understanding of adoption behavior (Awa et
al., 2011). Literatures have proved that
many studies combined TOE frameworks
with other theories to better explain IT
adoption (Alatawi et al., 2012).
From the literature review, the
present study revealed that DOI theory is the
main theory that is used together with the
TOE framework (e.g. (e.g. Chong & Chan,
2012; Picoto et al., 2012; Hossain &
Quaddus, 2011; Low et al., 2011; Wang et
al., 2010; Ramdani et al., 2009).
2.2 Diffusion of Innovation Theory
(DOI)
DOI theory by Rogers (1995) is a
theory of how, why, and at what rate new
ideas and technology spread through
cultures, operating at the individual and firm
level (Oliveira & Martins, 2011). DOI
provides insights into the innovation or
technological factors that influence the
adoption of innovation (Rogers, 1995).
Originally, innovation characteristics in DOI
was presented in the context of the
innovation adoption at the individual level,
however, Rogers (1995) argued that the
characteristics of innovations could also be
applied to the innovation adoption models at
the organizational level (Picoto et al., 2012;
Hameed & Counsell, 2012). Hence, DOI is
used in many studies to study innovation
adoption issues by firms (e.g. Tan et al.,
2009; Ramdani et al., 2009; Ramdani &
Kawalek, 2007; Hussin & Noor, 2005; Seyal
& Rahman, 2003; Premkumar & Roberts,
1999; Thong, 1999).
One of the main contributions of
DOI is its set of innovation attributes. DOI
suggests that innovations possess certain
attributes, which as perceived by adopters,
regularly determine the adoption of
innovation (Ozturk, 2010). The innovation
attributes include relative advantage,
compatibility, complexity, trialability and
observability (Roger, 1995). Each
characteristic helps to reduce a potential
adopter’s uncertainty regarding the
perceived benefits of innovation adoption
(Yoon, 2009). Consequently, innovations
which are perceived as having more relative
advantage, compatibility, trialability,
observability and having less complexity
will be adopted more rapidly than other
innovations (Rogers, 1995).
Among these characteristics, the
most frequently adopted factors are relative
advantage, compatibility and complexity.
They were chosen by many studies due to
frequently found as significance factors in
IT/IS adoption in many empirical researches
(e.g. Ramdani et al., 2009; Thong, 1999; Al-
Qirim, 2007b; Premkumar & Roberts,
1999). This is consistent with Tornatzky
and Klein (1982) which identified only three
characteristics of an innovation which would
be the most important: relative advantage;
compatibility; and complexity. This is based
on the finding of their meta analysis studies
on 75 innovation articles.
The more frequent use of DOI with
TOE framework also seems to be driven by
the fact that this framework is consistent
with TOE, where Rogers (1995) highlighted
individual as well as internal and external
characteristics of the organization (Alatawi
et al., 2012). Based on the DOI theory at
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firm level, innovativeness is related to such
independent variables as individual (leader)
characteristics, internal organizational
structure characteristics and external
characteristics of the organization (Rogers,
1995).
Accordingly, this study use the
TOE framework to specify the categories of
factors (Technological, Organizational and
Environmental) affecting CAIS adoption.
The technological factors are taken from
DOI theory, while the organizational factors
and environmental are adapted from
previous literatures. As the area in CAIS
adoption using this framework is among
pioneer studies, the basis for the selection of
the construct and formulation of subsequent
hypotheses have been made on adequate
evidence of the widely known significance
constructs in previous studies, with the
assumption that they will be proven
significant when implementing the adoption
of CAIS.
Derived from a strong theoretical
background, satisfactory empirical
validations, and suitability for the contexts
examined for SMEs and CAIS, it was
decided that TOE supplemented with DOI
theory would serve as a guiding framework
for this research.
2.3 DTOE framework for SMEs
(Thong’s (1999) Model)
As stated previously, in TOE
framework, the process by which a firm
adopts and implements technological
innovations is influenced by three aspects:
the technological context, the organizational
context, and the environmental context.
Thong (1999) on the other hand suggested
TOE theory in four dimensions when
studying SMEs sectors.
Extending the TOE theory, Thong
(1999) argued that based on SMEs highly
centralized structures, the CEOs or owner-
managers make most of the critical
decisions. As such, Thong (1999)
conceptualized and verified the importance
of a fourth dimension (besides
technological, organizational and
environmental) which has been classified as
CEO’s characteristics. Thong’s study
distinguished from others as most of the
study added together the characteristic of the
decision makers in organizational context
(e.g. Scupola, 2009; Chang et al., 2007;
Premkumar & Roberts, 1999; Kuan & Chau,
2001).
Following Thong (1999), Al-Qirim
(2007a) and Seyal and Rahman (2003) also
distinguished decision-maker context from
the organizational context, consequences
TOE framework in four dimensions:
decision-makers, technological,
organizational and environmental context
(DTOE).
In agreement with the significant
role played by the owner-manager’s in
SMEs, this study shall apply Thong’s (1999)
model by including the decision-maker
characteristics as one of the main variables
together with technological, organizational
and environmental context. However, this
study does not adopt all the variables in
Thong’s model. Several modifications have
been made on original model. By reviewing
previous technological innovation literature,
this study integrated and developed its own
variables which identified as suit with the
CAIS condition.
3.0 PROPOSED
CONCEPTUAL MODEL
The objective of this study is
related to the likelihood of CAIS adoption
which is targeted to CAIS non-adopters. As
shown in figure 1, using DTOE and DOI
theory, the model proposes that there are
significant relationships between decision
maker, technological, organizational and
environmental contexts and the likelihood of
CAIS adoption among non-adopters.
This conceptual model describes
the factors that are hypothesized to influence
the CAIS adoption. The decision-maker
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contexts comprised of the owner-manager
IT knowledge, owner-manager attitude
towards IT and owner-manager
commitment. The organizational context
contains factors such as organizational
readiness, employees IT knowledge and
satisfaction with manual systems. Although
none of the studies were found to be related
specifically to CAIS, these variables have
been gathered from the contemporary IS/IT
field of research and deemed significant to
be considered as the factors in the
organizational context for describing the
adoption of CAIS in Malaysia. The
environmental context relates to the factors
such a vendor support, competition and
government influence.
4.0 HYPOTHESES
DEVELOPMENT
Despite the lack of research which
particularly focused on CAIS adoption
factors and SMEs, general IT and IS
adoption studies however have been
extensively researched. Since CAIS is an
important sub-set of overall small business
IT research (Premkumar & Robert, 1999),
this study will adapt the finding of IT/IS
adoption literature to suit the current study.
In this research, the endogenous
variable is the likelihood of CAIS adoption
which is defined as the willingness of non-
adopters to adopt and utilize the CAIS to
support daily recording of business
transaction and decision making in the
business.
There are many adoption factors
have been studied in prior research.
However, it is not possible to study all the
factors identified in the technological
innovation literatures. Furthermore,
innovation researchers have argued that it
may not be possible to develop a unifying
theory of innovation due to the fundamental
differences between innovation types
(Thong & Yap, 1995). Hence, as previously
mentioned, this study has selected factors
that are more applicable to the adoption of
CAIS. These selected factors were based on
the DTOE context. Each of the factors is
discussed below, and a corresponding
hypothesis enunciated.
4.1 Decision-maker context
In organization, the decision for IT
adoption process is directly affected by top
management. In SMEs, top management
usually refers to the chief executive officers
(CEO’s) or owner-managers of the firm. In
SMEs studies, CEO and the owner-manager
was used interchangeable since in most
cases CEO and owner-manager is the same
person (Hussin & Noor, 2005; Thong,
1999).
In SMEs, it is often difficult to
separate SMEs owners from their firms
since all decisions from daily functions or
activities to future investments are made by
them (Thong, 1999). This also refers to IT
adoption decision from planning to
implementing and afterwards, maintaining
and upgrading the system. According to
Awa et al. (2011), IT adoption depends
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largely on the functional, and/or emotional
feelings of decision makers, which reflect
their attitudes, perceptions and motivations
towards IT adoption. As revealed in
Antlova’s (2009) study, he found that one of
the significant barriers to innovation
acceptance in SMEs is resistance to
organizational changes, especially in
connection with older owner-managers. For
this reason, Thong and Yap (1995)
suggested the rate at which a small business
changes depends not only on factors like
business size or market forces, but also on
the abilities and inclinations of the owner-
manager and the extent to which he is able
to prepare to devolve management. The
owner-manager therefore is an entrepreneur
figure who is crucial in determining the
innovativeness of the business. Hussin and
Noor (2005) pointed that the role of owner-
manager undoubtedly is very important in
SMEs, especially in a developing country
like Malaysia. This is because there is a
large power distance in the Malaysian
culture and therefore, the decision making
will be centered on the owner-manager
(Hussin & Noor, 2005).
Decision-maker’s characteristic is a
key adoption predicator of Thong’s (1999)
DTOE model. Thong (1999) separated
decision-makers characteristics from
organization in TOE and gave it boost to
bring the model to decision-maker,
technology-organization-environment
(DTOE). He proposed that the four
conceptual adoption predicators assume a
more detailed set of factors that assist to
predict the likelihood of IT adoption among
SMEs.
This study adopted three decision-
makers characteristics from previous
TOE/DTOE literatures that showed some
relevance strength to this study which
include owner-manager’s IS/IT knowledge,
owner-manager’s attitude towards IT and
owner-manager’s commitment.
4.1.1 Owner-manager’s IT Knowledge
(OM_IK)
Lack of understanding about IT is a
frequently cited reason for failure of small
businesses to consider computer
opportunities since decades ago (DeLone,
1988). Thong and Yap (1995) noticed that
many SMEs rejected the notion of IT in their
business as they had no idea of the benefits
that IT could potentially offer. This is due
to lack of basic knowledge and awareness of
IT among owner-manager.
According to Hameed and Counsell
(2012), IT knowledge of owner-manager is
important to realize the benefits of an
innovation adoption. Some knowledge of IT
possessed by the owner-manager also can
add value to the organization in order to
select the software with the information that
they require from the vendor (Proudlock et
al., 1999). Study by Caldeira and Wald
(2002) indicated that the lack of expertise to
select and adopt the software was one of the
reasons why the adoption has not succeeded.
The significant relationship
between the owner-manager IT knowledge
and the adoption of innovation technology
has been revealed by many studies. Study
by DeLone (1988) suggested that in firms
where the CEO is familiar with computers
and is involved in computerization, the
computer operations are more successful.
Thong and Yap (1995) found that small
businesses are more likely to adopt IT when
the owner-manager possessed greater IT
knowledge. Nguyen (2009) found the
understanding of IT and innovation skills
contribute substantially to the likelihood of
IT adoption. Later, Antlova (2009) stressed
that one of the barriers preventing
acceptance of IT by SMEs is connected to a
missing information strategy and an
insufficient knowledge of IT on the part of
the owner or manager of the organization.
And recently, Huy (2012) suggested the
knowledge of the information technology
possessed by owner-manager has an effect
on the adoption of IT and has a positive
influence on the degree of use of innovation
technology.
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Regarding CAIS, based on the
above reason, this study predicted that the
greater the understanding the owner-
manager has of IT, the more likely that they
will adopt CAIS. Therefore, this study
hypothesizes that:
H1a: There is a positive relationship
between owner-manager’s IT knowledge
and the likelihood of CAIS adoption.
4.1.2 Owner-manager’s Attitude
towards IT (OM_AI)
Owner-managers’ attitude towards
IT refers to the owner-managers’ perception
of IT to the degree of which they are agree
or disagree with the benefits that IT could
offer to their firms (Thong & Yap, 1995).
According to Rogers’ (1983), formation of a
favourable or unfavourable attitude towards
an innovation takes place before a decision
to adopt is made. In the case of SMEs, as
the main decision-maker is from the owner-
manager, his/her perception of the adoption
of IT is of prime importance (Rogers, 1983).
The owner-manager’s attitude
towards IT could relate to the IT knowledge
of the owner-manager. As such, a number
of studies suggested the greater the
understanding that the top management or
owner-manager has of IT, the more likely
that they will adopt IT and the more
successful the adoption (Nguyen, 2009;
Alam, 2009; Thong & Yap, 1995). The
explanation might be the owner-manager
who has been using the computer for some
time is able to know the advantages and
disadvantages of the technology (Alam,
2009). Consequently, computer skills of the
owner-manager could influence the attitude
towards IT and in turn increase the intention
to adopt innovation system among SMEs.
In another perspective,
implementing a new system requires
financial commitment. This includes the
initial cost of software and hardware, the
cost of personnel training and development
and the post implementation costs (Nguyen,
2009). For these reasons, the owner-
managers have to see or at least believe that
new IT will bring advantages to the firm.
Awa et al. (2011) argued from RBV point of
view, SMEs develop internal skills,
competences and capabilities subject to top
management perspectives and attitudes
towards IT adoption.
Therefore, many studies suggested
that owner-manager’s perception of IT is
that such tools that can provide them with
some advantage in the business environment
(Harrison et al., 1997; Lee & Runge, 2001;
Thong, 1999; Thong & Yap, 1995; Poon &
Swatman, 1999). For this point many
researchers have stressed the importance of
the attitudes of owner-managers towards
innovation in the adoption of the IT (Thong
& Yap, 1995; Grandon & Pearson, 2004;
Caldeira & Ward, 2002; Seyal & Rahman,
2003; Mehrtens et al., 2001; Kuan & Chau,
2001).
From the above discussion, it can
be said that the more positive perception that
the owner-manager have towards IT, the
higher the chances that they will adopt the
CAIS. This study therefore predicted that:
H1b: There is a positive relationship
between owner-manager’s attitude towards
IT and the likelihood of CAIS adoption.
4.1.3 Owner-manager’s Commitment
(OM_CM)
Owner-manager’s commitment
refers to the level of commitment by the
owner-manager towards the CAIS adoption.
Varukolu and Park-Poaps (2009) defined
owner-manager commitment as the degree
to which the values and perceptions of the
management are in favour of and open to
technology adoption.
DeLone (1988) noticed that top
management’s commitment is not only
important for initial decisions regarding
computerization, but also for ongoing
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computer decisions because computerization
is a continuous and evolving process. In
addition, the owner-manager’s commitment
in a variety of information and participation
in the implementation of CAIS encourages
users to develop positive attitudes towards
the use of CAIS (Kouser et al., 2011).
Ifinedo (2012) used the term
owner-manager’s support and owner-
manager’s commitment interchangeably and
his study found support for the relevance of
this factor in the successful adoption of e-
business. As such, when the owner-manager
of SMEs perceived an innovation
technology to be valuable, they would
manage IT-related activities within the
organization and outline things that would
affect the performance of the system
adopted, such as the strategies, policies and
future directions of the organization (Wang
et al., 2006). Therefore on many occasions,
failed implementation of technological
innovation was attributed to the lack of top
management’s commitment and support
(Yang et al., 2012; Varukolu and Park-
Poaps, 2009).
At the same time, if the owner-
manager has greater interest in IT, they will
give full commitment and could do a better
job in strengthening the prospect brought by
the adopted IT/IS and could encourage their
employees to utilize the IT/IS to generate
superior performance (Yang et al., 2012).
This is because owner-manager acts as
change agents in the adoption process of
technological innovations. Where such
commitment and support lacking, the
acceptance of technologies such as CAIS
tend to suffer (Ifinedo, 2011; Chatzoglou et
al., 2010; Igbaria, 1990; Igbaria et al., 1997).
Study by Hussin and Noor (2005)
proved that there was a linear relationship
between owner-manager’s commitment to
IT and e-commerce adoption. Past studies
have also shown that owner-manager
commitment’s and support to favour the
acceptance of technological innovations in
adopting organizations, including SMEs
(e.g. Ifinedo, 2012; Grandon & Pearson,
2004; DeLone, 1988; Iacovou, 1995;
Premkumar & Roberts, 1999).
Regarding CAIS, it could be
assumed that top management’s vision for
the use of technologies determines the levels
of support and policies for this technology
adoption. This means when owner-manager
understands the importance of technological
innovations such as CAIS in their
organizations, they tend to play a crucial
role in influencing other organizational
members to accept the use of such
innovations. Consequently, this study
believes that owner-manager’s commitment
is likely to shape the firm’s technology
adoption activities. At this point, owner-
manager’s commitment is suggested to
influence system success, with regard to the
new adoption. Based on the arguments, the
following hypotheses therefore formulated:
H1c: There is a positive relationship
between owner-manager’s commitment and
the likelihood of CAIS adoption.
4.2 Technological Context
As per TOE/DTOE, the
technological context of an organization is
important in influencing the adoption and
implementation of new IT/IS. Tornatzky &
Fleischer (1990) describes technological
context as both internal and external
technologies relevant to the firm. In more
detail, technological context refers to the
innovation that is to be adopted by the
organization (Teo et al., 2004) or
characteristics that relates to the
technologies available to an organization
(Chau & Tam, 1997). Its main focus is on
how technology characteristics themselves
can influence the adoption process (Chau &
Tam, 1997). It includes current practices
and equipment internal to the firm, as well
as the pool of available technologies
external to the firm (Tornatzky & Fleischer,
1990).
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The technological context in which
a firm operates plays an obvious role in
determining the firm’s adoption activity.
Decisions to adopt technology depend on
what is available, as well as how the
available technology fits with the firm’s
current technology (Tornatzky & Fleischer,
1990).
This research considers three
innovation characteristics in the context of
CAIS adoption: relative advantage,
compatibility and complexity. All these
constructs have been identified on the basis
of a Diffusion of Innovation (DOI) theory
by Roger (1983). Researchers have
combined aspects of DOI with TOE to
increase understanding of organizational IT
adoption (Oliveira & Martins, 2011).
Specifically, they suggested that the
technological context in TOE includes the
knowledge of innovation characteristics
from DOI (Rogers, 1995).
Roger’s (1983) model of
technological innovation in DOI Theory is
widely accepted in information systems
research. Roger (1983) identified five
critical characteristics of the innovation that
influences its adoption: relative advantage,
compatibility, complexity, trialability and
observability. However, among them,
compatibility, relative advantage and
complexity were found to have consistent
associations with innovation behaviours
(Tornatzky & Klein, 1982; Kuan & Chau,
2001).
Following the suggestion, this
study decides to examine these three
technological characteristics as the factors
contributing to the likelihood of CAIS
adoption. Therefore, the constructs will be
analyzed one by one for the formulation of
the hypotheses.
4.2.1 Relative Advantage (R_ADV)
According to DOI theory, Roger
(1995) defined relative advantage as the
degree to which an innovation is perceived
as being better than the idea it supersedes.
The degree of relative advantage is generally
expressed as the degree of perceived
benefits that the innovation may provide to
the organization, and thus, relative
advantage and perceived benefits are used
interchangeably in IT adoption literature
(Henderson et al., 2012; Oliveira & Martins,
2010; Iacovou et al., 1995; Yoon, 2009). In
CAIS context, it refers to the degree to
which the CAIS is perceived as providing
greater benefit for firms compared to the
manual system. DOI theory suggests that the
relative advantage of an innovation
positively influences an organization’s
propensity to adopt the innovation.
Since being proposed by Rogers in
DOI as a key factor affecting the adoption of
innovations, relative advantage has been
consistently found to have a significant
influence on SMEs adoption of innovation
technologies. For examples, Premkumar
and Roberts (1999) found that organizations
adopt the innovation technology because
they perceive a relative advantage of the
technology compared to traditional methods.
Many other prior IT adoption studies that
employ the TOE framework also suggested
relative advantage as one of most important
factors that affects firm adoption of an IT
innovation (e.g. Chau & Tam, 1997; Thong,
1999; Ramdani et al., 2009; Seyal et al.
,2007; Al-Qirim, 2007b; Premkumar &
Roberts, 1999; Ghobakhloo et al., 2011;
Low et al., 2011; Ifinedo, 2011; Shiau et al.,
2009; Hung et al., 2010). Based on these
studies, it is highly possible that when
organization perceived the benefits of the
new systems, they are more willing to adopt
the technology.
The above discussions were in line
with the argument from Premkumar et al.
(1994) who suggested that positive
perception of the benefits of the technology
should provide an incentive for users to use
the technology. As in the CAIS context,
firms that recognize the true potential of
CAIS should realize the need to fully adopt
CAIS to realize the benefits. From the
discussion, this study posits:
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H2a: There is a positive relationship
between relative advantage and the
likelihood of CAIS adoption.
4.2.2 Compatibility (COMP)
Likewise, compatibility is another
technological characteristics perceived by
individual which was suggested by DOI
theory as a driver of the decision to adopt a
new system. DOI theory defines
compatibility as the extent to which an
innovation is perceived as being consistent
with the existing values, needs, and past
experiences of potential adopters (Rogers,
1983). In most organizations, it is realized
as compatibility with IT infrastructure
(Henderson et al., 2012). In order to adopt
new technology, Shaharudin et al. (2012)
described that the existing infrastructure
should be compatible with the new
technology. This means the existing
infrastructure is important to the firm’s
adoption decision, in which, the more an
innovation is perceived as consistent with
present systems, procedures and value
systems of the potential adopters especially
in term of infrastructure, the more likely it
will be adopted (Henderson et al., 2012).
Prior research has discussed how
compatibility influences the IT/IS adoption.
Several prior researches on IT adoption
found that IT adoption and usage is
significantly affected by IT compatibility
(Alam, 2009; Al-Qirim, 2007b; Hong and
Zhu, 2006). In addition, prior IT adoption
studies based on the TOE framework
suggest that a high level of compatibility
between the technology to be adopted and
existing technologies (e.g. IT infrastructure)
motivates an organization to adopt an IT
innovation (Premkumar et al., 1994; Thong,
1999).
Compatibility is an important
consideration in a firm’s IT innovation
adoption decision because, with a high level
of compatibility, the organization needs to
make minimal adjustments and changes,
which implies less resistance to adoption
(Thong, 1999). Furthermore, compatibility
suggests lesser risk to potential adopter and
makes the innovation more meaningful to
the organization (Yoon, 2009). However,
lack of incompatibility may cause low
adoption and utilization (Alam, 2009).
When technology is viewed as significantly
incompatible, major adjustments in
processes that involve considerable learning
are required (Low et al., 2011). Sharing this
view, Huy (2012) described the
incompatibility of a new technologies with
existing procedures, value systems and
infrastructure negatively affects the attitudes
of users and increases their resistance to
change, which in turn hinder the adoption of
the technology.
Compatibility is important in the
context of CAIS as CAIS has the potential to
change the business reporting system.
Adopting CAIS also can introduce
additional systems integration issues. The
incompatibility of CAIS with current
processes and legacy system is a significant
factor for non-adoption of CAIS. The
incompatibility of the software in term of
data format with the business nature might
be a barrier to the use of CAIS. These
incompatibilities could result in
encountering resistance in the CAIS
adoption.
Another barrier is that CAIS
adoption replaces many of the manual work
procedures used in firm transaction
recording systems and can lead to significant
changes in work practices and procedures.
According to Premkumar et al. (1994),
organizations’s resistance to change due to
changes in work procedures and possible
loss of jobs as a result of automation of
document processing functions is a major
inhibiting factor in the use of technological
innovation.
For the above reasons,
compatibility is an essential factor that
affects the adoption and utilization of the
CAIS. When the firms have adequate
infrastructure for the adoption and it is
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compatible then the adoption and utilization
of the innovation is usually high because the
firms are not require to invest large sum on
the infrastructure. When a technology is
recognized as compatible with internal
values and work application systems, firms
are usually likely to consider the adoption of
new technology. Therefore, this study
expects:
H2b: There is a positive relationship
between compatibility and the likelihood of
CAIS adoption.
4.2.3 Complexity (CMPX)
In the DOI theory, complexity is
another important technological factor that
needs to be studied in depth in innovation
adoption. Complexity refers to the degree
to which an innovation is perceived as
difficult to use (Roger, 1983).
Generally, complexity is widely
recognized as a key barrier to IS adoption
(Thong, 1999). Henderson et al. (2012)
suggested that the complexity of innovation
technology originates from systems
integration issues and the tagging process.
For example, in the case of CAIS, the
difficulty of the tagging process stems from
the specialized financial knowledge required
to tag financial data. Lack of basic
accounting knowledge might cause
difficulty in keying in data. In Davis et al.
(2009), manual AIS users stated that the
complexity of CAIS system and that no one
in their firm knew how as one of the reasons
for not using CAIS. And for adopters, the
most influential factor that encouraged them
to maintain the usage of CAIS was ease of
use. Thus, complexity of an innovation can
act as a barrier to the implementation of new
technology such as CAIS. As well,
complexity of one particular system during
implementation will become the inhibitor
that discourages the greater usage of the
innovation (Low et al., 2011).
In another point, Henderson et al.
(2012) described that some technological
innovation is not perceived to be complex;
however, the changes in the business
processes, organizational culture and
environment introduce additional
complexity. Earlier, Ramamurthy et al.
(1999) has argued that integrating a new
system with various internal applications
can be complex due to the uniqueness of
individual firm’s system environment. As
such, many researchers perceived
complexity as reflecting a match between
the technical skill required to use the
innovation and skills the organization
possessed (Rui, 2007; Low et al., 2011;
Premkumar et al., 1994; Lin, 2008). For
that reason, an innovation could be
considered as complex by some firms who
lack associated knowledge and skill, but not
complex by some firms who have the
necessary knowledge and skill (Rui, 2007).
Hence, it could be suggested that complexity
is a fit-based concept between the technical
skill required and skills firms possess (Rui,
2007).
SMEs, due to lack of in-house
expertise and large information systems staff
may make new technology seem complex,
difficult to implement and may take a long
time to understand (Premkumar et al.,
1994). Although an innovation may appear
to be useful to the firm, it may not have
necessary expertise to use it, thereby
increase the risk in the adoption decision
and also creates greater uncertainty for
successful implementation (Huy, 2012). In
other words, firms may not have confidence
in this innovation if they assume the
technology is a complex system.
CAIS could be perceived as a
complex innovation, especially for SMEs,
since it is a hybrid innovation with record
keeping (changes in method of recording)
and technological (require IT infrastructure)
implication. Previous studies have indicated
that a complex innovation requires greater
resources and skills to adopt, and requires
increased cognitive effort on the potential
adopter, thus, the perceived complexity of
the innovation technology is expected to
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influence the decision to adopt them
negatively (Lin, 2008)
Many other prior IT adoption
literatures that employ the TOE framework
also suggested relative complexity as one of
most important factors that affects firm
adoption of an IT innovation. For example,
Al-Qirim (2007b) found that complexity
negatively affected the e-commerce
adoption in Jordan. Teo et al. (1995)
revealed complexity to be a strong predictor
of intention to adopt financial EDI in
Singapore. Azam and Taylor (2011) study
showed complexity of the technology is
significantly related to the likelihood of
standard business reporting (SBR) adoption
in Australia.
From the discussion this study
believes that complexity of an innovation
can function as an inhibitor to adoption, and
is usually negatively related to adoption
(Premkumar et al., 1994). Thus, the next
hypothesis will be:
H2c: There is a negative relationship
between complexity and the likelihood of
CAIS adoption.
4.3 Organizational Context
According to the TOE framework,
organizational adoption of technological
innovation can be influenced by the
organizational context. The organizational
context refers to the characteristics and
resources of the organization (Tan & Felix,
2010). It looks at the structure and
processes of an organization that constraint
or facilitates the adoption and
implementation of innovations (Chau &
Tam, 1997).
The previous IT adoption literature
based on TOE has proposed various
organizational factors that are significant
determinants of innovation technology
adoption. Example of these factors included
business size, top management support and
organizational readiness. Based on the IT/IS
system adoption literature, two
organizational variables were selected and
assumed to be most suited for analyzing the
CAIS adoption in Malaysian SMEs. These
organizational variables are organizational
readiness and employees IT knowledge.
Furthermore this study tries to examine a
new construct, satisfaction with manual
accounting system as it is predicted to be a
barrier in CAIS adoption.
4.3.1 Organizational Readiness
(O_REA)
The DOI theory in organizations
suggests that organizational resource
availability positively influences
organizational adoption of innovations
(Rogers, 1983). This theory emphasizes the
importance of organizational readiness in
the context of organizational adoption.
Organizational readiness is defined by
Iacovou et al. (1995) as the availability of
the needed organizational resources for
adoption.
Review of this study on IT/IS
adoption literature suggests that
organizational readiness in many studies
primarily concerns the technological
(hardware or software resources) and
financial resources of the organization
(Gemino et al., 2006; Chau & Hui, 2001;
Grandon & Pearson, 2004; Iacovou et al.,
1995; Chewlos et al., 2001; Nelson & Shaw,
2003; MacKay et al., 2004; Yoon, 2009). In
the case of SMEs in particular, even if the
owner-managers perceive the adoption of
new technologies as important, the
enterprises often do not have sufficient
resources to adopt them (Yang et al., 2012).
This is the major obstacles to the integrating
of new technologies in SMEs. Chau (2001)
pointed that only realizing potential benefits
may not be enough for an organization to
decide to adopt new innovation technology.
In this case, SMEs may be reluctant to adopt
innovation if they do not feel “ready” to
adopt. This lack of readiness may come
from certain organizational resources such
as financial readiness and technological
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readiness (Iacovou et al.,1995; Ramdani &
Kawalek, 2007). Therefore financial and
technological readiness is the important
issues to be considered in innovation
adoption as the organizational readiness
indicator.
Prior studies of IT/IS adoption also
found that technological and financial
readiness positively influences
organizational adoption of different types of
innovation technology. For example,
Mehrtens et al. (2001) find that an
organization’s decision to adopt the Internet
is positively influenced by financial and
technological readiness. Mackay et al.
(2004) also find that technical and financial
readiness has a positive influence on an
organization’s decision to establish a
website. Iacovou et al. (1995) and Chewlos
et al. (2001) find that organizational
readiness positively influences an
organization’s intent to adopt Electronic
Data Interchange (EDI). Another example
is found in Khalifa and Davidson (2006),
who found that organizations with higher
levels of organizational readiness have
greater intent to adopt electronic trading
systems.
However, in some cases, while the
technological and financial resources are
ready, it is also often the case that the
employees refuse to adopt the new
technology due to various reasons, such as
dangers of job loss and reluctant to change
the work practices (Tan & Felix, 2010).
Some employees may not believe that the
new system will change or improve the way
the business functions. As innovation
process will affect every function and
organizational stakeholder, it requires
fluidity of coordination (Powell & Dent-
Micallef, 1997). As for CAIS, many
alterations might significant in the adoption
process such as organizational structures,
communications patterns, and other
practices in daily processes. All these in the
first order require incremental modification
of existing behaviours. If people in
organization are readily to change and have
open behaviour on the new systems, than the
firms will be more likely to accept the
innovation (Ifinedo, 2012). Powell and
Dent-Micallef (1997) termed this condition
as organizational flexibility.
Inspired from Tan and Felix
(2010), Nguyen (2009) and Powell and
Dent-Micallef, this study decided to term
this third organizational readiness indicator
as organizational flexibility culture. As a
result, this study moves a step further than
prior studies as organizational readiness in
this study will be measured in term of
financial readiness, technological readiness
and organizational flexibility culture.
Drawing from the above lines of theoretical
argument, it can be visualized that the
organization must require financial,
technological as well as flexibility culture to
adopt CAIS. In other words, the firm
should have financial, technological and
organizational flexibility culture as
influential factors to the CAIS adoption. The
foregoing discussion then permits the
prediction that:
H3a: There is a positive relationship
between organizational readiness and the
likelihood of CAIS adoption.
4.3.2 Employees IT Level (E_ITL)
Nguyen (2009) suggested top
management or the owner-managers are not
only people who contribute to the success of
the business. It is clear that in most firms,
employees also make a contribution and
they have a major impact on the rise or fall
of the businesses (Nguyen, 2009). From this
point of view, employees are assets, as a
firm’s success depends on them. They are a
resource that needs to be developed
(Nguyen, 2009). This is also refers to IT
adoption success. At this point many studies
suggested that the level of employees IT
knowledge influence the adoption of
technological innovations (Ifinedo, 2012;
Thong & Yap, 1995; Zhu et al., 2006)
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Employees IT level refers to the
level of IT knowledge or experience that the
employees have (Hung et al., 2010).
Relevant IT knowledge and experience
variables have been investigated in many
studies. Kuan and Chau (2001) found that
prior IS experience influences the adoption
of new technologies. Study by Caldeira and
Ward (2002) proved that the firms that
revealed the lowest levels of satisfaction
with IT/IS adoption and use did not have
sufficient IS/IT knowledge to implement
their systems. Also Antlova (2009)
suggested one of the main barriers
preventing acceptance of ICT, especially by
SMEs is knowledge and skills regarding IT.
Many other studies also found IT knowledge
and technical skills are the important factors
in the adoption of new technologies. This
factor also has been found to be positively
related to IT adoption (e.g. Scupola, 2009;
Thong, 1999).
However, since typically SMEs
lack of this expertise, many of them unaware
of new technologies (Thong, 1999;
Premkumar and Roberts, 1999) or tempted
to postpone adoption of the innovation until
they have sufficient internal expertise (Hung
et al., 2010). Ramdani et al. (2009)
mentioned that those organizations that do
not have much IT/IS experience may not be
aware of new technologies and may not
desire to the risk by adopting them.
Therefore, Premkumar and Roberts (1999)
suggest that keeping employees informed or
aware of the new IT allows them to
maximize the resources that can help be
more productive. Hence, if employees of
SMEs are knowledgeable about IT, the
businesses may be more willing to adopt
technological innovations (Ifinedo, 2012;
Thong & Yap, 1995; Zhu et al., 2006)
Based on these discussions, the
employees IT level can be seen as important
to the technological innovation adoption
including CAIS. The evidence from
previous literature suggests that the
availability of IT knowledge among
employees will help a firm to adopt CAIS
systems. Therefore the next hypothesis of
this study is:
H3b: There is a positive relationship
between employees’ IT knowledge and the
likelihood of CAIS adoption.
4.3.3 Satisfaction with Manual System
(S_WMS)
Satisfaction is one of the most
important concepts especially in marketing
and information system, and has attracted
much of research interest (Limayem &
Cheung, 2008). Lots of researchers have
suggested that user satisfaction is one of the
key influencers leading to system success
(Chen et al., 2009).
Zhuo et al. (2012) refer satisfaction
as an effective state representing an
emotional response to the service encounter.
For Bokhari (2005), satisfaction is a sum of
one’s feelings and attitudes towards a
variety of factors affecting the situation.
While Winnie and Low (2012) mentioned
satisfaction as the response and outcome of
using processes which generate a
comfortable feeling and a positive attitude to
use the systems (Winnie & Low, 2012).
Satisfaction represents an individual emotive
state following first-hand experience with
the target object or behaviour (Premkumar
& Bhattacherjee, 2008). From the definition,
it is clear that researchers consider
satisfaction to be synonymous with attitude
and one of the psychological construct.
Satisfaction as a psychological
construct has been studied in various
contexts, including job satisfaction,
satisfaction with product or service
consumption, and end-user satisfaction with
IT usage (Premkumar & Bhattacherjee,
2008). Prior research on user satisfaction
typically use this variable (satisfaction) to
predict future intention to continue a service
(continuance intention), hence this variable
is more synonym in post-adoption stage
studies (Bhattacherjee, 2001; Ali et al.,
2012; Zhuo et al., 2012; Hossain &
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Quaddus, 2011; Limayem & Cheung, 2008;
Bokhari, 2005) except for Chau and Tam
(1997) and Alatawi et al. (2012). Chau and
Tam (1997) and Alatawi et al. (2012)
examine satisfaction variable in pre-
adoption stage.
This implies that there is still lack
of sufficient research effort to establish a
conclusive relationship between satisfaction
and technological innovation in pre-adoption
stage. Insufficient research however is in
some ways offering the opportunity for
researchers to further investigate the issues
and collaborate to the literatures (Bokhari,
2005).
Satisfaction construct differs in pre
and post adoption studies in several aspects.
Post adoption stage studies usually reporting
the influence of satisfaction on continuance
intention, meaning the focus is on the same
existing systems. In contrast, pre-adoption
stage studies attempt to show the influence
of satisfaction with existing system towards
the adoption of new innovation, meaning the
focus is on the new or alternative system.
As such, satisfaction with existing system is
believed to influence post-adoption attitude
and continuance intention positively. It
different in pre-adoption stage studies as
satisfaction with existing system is predicted
to have negative influence on adoption of
new system. However, review of this study
on previous literatures indicated that
satisfaction issues in post-adoption stage and
satisfaction issues in pre-adoption stage
owing to the similarity concept.
Bhattacherjee (2001) pointed that
user’s intention to continue service use is
determined primarily by their satisfaction
with prior use of that product or service.
Therefore, satisfaction is viewed as the key
to building and retaining a loyal base of
long-term usage. On this point,
Bhattacherjee (2001) mentioned that
satisfied users continue using the existing
services, while dissatisfied users discontinue
it or switch to alternative services.
Users are satisfied if their actual
experience exceeds their prior expectations
(Winnie & Low, 2012). Anderson and
Sullivan (1993) found that in the long-run,
firms that consistently providing high
satisfaction were less sensitive to the change
of satisfaction, that is, satisfied users tend to
use the same system (Zhuo et al., 2012).
Conversely, if system usage does not meet
user needs, satisfaction will decrease and
restrict further use (Bokhari, 2005). Bokhari
(2005) argued that in low satisfaction level
condition, dissatisfied users may discontinue
system usage and seek alternatives.
According to Chau and Tam
(1997), low satisfaction level with existing
system which generally referred to as
performance gap, will provide the impetus
to find new ways to improve performance.
In an organization, a performance gap may
result from a low satisfaction level with
existing performance of the existing systems
or inability to serve the organization’s new
needs (Chau & Tam, 2000). This means that
the greater the satisfaction with the existing
systems, the lower the incentive to change to
a new system (Chau and Tam, 1997). Using
the organizational context of a TOE
framework and on the basis of the above
arguments, in their study on organizational
adoption of open system, Chau and Tam
(1997) hypothesized that higher levels of
satisfaction with the existing systems will
negatively influence the possibility of open
systems adoption. The result showed that
satisfaction level with the existing systems
has a negative relationship with the open
systems adoption decision, thus support their
hypothesis.
This study builds upon this line of
argument and posits an equivalent
relationship in the CAIS context. However,
in contrast to Chau and Tam’s (1997) study
which measured satisfaction with existing
system in term of the evaluation on existing
computer system, and as a new contribution,
this study developed new items specifically
refers to the satisfaction with manual
accounting information systems practices.
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At the same time, this study attempt to
examine the openness to change from non-
computerised to computerised system.
Satisfaction with manual systems
may be defined as a positive attitude and
response towards a manual system. In the
CAIS context, satisfaction with manual
system associates with the extent to which
users believe the manual system meet their
information requirements.
Using CAIS could improve the
financial management and record keeping
practices (McChlery et al., 2005), thus
problems in or with manual system may lead
to the likelihood of CAIS adoption.
Therefore, in the context of adopting CAIS,
the satisfaction level with manual systems
should be closely related to the need for
improvement and thus, the adoption
decision. In this case, whenever the manual
systems satisfiy the needs of the
organization, the propensity to change
should be lower. This means that if the
manual system meets the requirements of
the users, the users’ satisfaction with the
system will increase, thus resulting in
refusal of adopting CAIS. This suggests that
deferring using CAIS might be a result from
high satisfaction from using the manual
system. Thus, satisfaction with manual
system was introduced for the first time and
especially developed for non-adopters model
in this study. This variable was predicted as
negatively affecting the willingness of CAIS
adoption among non-adopters. The above
arguments lead this study to this hypothesis:
H3c: There is a negative relationship
between satisfaction with manual systems
and the likelihood of CAIS adoption
4.4 Environmental Context
According to the TOE framework,
factors that pertain to the environmental
context influence organizational adoption of
technological innovations. The
environmental context is the area in which
the firm does business (Tornatzky and
Fleischer, 1990) or in another words
concerns the surroundings of the
organization, looking at how external
influences affect the motivations or barriers
to adopt an innovation (Teo et al., 2004).
Although the decision to adopt IT
is depending on the owner-manager and
internal organizational need as previously
suggested, the actions and decisions of
owner-manager would be affected by
external environment and they make policy
decision accordingly (Alatawi et al., 2012).
Therefore, the adoption of IT can be the
result of pressure exerted on the enterprise
by its environment.
The review of organizational IT/IS
adoption studies suggests that pressures and
supports from an organization’s external
environment are found to be significant in
influencing the decision to adopt innovation
technology. The external environmental
incorporates the structure of the industry,
such as the extreme competition was
frequently found encourages the adoption of
innovation. The support from vendors also
repeatedly showed as significant in
influencing innovation. Finally, government
regulation can have a favourable or negative
impact on organizations, depending on
whether its policy encourages or discourages
innovation (Alatawi et al., 2012). Based on
the IT/IS adoption literature, such adoption
drivers (vendor support, competition and
government influence) were selected and
assumed to be most suited for analyzing the
CAIS adoption in Malaysian SMEs.
4.4.1 Vendor Support (V_SPT)
One of the important aspects of the
IT adoption process is the assistance of
external support such as IT/IS vendors.
Vendor support refers to the existence of
support from IT/IS vendor for employing
and using the systems (Ramdani et al.,
2009). This construct has not only been
found to be a significant construct in IS
success, but also a determinant that
positively influences IS innovation adoption.
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Many researchers agreed that the
availability of IS vendor can mitigate the
lack of IT expertise in most SMEs. Thong et
al. (1996) noted that due to the nature of
SMEs, which generally lack of IT expertise
and skills, firms should seek professional
vendors when it comes to IT adoption.
Ramdani et al. (2009) suggested that with
increasing support from the third party,
firms are more willing to adopt IS
innovations. Nguyen (2009) pointed that
quality advice from IT professional such as
IT vendors is always useful for management
or owner-manager as many of them do not
have sufficient experience or understanding
of IT. Ifinedo (2012) then stressed that
vendor support should be considered in the
planning process and implementation of IT
adoption. And recently Yang et al. (2013)
also supported the crucial role of external
vendor for the implementation of IT
innovations, especially when the
organization is unfamiliar with the
technology (Yang et al., 2013). According
to Proudlock et al. (1999), the employment
of such external support can overcome
knowledge gaps and guide firms in
implementing appropriate IT.
The availability of external support
especially vendor also has been shown to be
an important factor in several adoption
studies, especially in small organizations.
Study by Thong et al. (1996) of 114 small
businesses in Singapore found that external
IT expertise plays an important role in the IT
implementation process. One year after,
study by Igbaria et al. (1997) also indicated
that external support is a significant variable
influencing system satisfaction and usage.
More recently, the results from Ellis and
Belle’s (2011) study on open source
software adoption in South African
identified technical support as a facilitator to
the ongoing operation of the ICT
infrastructure. Most organizations in their
study felt they could not function without
reliable ICT support services.
Regarding CAIS, the introduction
of CAIS may expose the firms with new
skill requirements. With little internal IT/IS
expertise, SMEs in Malaysia are believed to
rely on the advice and support from CAIS
vendors. The degree to which a vendor
possesses CAIS skills may make it easier for
SMEs to adopt and use the CAIS without
extensive in-house expertise, thus can help
lower the barriers in adopting CAIS.
Furthermore, researchers elsewhere have
found vendor support to be an important
factor in the adoption and usage of
innovation technologies; therefore, this
study also predicts the same effect on CAIS.
Thus, it is predicted that:
H4a: There is a positive relationship
between vendor support and the likelihood
of CAIS adoption.
4.4.2 Competition (CPTN)
It has long been empirically
recognized that competition can put pressure
on organizations to adopt an innovation
(Thong, 1999; Zhu et al., 2003; Yoon,
2009). In high competitive markets, IT
innovation adoption is necessary to maintain
and achieve competitive advantage (Yoon,
2009). Non-adoption of an IT innovation
that is adopted by others in such an
environment may result in competitive
disadvantage.
Porter and Millar (1985) argue that
IT adoption can enable an organization to
achieve competitive advantage in either cost
or differentiation. In other words, by
adopting IT, an organization can lower its
costs and differentiate itself from
competitors. The argument by Porter and
Miller can be applied to the context of
CAIS. Adopting CAIS may enable firms to
differentiate it in several ways especially
from competitors who have not adopted
CAIS. For example, CAIS may help a firm
to provide a standard and proper preparation
of financial information, thereby allowing
financial data to be automatically extracted
and efficiently analyzed by the top
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management. This benefit thus enhancing its
differentiation in term of accurate
information for decision making compared
to their non-adopters counterpart.
In addition, competition is an
important factor driving firms to adopt a
new technology in order to avoid
competitive decline which many studies
refer as competitive pressure (Zailani et al.,
2009; Hameed & Counsell, 2011; Zhu et al.,
2006; Chwelos et al., 2001). Ghobakhloo et
al. (2011) defined competitive pressure as
the extent to which firms perceive
themselves threatened by their counterparts
within their industry or substitute sector.
Many researchers who applied
Institutional Theory (Alatawi et al., 2012;
Yoon, 2009) believed that when firms face
pressures from their external environments,
they are likely to adopt innovations that
others in their environment have already
adopted. In other words, firms are likely to
adopt a technology when they perceive that
the number of their competitors that have
already adopted the technology increases
(Yoon, 2009). They also intend to adopt the
technology if they perceive that competitors
that have adopted the technology have
benefited or succeeded from using it.
Because their competitors have already
adopted the technology, firms will then
intend to do the same in order to achieve
organizational legitimacy. Organizational
legitimacy is referred to the acceptance of an
organization within its external environment
(Yoon, 2009). Those who choose not be
follow the trend, risk themselves from being
left behind and may at a disadvantaged
position as opposed to their competitors
(Chong & Ooi, 2008; Chong & Chan, 2012;
Ghobakhloo et al., 2011b).
It is reasonable therefore to assume
that the more a company feels a pressure in
its operating environment, the more likely it
will adopt a ‘best practice’. In some
instances, these pressures force companies
to look for best practices in the future
(Zailani et al., 2009). For that reason,
competitive pressure is generally perceived
to have a positive influence on the adoption
of innovation technology and is one of the
widely mentioned reasons for organizations
to adopt IT. It has driven many researchers
to analyze the strategic rationale underlying
the relationship between competition and
technology innovations (Ghobakhloo et al.,
2011; Zailani et al., 2009; Hameed &
Counsell, 2011; Varukolu & Park-Poaps,
2009; Chwelos et al. 2001).
In the CAIS context, the SMEs is
predicted to be more likely to adopt the
technology if they find that many of their
competitors have started using it. Salwani et
al. (2009) noted that decisions to engage in a
particular behaviour depends on perceived
number of similar others in an environment
that have already done likewise. It seems
therefore competition is one of the main
reasons for SMEs to adopt CAIS. It also
seems rational to believe that the
competition affects the adoption of CAIS
when SMEs perceive that the technology
may differentiate them from others and
assist them to achieve superior firm
performance. The SMEs also may consider
adopting CAIS when they perceived
themselves threatened of losing
competitiveness to their counterparts within
the industry. Derived from the above
discussions this study predicts that:
H4b: There is a positive relationship
between competition and the likelihood of
CAIS adoption
4.4.3 Government Influence (G_INF)
Above discussion in environmental
context described that competition and
external support from vendors are important
in technological innovation adoption. The
other pressing and practical reasons for
SMEs to adopt IT might also come from
government influence (Kuan & Chau, 2001).
Government influence refers to the
commitment and assistance provided by the
authority to encourage the spread of IT/IS
innovation in its context (Ifinedo, 2012).
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Government influence can also referred as
government support in many studies (e.g.
Ifinedo 2012; McKenzie, 2006; Hameed &
Counsell, 2012).
Government has great influence
over any kind of companies (Yang et al.,
2012). For instance, Yang et al. (2012)
suggested that the formulation of related
regulations can become limitations or entry
barriers for companies’ investments, or
subsidies that can motivate the companies to
adopt information technologies or to
develop new techniques. However,
McKenzie (2006) described that
governments around the world are eager to
see small businesses to adopt technological
innovations. Governments from various
countries also understand how important IT
is to their nation’s growth (Chong & Ooi,
2008). As such, many researchers agreed
that government play a indispensable role in
firms’ adoption of technological innovation
(Yang et al., 2013; Hameed & Counsell,
2012; Yang et al., 2012; Riyard et al., 2009;
Chong & Ooi, 2008; Thatcher et al., 2006;
Looi, 2005; Lee & Kim, 2004; Scupola,
2003).
The development of digital
technology and the emergence of new
products and services require formulation of
a new policy and regulatory framework.
These policies include direct research and
development (R&D) funding, agency level
research policy, investment tax credits,
industry policy and R&D tax credits (Yang
et al., 2012). This is because without
parallel development of laws, policies and
strategic directions by government can result
in abuses and discourages the adoption and
use of technological innovation (Riyard et
al., 2009). Sharing this view, many studies
suggested government through regulations
can encourage the adoption of innovation in
organizations. Thatcher et al. (2006) pointed
out that the existence (or non-existence) of
government policies and incentives are
influential in encouraging (or discouraging)
companies to adopt technology. Riyard et al.
(2009) mentioned that government through
setting up infrastructure and enacting rules
and regulations can create environment for
SMEs for technological intake. Recently,
Yang et al. (2013) suggested government
involvement through policies and support
can influence the decision to adopt new
systems to a large extent.
Besides regulatory framework,
many researchers agreed government
support in terms of providing incentives
would facilitate innovation adoption and
usage. In Looi’s (2005) study, government
initiatives like the e-government
programme, entrepreneurship development
programme and the information support
programme were found to be the dominating
factors for internet growth and IT adoption
(Looi, 2005). More recently, Hameed and
Counsell (2012) mentioned that by
providing training, guideline, financial
assistance, technical support, independent
advice and other incentives government can
encourage adoption of IT in organizations.
Yang et al. (2012) when discussed the role
of government in influencing adoption of IT
suggested the subsidies that the government
offers will encourage the companies to
accelerate the pace of their introduction of
new IT so that they can improve the
condition of their operations and, in turn,
influence the performance of the IT
implemented by the companies. This is to
say that government can stimulate the
introduction of new IT in the companies
through the institution of certain regulations
or the provision of related assistances.
Many studies also suggest the
important of government role as one of the
external related factors that is very important
to break through the barriers of ICT
adoption. Study by Lee & Kim (2004) on
driving factors and barriers of e-business in
Korea found that the government related
factors are very important in the reduction of
the main barriers and the creation of the
atmosphere of ICT adoption in SME sector
especially related to the cost issues. Lee and
Kim (2004) stressed that the cost issue
seems to be difficult to solve by SMEs, per
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se, because of the inferiority of the SMEs’
environment. Their study also revealed the
type of government support that SMEs
wished in their study are mostly related to
the reduction of cost burden such as
financial support of development of ICT
service platform, funds for training and tax
cuts. Lee and Kim (2004) suggested that the
main role of government is to open the way
for using IT without the burden cost and to
create the atmosphere of IT usage through
systematic support to let the SMEs realize
benefits of IT and to give more motivation
in all possible areas.
It is clear therefore, government
involvement plays an important role in
promoting technological innovations,
facilitate the adoption and break through the
barriers of innovation adoption in
organizations (Tan et al., 2009). Several
researchers in recent years have studied the
role of government in the adoption of
innovation technology and it is generally
agreed that the government support has a
positive relationship on adoption of
innovation technology (Dhurbakula & Kim,
2011; Riyard et al., 2009; Lin, 2008;
Iacovou et al., 1995; Kuan & Chau, 2001).
The important of government influence also
made some studies expand the TOE
framework to four dimensions in which
government dimension has been extracted as
another important dimensional factor (e.g.
Riyard et al., 2009; Durbhakula & Kim,
2011).
According to the literature review
as discussed above, government entities are
among the most powerful institutional forces
affecting innovation. One can see that the
more appealing the government’s assistance
is the more contribution the government can
make toward innovation technology
adoption in a firm. Regarding CAIS, this is
to say that government can stimulate the
introduction of this technology in the firms
through the institution of certain regulations
or provision of related assistances. Based on
the influence government factor has on
technology adoptions in previous literatures,
this study hypothesizes that:
H4c: There is a positive relationship
between government influence and the
likelihood of CAIS adoption
5.0 SUMMARY AND
CONCLUSION
The SMEs have always been
recognized as an important segment of the
economy and will remain as a backbone of
economic development in many economies
throughout the world (Tan et al., 2008). As
a developing country, SMEs represent a
vital segment of Malaysian economy.
Therefore, the financial stability of SMEs is
very important to the health of Malaysian
economy, and the impact of SMEs failures
on the economy is a very important concern.
Several factors are important in
determining the failure of the SMEs, one of
which is accounting records. Accounting
reports are the principle source of
information for the management of SMEs.
Therefore, the importance of the accounting
system for SMEs cannot be disregarded.
Today, with efficient computer
operations such as CAIS, an adequate
accounting system could be achieved more
easily than through traditional methods.
Moreover, with the introduction of lower-
cost and more user-friendly accounting
softwares in the market, there appears to be
fewer obstacles to improved record keeping
practices. However, some SMEs are not yet
ready for this innovation. For the roles play
by the CAIS in improving financial
management in SMEs, is it important to
examine the factors that influence the
likelihood of CAIS adoption among non-
adopters in Malaysian SMEs. For that
purpose, this study proposes the conceptual
model to be used in future research.
The proposed research model has
been devised on careful consideration of the
models used in previous IT adoption studies
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at the organizational level. The developed
research model was based on the TOE
framework using the DOI theory in its
technological contexts. The DOI theory has
been used by many innovation researchers
since more than two decades ago. The use
of this framework therefore will not only
empirically validate its usefulness but will
also test the performance of the DOI theory
which has been used for a long of time.
More importantly, based on the works by
Thong (1999,) a TOE resource-based model
for SMEs is developed. This further
complements the use of DTOE framework
for SMEs. For the integration of TOE
framework, DOI theory and Thong’s model,
this conceptual model is hoped to produce
useful combination especially in
constructing specialized model for SMEs.
5.1 Limitation and Future Research
Directions
The formulation of the proposed
research model is based on the empirical
validation of the constructs taken from
different research studies of IT adoption at
the organizational level and not fully
exploited from the extant research on CAIS
adoption. Therefore, the constructs
proposed for this model is need to be
empirically validated. The next direction for
this research is to collect data from the
various types of SMEs in Malaysia in the
future in order to support the hypotheses of
the proposed research model. In addition, if
this model is proven to be one of the
accepted models for the adoption of CAIS, it
can be tested further to see whether its result
remains similar in the contexts of other
countries and other IT innovations.
REFERENCES
1. Abu-Musa, A.A. (2005). Investigating
the perceived threats of computerized
accounting information systems in
developing countries: An empirical
study on Saudi Organizations. J. King
Saud Univ, Comp. & Info. Science,
18, 1-26
2. Adhikari, A. & Zhang, H. (2003).
Organizational context and selection
of international accounting software:
An exploratory study. Advances in
International Accounting, 16, 1-16.
3. Adhikari, A., Lebow, M.I. & Zhang,
H. (2004). Firm characteristics and
selection of international accounting
software. Journal of International
Accounting, Auditing & Taxation, 13,
53-69.
4. Ahmad,N.A. & Seet,P. (2009).
Dissecting behaviours associated with
business failure: A qualitative study
of SME owners in Malaysia and
Australia. Asian Social Science, 5(9),
98-104.
5. Alatawi, F.M.H., Dwivedi, Y.K.,
Williams, M.D., & Rana, N.P. (2012).
Conceptual model for examining
knowledge amanagement system
(KMS) adoption in public sector
organizations in Saudi Arabia. Paper
presented at the tGOV Workshop ’12
(tGOV12), Brunei Universiti, West
London.
6. Alam, S.S. (2009). Adoption of
internet in Malaysian SMEs. Journal
of Small Business and Enterprise
Development, 16(2), 240-255.
7. Ali, A., Rahman, M.S., & Ismail,
WNW (2012). Predicting continuance
intention to use accounting
information systems among SMEs in
Terengganu, Malaysia. International
Journal of Economics and
Management, 6(2), 295-320.
8. Al-Qirim, N. (2007a). The adoption of
eCommerce communications and
applications technologies in small
businesses in New Zealand.
Electronic Commerce Research and
Applications, 6, 462-473.
9. Al-Qirim, N. (2007b). The adoption
and diffusion of e-commerce in
developing countries: The case of an
NGO in Jordan. Information
Technology for Development, 13(2),
107-131.
Page 23
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
144
10. Anderson, E.W., & Sullivan (1993).
The antecedents and consequences of
customer satisfaction for firms.
Marketing Science, 12(2), 125-143.
11. Antlova, K. (2009). Motivation and
barriers of ICT adoption in small and
medium-sized enterprises. E + M
Ekonomie a Management, 2, 140-155
12. Ajzen, I. (1991). The theory of
planned behavior. Organizational
Behavior and Human Decision
Processes, 50(2), 179-211.
13. Anderson, J.E., & Schwager, P.H.
(2003). SMEs adoption of wireless
LAN technology: Applying UTAUT
model. Proceedings of the 7th Annual
Conference of the Southern
Association for Information Systems.
14. Arpaci, I., Yardimci, Y.C., Ozkan, S.,
& Turetken, O. (2012).
Organizational adoption of
information technologies: A literature
review. International Journal of
eBusiness and eGovernment Studies,
4(2), 37- 50.
15. Awa, H.O., Eze, S.C., Urieto, J.E., &
Inyang, B.J. (2011). Upper echelon
theory (UET): A major determinant of
information technology (IT) adoption
by SMEs in Nigeria. Journal of
Systems and Information Technology,
13(2), 144-162.
16. Ang, S.K., & Hussin, W. (2012). A
study on implication of adopting e-
business technology by SMEs.
Proceedings of the 2012 International
Conference on Computer and
Information Science (ICCIS2012).
Kuala Lumpur, Malaysia
17. Azam, S. & Taylor, D. (2011).
Adopting standard business reporting
(SBR) in Australia: are CFOs
persuaded by technology attributes?
Critical Perspectives on Accounting.
Florida, USA. Paper available at
visar.csustan.edu/aaba/Azam&Taylor
2011.pdf
18. Bokhari, R.H. (2005). The
relationship between system usage
and user satisfaction: a meta-analysis.
The Journal of Enterprise Information
Management, 18(2), 211-234.
19. Breen, J., Sciulli, N. & Calvert, C.
(2003). The use of computerized
accounting systems in small business.
Paper presented at 16th Annual
Conference of Small Enterprise
Association of Australia and New
Zealand, 28th September-1st October
2003.
20. Butkevicius, A. (2009). Assessment
of the integration of the accounting
information system in small and
medium Lithunian enterprises.
Ekonomika, 88, 144-163.
21. Caldeira and Ward (2002).
Understanding the successful
adoption and use of IS/IT in SMEs: an
explanation from Portuguese
manufacturing industries. Information
Systems Journal, 12, 121-152.
22. Chang, I., Hwang, H., Hung, M., Lin,
M. & Yen, D. (2007). Factors
affecting the adoption of electronic
signature: Executives’ perspective of
hospital information department.
Decision Support Systems, 44, 350-
359.
23. Chatzoglou, P.D., Vraimaki, E.,
Diamantidis, A., & Sarigiannidis, L.
(2010). Computer acceptance in
Greek SMEs. Journal of Small
Business and Enterprise
Development, 17(1), 78-101.
24. Chau, P.Y.K. & Tam, K.Y. (1997).
Factors affecting the adoption of open
systems: An exploratory study. MIS
Quarterly, 1-24.
25. Chau, P.Y.K. (2001). Inhibitors to
EDI adoption in small businesses: An
empirical investigation. Journal of
Electronic Commerce Research, 2(2),
78-88.
26. Chen, S., Chen, H., & Chan, M.
(2009). Determinants of satisfaction
and continuance intention towards
self-service technologies. Industrial
Management & Data Systems, 109(9),
Page 24
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
145
1248-1263.
27. Chewlos, P., Benbasat, I. & Dexter,
A.S. (2001). Research report:
Empirical test of an EDI adoption
model. Information System Research,
12(3), 304-321.
28. Chong, A., Y-L., & Chan, F.T.S.
(2012). Structural equation modeling
for multi-stage analysis on Radio
Frequency Identification (RFID)
diffusion in the health care industry.
Expert System with Applications, 39,
8645-8654.
29. Chong , A.Y.L., & Ooi, K.B. (2008).
Adoption of interorganizational
system standards in supply chains: An
empirical analysis of RossaNet
standards. Industrial Management &
Data Systems, 108, 529-547.
30. Davis, F.D. (1989). Perceived
Usefulness, Perceived Ease of Use
and User Acceptance of Information
Technology, MIS Quarterly, 13(3),
319-339.
31. DeLone, W.H. (1988). Determinants
of success for computer usage in
small business. MIS Quarterly, 51-61.
32. Davis, D., Dunn, P. & Boswell, K.
(2009). The importance of capturing
and using financial information in
small business. American Journal of
Economics and Business
Administration, 1(1), 27-33.
33. Durbhakula, V.V.K., & Kim, D.J.
(2011). E-business for nations: a study
of national level e-business adoption
factors using country characteristics-
business-technology-government
framework. Journal of Theoretical
and Applied Electronic Commerce
Research, 6(3), 1-12.
34. Dyt, R. & Halabi, A.K. (2007).
Empirical evidence examining the
accounting information systems and
accounting reports of small and micro
business in Australia. Small
Enterprise Research, 15(2), 1-9.
35. Ellis, J & Belle, J.V. (2011). Open
source software adoption by South
African MSEs: Barriers and enablers.
Proceedings of the 2009 Annual
Conference of the Southern African
Computer Lecturers’ Association,
Eastern Cape, South Africa, 29 June –
1 July 2009, 41-49.
36. Fadhil, N.F.M. & Fadhil, N.F.M.
(2010). Managing company’s
financial among small and medium
non-manufacturing companies. Far
East Journal of Psychology and
Business, 2(1), 17-36.
37. Fowzia, R., & Nasrin, M. (2011).
Appreciation of Computerized
Accounting System in Financial
Institutions in Bangladesh, World
Review of Business Research, 1(2), 1-
9.
38. Gemino, A., Mackay, N., & Reich,
B.H. (2006). Executive decisions
about website adoption in small and
medium-sized enterprises. Journal of
Information Technology Management,
XVII(1), 34-49.
39. Ghobakhloo, M., Arias-Aranda, D. &
Benitez-Amado, J. (2011). Adoption
of e-commerce applications in SMEs.
Industrial Management & Data
Systems, 111(8), 1238-1269.
40. Grandon, E.E. & Pearson, J.M.
(2004). Electronic commerce
adoption: an empirical study of small
and medium US businesses.
Information & Management, 42(1),
197-216.
41. Grandon, E.E., Nasco, S.A., &
Mykytyn, P.P. (2011). Comparing
theories to explain e-commerce
adoption. Journal of Business
Research, 64, 292-298.
42. Halabi, A.K., Barret, R., Dyt, R.
(2010). Understanding financial
information used to assess small firm
performance. Qualitative Research in
Accounting & Management, 7(2),
163-179.
43. Hameed, M.A., & Counsell, S.
(2012). Assessing the influence of
Page 25
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
146
environmental and CEO
characteristics for adoption of
information technology in
organizations. Journal of Technology
Management & Innovation, 7(1), 64-
84.
44. Harrison, D.A., Mykytyn, P.P., &
Riemenschneider, C.K. (1997).
Executive decisions about adoption of
information technology in small
business: Theory and empirical tests.
Information Systems Research, 8(2),
171-195.
45. Henderson, D., Sheetz, S.D., &
Trinkle, B.S. (2012). The
determinants of inter-organizational
and internal in-hounse adoption of
XBRL: A structural equation model.
International Journal of Accounting
Information Systems, 13, 109-140.
46. Hossain, M.A., & Quaddus, M.
(2011). The adoption and continued
usage intention of RFID: an integrated
framework. Information Technology
& People, 24(3), 236-256.
47. Hong, W., & Zhu, K. (2006).
Migrating to internet-based e-
commerce: Factors affecting E-
Commerce adoption and migration at
the firm level. Information &
Management, 43(2), 204-221.
48. Hung, S., Hung, W., Tsai, C., &
Jiang, S. (2010). Critical factors of
hospital adoption on CRM system:
organizational and information system
perspectives. Decision Support
Sytems, 48, 592-603.
49. Hussin, H., & Noor, R.M. (2005).
Innovating business through e-
commerce: Exploring the willingness
of Malaysian SMEs. The Second
International Conference on
Innovations in IT (IIT’ 05). Paper
available at http://www.it-
innovations.ae/iit005/proceedings/arti
cles/I_4_IIT05_Hussin.pdf
50. Huy, L.V. (2012). An empirical study
of determinants of E-commerce
adoption in SMEs in Vietnam: An
economy in transition. Journal of
Global Information Management,
20(3), 32 pages.
51. Iacovou,C.L., Benbasat,I. & Dexter,
A.S. (1995). Electronic data
interchange and small organizations:
Adoption and impact of technology.
MIS Quarterly, 465-485.
52. Ifinedo, P. (2011). Internet/e-business
technologies acceptance in Canada’s
SMEs: an exploratory investigation.
Internet Research, 21(3), 255-281.
53. Ifinedo, P. (2012). Understanding
information systems security policy
compliance: An integration of the
theory of planned 146o-worker and
the protection motivation theory.
Computers & Security, 31, 83-95.
54. Igbaria, M. (1990). End-user
computing effectiveness: a structural
model. Omega, 18(6), 637-652.
55. Igbaria, M., Zinatelli, N., Cragg, P., &
Cavage, A.L.M. (1997). Personal
computing factors in small firms: a
structural model. MIS Quarterly,
21(3), 279-305.
56. Illias, A., Abd Razak, M.Z., Abdul
Rahman, R., & Yasoa’, M.R. (2009).
End-user computer satisfaction
(UECS) in computerized accounting
system (CAS): Which the critical
factors? A case in Malaysia.
Computer and Information Science,
2(1), 18-24
57. Ismail, N.A. & Mat Zin, R. (2009).
Usage of Accounting Information
among Malaysian Bumiputra Small
and Medium Non-Manufacturing
Firms. Journal of Enterprise resource
Planning Studies, 1(2), 11-17.
58. Ismail, N.A. (2009). Factors
influencing AIS effectiveness among
manufacturing SMEs: Evidence from
Malaysia. The Electronic Journal on
Information Systems in Developing
Countries, 38(10), 1-19.
59. Jacks, T., Palvia, P., & Schilhavy, R.
(2011). A framework for the impact
Page 26
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
147
of IT on organizational performance.
Business Process Management
Journal, 17(5), 846-870.
60. Khalifa, M., & and Davidson, R.M.
(2006). SME adoption of IT: The case
of electronic trading systems’. IEEE
Transactions on Engineering
Management, 53(2), 275-284.
61. Kijsanayotin, B., Pannarunothai, S., &
S. M. Speedie (2009). Factors
influencing health information
technology adoption in Thailand’s
community health centers: Applying
the UTAUT model. International
Journal of Medical Informatics, 78,
404-416.
62. Kouser, R., Rana, G., & Shahzad,
F.A. (2011). Determinants of AIS
effectiveness: assessment thereof in
Pakistan. International Journal of
Contemporary Business Studies,
2(12), 6-21
63. Kuan,K.K.Y. & Chau,P.Y.K. (2001).
A perception-based model for EDI
adoption in small businesses using a
technology-organization-environment
framework. Information &
Management, 38:507-521.
64. Lee, J.M., & Runge, J. (2001).
Adoption of information technology
in small business: testing drivers of
adoption for entrepreneurs. The
Journal of Computer Information
Systems, 42(1), 44-57.
65. Lee, S.W., & Kim, D.J. (2004).
Driving factors and barriers of
information and communication
technology for e-cbusiness in SMEs:
A case study in Korea. IADIS
International Conference e-Society,
163-171.
66. Lertwongsatien, C. &
Wongpinunwatana, N. (2003). E-
commerce adoption in Thailand: An
empirical study of small and medium
enterprises (SMEs). Journal of
Global Information Technology
Management, 6(3), 67-83.
67. Li, X., Troutt, M. D., Brandyberry,
A., & Wang, T. (2011). Decision
factors for the adoption and continued
use of online direct sales channels
among SMEs. Journal of the
Association for Information Systems,
12(1), 1-31.
68. Liang, T., You, J., & Liu, C. (2010).
A resource-based perspective on
information technology and firm
performance: a meta analysis.
Industrial Management & Data
Systems, 110(8), 1138-1158.
69. Limayem, M., & Cheung, C.M.K.
(2008). Understanding information
systems continuance: The case of
internet-based learning technologies.
Information & Management, 45, 227-
232.
70. Lin, H. & Lin, S. (2008).
Determinants of e-business diffusion:
A test of the technology diffusion
perspective. Technovation, 28, 135-
145.
71. Lin, H. (2008). Empirically testing
innovation charateristics and
organizational learning capabilities in
e-business implementation success.
Internet research, 18(1), 60-78.
72. Low, C., Chen, Y. & Wu, M. (2011).
Understanding the determinants of
cloud computing adoption. Industrial
Management & Data Systems, 111(7),
1006-1023.
73. Looi, H.C. (2005). E-Commerce
adoption in Brunei Darussalam. A
quantitative analysis of factors
influencing its adoption.
Communications of the Associaion for
Information Systems, 15, 61-81.
74. Mackay, N., Parent, M. & Gemino, A.
(2004). A model of electronic
commerce adoption by small
voluntary organizations. European
Journal of Information Systems, 13,
147-159.
75. McClery, S., Godfrey, A.D. &
Meechan, L. (2005). Barriers and
catalysts to sound financial
management systems in small sized
Page 27
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
148
enterprises. The Journal of Applied
Accounting Research, 7(3), 1- 25.
76. Mcmahon, R.G.P. (2001). Growth and
performance of manufacturing SMEs:
The influence of financial
management characteristics.
International Small Business Journal,
19(3), 10-28.
77. MacKenzie, L.M. (2006). Use of the
internet as a business tool by small
and medium-sized enterprises
(SMEs): A descriptive study of small
Minnesota-based manufacturers’
internet usage. Dissertation Degree
Doctor of Philosophy, Capella
University.
78. Mehrtens, J., Cragg, P.B., & Mills,
A.J. (2001). A model of internet
adoption by SMEs. Information &
Management, 39(3), 165-176.
79. Nazem, S. (1990). Sources of
software and levels of satisfaction for
small business computer applications.
Information & Management, 19, 95-
100.
80. Nelson, M.L. & Shaw, M.J. (2003).
The adoption and diffusion of
interorganizational system standards
and process innovation, standard
Making: A critical Research Frontier
for Information Systems, MISQ
Special Issue Workshop.
81. Nguyen, T.H. (2009). Information
technology adoption in SMEs: an
integrated framework. International
Journal of Entrepreneurial Behaviour
& Research, 15(2), 162-186.
82. Oliveira, T. & Martins, M.F. (2010).
Understanding e-business adoption
across industries in European
countries. Industrial Management &
Data Systems, 110(9), 1337-1354.
83. Oliveira, T., & Martins, M.F. (2011).
Literature review of information
technology adoption models at firm
level. The Electronic Journal
Information Systems Evaluation.
14(1), 110-121.
84. Ozturk, a.B. (2010). Factors affecting
individual and organizational RFID
technology adoption in the hospitality
industry. Published phD Dissertation.
Oklahoma State University, USA.
85. Peel, M.J. & Wilson, N. (1996).
Working capital and financial
management practices in the small
firm sector. International Small
Business Journal, 14(2), 52-68
86. Picoto, W., Belanger, F., & Palma-
dos-Reis, A. (2012). Leveraging on
mobile business to enhance firm
performance: An organizational level
study. ECIS 2012 Proceedings. Paper
113
87. Porter, M., & Millar, V.E. (1985).
How information gives you
competitive advantage. Harvard
Business Review, 63(4), 149-160.
88. Powell, T.C. & Dent-Micallef, A.
(1997). Information technology as
competitive advantage: The role of
human, business, and technology
resources. Strategic Management
Journal, 18(5), 375-405.
89. Poon, S. & Swatman, P. (1999). The
role of interorganizational and
organizational factors on the decision
mode for adoption of
interorganizational system. Decision
Sciences, 303-336.
90. Premkumar, G. & Bhattacherjee, A.
(2008). Explaining information
technology usage. A test of competing
models. OMEGA, 36(1), 64-75
91. Premkumar, G. & Roberts, M. (1999).
Adoption of new information
technologies in rural small businesses.
Omega.The International Journal of
Management Science, 27, 467-484.
92. Premkumar, G. (2003). A meta-
analysis of research on information
technology implementation in small
business. Journal of Organizational
Computing and Electronic Commerce,
13(2), 92-121.
93. Premkumar, G., Ramamurthy, K. &
Page 28
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
149
Nilakanta, S. (1994). Implementation
of Electronic Data Interchange: An
innovation diffusion perspective.
Journal of Management Information
Systems, 11(2), 157-186.
94. Proudlock,M., Phelps, B., & Gamble,
P. (1999). IT adoption strategies: Best
practice guidelines for professional
SMEs. Journal of Small Business and
Enterprise Development, 6(3), 240-
252.
95. Ramanathan, R., Ramanathan, U.,
Hsiao, H. (2012a). The impact of e-
commerce on Taiwanese SMEs:
Marketing and operations effects. Int.
J. Production Economics, 140, 934-
943.
96. Ramdani, B. & Kawalek, P. (2007).
SME adoption of enterprise systems
in the Northwest of England: An
environmental, Technological and
Organizational perspective. IFIP
International Federation for
Information Processing, 235, 409-
429.
97. Ramdani,B., Kawalek,P. &
Lorenzo,O. (2009). Knowledge
management and enterprise systems
adoption by SMEs: Predicting SMEs’
adoption of enterprise systems.
Journal of Enterprise Information
Management, 22(1/2),10-24.
98. Riemenschneider, C.K., Harrison,
D.A., & Mykytyn, Jr., P.P. (2003).
Understanding IT adoption decisions
in small business: Integrating current
theories. Information & Management,
40(4), 269-285.
99. Riyard, A.N., & Akter, M.S., & Islam,
N. (2009). The adoption of e-banking
in developing countries: A theoretical
model for SMEs. International
Review of Business Research Papers,
5(6), 212-230.
100. Roger, E.M. (1995). Diffusion of
Innovations (4th ed.). The Free Press,
New York, NY.
101. Rui, G. (2007). Information systems
innovation adoption among
organizations: A match-based
framework and empirical studies.
Published PhD Thesis, National
University of Singapore.
102. Salleh,N.A.M. & Rohde,F. (2005).
Enacted capabilities on adoption of
information systems: A study of
small-and medium-sized enterprises.
Communications of the IIMA, 5(3), 1-
16.
103. Salwani, M.I., Marthandan, G.,
Norzaidi, M.D., & Chong, S.C.
(2009). E-commerce usage and
business performance in the
Malaysian tourism sector: empirical
analysis. Information Management &
Computer Security, 17(2), 166-185.
104. Scupola, A. (2003). The adoption of
internet commerce by SMEs in the
South of Italy. An environmental,
technological and organizational
perspective. Journal of Global
Information Technology Management,
6(1), 52-71.
105. Scupola, A. (2009). SMEs’ e-
commerce adoption: perspectives
from Denmark and Australia. Journal
of Enterprise Information
Management, 22( ½ ), 152-166.
106. Seyal, A.H. & Rahman, M.N.A.
(2003). A preliminary investigation of
E-Commerce adoption in small &
medium enterprises in Brunei.
Journal of Global Information
Technology Management, 6(2),6-26.
107. Seyal, A.H., Rahman, M.N.A., &
Mohammad, A.Y.A. (2007). A
quantitative analysis of factors
contributing electronic data
interchange adoption among Bruneian
SMEs. A pilot study. Business
Process Management Journal, 13(5),
728-746.
108. Shiau, W., Hsu, P. & Wang, J. (2009).
Development of measures to assess
the ERP adoption of small and
medium enterprises. Journal of
Enterprise Information Management,
22(1/2):,99-118.
Page 29
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
150
109. Shaharuddin, M.R., Omar, M.W.,
Elias, S.J., Ismail, M., Ali, S.M. &
Fadzil, M.I. (2012). Determinants of
electronic cmmerce adoption in
Malaysian SMEs’ furniture industry.
African Journal of Business
Management, 6(10), 3648-3661.
110. Stefanou, C.L. (2006). The
complexity and the research area of
AIS. Journal of Enterprise
Information Management, 19(1), 9-
12.
111. Tan & Felix, T.C. (2010). A
perception-based model for
technological innovation in small and
medium enterprises. Paper presented
at 18th European Conference on
Information Systems (ECIS). Paper
33.
112. Tanwongsvai, V. & Pinvanichkul, T.
(2007). Accounting information
requirement and reporting practices of
Thai SMEs. Journal of Accounting
Profession, 59-74.
113. Tan, K.S., Chong, S.C., Lin, B. &
Eze, U.C. (2009). Internet-based ICT
adoption: evidence from Malaysian
SMEs. Industrial Management &
Data Systems, 109(2), 224-244.
114. Teo, T.S.H., & Ranganathan, C.
(2004). Adopters and non-adopters of
E-Procurement in Singapore. .
OMEGA. The International Journal of
Management Science, 37(5), 972-987.
115. Thong, J.Y.L. (1999). An integrated
model for information systems
adoption in small businesses. Journal
of Management Information Systems,
187-214.
116. Thong, J.Y.L. & Yap, C.S. (1995).
CEO characteristics, organizational
characteristics and information
technology adoption in small
businesses. OMEGA. The
International Journal of Management
Science, 23(4): 429-442.
117. Thatcher, S.M.B., Foster, W., & Zhu,
L. (2006). B2B e-commerce adoption
decisions in Taiwan: The interaction
of cultural and other institutional
factors. Electronic Commerce
Research and Applications, 5, 92-104.
118. Thong, J.Y.L. (1999). An integrated
model of information systems
adoption in small businesses. Journal
of Management Information Systems,
15(4), 187-214.
119. Tornatzky, L.G. & Fleischer, M.
(1990). The process of technology
innovation. Lexington Books,
Lexington, MA.
120. Tornatzky,L.G. & Klein, K. (1982).
Innovation characteristics and
innovation adoption-implementation:
A meta-analysis of findings. IEEE
Transactions on Engineering
Management, 29(1),28-43.
121. Vance, A., Elie-Dit-Cosaque, C. &
Straub, D.W. (2008). Examining trust
in information technology artifacts:
The effects of system quality and
culture. Journal of Management
Information Systems, 24(4), 73-100
122. Varukolu, V. & Park-Poaps, H.
(2009). Technology adoption by
apparel manufacturers in Tirupur
Town, India. Journal of Fashion
Marketing and Management, 13(2),
201-214.
123. Ven, K. & Verelst, J. (2011). An
empirical investigation into the
assimilation of open source server
software. Communications of the
Association for Information Systems,
28(9), 117-140.
124. Venkatesh, V. (2000). Determinants
of perceived ease of use: Integrating
control, intrinsic motivation, and
emotion into the technology
acceptance model. Information
Systems Research, 11(4), 342-365.
125. Wang, Y.M., Wang, Y.S., and Yang,
Y.F. (2010). Understanding the
determinants of RFID adoption in the
manufacturing industry.
Technological Forecasting and Social
Change, 77, 803-815.
126. Wang, E.T.G., Tai, J.C.F., & Wei,
Page 30
International Journal of Information Technology and Business Management 29
th July 2013. Vol.15 No.1
© 2012 – 2013 JITBM & ARF. All rights reserved
ISSN 2304-0777 www.jitbm.com
151
H.L. (2006). A virtual integration
theory of improved supply chain
perfroamnce. Journal of Management
Information Systems. 13(2), 41-64.
127. Wernerfelt, B. (1984). The resource-
based view of the firm. Strategic
Management Journal, 5(2),171-180.
128. Winney, P. W., & Lo, M. (2012). The
impact of trustworthiness on customer
e-loyalty and e-satisfaction.
Proceeding of 2nd Annual Summit on
Business and Entrepreneurial studies
(2nd ASBES), 15th – 16th October
Hilton Hotel, Kuching, Sarawak.
129. Yang, S., Chao, Z., Lin, G., & Chen,
G. (2012). The role of top
management and dynamic capability
in inter-organizational information
system assimilation. Business and
Information, 313-336 (Sapporo, July
3-5).
130. Yang, Z., Kananhalli, A., Ng, B., &
Lim, J.T.Y. (2013). Analyzing factors
for the organizational decision to
adopt healthcare information systems.
Decision Support Systems. In Press.
131. Yoon, T. (2009). An empirical
investigation of factors affecting
organizational adoption of virtual
worlds. Doctoral Dissertation, The
Florida State University College of
Business, 2009.
132. Zailani, S., Dahlan, N., & Jallaludin,
Y.H. (2009). E-business adoption
among SMEs in Malaysia:
Investigation from the supply cahin
perspective. Problems and
Perspective in Management, 7(4), 46-
61.
133. Zhao, L., Lu, Y., Zhang, L., & Chau,
P.Y.K. (2012). Assessing the effects
of service quality and justice on
customer satisfaction and the
continuance intention of mobile
value-added services: An empirical
test of a multidimensional model.
Decision Support Systems, 52, 645-
656.
134. Zhu, K. Dong, S., Xu, S. X., Kraemer,
K.L. (2006). Innovation diffusion in
global contexts: Determinants of post-
adoption digital transformation of
European companies. European J of
Information Systems, 15(6), 601-616.