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Top Management Support, External Expertise and Information Systems Implementation
in Small Businesses
Author(s): James Y. L. Thong, Chee-Sing Yap and K. S. Raman
Source:
Information Systems Research
, June 1996, Vol. 7, No. 2 (June 1996), pp. 248-
267
Published by: INFORMS
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Top Management Support, External
Expertise and Information Systems
Implementation in Small Businesses
James Y. L. Thong • Chee-Sing Yap • K. S. Raman
Department of Information Systems and Computer Science, National University of Singapore, Singapore 119260
jthong@iscs.nus.sg
yapcs@iscs.nus.sg
ksraman@iscs.nus.sg
Top management support is a key recurrent factor critical for effective information systems (IS)
implementation. However, the role of top management support may not be as critical as external
IS expertise, in the form of consultants and vendors, in small business IS implementation due to the
unique characteristics of small businesses. This paper describes an empirical study of the relative
importance of top management support and external IS expertise on IS effectiveness in 114 small
businesses. Partial least squares (PLS) was used for statistical testing. The results show that top man
agement support is not as important as effective external IS expertise in small business IS implemen
tation. While top management support is essential for IS effectiveness, high quality external IS expertise
is even more critical for small businesses operating in an environment of resource poverty. These
findings call for more research efforts to be directed at selecting and engaging high quality external
IS expertise for IS implementation in small businesses.
(Top Management Support; External Expertise-, Consultant; Vendor; Small Businesses)
1. Introduction
Top management support has been identified as a key
recurring factor critical to information systems (IS) ef
fectiveness in both large and small businesses (see Cer
veny and Sanders 1986, DeLone 1988, Ginzberg 1981,
Keen and Scott-Morton 1978, Kwon and Zmud 1987,
Lucas 1981, Yap et al. 1992). Kwon and Zmud (1987)
asserted that successful IS implementation occurs when
sufficient organizational resources (sufficient developer
and user time, sufficient funding, sufficient technical
skills, etc.) are directed toward, first, motivating and
then sustaining the implementation effort. By virtue of
their leadership role, top management are able to ensure
sufficient allocation of resources and act as a change
agent to create a more conducive environment for IS
implementation (Lucas 1981). Top management have
the authority to influence other members of the busi
ness, and are more likely to succeed in overcoming or
ganizational resistance to accept the IS (Keen 1981, Mar
kus 1983). Strong top management commitment is ex
pected to lead to superior conversion effectiveness (the
way IS is converted to productive outputs) and thus
better IS performance for the same level of IS investment
(Weill 1992). Jarvenpaa and Ives (1991) noted that hands
on management in IS projects might be much more im
portant in a small business where the CEO commonly
makes most key decisions and is perhaps the only one
who can harness information technology (IT) to corpo
rate objectives and strategy. A supportive CEO is more
likely to commit scarce resources and adopt a longer
range perspective to the benefits of IS implementation.
IT can help small businesses to develop their markets,
increase sales turnover, raise profitability, secure their
positions within the industries, and gain a competitive
edge (Clark 1987, Dwyer 1990, Lincoln and Warberg
1987, Massey 1986, Poutsma and Walravens 1989).
Information Systems Research
Vol. 7, No. 2, June 1996
1047-7047/96/0702/0248$01.25
Copyright © 1996, Institute for Operations Research
and the Management Sciences
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
However, small businesses face substantially greater
risks in IS implementation than larger businesses due
to their unique characteristics (Ein-Dor and Segev 1978,
West 1975, Whistler 1970).
Organizational theories and practices that are appli
cable to a large business may not fit a small business
(see Blau et al. 1966, Blili and Raymond 1993, Cohn and
Lindberg 1972, Raymond 1985, Senn and Gibson 1981).
There is a need to take off the "big-organization
glasses" and look at small businesses separately, not in
the relational view commonly used (Dandridge 1979).
A small business is not a scale model of a large business.
Small businesses tend to have simple and highly cen
tralized structures with the chief executive officers
(CEOs) making most of the critical decisions (Mintz
berg 1979). They also tend to employ generalists rather
than specialists. Operating procedures are not written
down or standardized. In addition, small businesses
suffer from resource poverty such as financial con
straints, lack of professional expertise, and susceptibil
ity to external forces, because they are operating in a
highly competitive environment (Welsh and White
1981). Hence, they have to watch their cash flows care
fully, do not have the necessary in-house IS expertise,
and tend to have a short-range management perspective
with regard to IS implementation.1 While it is true that
large businesses also suffer from many of the same con
straints, the effect on small businesses is more signifi
cant. Skills, time, and staff necessary for planning are
not major issues in large businesses, yet these same is
sues represent most of the planning related manage
ment difficulties of small businesses (Cohn and Lind
berg 1972). Small businesses tend to choose the lowest
cost IS which may be inadequate for their purpose and
underestimate the amount of time and effort required
for IS implementation (Yap 1989a). Thus, inadequate
planning for IS implementation increases the risk of im
plementation failure. Further, few small businesses uti
lize management techniques such as financial analysis,
1 In this paper, we adopt Lucas' (1981) definition of IS implementa
tion as not the final stage in the systems life cycle but as an on-going
process which includes the entire development of the system from
the original suggestion through the feasibility study, systems anal
ysis and design, programming, training, conversion, and installation
of the system.
forecasting, and project management (D'Amboise and
Gasse 1990). The decision process of small business
managers are more intuitive, based on "guesswork"
and less dependent on formal decision models (Rice
and Hamilton 1979).
Due to the unique characteristics of small businesses,
the roles played by top management support, external
consultants, and vendors in small businesses may be
significantly different from that in large businesses. Be
cause of the much simpler organization structure, there
are relatively limited political problems in small busi
nesses and the role of top management as a "fixer" in
IS implementation may not be as important as in large
businesses. In contrast, because of the lack of in-house
IS expertise, small businesses are likely to be much more
dependent on external IS expertise such as consultants
and vendors (Couger and Wergin 1974, Senn and Gib
son 1981). Small businesses generally lack computer ex
perience and do not have sufficient internal IS expertise
(DeLone 1988, Gable 1991). Further, small businesses
face difficulties in recruiting and retaining internal IS
experts due to scarce qualified IS experts and limited
career advancement prospects. Hence, while top man
agement support is important for IS implementation,
external IS expertise may be even more important in the
small business context.
Recently, Attewell (1992) proposed a theory of tech
nology diffusion to explain adoption of business com
puting by organizations. His theory emphasizes organi
zational learning and the role of external entities such
as consultants and IT vendors as knowledge providers
to lower the knowledge barrier or knowledge deficiency
on the parts of potential IT adopters. Businesses tend to
delay in-house adoption of IT because they have insuf
ficient knowledge to implement and operate IT success
fully. In response to this knowledge barrier, mediating
entities come into existence which progressively lower
this barrier, and make it easier for businesses to adopt
and use IT without extensive in-house expertise. These
mediating entities can capture economies of scale in
learning. After developing many accounting systems,
the IT vendor would have learned from earlier attempts
and develop a relatively error-free system. Similarly,
the consultant would have acquired a wealth of expe
rience in IS implementation. Hence, external consult
ants and IT vendors can play an important role in
Information Systems Research
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
assisting businesses, especially small businesses, to
adopt IS successfully.
The above discussion suggests a need to reexamine
the role of top management support in IS implementa
tion in small businesses. Given Attewell's (1992) theory
of lowering knowledge barrier, it is important to com
pare the effects of top management support vis-a-vis
external IS expertise in small business IS implementa
tion. Is top management support indispensable in IS im
plementation? Does the importance of top management
support overwhelm the influence of external IS exper
tise in small business IS implementation or vice versa?
Or, are the two factors equally critical? These questions
are important as external IS expertise has not been com
pared with the role of top management support in IS
implementation. Further, prior studies on external IS ex
pertise have been prescriptive in nature or based on case
studies (Gable 1991, Kole 1983, Newpeck and Hallbaur
1981, Senn and Gibson 1981). These research questions
also have practical implications for small businesses
contemplating engaging external IS experts. If top man
agement support is more important than external IS ex
pertise, future IS implementation efforts should con
tinue to focus on securing high levels of top manage
ment support, as prescribed in the IS literature.
Researchers would then need to explore the best ways
to secure top management support. Conversely, if ex
ternal IS expertise is found to overwhelm the influence
of top management support, practitioners and research
ers should pay more attention to the roles of external
consultants and vendors in IS implementation. Future
research should then be directed at identifying attri
butes of "good" or "effective" consultants and vendors,
and developing effective approaches for engaging con
sultants and vendors.
The rest of this paper is organized as follows. In §2,
the research model and propositions are discussed in
detail. Section 3 describes the research methodology
adopted for this study. Section 4 describes the data anal
ysis technique and presents the results of propositions
testing. In §5, the results are discussed. Finally, §6 sum
marizes and concludes the paper.
2. Research Model
Figure 1 shows the conceptual model in this research.
The IS implementation environment is conceptualized
Figure 1 Conceptual Model
in terms of top management support and external IS
expertise. The conceptual model is based on the theory
that small businesses lag behind larger businesses in the
use of IS due to resource poverty, and top management
support and external IS expertise are two key factors
that can alleviate the poverty. We will elaborate on these
two factors below.
2.1. Top Management Support
The importance of top management support in IS im
plementation has been recognized often in the IS liter
ature since the late 1960s (Argyris 1971, Dean 1968, Die
bold 1969, Senn 1978). More recently, it has been
preached religiously in numerous text books on infor
mation systems management (Cash et al. 1992, Earl
1989, Lucas 1986, Sprague and McNurlin 1986). There
is also ample evidence of the importance of top man
agement support for effective IS in the case study liter
ature (e.g. Elam 1988, Stoddard 1986, Vitale 1988, Yap
1989b) and empirical studies in both small and large
businesses (Bruwer 1984, Couger and Wergin 1974,
DeLone 1988, Doll 1985, Greenwood 1981, Newpeck
and Hallbaur 1981, Sanders and Courtney 1985, Van
lommel and De Brabander 1975, Yap et al. 1992).
Yap (1989b) offered two reasons why top manage
ment should be supportive of IS implementation. First,
top management, with their broader perspectives, are
in a better position than system analysts to identify busi
ness opportunities for the exploitation of IT. This is es
pecially true in a small business where the CEO is the
person who understands the business best. Second, IS
implementation involves huge investments and often
has organization-wide implications. The future of the
business may be jeopardized by unsuccessful invest
ments in IS because a technical failure in the IS can have
a major negative impact on the business that is heavily
dependent on it. The setback has even greater implica
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
tion for a small business as it may even result in busi
ness failure (Senn and Gibson 1981). Due to their
unique characteristics, small businesses have a much
higher mortality rate than large businesses (Singh et al.
1986). Ginzberg (1981) found that top management
commitment to the IS project and to organizational
change can differentiate between successful and unsuc
cessful IS implementation. Visible top management
support encourages positive attitudes on the part of
users toward use of the IS and leads to a smoother con
version from the existing work procedures.
Essentially, top management support can take the
form of managerial guidance in planning, design, de
velopment, and implementation activities (Bruwer
1984). Other avenues of top management support in
clude written overall development plans, mutually
agreed upon development priorities, long-term funding
commitments, system planning objectives, and project
development policies (Benjamin et al. 1984, Doll 1985,
Ives and Learmonth 1984, Porter and Millar 1985).
While top management can be supportive of IS imple
mentation through participation in executive steering
committees in large businesses (Nolan 1982, Raghuna
than 1992, Raghunathan and Raghunathan 1989), the
approach in small businesses tends to be informal with
no official committees. There are usually no written
plans or policies. Essentially, the CEO of a small busi
ness attends project meetings with the external IS ex
perts to specify the business requirements, to clarify is
sues related to the project, and to monitor the progress
of the project.
2.2. External IS Expertise
Small businesses rely on consultants and vendors in
their IS implementation projects. The effectiveness of
consultants and the quality of vendor support are im
portant for successful IS implementation.
2.2.1. Consultant Effectiveness. The IS literature
contains mainly descriptive surveys and case studies on
the engagement of consultants. These studies are
mainly practitioner-oriented and tend to prescribe ap
proaches to select, install, use, and control information
systems. For example, Senn and Gibson (1981) strongly
recommended engaging a consultant who has technical
expertise as well as knowledge of small business oper
ations. Newpeck and Hallbauer (1981) believed that an
outside consultant is imperative to making the best de
cisions regarding the acquisition and use of information
systems. Based on case studies, Gable (1989) and Kole
(1983) found that the experience and capabilities of the
consultant or consultant effectiveness plays an impor
tant role in IS implementation in small businesses.
There is also some empirical evidence that IS effective
ness is positively correlated with consultant effective
ness (Yap et al. 1992).
The primary duties of a consultant are to provide con
sultancy service specifically to help businesses imple
ment effective information systems. Consultancy ser
vice can include performing information requirements
analysis, recommending suitable computer hardware
and software, and managing implementation of the in
formation systems.
Intuitively, we would expect small businesses, due to
insufficient internal technical expertise, to engage some
form of external IS expertise. Simon (1990) pointed out
four advantages of engaging external consultants over
employing internal IS staff. First, the small businesses
need not maintain expensive internal IS staff when the
IS implementation is completed and maintenance is in
frequent. Second, they need not provide expensive on
going professional training for the internal IS staff to
keep up with advancing technology. Third, it is difficult
to engage qualified internal IS staff due to their scarcity
and the limited career advancement prospects in a small
business. Fourth, the increasingly complex technology
will require hiring of various specialists which is not
feasible in small businesses.
However, there appears to be a lack of understanding
of the consulting process by small businesses. They tend
to overestimate the impact of external IS experts in
achieving effective IS implementation, and underesti
mate the importance of their own involvement. Lees
(1987) found that if the consultants have inadequate ex
perience and abilities, decreased top management in
volvement may have negative effects on user satisfac
tion and system usage. There is a need for pro-active
top management involvement in IS implementation
even when a consultant is engaged (Gable 1991).
2.2.2 Vendor Support. Vendor support is another
form of external IS expertise for the resource-limited
small businesses. With little internal computer expertise,
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
small businesses are very reliant on the advice and
support from vendors (Cragg and King 1993). The lit
erature on vendor support has tended to be descriptive
in nature. Typical of this genre, Heintz (1981) discussed
three approaches to engaging vendors in IS implemen
tation: (1) rely on vendor advice, (2) start with a simple
IS and take one step at a time, and (3) prepare a formal
request-for-proposal; and concluded that the last ap
proach is the most desirable. This approach assumes,
correctly or incorrectly, that the small business has
enough expertise to prepare a formal request-for
proposal that has realistic expectations. Other popular
recommendations include checking on vendors' creden
tials and purchasing hardware and software from rep
utable vendors with large customer base (Cheney 1983,
Garris and Burch 1983, Greenwood 1981, Lees and Lees
1987, Newpeck and Hallbaur 1981, Pipino and Necco
1981). There is also empirical evidence to suggest pos
itive relationships between measures of IS effectiveness
and vendor support (Lees 1987, Wong 1986, Yap et al.
1992).
The duties of a vendor generally include providing
the computer hardware, software packages, technical
support, and training of users. In some cases, a vendor
also plays the role of a consultant. For small businesses
that want to implement basic operational systems, a
vendor often can provide the same level of consultancy
service as a specialized consultant (Thong et al. 1994).
A common concern of some researchers is the lack of
independence of vendors (Heintz 1981, Senn and Gib
son 1981). The vendors may recommend products in
which they have a vested interest but which may not
suit the requirements of the small business (Yap 1989a).
If this is allowed to occur, the small business may have
to modify requirements to suit the products offered by
the vendors and settle for a less effective information
system. Alternatively, the small business may have to
change work procedures, for better or worse, to work
with the new system. To some extent, the problems aris
ing from a lack of independence of vendors may be
ameliorated by the highly competitive IT market place
which dictates that the prices of similar products do not
vary drastically and the products must meet acceptable
standards (Thong et al. 1994). Computer hardware, es
pecially personal computers, and software are becom
ing standardized commodity products. It is also not un
common to find different vendors marketing the same
products. Hence, vendors are compelled to provide
quality products and services at reasonable prices to re
main competitive.
2.3. IS Effectiveness
IS effectiveness may be defined as the extent to which
an information system actually contributes to achieving
organizational goals, i.e., its effect on organizational
performance (Hamilton and Chervany 1981, Raymond
1990). However, there is no consensus among IS re
searchers on the conceptualization and operationaliza
tion of IS effectiveness (DeLone and McLean 1992,
Goodhue 1992, Srinivasan 1985). Approaches to mea
sure IS effectiveness that have been utilized in previous
research include cost-benefit analysis, system usage es
timation, user satisfaction, incremental performance in
decision-making effectiveness, information economics,
utility analysis, analytic hierarchy approach, and infor
mation attribute examination (Srinivasan 1985). Based
on a review of the literature on IS effectiveness, DeLone
and McLean (1992) concluded that it is unlikely that any
single, overarching measure of IS effectiveness will
emerge; and so multiple measures will be necessary, at
least in the foreseeable future. In this study, IS effect
iveness is measured by user satisfaction, organizational
impact, and overall IS effectiveness. These measures are
discussed further in §3.1.
2.4. Propositions
In this study, the main research question is to examine
the relative importance of top management support and
external IS expertise in small business IS implementa
tion. This research question can be tested through par
tial least squares (PLS), a powerful structural equation
modeling technique, by examining the relative size and
significance of the path coefficients (Chin and Gopal
1993). Hence, we formulate our propositions in terms
of a causal model. The propositions derived from the
research model are now described (see Figure 2).
2.4.1. Top Management Support. In environments
with low level of top management support, top man
agement may approve the purchase of the computer
system but are not involved in other aspects of IS im
plementation. They may not attend project meetings or
be involved in information requirements analysis, re
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
Figure 2 Research Model
view of consultant's recommendations, participate in
decision-making, or monitor the project. Hence, IS ef
fectiveness is expected to be low when the level of top
management support is low. In environments which
have a high level of top management support, members
of top management will attend project meetings regu
larly and will be involved in information requirements
analysis, review consultant's recommendations, partic
ipate in decision-making, and monitor the project.
Hence, IS effectiveness is likely to be high when the
level of top management support is high.
Proposition la. Greater top management support will
result in greater user satisfaction.
Proposition lb. Greater top management support will
result in greater organizational impact.
Proposition lc. Greater top management support will
result in greater overall IS effectiveness.
2.4.2. Consultant Effectiveness. The level of con
sultant effectiveness is low when the consultant does
not conduct a proper information requirements analy
sis, recommends an IS which turns out to be ineffective,
manages implementation badly, and has poor working
relationships with other parties in the project. Under
such environments, the level of IS effectiveness is likely
to be low. Conversely, when the level of consultant ef
fectiveness is high, the level of IS effectiveness is likely
to be high.
Proposition 2a. Greater consultant effectiveness will
result in greater user satisfaction.
Proposition 2b. Greater consultant effectiveness will
result in greater organizational impact.
Proposition 2c. Greater consultant effectiveness will
result in greater overall IS effectiveness.
2.4.3. Vendor Support. The level of vendor support:
is low when the vendor is unreliable, provides inade
quate and poor technical support, gives insufficient and
poor training, and blames hardware and software prob
lems on other parties. Consequently, the implemented
IS may fail to satisfy user requirements and do not pro
duce the expected benefits. Hence, the level of IS effect
iveness is likely to be low when the level of vendor sup
port is low. Conversely, the level of IS effectiveness is
expected to be high when the level of vendor support
is high.
Proposition 3a. Greater vendor support will result in
greater user satisfaction.
Proposition 3b. Greater vendor support will result in
greater organizational impact.
Proposition 3c. Greater vendor support will result in
greater overall IS effectiveness.
3. Research Methodology
This section describes the operationalization of con
structs, the survey sample, and the data collection pro
cedure. The characteristics of the survey sample are also
presented.
3.1. Measures
The measures used in this study have either been for
mally validated in previous methodological studies or
have been used previously in empirical studies. Table 1
presents the operationalization of the constructs.
3.1.1. Top Management Support. Active engage
ment of top management with IS implementation is
highly desirable in businesses of every size (Rockart and
Crescenzi 1984). In the case of a small business, top
management is synonymous with the CEO. This is be
cause most small businesses have a flat organizational
structure and are managed by the owner who is usually
the CEO (Raymond and Magnenat-Thalmann 1982, Sol
omon 1986). The CEO is the most influential person in
a small business and his or her influence has a much
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
Table 1 Operationalization of Constructs
Construct Measure Scale
Top Management Support
1. CEO attendance at project meetings 7 point scale
2. CEO involvement in information requirements analysis Yap et al. (1994)
3. CEO involvement in reviewing consultant's recommendations
4. CEO involvement in decision-making
5. CEO involvement in monitoring project
Consultant Effectiveness
1. effectiveness in performing information requirements analysis 7 point scale
2. effectiveness in recommending suitable computer solution Thong et al. (1994)
3. effectiveness in managing implementation
4. relationship with other parties in the project (CEO, Users, Vendor)
Vendor Support
1. adequacy of technical support during IS implementation 7 point scale
2. adequacy of technical support after IS implementation Thong et al. (1994)
3. quality of technical support
4. adequacy of training provided
5. quality of training provided
6. relationship with other parties in the project (CEO, Users, Consultant)
User Satisfaction
1.
convenience of access 7 point scale
2. currency of reports Adapted from Raymond (1987)
3. timeliness of reports
4. reliability of reports
5. relevancy of reports
6. accuracy of reports
7. completeness of reports
Organizational Impact
1. pre-tax profit 7 point scale
2.
sales revenue Adapted from DeLone (1990)
3. staff productivity
4. competitive advantage
5.
operating cost
6. quality of decision-making
Overall IS Effectiveness
1. Overall IS effectiveness 7 point scale
wider impact than his or her counterpart in a large busi
ness (Doukidis et al. 1992). The CEO is also the main
information user and decision-maker in a small busi
ness and is in the best position to identify critical busi
ness applications to computerize. Hence, in this study,
top management support is measured by CEO support,
a measure proposed and validated by Yap et al. (1994).2
The measure consists of six items: (1) frequency of at
tendance at computerization project meetings, (2) level
2 The measure was developed through an extensive literature review
followed by iterative reviews by both practitioners and experienced
small business researchers. The measure was then pilot-tested in the
field followed by a questionnaire survey. It was found to demonstrate
adequate reliability and validity.
of involvement in information requirements analysis,
(3) level of involvement in reviewing consultant's rec
ommendations, (4) level of involvement in decision
making relating to the computerization project, and (5)
level of involvement in monitoring the project. These
items reflect the major IS implementation stages in a
small business.
3.1.2. Consultant Effectiveness. In this study, there
is a need to assess the consultant's performance in dif
ferent stages of IS implementation. The measure of con
sultant effectiveness was proposed and validated by
Thong et al. (1994). It is based on the IS implementation
life cycle, and comprises the following items: (1) con
sultant effectiveness in performing information require
ments analysis, (2) consultant effectiveness in recom
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
mending suitable computerization solution, (3) con
sultant effectiveness in managing the IS implementation
project, and (4) relationship between consultant and
other parties in the project (CEO, users, and vendor).
3.1.3. Vendor Support. Thong et al. (1994) devel
oped and validated a measure of vendor support based
on a review of vendor support literature (Heikkila et al.
1991, Lees 1987, Lucas et al. 1988, Soh et al. 1992, Wong
1986, Yap et al. 1992). The measure consists of six items:
(1) adequacy of technical support during implementa
tion, (2) adequacy of technical support after implemen
tation, (3) quality of technical support, (4) adequacy of
training provided, (5) quality of training provided, and
(6) relationship between vendor and other parties
(CEO, users, consultant) in the IS implementation proj
ect. This measure takes into consideration the adequacy
and the quality in addition to the amount of technical
support and training provided. The adequacy of tech
nical support and training provided do not fully reflect
the effectiveness of the technical support and training
provided respectively. Quality of these services is also
important. It is also necessary to measure the adequacy
of technical support during and after implementation.
The effectiveness of vendor support may deteriorate af
ter the information system has been delivered and pay
ment has been made.
3.1.4. IS Effectiveness. The first measure of IS ef
fectiveness, user satisfaction, is an attitudinal measure
toward use of the resulting information systems. This
measure of IS effectiveness is popularly operationalized
by the Bailey-Pearson instrument and its derivatives:
Ives-Olson-Baroudi (1983), Baroudi-Orlikowski (1988),
and Raymond (1987). In small business research, user
satisfaction has often been utilized as a dependent vari
able (Lees 1987, Montazemi 1988, Raymond 1985, Ray
mond 1990, Soh et al. 1992, Thong et al. 1994, Yap et al.
1992, Yap et al. 1994). Recently, a number of IS research
ers have expressed reservations over these instruments
and measurement of user satisfaction in general (Doll
and Torkzadeh 1988, Galletta and Lederer 1986, Good
hue 1986, Iivari 1987, Kim 1989, Klenke 1992, Melone
1990, Treacy 1985). Despite these criticisms, user satis
faction instruments are still used widely in research on
IS implementation in both large and small businesses.
This is because there are no other equivalent instru
ments that can supersede them satisfactorily. Moreover,
the use of previously developed standard instruments
allows for comparison of results with other similar stud
ies and accumulation of knowledge.
The second measure of IS effectiveness, organiza
tional impact, is a perceptual measure of the impact of
an information system on the performance of the busi
ness. An information system is only effective when it
contributes to organizational effectiveness. In a small
business, the impact of the information system is likely
to be achieved by time savings, and formalizing and
restructuring of work processes (Heikkila et al. 1991).
DeLone (1990) suggested that organizational impact
may be measured in terms of profit, sales revenue, staff
productivity, competitive advantage, operations effi
ciency, and improved decision-making. All six items are
used to measure organizational impact in this study.
This measure of organizational impact is necessarily
broad as there are many dimensions to it. Ideally, ob
jective data of costs and benefits should be collected at
two points in time: before and after IS implementation.
However, as pointed out by Lucas (1981), costs and ben
efits of information systems are difficult to quantify, and
objective assessment of benefits of information systems
for decision support often cannot be demonstrated with
any certainty. Further, even if data on IS effectiveness
may be determined, they are usually not recorded and
thus not available. In view of the operationalization dif
ficulties with economic analysis of the value of infor
mation systems, a perceptual measure of organizational
impact is used in this study.
Finally, an overall measure of IS effectiveness is in
cluded. This overall measure is included as we want to
capture the respondents' conceptualization of IS effect
iveness which may be different from ours.
3.2. The Sample
There is no generally accepted definition of a small busi
ness. Three commonly used criteria for defining a small
business are number of employees, annual sales, and
fixed assets (Chew 1988, Ibrahim and Goodwin 1986).
In this study, the criteria for defining a small business
are adopted from the Association of Small and Medium
Enterprises (ASME) in Singapore. A small business is
one that satisfies at least two of the following criteria:
(1) the number of employees in the business should not
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
exceed 100; (2) the business's fixed assets should not
exceed US $7.2 million; and (3) the business's annual
sales should not exceed US $9 million.
The names and addresses of small businesses that
have computerized were obtained from a small busi
ness database maintained by the National Computer
Board (NCB) in Singapore. The NCB conducts a na
tional IT survey on a large cross-section of business or
ganizations every two years. Stratified random sam
pling was used to ensure that the sample was represen
tative of the national profile. Hence, our sample is not
a convenient sample per se. Nonprofit businesses,
public-listed businesses, and wholely owned subsidia
ries of large businesses were excluded from the survey
sample. Three hundred and four small businesses fulfill
the ASME criteria and were included in the study. Two
weeks after the questionnaires were mailed, follow-up
telephone calls were made to nonresponding businesses
to encourage a higher response rate. One hundred and
thirty small businesses responded, giving a response
rate of 43 percent. This response rate is considered rea
sonable notwithstanding that the survey was unsoli
cited, without any prior knowledge on the part of the
respondents. The remaining businesses declined to
participate due to reasons of time pressures and con
fidentiality. Responses from 16 businesses were ex
cluded from the final sample because they had too
much incomplete data. This resulted in 114 usable sets
of questionnaires. In order to assess the possibility of
non-response bias, we compared the responses of the
early returns to late returns as suggested by Armstrong
and Overton (1977). The MANOVA test did not detect
any significant differences in the research variables.
Hence, non-response bias was not considered to be a
problem.
3.3. Data Collection
The study was conducted in Singapore in two phases:
a pilot study and a questionnaire survey. Two question
naires, the Project Manager Questionnaire and the Com
puter User-Manager Questionnaire, were designed for
data collection.
In the pilot study phase, five small businesses were
randomly chosen from the small business database to
pre-test the questionnaires. Five project managers and
fifteen computer user-managers completed the ques
tionnaires. Next, interviews were conducted with these
project managers and computer user-managers to de
termine whether there were any problems with the
questionnaires. Through these interviews, it was pos
sible to identify inconsistencies with the questionnaire
data and to check that the respondents understood the
questions. Based on feedback from these small busi
nesses, very minor modifications were made to the
questionnaires for the next phase of the study. Re
sponses from the five pilot study businesses were not
included in the final sample.
In the questionnaire survey, a package was mailed to
the CEO of each of the small businesses in the survey
sample. The package contained four items: a covering
letter; one Project Manager Questionnaire; three Com
puter User-Manager Questionnaires; and a reply-paid
envelope. The covering letter requested permission
from the CEOs to conduct a survey on the most major
IS implementation project in their businesses. If the
CEOs agreed, they were asked to pass the relevant ques
tionnaires to the manager in charge of the IS implemen
tation project and three computer user-managers. The
completed questionnaires were to be returned to us
within two weeks in the reply-paid envelope. The re
spondents were assured of the confidentiality of their
responses. As a further safeguard, they could return the
questionnaires in individually sealed envelopes. The
Project Manager Questionnaire was completed by the
in-house person who is administratively responsible for
the IS implementation. It solicited data on: (1) levels of
CEO support, consultant effectiveness, and vendor sup
port; (2) levels of organizational impact and overall IS
effectiveness; and (3) information systems characteris
tics such as hardware type and software applications.
The Computer User-Manager Questionnaires were to be
completed by three managers who were users of their
companies' computer systems and computer-produced
reports. We chose to survey three respondents in order
to get more representative responses. The Computer
User-Manager Questionnaire requested data on user
satisfaction. Where necessary, follow-up telephone
calls were made to obtain missing data and gain in
sights into responses. In cases where the respondent
had inadvertently left out responses to questions (e.g.
skipped a section accidentally), he or she was inter
viewed over the phone, otherwise no change was made
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
to the missing data. Thus, there is no risk of significant
researcher bias or confounding having crept into the
survey data.
A member of the research team visited 67 of the small
businesses to conduct separate interviews with the proj
ect managers and computer user-managers subsequent
to their completion of their respective questionnaires.
As far as possible, all computer user-managers in the
businesses were included in the study. Responses from
the project manager and computer user-managers were
not revealed to each other or the CEOs of the businesses.
During the interviews, respondents were asked to ex
plain in greater detail their responses to the question
naires and to qualitatively relate their experience with
the IS implementation projects. The interviews helped
us to interpret the questionnaire data through deeper
insights into IS implementation issues faced by small
businesses. To check whether the CEOs in the non
interviewed businesses were biased in selecting users
who were more satisfied, a MANOVA test was con
ducted on all items of constructs between the 67 inter
viewed businesses and the 47 non-interviewed busi
nesses. No significant difference was found (Wilks' X.
= 0.592; p = 0.221). Thus, there is no evidence of sig
nificant selection bias or confounding having crept into
the data.
As the unit of analysis is at the organization level
rather than at the individual user level, computer user
managers' responses for user satisfaction were aggre
gated within each small business for purpose of statis
tical analysis. The aggregation of responses does not
necessarily result in bias if it can be justified on a theo
retical basis (Langbein and Lichtman 1978). In this
study, respondents are members of top management in
the small businesses and have an overall view of IS ef
fectiveness in their respective businesses. Hence, their
satisfaction levels are representative of the user satisfac
tion of top management within their businesses. Anal
ysis of variance revealed significantly greater variance
on user satisfaction between the small businesses than
within them (F = 2.30; F-prob = 0.000).
Quantitative data on the organizational characteris
tics (e.g. business sector, number of employees, annual
sales) of the small businesses were obtained from the
Registry of Companies and Businesses (RCB) and the
Central Provident Fund Board (CPF Board) in Singa
pore. All businesses are required to lodge their annual
reports with the RCB while the CPF Board maintains
data on the number of employees in all businesses in
Singapore.
3.4. Characteristics of the Sample
Table 2 presents the characteristics of the survey sam
ple. The responding small businesses are from the man
ufacturing, commerce, and service sectors. They all sat
isfied the criteria of a small business as defined earlier.
There are 5 businesses with more than 100 employees
and 25 businesses with annual sales above US $9 mil
lion. Most of these businesses with large annual sales
are in the commerce sector that tend to have small num
ber of employees. On average, small businesses in the
sample have 50 employees and the mean annual sales
is US $6 million. These figures are comparable to those
found in previous studies on small businesses. For ex
ample, DeLone's (1988) sample averaged 62 employees
and US $5 million in annual sales. The small businesses
have a mean of four years of computer experience, and
the majority have spent more than US $30,000 on their
IS implementation projects. There is an equal distribu
tion of hardware platforms across microcomputers, mi
crocomputers with local area networks (LAN), and
minicomputers in the sample. Most of the small busi
nesses have implemented operational and management
information systems applications such as accounting
systems, inventory control, sales analysis, sales order
processing, and payroll. Finally, all the small businesses
have engaged external IS expertise to implement their
information systems.
The effects of six other independent variables on
the measures of IS effectiveness were examined.
These variables were number of employees, annual
sales, computer experience, computer expenditure,
type of hardware and business sector. Table 3 shows
that there is no evidence of significant correlations at
the 10 percent level between IS effectiveness and the
first four variables. The effects of type of hardware
configuration and business sector on IS effectiveness
were tested using one-way ANOVAs. Similarly,
there is no evidence of significant relationships (all
p-values greater than 10 percent level). In summary,
these variables have no effect on the implementation
results.
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
Table 2 Characteristics of Sample
Sector
Service
Commerce
Manufacturing
Number of Employees
1-24
25-49
50-74
75-100
>100
Annual Sales (US$ Million)
<$1,499
$1.5—$2,999
$3.0—$5,999
$6.0-$9.0
>$9.0
Computer Experience (years)
0-1
2-3
4-5
6-10
>10
Computer Expenditure (US$'000)
0-30
31-60
61-120
>120
Hardware
Minicomputers and microcomputers
Microcomputers and LAN
Microcomputers only
Top 10 Software Application
Accounts Receivable
General Ledger
Accounts Payable
Inventory Control
Sales Analysis
Sales Order Processing
Payroll
Purchasing
Budgeting
Job Costing
Frequency (n = 114)a
31
25
55
48
24
15
21
5
28
27
14
14
25
18
34
22
32
8
42
25
21
26
43
34
33
96
90
87
74
50
47
40
29
24
23
a Figures may not add up due to missing data.
4. Data Analysis
Structural equation modeling is an approach to assess
a model involving multiple constructs with multiple ob
served items so as to simultaneously assess the struc
tural component and the corresponding measurement
component in an optimal fashion. Structural equation
modeling is considered a powerful second generation
multivariate analysis technique for studying causal
models (Fornell 1982). In this paper, Figure 2 represents
the structural model being examined. This model de
scribes the relationships or paths among the constructs.
Further, for each construct in the structural model, there
is a related measurement model (not shown in the fig
ure), which links each construct in the diagram with a
set of manifest (or observed) variables. The manifest
variables are typically the items on a questionnaire (see
Table 1).
Structural equation modeling is superior to tradi
tional regression and factor analysis because the mea
surement model is assessed within the context of the
theoretical structural model (Fornell 1982). It addresses
both models at the same time; compared to factor anal
ysis which assesses the measurement model only and
path analysis which addresses the structural model
alone. Partial least squares (PLS) and LISREL are the
most widely known implementation of structural equa
tion modeling. PLS was developed by Wold (1982)
while LISREL was developed by Joreskog and Sorbom
(1981). In choosing between PLS and LISREL, some con
ditions need to be considered. LISREL demands some
rather restrictive assumptions, including strong theo
retical knowledge, multivariate normal distributions,
interval scales, and fairly large sample sizes (Fornell
and Bookstein 1982). PLS, on the other hand, has less
restrictive assumptions. It does not depend on having
multivariate normal distributions (distribution-free),
interval scales, or large sample size. PLS is also consid
Table 3 Pearson Correlations Between Sample Characteristics and IS
Effectiveness
User Organizational
Overall IS
Variables
Satisfaction
Impact Effectiveness
Number of Employees
-0.110
-0.101 0.078
Annual Sales 0.017
-0.083
-0.031
Computer Experience
-0.013 0.118 0.067
Computer Expenditure
0.039
-0.118
-0.006
' p< 0.1; **p< 0.05; p< 0.01.
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
ered more appropriate in earlier stages of theory devel
opment. PLS has been used successfully in marketing
(Fornell and Bookstein 1982), organizational behaviour
(Howell and Higgins 1990), and IS (Amoroso and Che
ney 1991, Gopal et al. 1993, Igbaria 1993, Rivard and
Huff 1988, Thompson et al. 1991).
Given the early stage of theory development in IS im
plementation in small businesses and the relatively
small sample size, PLS was the preferred technique for
data analysis in this study. PLS was used to assess the
overall reliability and validity of the research model,
and particularly to assess the variances explained in IS
effectiveness by top management support and external
IS expertise. Lohmoller's (1990) PLS program, LVPLS
1.9 was used to analyze the data.
4.1. Testing the Measurement Model
The measurement model consists of the relationships
between the constructs and the items used to measure
them. It involves examining the convergent and dis
criminant validity of the research instrument, which in
dicates the strength of the constructs used to test the
research model. Three tests have been suggested for as
sessing convergent validity (Fornell and Larcker 1981).
The first test is item reliability which is measured by the
factor loading of the item on the construct. The second
test of convergent validity is composite reliability of
each construct. The third test is the average variance
extracted by each construct. There is no generally ac
cepted level of what constitutes an acceptable factor
loading in PLS analysis. Fornell (1982) recommended a
minimum loading of 0.70 which suggests that the item
explains almost 50 percent of the variance in the con
struct; while Falk and Miller (1992) recommended a
loading should be at least 0.55 which explains at least
30 percent of the variance in the construct. However,
many IS researchers who used PLS analysis have used
the 0.50 level (see Amoroso and Cheney 1991, Aubert et
al. 1994, Igbaria 1993, Igbaria et al. 1994, Rivard and
Huff 1988, Thompson et al. 1991). In addition, the factor
loading should be statistically significant (Hair et al.
1992). Nunnally's (1978) guideline of 0.80 for assessing
reliability coefficients was used to assess composite re
liability. Fornell and Larcker's (1981) criterion that the
average extracted variance should be 0.50 or more was
used to assess the shared variance coefficients.
Table 4 presents the assessment of the measurement
model. The results suggest that the convergent validity
of the research variables is adequate. All the reliability
coefficients exceeded 0.80 while the average extracted
variances were 0.50 and above. In addition, Cronbach
alpha of each construct was calculated. All the Cron
bach alphas exceeded 0.80, suggesting that the con
structs were reliable. The item-total correlation coeffi
cients of user satisfaction (0.72 to 0.85), organizational
impact (0.50 to 0.74), top management support (0.74 to
0.85), consultant effectiveness (0.68 to 0.80), and vendor
support (0.73 to 0.84) were also high. An additional
overall item was included in the questionnaires for each
of the constructs. The overall item-aggregated construct
correlation coefficients of user satisfaction (0.66), orga
nizational impact (0.76), top management support
(0.76), consultant effectiveness (0.75), and vendor sup
port (0.77) were high indicating high reliability of the
constructs. In conclusion, the constructs in the measure
ment model demonstrated more than adequate reli
ability.
Discriminant validity is the degree to which items dif
ferentiate between constructs, or measure different con
structs. Discriminant validity can be assessed using two
tests. The first test involves verifying that each item
loads more highly on its associated construct than on
any other construct (Thompson et al. 1991, Compeau
1992). The second test for discriminant validity is that
each item should correlate more highly with other items
of the same construct than with items of other con
structs. To assess this, the squared correlation (shared
variance) between two constructs should be less than
the average variances extracted by the items measuring
the constructs (Fornell and Larcker 1981, Grant 1989).
Table 5 presents the factor pattern matrix that shows
the loadings of each item on all constructs. All the item
loadings were greater than or equal to 0.55 and loaded
more highly on their hypothesized constructs than on
any other constructs. The relevant item loadings were
also statistically significant at the 5 percent level. Hence,
all items passed the first test for discriminant validity.
Table 6 presents the results of the second test of discrim
inant validity. In all cases, the shared variance between
two constructs was less than the average variances ex
tracted by the items measuring the constructs. Hence,
the requirement for the second test of discriminant
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THONG, YAP, AND RAMAN
Implementation in Srmll Businesses
Table 4 Assessment of the Measurement Model in PLS
Standard
Reliability Portion of Cronbach
Construct
Mean
Deviation
Range
Coefficient Variance Extracted
Alpha
Top Management Support 0.86 0.56 0.92
TopMgmt 1 4.85 1.68 1-7
0.75a
TopMgmt 2 4.88
1.50 1-7 0.80
TopMgmt 3 5.07 1.55
1-7 0.85
TopMgmt 4 5.59
1.41
1-7 0.74
TopMgmt 5 4.94
1.52
1-7 0.79
Consultant Effectiveness 0.89 0.67 0.88
Consult 1 5.03 1.17
2-7
0.72a
Consult 2 4.59 1.26
1-7 0.68
Consult 3 4.78 1.26 1-7 0.78
Consult 4 5.12
1.31 1-7 0.80
Vendor Support 0.85 0.50 0.93
Vendor 1 4.77
1.43 1-7 0.80a
Vendor 2 4.49
1.69
1-7 0.76
Vendor 3 4.67 1.50
1-7 0.80
Vendor 4 4.28
1.59 1-7 0.84
Vendor 5 4.27 1.57
1-7 0.83
Vendor 6 4.72
1.32
1-7 0.73
User Satisfaction 0.95
0.74 0.94
Satisf 1 5.59
1.10
1-7 0.72a
Satisf 2 5.73
1.10
1-7 0.79
Satisf 3
5.71 1.06
1-7 0.83
Satisf 4 5.63
1.13
1-7 0.82
Satisf 5 5.70 1.14 1-7 0.80
Satisf 6 5.77
1.13 1-7 0.80
Satisf 7 5.54
1.14
1-7 0.85
Organizational Impact 0.87 0.54 0.85
Orglmp 1 4.50 0.95
1-7
0.69a
Orglmp 2 4.48
0.92 1-7 0.74
Orglmp 3 5.32 1.03
2-7 0.56
Orglmp 4 4.96 0.99
2-7 0.72
Orglmp 5 4.21
1.18
1-7 0.50
Orglmp 6 5.16 0.84
1-7 0.54
Overall IS Effectiveness 5.02 1.19 1-7
a Item-total correlation.
validity was satisfied, indicating that the measurement
model discriminated adequately between the con
structs.
4.2. Testing of Propositions
Following confirmation of good psychometric proper
ties in the measurement model, we proceeded to ex
amine the structural model. This evaluation consisted
of an assessment of the explanatory power of the inde
pendent constructs, and an examination of the size and
significance of the path coefficients. Jackknifing, a non
parametric technique, was recommended by Fornell
and Barclay (1983) to produce parameter estimates,
standard errors, and T-values. A 5 percent level of sig
nificance was used for all the statistical tests.
Figure 3 presents the results of the structural model.
Thirty-one percent of the variance in user satisfaction,
10 percent of the variance in organizational impact, and
19 percent of the variance in overall IS effectiveness are
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
Table 5 Factor Pattern Matrix of Measurement Model in PLS
Construct
Measure
1
2 3
4
5
6
Top Management Support
TopMgmt 1 0.60 0.13 0.09 0.17
0.10 0.17
TopMgmt 2
0.55 0.17
0.07 0.17 0.08 0.16
TopMgmt 3
0.80 0.20
0.18 0.20 0.20 0.18
TopMgmt 4
0.93 0.23
0.17 0.18
0.23 0.26
TopMgmt 5 0.81 0.18
0.23 0.16 0.16 0.25
Consultant Effectiveness
Consult 1 0.17
0.84
0.36 0.37
0.13 0.27
Consult 2 0.14 0.60
0.41 0.23
0.18 0.19
Consult 3 0.20 0.87
0.49 0.38 0.18 0.26
Consult 4 0.23 0.93
0.51
0.41 0.17 0.28
Vendor Support
Vendor 1 0.05 0.36 0.56 0.30
0.09
0.23
Vendor 2 0.04 0.37 0.70 0.37
0.20 0.24
Vendor 3 0.15
0.41
0.71 0.38
0.12 0.29
Vendor 4 0.14 0.53 0.59 0.30 0.12 0.24
Vendor 5 0.13
0.49 0.68 0.34 0.10
0.31
Vendor 6 0.24 0.55 0.94 0.49
0.24 0.34
User Satisfaction
Satisf 1 0.16 0.35
0.37 0.80 0.45 0.32
Satisf 2 0.14 0.34 0.40
0.84
0.41 0.36
Satisf 3 0.20 0.43
0.49
0.89 0.46 0.28
Satisf 4
0.11 0.38
0.58 0.87 0.47 0.39
Satisf 5 0.19 0.37
0.35
0.85
0.46 0.37
Satisf 6
0.17 0.37 0.44 0.86 0.46 0.37
Satisf 7
0.22 0.40 0.43 0.90
0.52 0.28
Organizational Impact
Organ 1
0.02 0.04 0.14 0.28 0.67
0.31
Organ 2 0.10
0.02 0.06 0.27 0.75 0.33
Organ 3
0.21 0.13
0.23 0.49 0.80 0.39
Organ 4
0.17 0.13 0.22 0.38 0.82 0.34
Organ 5 0.03 0.05 0.17 0.28 0.58 0.16
Organ 6 0.30 0.26
0.21 0.47 0.76 0.28
Overall IS Effectiveness
0.28 0.30 0.36 0.39 0.42
1.00
Note: Figures are factor loadings.
accounted for by the model. The percentages of variance
explained are greater than or equal to 10 percent, im
plying a satisfactory and substantive model (Falk and
Miller, 1992). The propositions can be evaluated based
on the size, sign, and significance of the standardized
path coefficients. All except one of the standardized
path coefficients are significant at the 5 percent level of
significance. This indicates that all the relationships hy
pothesized except for proposition la are supported by
the PLS analysis. Vendor support is the construct most
closely related to all three measures of IS effectiveness.
5. Discussion
5.1. Top Management Support vs External
IS Expertise
The PLS results show that vendor support, a form of
external IS expertise, is more closely related to user sat
isfaction, organizational impact, and overall IS effect
iveness than top management support or even consult
ant effectiveness. This suggests that top management
support is not the most important factor for small busi
ness IS implementation. It also lends credence to Senn's
(1978) assertion that top management involvement, in
teraction, and support is a necessary but not sufficient
factor for successful IS implementation.
Previous studies reported that when small businesses
engage external IS expertise, top management tend to
overestimate the impact of external IS expertise and un
derestimate the importance of their own involvement
(Gable 1991, Lees 1987). The CEO, after approving the
project, is not actively involved in the IS implementa
tion and prefers to rely on the advice and recommen
dations of the external IS experts. Conventional wisdom
suggests that this lack of top management support
would lead to lower IS effectiveness. Our findings show
that lack of top management support may be compen
sated by high external IS expertise. In a small business
environment with a simple organizational structure and
limited interpersonal and departmental politics, IS im
plementation is basically a technical matter (Thong et
al. 1994). Sound technical knowledge of external IS ex
perts can compensate for the lower top management
support. While top management should be involved in
key decisions affecting the business and business pro
cesses, they need not be actively involved throughout
the implementation process. In fact, given the heavy de
mand on the CEO's time and attention, it is impractical
to advise the CEO to devote a significant amount of at
tention to the IS implementation project in small busi
nesses.
The above finding is also consistent with Attewell
(1992) notion of "knowledge barriers." Attewell argued
that service bureaus, consultants, and manufacturers
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
Table 6 Discriminant Validity
Construct
1 2 3 4 5 6
1. Top Management Support
2. Consultant Effectiveness
3. Vendor Support
4. User Satisfaction
5. Organizational Impact
6. Overall IS Effectiveness
0.560
0.053 0.670
0.047 0.254 0.500
0.040 0.195 0.265
0.058 0.029 0.066
0.077 0.092 0.132
0.740
0.287 0.540
0.154 0.174 1.00
Note: Diagonals represent the average variance extracted; other entries represent the shared
variances.
play important roles in lowering the knowledge barriers
to technology diffusion, making it easier for businesses
to adopt and use IT without extensive in-house exper
tise. In the case of small businesses, vendors and con
sultants perform the role of external institutions which
aim to lower the knowledge barriers and make it easier
for small businesses to adopt IS. Under such situations,
it is important to engage vendors and consultants who
are experienced, effective, reliable, understand the re
quirements of small businesses, and maintain good re
lationships with all concerned parties. It should be
noted that even if the level of top management support
was high, the IS implementation would likely result in
failure if the external IS experts were ineffective in car
rying out their respective functions.
5.2. Small vs Large Businesses
The analyses of the small business IS implementation en
vironments suggest that the widely-held notion "top man
agement support is vital for effective IS implementation"
may not be universally valid. In fact, notwithstanding the
level of top management support, it is the level of external
IS expertise, specifically vendor support, that is likely to
determine the level of user satisfaction, organizational im
pact, and overall IS effectiveness among small businesses.
A possible explanation is that the types of issues faced by
small businesses are different from large businesses.
In a study of 74 manufacturing businesses, DeLone
(1981) found that small businesses tend to have less
computer experience, more dependent on external soft
ware support, spend proportionately less of revenue on
IS implementation, and spend most of IS budget on
computer hardware than large businesses. He also
found that small businesses are more concerned with
poor quality software and poor service from external
vendors and consultants while large businesses com
plain of poor user understanding and complex systems.
These differences may be due to resource poverty. Small
businesses, whether in Singapore or other countries,
suffer from this unique condition characterized by se
vere limitation on finance, limited internal availability
of IS expertise, and a short-range management perspec
tive (Welsh and White 1981). As a result, small busi
nesses often need to rely on external IS expertise to as
sist in IS implementation. In comparison, large busi
nesses do not experience resource poverty to the same
extent as small businesses. Large businesses tend to
have their own internal IS department and are not as
Figure 3 Assessment of Structural Model
R2= 0.31
User
Satisfaction
R = 0.10
Organizational
Impact
R = 0.19
Overall IS
Effectiveness
Note: a All lvalues for the standardized path coefficients are significant at
0.05 or better except for this coefficient, f-values were calculated using
Tukey's jackknifing method.
Information Systems Research
Vol. 7, No. 2, June 1996
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
dependent on external IS expertise. For example, Turner
(1982) found that larger banks tend to invest in internal
IS expertise while smaller banks tend to depend on ex
ternal IS expertise. Thus, small businesses face different
issues and need to adopt different strategies from large
businesses in order to manage their computer-related
problems including availability of IS expertise. The re
sults of this study provide further support that organi
zational theories and practices that are applicable to a
large business may not be appropriate for a small busi
ness.
5.3. "Singaporeness"
As this study was carried out in Singapore, it is neces
sary to examine the business and IT environments of
Singapore. It could very well be that for small busi
nesses in Singapore, top management support is not
very important but external IS expertise is, while the
opposite may be true for small businesses in other coun
tries. Thus, we need to discuss the issue of "Singapore
ness," or what is special about Singapore.
Singapore is a newly industrializing country located
at the southern tip of the Malay peninsula. As an in
tegral part of its overall economic planning, Singapore
has implemented a series of national IT plans and pro
grammes to encourage diffusion of information tech
nology in both public and private sectors (including
small businesses) (Gurbaxani et al. 1990, Sisodia 1992).
What differentiates Singapore from many other coun
tries that also have major initiatives to promote IT is
the comprehensiveness and coordination effort in im
plementing her IT plans (Wong 1992). The Singapore
experience is a model of very pro-active government
strategy. In 1980, the Singapore government appointed
the Committee on National Computerization (CNC)
under the chairmanship of a minister. A new govern
ment agency, the National Computer Board (NCB),
was set up with the mission to move Singapore toward
an information society. The NCB is responsible for ef
fecting successful application of IT in the government,
building an IT infrastructure, cultivating an IT culture,
facilitating development of a strong export-oriented IT
industry, and formulating IT human resource devel
opment policies and plans. In most of these objectives,
the NCB has either achieved or surpassed its goals (Sis
odia 1992).
Compared to businesses in other countries which
started IS implementation much earlier, Singapore busi
nesses lag behind in the use of IT. Hence, they have a
lot of catching up to do. To remain competitive in the
global market, these businesses realize that they need to
computerize their operations in a short time. They can
not afford a long learning curve or a trial-and-error ap
proach to IS implementation. These businesses are also
small in size compared to Fortune 500 companies in the
U.S.A. and lack in-house technical expertise. Under
such an environment, they find it necessary to leverage
their own efforts through the use of external vendors
and consultants. In other words, the combination of re
source poverty and a come-from-behind environment
of IT use makes it especially important for businesses
to rely on external expertise.
In general, relying on external expertise is more risky
than in-house IS professionals because of the lack of
control over these experts. However, this risk appears
to be acceptable to Singaporean businesses as they tend
to have lower uncertainty avoidance and lower individ
ualism (Hofstede 1991, Raman and Watson 1994, Wat
son and Brancheau 1991). Singaporean businesses have
lower uncertainty avoidance, i.e., the degree to which
people prefer structured over unstructured situations.
They tend to be less structured, have fewer rules, em
ploy more generalists, and be multiform. As a result,
their managers are more involved in strategy, more
person-oriented, flexible in their style, and more willing
to take risks. Also, in this environment, top manage
ment may rely on employees for the successful imple
mentation of IS. This is a reasonable assumption for de
veloping countries since most of the initial IS imple
mentation can be categorized as transaction processing
systems. Hence, the participation of CEOs in IS imple
mentation would not be as critical. Singaporean em
ployees are also less individualistic than those in the
developed countries. Employees in low individualistic
cultures expect their employers to look after them like
a family member, and organizational procedures are
based on loyalty and a sense of duty. Hence, the Sin
gaporean business culture is different from that of de
veloped countries like Australia, Great Britain, and
United States.
In conclusion, contextual factors such as resource
poverty, a come-from-behind environment of IT use,
Information Systems Research
Vol. 7, No. 2, June 1996
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THONG, YAP, AND RAMAN
Implementation in Small Businesses
and cultural differences, may explain the relative im
portance of external IS expertise over top management
support in IS implementation in Singaporean small
businesses. Hence, in making generalization from our
research findings, one has to take into consideration
these contextual factors. Our findings may not be uni
versally true, but they are likely to be applicable to
adoption of computer applications by small businesses
in similar environments such as the other newly indus
trializing countries and developing countries.
5.4. Limitations and Directions for Future Research
This section describes the limitations of this research.
As this study was conducted on small businesses in
Singapore, the results may not be generalizable to busi
nesses in countries with very differing institutional
and cultural contexts. Further, the data is cross
sectional in nature. Future research could replicate this
study in other environments and possibly use longi
tudinal design. Such studies can contribute to an un
derstanding of the generalizability of the effect of ex
ternal IS expertise.
Face validity is the perception of knowledgeable in
dividuals regarding the quality of the measures. A
content-valid instrument is difficult to create and per
haps even more difficult to verify because the universe
of possible content is virtually infinite (Straub 1989). To
tackle this, Cronbach (1971) recommended a review
process whereby experts familiar with the content uni
verse evaluate versions of the instrument repeatedly un
til a form of consensus is reached. The measures used
in this study were developed through an extensive lit
erature review followed by iterative reviews by both
practitioners and experienced IS researchers. Further,
the research variables have been used in prior studies
and found to demonstrate adequate reliability and con
tent validity. The questionnaires were also pilot-tested
in the field. Notwithstanding this, future researchers
can supplement the measure of top management sup
port with additional items to capture other notions of
top management support in small businesses.
On hindsight, we should have asked the computer
user-managers to evaluate the organizational impact
and overall IS effectiveness. However, as user satisfac
tion of the computer user-managers is correlated with
both measures of IS effectiveness, we feel that the po
tential for project manager bias is minimal. Neverthe
less, multiple response is to be encouraged. Further, in
order to capture other dimensions of IS effectiveness,
other measures (e.g. system usage) could be included
in place of an overall measure of IS effectiveness.
6. Conclusion
The importance of top management support in IS im
plementation as expounded in previous studies needs
to be qualified. Although top management support
plays an important role in influencing IS effectiveness,
it is not as important as external IS expertise, especially
vendor support, in the small business environment
characterized by resource poverty, low uncertainty
avoidance, less individualistic culture, and a come
from-behind use of IT. While top management may pro
vide the resources needed for the project, ultimately it
is the external IS experts in the forms of vendors and
consultants who implement the systems. The implica
tion for small business management is that to achieve a
high level of implementation effectiveness, they should
direct more efforts at selecting and engaging high qual
ity external vendors and consultants. The implication
for research is to identify attributes of "good" or "ef
fective" vendors and consultants, and develop effective
approaches for engaging them.3
3 The authors thank the Editor, the Associate Editor, and four anony
mous reviewers for their helpful comments on earlier versions of the
paper.
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Vol. 7, No. 2, June 1996
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