The Relationship Between Business Model And Performance Of Manufacturing Small And Medium

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In this such a outline pertaining to the relationship between business model and performance of manufacturing small and medium.

African Journal of Business Management Vol. 5(22), pp. 8918-8932, 30 September, 2011
Available online athttp://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.474
ISSN 1993-8233 ©2011 Academic Journals

Full Length Research Paper

The relationship between business model and
performance of manufacturing small and medium
enterprises in Malaysia

Sumaiyah Abd Aziz
1
* and Rosli Mahmood
2

1Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri
Sembilan, Malaysia.
2College of Business, Universiti Utara Malaysia (UUM), 06010 UUM Sintok, Kedah, Malaysia.

Accepted 30 May, 2011

Business performance has been researched previously in relation to entrepreneurial orientation, market
orientation, business strategy or strategic planning, and the characteristics of the owners/managers
themselves. Recent studies initiated that the firm’s business model plays significant roles in
determining the firm’s performance. However, not much has been done looking at the relationship
between business model and performance of the firm, especially on manufacturing small and medium
enterprises (SMEs) in Malaysia. A study has been conducted on manufacturing SMEs in Malaysia using
mail survey questionnaire. Preliminary analyses conducted revealed that only competencies dimension
of the business model has a significant direct impact on firm performance. The findings of this study
suggest that in order to increase the firm’s performance, one of the important factors to be emphasized
is to have a practical business model. This research gives benefit to the SMEs, business owners,
Malaysian government as well as the entire agencies and the academicians on the importance of the
business model on SMEs’ performance in Malaysia. Furthermore, the findings benefit entrepreneurs as
well as the decision makers, and the outcomes from this research are expected to have policy
implications for the future development of entrepreneurship and SME programs for current and future
entrepreneurs and also for business owner/managers in Malaysia.

Key words: Business model, small and medium enterprise (SME), SME performance, Malaysia.

INTRODUCTION

The importance of small medium enterprise (SMES) to
the nation’s economy has been well established, in that
SMEs are considered the most dynamic businesses in
both the developed and developing countries. SMES also
exert a strong influence on the economies of all nations
and have been the source of employment creation
worldwide (Ghobadian and Gallear, 1996; Ladzani and
Van, 2002). In the United States, SMEs drive the econo-
my and sustain the technological lead in the market place
(Bovee et al., 2007). Over 60% of all new jobs created
yearly in the United States as a result of SME entrepre-
neurs creating opportunities for their businesses and

*Corresponding author. E-mail: [email protected]. Tel:
+6016-4423231. Fax: +606-7986302.
SMEs also represent 99.7% of all employer firms, and
45% of all private sector employees work for this sector
(Bovee et al., 2007). SMEs also create new ideas and
processes through innovation which adds vigor to the
market place (Griffin and Ebert, 2006) and they are im-
portant to the large firms, not only in supplying their raw
material needs, but also channeling the goods made by
these firms to the target markets.
In the developing countries, SMEs’ contributions
include: (a) addressing poverty by creating jobs and
increasing income, (b) dispersing economic activities in
the countryside, and providing broad-based sources of
growth, (c) serving as suppliers and providers of support
services for large enterprises, (d) stimulating entrepre-
neurial skills among the populace, and (e) acting as
incubators for developing domestic enterprises into large
firms (Habaradas, 2008). SMEs are also very important in

Malaysia, in that statistics show that 99.2% of the total
businesses establishments in Malaysia are SMEs (Amry,
2009; Ang, 2010). Malaysian SMEs have been the
backbone of economic growth of an economy in driving
industrial development (Normah, 2007), and SMEs also
are the backbone of the nation (StarBiz, 2009). Thus,
SMEs in Malaysia continue to remain significant in the
country’s economy and this importance is even more
significant as Malaysia moves towards realizing the
objective of becoming the developed country status by
the year 2020 (SMIDEC, 2008). The census of establish-
ment and enterprise (Census) that was conducted in
2005 and based on the response of 550,704 business
enterprises in the agriculture, manufacturing and service
sectors, found that 99.2% or 546,218 of the business
establishments were SMEs, of which 433,517 or about
80% were micro enterprises (Central Bank of Malaysia,
2006). The census results also showed that SMEs were a
major source of employment, providing jobs of over 5.6
million workers and accounting for 56% of the total
employment (Central Bank of Malaysia, 2006). SMEs
also make up 95% of the average 40,000 new companies
that registered with the companies’ commission of
Malaysia per year (Business Times, 2010). However,
SMEs contributed only to 32% of the Malaysian gross
domestic product (GDP) as compared to about 50%
contribution to GDP in other countries, although SMEs
account for the bulk of the business enterprises and
employ 56% of the total workforce (Ang, 2010). In addi-
tion, they contributed only about 19% of the total export
value. The Malaysian SMEs are thus, still a far cry from
countries such as Italy with SMEs contributing 70% of
employment and 42% of exports (Boey and Shamini,
2009). Nevertheless, the contribution of Malaysian SMEs
to the GDP is targeted to increase to 37% in 2010
(Bernama, 2009). It is common to see the increasing
number of companies, including SMEs, come into opera-
tion. However, the main challenge, as a point of fact, is
running and keeping the business alive (Boey, 2009). So,
the most important issue to deal with is actually how to
make the companies stay alive or remain in the industry
for several years and later on expand their current
operation to a higher level. Establishing a new venture is
risky because all new ventures operate in a highly
tentative environment, that is, they deal with a new
product/service, they do not know how to manufacture
the product/service efficiently, and they do not know the
customer who wants to buy the new product/service.
Thus, it is common to hear that the success rate of new
businesses is still low and some statistics suggest that
the failure rate of small businesses in the first five years
is more than 50% (Reiss, 2007). The national venture
capital association in the US finds that the expected
success rate for new ventures is very low, estimated at
less than two in ten (Sarasvathy, 2001).
Even though there have been no comprehensive stu-
dies or accurate figures published so far in Malaysia’s
Aziz and Mahmood 8919

context, the estimated failure rate for SMEs was 60%
(Portal Komuniti KTAK, 2006). Only 10% of the start-ups
survived beyond the 10 years mark (Che et al., 2006).
Boey (2009) stressed that businesses can be considered
successful if they can survive at least 5 years of
business, but unfortunately many do not even survive the
3 year mark. As being mentioned earlier, SMEs’ con-
tribution to the economy is relatively small. Their contri-
butions should be increased to a higher level so that it will
be more significant to the economic growth in Malaysia.
Economic growth in developed countries such as Japan,
Taiwan, Korea and many others, was significantly gene-
rated by SME activities (Normah, 2007). There are rooms
for SMEs to improve their productivity and goes further
than their current state of operation in view of the fact that
SMEs have been targeted as the mechanism in genera-
ting domestic-led investment, stimulating economic
expansion and increasing the job market for the country
(Normah, 2007). Recent findings suggest that the firm’s
business model plays significant roles in determining the
firm’s performance (Malone et al., 2006; Zott and Amit,
2007). Malone et al. (2006) found that some models do
have a better financial performance than others, such as
Physical Creators and Physical Landlords, which have
greater cash flow on assets. Zott and Amit (2007)
focused on two business model design themes: (1)
efficiency-centered, and (2) novelty-centered business
model, taking into consideration the potentially
moderating role of the environment. The study of Zott and
Amit (2007) showed the novelty-centered business model
design matters to the performance of the entrepreneurial
firm.
However, not much has been done looking at the
relationship between business model and performance of
the firm, particularly in the Malaysian SMEs context. Stu-
dies on SMEs, especially in Malaysia, emphasize more
on studying the entrepreneur’s demographic features,
business profile and motivation, problem faced by entre-
preneurs, government assistance program, and process
to start a business (Md Zabid, 1992; Mohd et al., 2002;
Mohd et al., 2005; Nanthakumar et al., 2004; Norita et al.,
2007). Since there is evidence proving that the design of
the business model matters to firms’ performance and
SMEs’ performance is important in enhancing the
Malaysian economy, it will be useful to study SMEs’
performance based on their business model. Thus, the
objective of this paper is to investigate the relationship
between business model and performance of
manufacturing SMEs in Malaysia.

Small and medium enterprises (SMEs) in Malaysia

SMEs are very important in Malaysia. SMEs encourage
private ownership and entrepreneurship, provide broad
based growth whilst also acting as incubators for
developing domestic enterprises into large corporations
8920 Afr. J. Bus. Manage.

Table 1. SMEs’ contribution to the economy.

Performance of SMEs 2005 (%)
SMEs’ contribution to GDP 32.0
SMEs’ contribution to employment 56.4
SMEs’ share of total exports 19.0

Source: Census of establishments and enterprises, 2005 (Bank Negara
Malaysia, 2008).

(Bank Negara Malaysia, 2008). With SMEs representing
99.2% of total business establishments and employing
greater than 5.6 million workers, developing a compe-
titive, productive and resilient SME sector is an essential
thrust to support the government’s aim of achieving
balanced economic development and higher standards of
living at all levels of the society (Bank Negara Malaysia,
2008). Based on the census of establishments and
enterprises in 2005, SMEs’ contribution to the economy is
as follows (Table 1). However, these figures are relatively
small compared to other countries. In developed Asian
countries, like Japan and PR China, SMEs’ contribution
to the GDP is already above 55% as compared to 32%
recorded by Malaysian SMEs (Bank Negara Malaysia,
2008). For example, it was recorded in China that in the
year 2004, 99% of the total number of firms established
were SMEs, contributing to 75% of the total workforce
and 56% of SME contribution to GDP, while her closest
neighboring country, Indonesia, recorded 99.9% of SMEs
contributing to 99.6% of the total workforce and 57% of
SME contribution to GDP in the year 2006 (Habaradas,
2008). Furthermore, Korea recorded 50% of SMEs’ con-
tribution to GDP in the year 2003 and Thailand recorded
39% in the year 2002 (Habaradas, 2008).
The Malaysian government has accorded high priority
to the development of SMEs, in order to fully realize their
potential. The commitment of the government is reflected
in the national development agenda. Both the Ninth
Malaysia Plan (9MP) and third industrial master plan
(IMP3) outlined key strategies for SME development for
the 2006 to 2010 and 2010 to 2015 periods, respectively
(Bank Negara Malaysia, 2008). SME definitions vary in
different countries, including Malaysia. In Turkey, The
Turkish small and medium Industry development organi-
zation defines manufacturing organizations employing 1
to 50 employees as small-sized enterprises, and those
employing 51 to 150 employees as medium-sized
enterprises (Gurbuz and Aioli, 2009). SMEs are defined
differently by different agencies, based on their own
criteria since there is no common or standard definition of
SME. Usually, the benchmarking of SME definition are
based on annual sales turnover, number of full-time
employees or shareholders’ fund (Secretariat to National
SME Development Council, 2005). Common definition
related SMEs as firms that employ less than 200 emplo-
yees (Man and Wafa, 2007; Mohd, 1997; Salleh, 1990).

This definition is similar to the one used by the World
Bank (1984), United Nation Development Organization
(1986) and the Asian development bank (1990) who
defined small enterprises as firms employing fewer than
50 employees and medium enterprises as firms em-
ploying between 50 and 199 employees. However, on 9
June 2005, the National SME development council
approved the common definitions of SMEs across econo-
mic sectors, for adoption by all government ministries and
agencies involved in SME development, as well as
financial institutions (Secretariat to National SME
Development Council, 2005). According to National SME
Development Council (NSDC), Malaysian SMEs can be
grouped into three categories: micro, small and medium.
These groupings are based on two criteria: (1) number of
employees, and (2) annual sales turnover. An enterprise
will be classified as an SME if it meets either the
specified number of employees or annual sales turnover
definition (Table 2). The definitions are applied for the
following sectors:

(1) Primary agriculture.
(2) Manufacturing (including agro-based).
(3) Manufacturing-related services (MRS).
(4) Services (including information and communication
technology).

Classification of economic activities are based on the
Malaysian Standard Industrial Classification (MSIC) 2000
codes (Secretariat to National SME Development
Council, 2005). For the purpose of this study, SMEs’
definition was based on manufacturing (including agro-
based) and manufacturing-related services which were
employed between 1 and 150 full-time employees. This
study did not use the annual sales turnover information
since firm performance was measured using financial and
non-financial self-reporting assessment by the
respondent from each SME without taking into account
the actual firm’s annual sales turnover.

Firm performance

The ultimate dependent variable in the study of strategy
is the performance of the firm. Performance, which
reflects the perspective of strategic management, is con-
sidered to be a subset of the broader concept of orga-
nizational effectiveness (Venkataraman and Ramanujam,
1986). Many researchers have identified the importance
of congruence or fit among various elements of corporate
entrepreneurship in the explanation and prediction of firm
performance (Burns and Stalker, 1961; Galbraith, 1977;
Nadler and Tushman, 1997; Tosi and Slocum, 1984).
There are many factors that affect firm performance and
these factors can be attributed to the internal and
external factors of the firm (Kotey and Meredith, 1997;
Pearce and Robinson, 2002). Past studies have shown
positive relationships between entrepreneurial orientation
Aziz and Mahmood 8921

Table 2. SMEs’ definitions based on number of full-time employees and annual sales turnover.

Sector Primary agriculture
Manufacturing (including Agro-
based and MRS)
Services sector (including ICT)
Micro
Less than 5 employees or less than
rm200,000 of annual sales turnover
Less than 5 employees or less than
rm250,000 of annual sales turnover
Less than 5 employees or less than
RM200,000 of annual sales turnover

Small
Between 5 and 19 employees or
between RM200,000 and less than
RM1 million of annual sales turnover
Between 5 and 50 employees or
between RM250,000 and less than
RM10 million of annual sales turnover
Between 5 and 19 employees or
between RM200,000 and less than
RM1 million of annual sales turnover

Medium
Between 20 and 50 employees or
between RM1 million and RM5
million of annual sales turnover
Between 51 and 150 employees or
between RM10 million and RM25
million of annual sales turnover
Between 20 and 50 employees or
between RM1 million and RM5
million of annual sales turnover

Source: Secretariat to National SME Development Council (2005).

and firm performance (Smart and Conant, 1994; Wiklund,
2005; Yusuf, 2002). Apart from entrepreneurial orienta-
tion, market orientation (Kara et al., 2005; Narver and
Slater, 1990; Pelham, 2000; Slater and Narver, 2000),
strategic planning (Fossen et al., 2006) and innovation
(Deshpande et al., 1993; Dwyer and Mellor, 1993;
Prajogo, 2006; Salavou, 2002; Subramanian and
Nilakanta, 1996) were also found to be the factors
affecting firm performance. Recent studies suggest that
business model plays significant roles in determining the
firm’s performance (Malone et al., 2006; Zott and Amit,
2007).
There are some different ways to approach measuring
a firm’s performance. Individuals with a capability-based
view measure a company’s performance in terms of
stakeholder groups, including shareholders, employees,
customers and communities (Atkinson et al., 1997). How-
ever, many researchers insist that financial measures are
more reasonable in measuring a firm’s performance than
others (Cheng and McKinley, 1983; Dalton et al., 1980).
The significant advantages of financial measures are
their usefulness for practitioners (Cheng and McKinley,
1983).
Numerous researchers have posited that multiple
dimensions of firm performance should be used in
organization research (Lumpkin and Dess, 1996;
Venkatraman and Ramanujam, 1986; Walker and
Ruekert, 1987; Wiklund and Shepherd, 2005).
Chakravarthy (1986) and Cameron (1978) insist that it is
vital to recognize the multidimensional nature of the per-
formance construct. Lumpkin and Dess (1996) suggest
that entrepreneurial processes may lead to favorable out-
comes on one performance dimension and unfavorable
outcomes on another performance dimension. For
example, a large investment of resources for a long-term
project may detract from short-term performance. Murphy
et al. (1996) suggest that multiple measures incorporating
both financial and non-financial goals supporting the stra-
tegic plan should be utilized to allow for a broader, more
comprehensive conceptualization of firm performance.
Business model

The discussion of business model has gained more
attention from business scholars as well as practitioners
since the emergence of the dot.com businesses. The
term ‘business model’ has become increasingly popular
within information systems, management and strategy
literature (Hedman and Kalling, 2003). Information sy-
stems and business literature refer to the concept of the
business model as the means of creating value for
customers, and to the way in which a business turns
market opportunities into profit through sets of actors, ac-
tivities and collaboration (Rajala and Westerlund, 2007).
Due to the importance of having a clearly articulated
business model as early as possible in the new venture
creation process (Barringer and Ireland, 2006), the
business model is now being emphasized in the entrepre-
neurship literature. Creating a business model is quite
similar to writing a good story – a story that explains how
an enterprise works or operates (Barringer and Ireland,
2006; Magretta, 2002). Magretta (2002) argues that a
good business model answers Peter Drucker’s long
standing questions regarding who is the customer and
what does the customer value. It should also answer the
most significant questions that every manager must ask:

(1) How do we make money in this business?
(2) What is the underlying economic logic that explains
how we can deliver value to customers at an appropriate
cost (Magretta, 2002)?

A famous story about business models relates to how
Dell Inc. eliminates the middleman and builds its
competitive advantage through their interesting business
idea. While several other firms have attempted to imitate
Dell’s business model, no company has been able to
come close to doing so (Barringer and Ireland, 2006).
This is because in order to fully imitate Dell’s business
model, the company that intended to do so will have to
change the entire process of doing business and this will
8922 Afr. J. Bus. Manage.

upset the current arrangement such as the relationships
with retailers (middleman). By looking at Dell, the com-
pany’s business model can be the source of competitive
advantage that will differentiate it with others competing
in the same industry. In other view, this shows that
variation in part of the business model design exist even
though Dell and its competitors are competing in the
same industry and producing quite similar range of
products. Even when entrepreneurial firms imitate the
business models of existing organizations (Aldrich, 1999),
they may have to adapt these designs to their own parti-
cular market niche (McGrath and MacMillan, 2000).
Numerous components of the business model are
available in the literature. Shafer et al. (2005) review of
the relevant literature uncovered 12 definitions in esta-
blished publications during the year 1998 to 2002 from
different perspectives (e-business, strategy, technology
and information systems). Across the 12 definitions, they
catalogued 42 different business model components,
elements or building blocks. They developed an affinity
diagram to categorize the business model components
that were cited twice or more. Based on that, they
identified four major categories, namely: (1) strategic
choices, (2) creating value, (3) capturing value, and (4)
the value network. Table 3 listed components of the
business model discussed by several authors. A study by
Abd Aziz et al. (2008) clustered the various business
model components that were discussed in the literature
to a common business model construct. They found in
their study that there are four clusters of the business
model construct, namely: stakeholders, competencies,
value creation and value capture (Abd Aziz et al., 2008).
Stakeholders’ dimension contains components relating
to the firm’s suppliers, stakeholders and stakeholder
networks, as well as customer value and relationships
with the customer. Competencies include components,
such as: organizational characteristics, firm culture,
management and the sources of resources required,
infrastructure of the firm and infrastructure management,
relation to organizational strengths, valuable resources and
knowledge in the firm. Value creation contains elements
on firm’s value proposition - value proposition, value
model, value creation and differentiation. Value capture
contains elements related to firm’s competitive strategy –
competitors, competitive strategy, how the firm creates
profits, as well as costs and cost structures. These
constructs align with Shafer et al.’s (2005) compo-nents
of the business model - strategic choices, value
networks, value capture and value creation. Also, they
support the business model frameworks of Morris et al.
(2005), which identified six main aspects of the entre-
preneur’s business model, namely: value creation, target
customer, core competencies, differentiation, revenue
model, and the entrepreneur’s aspirations concerning
size, time and scope. The constructs also supported
Hamel’s idea on what are the components of a business
model (Hamel, 2000) and were comparable to some of
the business model components listed by Dubosson-

Torbay et al. (2002).

MATERIALS AND METHODS

Development of hypotheses

Recently, business model emerges as an important determinant of
business performance (Malone et al., 2006; Zott and Amit, 2007).
Zott and Amit (2007) found a positive relationship between the
design of the business model (novelty-centered and efficiency-
centered business model design) and business performance
(measured as stock market value). The empirical results show that
novelty-centered business model design matters to the perfor-
mance of entrepreneurial firms (Zott and Amit, 2007). Another study
on business model design and performance was conducted by
Malone et al. (2006). They defined four basic business models
based on what assets’ rights are sold (creators, distributors, land-
lord and brokers) and four variations of each based on what type of
assets are involved (financial, physical, intangible and human).
They also analyzed the firms’ financial performance in three cate-
gories, namely: market value, profitability and operating efficiency.
Their study suggested that some models do have a better financial
performance than others, such as physical creators and physical
landlords having greater cash flow on assets. Thus, the evidence
on the design of the business model is significant to the firms’
performance; therefore, this study further enhance the knowledge
on business model and performance of the firm by looking at the
manufacturing SMEs in Malaysian context.
The business model in this study focused on four dimensions:
stakeholders, competencies, value creation and value capture (Abd
Aziz et al., 2008). “Stakeholders” factor contains components rela-
ting to the firm’s suppliers, stakeholders and stakeholder networks,
as well as customer value and relationships with the customer.
Stakeholders were identified by Shafer et al. (2005) and Hamel
(2000) through their value network factor. Consequently, this study
examined the relationship between stakeholders, as one of the
business model dimensions and firm performance. Thus, the
following hypothesis is formulated.

H1: Stakeholders in the firm’s business model are positively related
to the firm’s performance.

The second dimension is “competencies”. Competencies include
components such as: organizational characteristics, firm culture,
management and the sources of resources required, infrastructure
of the firm and infrastructure management, relation to organi-
zational strengths, valuable resources and know-ledge in the firm.
Competencies were identified as strategic resources by Hamel
(2000) and Morris et al. (2005) as internal capability factors.
Therefore, we have the following hypothesis:

H2: Competencies in the firm’s business model are positively
related to the firm’s performance.

The third dimension is “value creation” and this factor was also
identified by Shafer et al. (2005) as value creation, while the factors
related to the offering and market factors were identified by Morris
et al. (2005). Value creation contains elements of firm’s value pro-
position, such as: value proposition, value model, value creation
and differentiation. Thus, this study examined the relationship
between value creation, as one of the business model dimensions
and firm performances. As such, the following hypothesis is
formulated:

H3: Value creation in the firm’s business model is positively related
to the firm’s performance.
Aziz and Mahmood 8923

Table 3. The business model components discussed by several authors.

Author(s) Business model components
Timmers (1998) Value network (suppliers), revenue/pricing, information flows, product/service flows

Hamel (2000)
Four major components: customer interface, core strategy, strategic resources, and value network. The
subcomponents are as follows:

1) Customer Interface: Fulfillment and support, information and insight, relationship dynamics, and pricing
structure.
2) Core Strategy: Business mission, product/market scope, and basis for differentiation.
3) Strategic Resources: Core competencies, strategic assets, and core processes.
4) Value Network: Suppliers, partners and coalitions.

Kim and Mauborgne
(2000)
Cost, customer (target market, scope), value chain, pricing/revenue, capabilities, value proposition, profit
and value network

Amit and Zott (2001)
Product, information, resources, capabilities, output (offering), value creation, business opportunities,
transaction content, transaction governance and transaction structure

Dubosson-Torbay et
al. (2002)
Four principal components: Product innovation, customer relationship, infrastructure management and
financial aspects. The subcomponents are as follows:

1) Product Innovation: Value proposition, target market, and capabilities.
2) Customer Relationship: Get a feel for the customer, branding, and serving the customer.
3) Infrastructure Management: Resources/assets, activity and processes, and partner network
4) Financial Aspects: Revenue, cost, and profit.

Magretta (2002) Economic logic, customers, profit, cost, value proposition

Vorst et al. (2002)
Value network (suppliers), value proposition, processes/activities, functionalities, infrastructure
applications and specific characteristics

Hoque (2002)
Value network (suppliers), customer (target market/scope), resources/assets, competitors, strategy,
branding, differentiation, mission, culture, environment, firm identity and firm reputation

Chesbrough and
Rosenbloom (2002)
Market, value proposition, value chain, cost and profit, value network, competitive strategy,
revenue/pricing, competitors, output (offering) and value creation

Hedman and Kalling
(2003)
Value network (suppliers), resources/assets, capabilities/competencies, processes/activities, competitors,
output (offering) and management

Morris et al. (2005)
Customer (target market/scope), value proposition, capabilities, cost, offering, strategy, value creation,
economic logic, time, scope and size ambition, pricing and revenue sources

The fourth dimension is “value capture” and it contains elements
related to the firm’s competitive strategy (competitors, competitive
strategy, how the firm creates profits, as well as costs and cost
structures). This dimension is also identified as ‘value capture’ by
Shafer et al. (2005). Thus, it is hypothesized that value capture in
the business model of a firm is significantly related to the firm’s
performance. Therefore, the following hypothesis is suggested.

H4: Value capture in the firm’s business model is positively related
to the firm’s performance.

Procedure and sample

In this study, a quantitative research approach was utilized, while a
cross-sectional research design was adopted. Cross-sectional
design involves the collection of information, only once, from any
given sample of population elements (Malhotra, 1996). This study
also employed the survey method, which makes use of a question-
naire. The survey method was chosen because it is an approach
that uses several basic procedures to obtain information from
people in the natural environment (Graziano and Raulin, 2004).
Survey is considered to be best suited for measuring attitudes and
obtaining personal and social facts, as well as beliefs (Babbie,
1990). Survey was also conducted with the specific intent of gene-
ralizing the results to the population (Girden, 2001). The survey
method has also relatively high levels of validity since questions
can be posed directly addressing the underlying nature of a con-
struct (Lyon et al., 2000). Respondents selected for this study were
owners/managers of the firms. Owners and managers were
8924 Afr. J. Bus. Manage.

targeted in the survey because they are the persons who are
involved in the running of the firms. It has been found that the
business owners or top executive in small entrepreneurial firms
often represent the views of the entire firm (Brush and Vanderwerf,
1992; Chandler and Hanks, 1994). A total of 1000 questionnaires
were mailed, along with a cover letter and self addressed stamped
return envelope. The paper used was plain white, as it has been
found that the use of coloured paper does not significantly improve
response rates (Newby et al., 2003). Respondents were asked to
complete the questionnaire and return it. The mail questionnaire
survey was chosen since this is one of the methods of collecting
data that can cover-up a wide geographical area (Sekaran, 2003)
with less amount of money spent on travelling. The mailed
questionnaire is considered an appropriate approach for surveying
organizational processes in the settings where they naturally occur
allowing for minimal intrusion by the researcher (McGrath, 1982).
However, it is known that this method also has a low response rate,
and any doubts that the respondents might have cannot be clarified
(Sekaran, 2003). The advantages of choosing this method are:
anonymity is high, wide geographic regions can be reached, token
gifts can be enclosed to seek compliance, respondents can take
more time to respond conveniently and the questionnaire can be
administered electronically, if desired (Cavana et al., 2001). The
population of this study refers to all Malaysian manufacturing small
and medium-sized enterprises (SMEs), including agro-based and
manufacturing-related services which were employed between 1
and 150 full-time employees. They were chosen based on the
availability of data from the online databases. SME Business
Directory (accessible online at www.smeinfo.com.my) was used as
reference for the sampling frame of the study. The online database
helps in providing the firms’ addresses in order for the survey to be
sent. A systematic sampling technique was used in this study.
Under this technique, a sample is chosen by selecting a random
starting point and then picking every Kth element in succession
from the sampling frame (Malhotra, 1996). Similar to the simple
random sampling, each element in the population has a known and
equal chance of being selected. However, the accuracy of
systematic sampling can exceed that of simple random sampling
when the ordering of the elements is related to the characteristics of
interest because the sample will be more representative of the
population (Aaker et al., 1998). In this study, every 7th name was
automatically selected from the list in the sampling frame. For
example, the sample included the 7th name, the 14th, the 21st, and
so forth.
Roscoe (1975) rule of thumb proposed that the sample size
which is larger than 30 and less than 500 is appropriate for most
studies. According to Saunders et al. (2007), for a population of
around 10000, the appropriate sample is 370. Thus, for a popula-
tion of 7340 SMEs, a total of 370 firms were chosen to participate in
this study. After taking into account the low feedback rate in
Malaysia (Sany Sanuri, 2007) and to overcome the probability of
not getting the appropriate response, the numbers of survey
questionnaires sent out were tripled than the intended sample
needed. A total of 1000 names were selected from the list of more
than 7000 SMEs. Data collection was carried out from July to
November 2009. After five months of data collection, 202 (20.2%)
owners/managers of manufacturing SMEs responded to this study.

Measurement

Data were collected through the use of fully structured and closed-
ended questionnaires. The use of closed-ended questionnaire gives
a uniform frame of reference for respondents to decide their
answers (Weisberg and Bowen, 1977). All constructs included in
this study were measured using established measures drawn from
previous studies. Some of the questions used were slightly modified
to make them more relevant to the purpose of this study. Self-report

technique was used to gather data on SMEs’ firm performance.
Several previous researchers also employed this technique in order
to obtain data on firm performance (Dess and Robinson, 1984;
Gupta and Govindarajan, 1984; Lumpkin and Dess, 1996). Several
studies have employed the subjective assessment for business
performance (Curkovic et al., 2000; Forker et al., 1996; Tan et al.,
2002; Tracey et al., 2005; Yamin et al., 1997), and have shown that
the method can yield useful insights. Since most of the firms in this
research were expected to be closely held, it was expected that
owners/managers would be unwilling to provide full accounting
data. Thus, subjective assessment was used in this study.
This study utilized four items to measure firm’s growth: sales
growth rate, employment growth rate, sales growth relative to
competitors and market value growth relative to competitors.
Financial performance was measured using three items: gross
profit, return on asset (ROA) and return on investment (ROI). This
study also employed the usage of “overall performance” item to
measure business performance. “Overall performance” item has
been utilized in order to ensure and verify respondents’ answers to
the other business performance items (Lumpkin and Dess, 1996).
All these items were measured using a five-point Likert scale
ranging from 1 (much lower performance) to 5 (much higher
performance). Respondents were asked to answer their firms’
performance based on the previous three years record. According
to Covin et al. (2001), an average record of three years was used in
order to reduce the decision variation impact of the annual firms’
financial report. It is also appropriate to illustrate the current
financial performance of SME firms. Business model instrument
was adapted from the study of Abd Aziz et al. (2008). The list
consisted of 54 distinct components of the firm’s business model.
This business model consists of four dimensions: stakeholders,
competencies, value creation and value capture. Respondents
were asked to rate the importance of that particular component to
their firm’s business model on a five-point Likert scale ranging from
1 (not being important) to 5 (being extremely important). The survey
questionnaire also has several questions on respondents’
background such as age, gender and highest education level. It
also has several questions to capture firms’ background such as
years of establishments, number of employees, and firm’s type and
structure of ownership.

FINDINGS AND DISCUSSION

Sample profile

Two follow-ups had been carried out in order to increase
the response rate of the data collected using mail survey.
Follow-up procedure to the non-response rate was
carried out using email and phone call. After two follow-
ups, completed surveys were returned by 202 of the 1000
(20.2%) owners/managers of the manufacturing SMEs.
Of the 202 respondents, males accounted for 62.4%
(126) of the sample population, while females accounted
for 37.6% (76). Still, it is common to see that males domi-
nate the business world, while the number of women
participating in business (as the owner/manager) is
increasing. In terms of their age, 22.3% (45) of the
respondents were below 30 years old, 39.6% (80) were in
the range of 31 to 40 years, 23.3% (47) were in the range
of 41 to 50 years, 11.4% (23) were in between 51 and 60
years, and 3.5% (7) were 61 years old and above. It can
be concluded that majority of the owners/managers that
participated in this study were in their thirties. In relation
Aziz and Mahmood 8925

Table 4. Respondents’ profile.

Variable Frequency Percentage
Gender:
Male 126 62.4
Female 76 37.6

Age (years):
Below 30 years old 45 22.3
31 – 40 years old 80 39.6
41 – 50 years old 47 23.3
51 – 60 years old 23 11.4
61 years and above 7 3.5

Highest education level:
Secondary school 48 23.8
Diploma 49 24.3
Degree 85 42.1
Master 15 7.4
Ph.D 5 2.5

to the highest education obtained by these owners/
managers, majority of them that participated in this study
holds a degree qualification (42.1%), followed by diploma
(24.3%), secondary school (23.8%), Masters’ degree
(7.4%) and PhD (2.5%). Table 4 summarizes these
respondents’ profile. Majority of the manufacturing SMEs
are made up of small firms (64.4%), reflected by the
number of full-time employees working with the firms.
Regarding years of establishment, 21.3% (43) firms were
established less than 5 years ago, 26.7% (54) were
established 5 to 0 years back, 27.7% (56) were esta-
blished 11 to 15 years, 7.4% (15) were established 16 to
20 years ago and 16.8% (34) firms were established
more than 20 years ago.
The manufacturing sector in Malaysia comprises
several sub-sectors. The survey was designed to capture
the firm’s type (in this case, the sub-sectors). Majority (81
= 40.1%) of the firms that participated in this study were
in food and beverages sub-sectors, while 62 (30.7%)
firms were in other sub-sectors. Others comprise phar-
maceutical, cosmetics, giftware, craft, printing and
traditional / herbal medicines. It was observed that 17
(8.4%) of the responses were from textiles and apparels
and 10 (5.0%) were from rubber and plastics. However,
the full firms’ profile is presented in Table 5.

Descriptive statistics

A summary of means and standard deviations for the
independent and dependent variables of this study is
shown in Table 6. Results showed that among four
dimensions of business model, stakeholders had the
highest mean (4.0845), followed by value creation
(3.9884), competencies (3.9835) and value capture
(3.9607). However, the mean score of dependent
variables (namely performance) was 3.4412.

Goodness of measure

Goodness of measure was checked using validity,
reliability and correlations. In relation to validity, factor
analyses were conducted. Factor analysis is a data
reduction technique that summarizes a large set of varia-
bles into a smaller set of factors or components (Pallant,
2007). The primary purpose of this analysis is to deter-
mine the underlying structure among the variables in the
analysis (Hair et al., 2006). All measurement tools for the
present study were adopted from previous studies and
the variables were factorized; however, this study
reaffirmed the previous findings by conducting another
exploratory factor analysis. The data in this study were
initially submitted for exploratory principal component
factoring (PC) with varimax rotation via simplification of a
large number of items to a few representative factors or
dimensions, to test the patterns of correlation among the
items of variables, and to establish the goodness of
measures for testing the hypotheses (Hair et al., 1998,
2006; Tabachnick and Fidell, 2007). There were 54 items
altogether used to measure the business model. Accor-
ding to the study of Abd Aziz et al. (2008), there were
four business model constructs or dimensions, namely
stakeholders, competencies, value creation and value
capture. Based on their initial findings, stakeholders’
dimension consists of 13 items, competencies consist of
15 items, value creation consists of 12 items, and value
capture dimension consists of 14 items altogether (item
8926 Afr. J. Bus. Manage.

Table 5. Firms’ profile.

Variable Frequency Percentage
Number of employees
Less than 5 employees
5 – 50 employees
51 – 150 employees

29
130
43

14.4
64.4
21.3
Years of establishment
Less than 5 years
5 – 10 years
11 – 15 years
16 – 20 years
More than 20 years

43
54
56
15
34

21.3
26.7
27.7
7.4
16.8
Firm’s type
Textiles and Apparels
Wood and Furniture
Food and Beverages
Chemicals
Transport Equipment
Metal Products
Electrical and Electronics
Rubber and Plastics
Others

17
9
81
4
3
7
9
10
62

8.4
4.5
40.1
2.0
1.5
3.5
4.5
5.0
30.7

Table 6. Descriptive statistics for the main variables of the study.

Variable Mean Standard deviation
Competencies 3.9835 0.54930
Stakeholders 4.0845 0.55661
Value creation 3.9884 0.55140
Value capture 3.9607 0.55066
Performance 3.4412 0.65887

loadings of 0.3 and above for each factors). This study
also came out with four business model dimensions,
which explained 54.94% of the variance in the responses.
The Kaiser-Meyer-Olkin (KMO) measure of sampling
adequacy value for the items were 0.942, indicating that
the items were interrelated and they shared common
factors. Meanwhile, the measure of sampling adequacy
(MSA) values for individual items ranged from 0.895 to
0.968 and they denoted that the data matrix was suitable
for factor analysis. For business performance, eight items
were used to measure business performance. Only one
factor was extracted for this variable. As such, the KMO
measure of sampling adequacy value for the items was
0.934; implying that the items were correlated and they
shared common factors. Meanwhile, the MSA values for
individual items that ranged from 0.903 to 0.953 also
denoted that the data matrix was appropriate for factor
analysis. Besides, the factor analysis that resulted in one
factor with eigenvalue greater than 1 explained 74.668%
of the variance in the data. This one factor accounted for
74.668% of the total variance with an eigenvalue of
5.973. Factor loading for items in this factor ranged from
0.805 to 0.909. This factor consisted of eight items
relating to business performance. Reliability test was
conducted to examine the internal consistency of the
instruments. Consistency indicates how well the items
measuring a concept come together as a set (Cabanas et
al., 2001). Cronbach’s alpha is a reliability coefficient that
indicates how well the items in a set are positively
correlated to one another and is computed in terms of the
average intercorrelations among the items measuring the
concept (Cavana et al., 2001). It was chosen due to its
versatility with the use of continuous variables (Huck,
2004). The reliability coefficient as indicated by the
Cronbach’s alpha values reflected the reliability of the
instruments. This coefficient can hold a value of zero to 1
Aziz and Mahmood. 8927

Table 7. Results of reliability analysis.

Instrument Number of item Cronbach’s alpha
Cronbach’s alpha based on
standardized item
Stakeholders 13 0.845 0.847
Competencies 15 0.887 0.892
Value creation 12 0.846 0.847
Value capture 14 0.900 0.904
Business performance 8 0.944 0.944

Table 8. Correlations of the study.

CS SH VP VC PERF.
CS 1.00
0.721*
(0.000)
0.712*
(0.000)
0.723*
(0.000)
0.434*
(0.000)

SH
0.721*
(0.000)
1.00
.690*
(0.000)
0.712*
(0.000)
391*
(0.000)

VP
0.712*
(0.000)
0.690*
(0.000)
1.00
0.673*
(.000)
0.404*
(0.000)

VC
0.723*
(0.000)
0.712*
(0.000)
0.673*
(0.000)
1.00
0.395*
(0.000)

PERF.
0.434*
(0.000)
0.391*
(0.000)
0.404*
(0.000)
0.395*
(0.000)
1.00

*Correlation is significant at the 0.01 level (1-tailed); Note: CS = Competencies; SH = Stakeholders; VC = Value
Creation; VP = Value Capture; PERF = Performance.

(Cavana et al., 2001). Generally, an alpha coefficient of
0.8 or higher is accepted (Bryman and Cramer, 1990),
although Nunnally and Bernstein (1994) recommended
that the reliability acceptance level should be set at a
minimum of 0.70. Results of reliability testing in this study
are presented in Table 7. All constructs used in this study
have achieved the acceptable level of reliability (Hair et
al., 2003; Murphy and Davidshofer, 2005). Correlation
analysis was performed to determine if there was any
correlation between the business model dimensions
(namely: value creation, value capture, stakeholders and
competencies) and the dependent variable of this study
(business performance). The Pearson correlation coef-
ficients (r) were used to identify the magnitude and direc-
tion of the relationships between variables. For example,
the value can range from -1 to +1, with a +1 indicating a
perfect positive relationship, 0 indicating no relationship,
and -1 indicating a perfect negative or reverse relation-
ship (as one grows larger, the other grows smaller).
Table 8 shows the correlation coefficients for variables
used in this study. The correlation measure indicates that
a relationship exists between variables; however, it does
not indicate that any one variable causes the other
(Pallant, 2005).

Testing of hypotheses

In order to test the direct effect of hypotheses, multiple
regression analysis was utilized. Several assumptions,
such as normality, linearity, homoscedasticity, multicol-
linearity, outlier and error-term free, need to be fulfilled in
relation to using multiple regression analysis. To select
the appropriate statistical techniques to test hypotheses
of this study, a normality test was extremely desirable. As
a general rule when the sample size is at least 30, the
sampling distribution of the mean will be assumed to be
approximately normal (Berenson et al., 2004). Since the
respondents in this study are 202, it is assumed that the
assumption of normality may be met in this study.
However, it is prudent to use some techniques to provide
sufficient evidence to support this assumption. Normal
probability plot is applied to test the normality as
suggested by Coakes and Steed (2003). The results of
normal probability plots showed that all the cases fall
more or less in a straight line. Thus, normality was
8928 Afr. J. Bus. Manage.

assumed for all the variables in this study. The next as-
sumption is linearity. Linearity is important for regression
analysis because one of the underlying assumptions of
this technique is that the relationship between indepen-
dent and dependent variables is linear. Linearity was
examined by looking at residual plots, while standardized
residuals were plotted against predicted values using
SPSS PLOT. Most of the residuals were scattered
around zero points and they had oval-shapes, which
suggested that the assumption of linearity was met
(Tabachnick and Fidell, 2007).
Further analysis was conducted to fulfill the assumption
on homoscedasticity. The assumption of homoscedas-
ticity is that the variance of the dependent variable is
approximately the same at different levels of the expla-
natory variables (Hair et al., 1998). In other words, the er-
ror terms in a regression model have constant variance.
Homoscedasticity is, therefore, examined by visual
inspection of the scattered plot of regression residuals.
An examination of residual plots for explanatory variables
indicated that the assumption of homoscedasticity was
supported. The next assumption is multicollinearity.
Multicollinearity refers to the degree to which explanatory
variables are highly correlated with one another. The
multiple regression procedure assumes that no explana-
tory variable has a perfect linear relationship with another
explanatory variable (Tabachnick and Fidell, 2007).
Intercorrelations of greater than 0.8 are considered to be
evidence of high multicollinearity (Berry and Feldman,
1985). The assumption of multicollinearity was examined
by comparing the bivariate correlations between all
explanatory variables in the equation. An examination of
the results of these tests (with regards to goodness of
measure) indicated that multicollinearity was not a
problem. To detect univariate outliers, inspection through
extreme cases in boxplot analyses was carried out
(Tabachnick and Fidell, 2007) for each variable in this
study. There were several outliers detected. However,
the outliers were not too obvious. Given the fact that the
values were not too different from the remaining distri-
bution, the cases were retained in the data file (Pallant,
2007). Here, the relationship between the business
model in the context of value creation, value capture,
stakeholders, competencies and business performance
was reported. Four hypotheses were developed to test
the direct relationship between the business model
dimensions (stakeholders, competencies, value creation
and value capture) and performance of the firm. As such,
multiple regression analysis was used to test these
relationships. The first hypothesis stated that there is a
positive relationship between stakeholders and firm
performance. Hypothesis 2 stated that competencies in
the business model of a firm are positively related to the
firm’s performance. Hypothesis 3 stated that value
creation in the business model of a firm is positively
related to the firm’s performance. Hypothesis 4 stated
that value capture in the business model of a firm is

positively related to the firm’s performance.
The results of the multiple regression analysis conduc-
ted revealed that only competencies’ dimension was
found to be significant, while the others (stakeholders,
value creation and value capture) were not significant
predictors of firm’s performance. Therefore, only Hypo-
thesis 1 was accepted. Table 9 presents the complete
results of the multiple regression analysis conducted.
From the table, the multiple regression model of all the
business model dimensions significantly explained 19%
of the variance in business performance. However, only
competencies’ dimension was found to be the significant
predictor in business model and performance relationship
(? = 0.453, t = 2.114, p < 0.1). Table 10 presents the
results summary of all hypotheses tested in this study.

DISCUSSION

The primary goal of this study was to assess the relation-
ships between business model dimensions (stakeholders,
competencies, value creation and value capture) and
performance of manufacturing SMEs in Malaysia. Four
hypotheses on the direct relationship of the business
model dimensions (stakeholders, competencies, value
creation and value capture) and performance were deve-
loped. The first hypothesis, developed to examine this
relationship, stated that there is a positive relationship
between stakeholders and firm performance. The second
hypothesis stated that competencies in the business
model design of a firm are positively related to the firm’s
performance. The third hypothesis stated that value crea-
tion in the business model design of a firm is positively
related to the firm’s performance. The fourth hypothesis
stated that value capture in the business model design of
a firm is positively related to the firm’s performance.
Overall, the multiple regression models of all the
business model dimensions significantly explained 19%
of the variance in business performance. Findings also
revealed that only competencies dimension was found to
be a significant predictor in this relationship, while other
dimensions (stakeholders, value creation and value
capture) were not significant.
In general, the significant result of the competencies’
dimension of the business model shows that business
model can be considered as one of the important
predictors to the success of a firm, since it is related to
performance. These findings are similar to those of Zott
and Amit’s (2007) study on two business model designs:
efficiency-centered and novelty-centered business
models that have a positive relationship with performance
(measured as stock market value). Even though only
competencies’ dimension of the business model was a
significant predictor in the relationship of business model
and performance, it is also valuable to enhance the
knowledge in this area since the study has been conduc-
ted on manufacturing SMEs in Malaysia. These findings
Aziz and Mahmood 8929

Table 9. Multiple regression analysis of business model dimensions and
performance.

Independent variable
Firm performance
? t-value p-value
Competencies 0.453 2.114 0.036
Stakeholders -0.075 -0.401 0.689
Value creation -0.019 -0.103 0.918
Value capture -0.074 0.450 0.653

R
2
0.190
Adjusted R
2
0.173
Sig. F. 11.516
Durbin-Watson Index 1.558

Table 10. Results summary of all hypotheses.

Hypothesis Description Results
H1 Stakeholders in the firm’s business model are positively related to the firm’s performance. Accept
H2 Competencies in the firm’s business model are positively related to the firm’s performance. Reject
H3 Value creation in the firm’s business model is positively related to the firm’s performance. Reject
H4 Value capture in the firm’s business model is positively related to the firm’s performance. Reject

provide a valuable addition to the literature in terms of
demonstrating that firm performance and business model
are positively related. Apart from that, studies on
business model dimensions available in the current
literature were conducted on more established firms,
particularly on big companies and also public listed
companies outside Malaysia (Western countries), such
as studies by Zott and Amit (2007) and Malone et al.
(2006). This study however was conducted on manufac-
turing SMEs in Malaysia, which was different from the
previous settings. The study further contributes by
extending the theory’s application, specifically, to a
population that has not been reported to have studied the
manufacturing SMEs before now.
Although the response rate is acceptable, the implica-
tion for this study could have been enhanced if the res-
ponse rate had been higher. Response rates for mailed
surveys in small business research have historically been
lower than response rates for research on large
businesses or the general population (Bartholomew and
Smith, 2006). Nearly one-third of articles, using a mailed
survey in entrepreneurship or small business journals,
reported a response rate of less than 25% (Aldrich and
Baker, 1997). The alternative approach to mail survey is
to conduct interviews for these owners/managers. How-
ever, this approach will incur higher costs to the survey
and the questionnaire has to be kept within an
appropriate length. In addition, this research investigates
the relationships of business model and performance at a
particular point in time. The richness of the study is
restricted by the ‘snapshot’ taken in the study. According
to Sekaran (2003), one of the limitations of the cross-
sectional study is the restriction to prove the cause-effect
relationship amongst the variables. This study’s
framework only described how business model and per-
formance relates, but did not provide many insights into
how firms evolve amidst changing internal and external
dynamics. In addition, cross-sectional data can only
provide a ‘snapshot’ of one point at a time. While useful
and informative, assertions based on temporal snap
shots were limited to the time frame, when the data were
collected.

Conclusion

In conclusion, business model in the context of compe-
tencies has a significant direct impact on firm
performance. It is suggested that in order to increase the
firm’s performance, one of the important factors to be
emphasized on is to have a practical business model.
The findings of this study would be useful to the policy
makers and practitioners especially in designing the
future development of entrepreneurship programs for
current and future entrepreneurs in Malaysia. Since
business model is considered an important thing in
managing business, some knowledge and exposure to
these concepts should be included in the training syllabus
or programs. The findings would also have implications
for SME owners/managers by providing an empirically
tested model to better understand the effects of variables
on business performance. This would help them to
8930 Afr. J. Bus. Manage.

develop better strategies regarding the development of
business model to gain potential benefits and competitive
advantages. Future researches should consider a longi-
tudinal design in studying the effect of firm performance,
and overcoming the inherent limitation of using cross-
sectional data that lead to more specific and accurate
assessments. Furthermore, the longitudinal study would
help future researchers to validate the findings gathered
from the cross-sectional study, since the business model
of a firm would change over time.
Moreover, additional empirical study is needed to
enhance the understanding of the relationships between
business model and its effects on performance. Future
researches should examine, in more detail, the nature of
these relationships, looking for possible causal and
medium patterns of relationships that affect firm
performance. Also, they are needed to determine other
measures of firm performance, such as productivity, and
should consider developing a more complex but palatable
measure and control for other influences on performance.
In order to increase the response rate, future researches
should offer either incentive for all respondents or
attractive prizes for early respondents. A web version of
the questionnaire can also be developed to give
participants an option to complete the survey.

REFERENCES

Aaker DA, Kumar V, Day GS (1998). Marketing research. New York:
John Wiley.
Abd Aziz S, Fitzsimmons J, Douglas E (2008). Clarifying the business
model construct. Paper presented at the 5th AGSE International
Entrepreneurship Research Exchange, Melbourne, Australia.
Aldrich HE (1999). Organizations evolving. Thousand Oaks, CA: Sage.
Aldrich HE, Baker T (1997). Blinded by the cites? Has there been any
progress in entrepreneurship research. Chicago, Illinois: Upstart
Publishing Company.
Amit R, Zott C (2001). Value creation in E-business. Strategic Manage.
J., 22(6-7): 493-520.
Amry S (2009). 1977 turmoil prepared SMEs to face new crisis. New
Sunday Times.
Ang E (2010). Taxing time for traders: More needs to be done - by both
Businesses and the Government - to ease the cost of doing business,
especially in the current economic environment. The Star. 28 March
Asian Development Bank (1990). Malaysia: study on small and medium
enterprises with special references to technology development. Staff
Working Paper, April.
Atkinson AA, Waterhouse JH, Wells RB(1997). A stakeholder approach
to strategic performance measurement. Sloan Manage. Rev., 38(3):
25 - 37.
Babbie E (1990). Survey research method. Belmont, CA: Wadsworth.
Bank Negara Malaysia (2008). Small and Medium Enterprise (SME)
Annual Report 2007. Kuala Lumpur: National SME Development
Council.
Barringer BR, Ireland RD (2006). Entrepreneurship: successfully
launching new ventures. Upper Saddle River, NJ: Pearson Prentice
Hall.
Bartholomew S, Smith AD (2006). Improving survey response rates
from chief executive officers in small firms: the importance of social
networks. Entrep. Theory Pract., 30(1): 83-96.
Berenson ML, Levine DM, Krehbiel TC (2004). Basic business statistics
(9th ed.). Upper Sadle River, NJ: Prentice Hall.
Bernama (2009). Smidec to help SMEs in difficulties duing downturn.
The Star, p. B8.
Berry WD, Feldman S (1985). Multiple regression in practice. Beverly

Hills, CA: Sage Publications.
Boey J (2009). How not to scr*w up your business. SME Entrep. Mag.,
pp. 24-27.
Boey J, Shamini M (2009). Gerak Usahawan Nasional 2009. SME
Entrep. Mag., pp. 28-29.
Bovee C, Thill J, Mescon M (2007). Excellence in business. New York:
Pearson Prentice Hall.
Brush C, Vanderwerf P (1992). A comparison of methods and sources
for obtaining estimates of new venture performance. J. Bus.
Venturing. 7: 157 - 170.
Bryman A, Cramer D (1990). Quantitative data analysis for social
scientists. London: Routledge.
Burns T, Stalker G (1961). The management of innovation. London:
Tavistock.
Business Times (2010). SMEs to benefit from fee cut, April 8, p. 10.
Cameron K (1978). Measuring organizational effectiveness in
institutions of higher education. Adm. Sci. Q., 23: 604-632.
Cavana R, Delahaye B, Sekaran U (2001). Applied business research:
qualitative and quantitative methods (3rd ed.). Milton, Qld: John Wiley
& Sons Australia.
Central Bank of Malaysia (2006). BNM Annual Report 2006. Kuala
Lumpur, Malaysia: Central Bank of Malaysia.
Chakravarthy B (1986). Measuring strategic performance. Strateg.
Manage. J., 6: 437-458.
Chandler GN, Hanks SH (1994). Market attractiveness, resource-based
capabilities, venture strategies and venture performance. J. Bus.
Venturing, 9: 331 - 349.
Che RR, Kumar N, Yen LL (2006). Entrepreneurs success factors and
escalation of small and medium-sized enterprises in Malaysia. J. Soc.
Sci., 2(3): 74 - 80.
Cheng JL, McKinley W (1983). Toward an integration of organization
research and practice: a contingency study of bureaucratic control
and performance in scientific settings. Adm. Sci. Q., 28: 85-100.
Chesbrough H, Rosenbloom RS (2002). The role of the business model
in capturing value from innovation: Evidence from Xerox.
Corporation's technology spin-off companies. Ind. Corp. Change,
11(3): 529 - 555.
Coakes JJ, Steed LG (2003). SPSS: analysis without anguish: version
11.0 for Windows. Singapore: Kyodo.
Covin JG, Slevin DP, Heeley MB (2001). Strategic decision making in
an intuitive vs. technocratic mode: Structural and environmental
considerations. J. Bus. Res., 52(1): 51-67.
Curkovic S, Vickery SK, Droge C (2000). Quality-related action
programs: their impact on quality performance and firm performance.
Decis. Sci., 31(4): 885-905.
Dalton D, Todor W, Spedolini M, Fielding G, Porter L (1980).
Organization structure and performance: a critical review. Acad.
Manage. Rev., 5(1): 49-64.
Deshpande R, Farley JU, Webster JFE (1993). Corporate culture,
customer orientation, and innovativeness in Japanese firms: a
quadrad analysis. J. Mark., 57(1): 23-27.
Dess GG, Robinson RB (1984). Measuring organizational performance
in the absence of objective measures: the case of the privately-held
firm and conglomerate business unit. Strateg. Manage. J., 5(3): 265 -
273.
Dubosson-Torbay M, Osterwalder A, Pigneur Y (2002). E-business
model design, classification, and measurements. Thunderbird Int.
Bus. Rev., 44(1): 5 - 23.
Dwyer L, Mellor R (1993). Product innovation strategies and
performance of Australian firms. Austr. J. Manage., 18(2): 159 - 180.
Forker LB, Vickery SK, Droge CLM (1996). The contribution of quality to
business performance. Int. J. Oper. Prod. Manage., 16(8): 44 - 62.
Fossen RJSV, Rothstein HR, Korn, HJ (2006). Thirty-five years of
strategic planning and firm performance research: a meta-analysis.
Paper presented at the Academy of Management.
Galbraith J (1977). Organizational design. Reading, MA: Addison-
Wesley.
Ghobadian A, Gallear D (1996). Total quality management in SMEs.
Omega, 24(1): 83.
Girden ER (2001). Evaluating research article: from start to finish.
London: Sage.
Graziano AM, Raulin ML (2004). Research methods: a process of

inquiry. Boston, MA: Pearson.
Griffin T, Ebert R. (2006). Business (8th ed.). New York: Pearson
Prentice Hall.
Gupta AK, Govindarajan V (1984). Business unit strategy, managerial
characteristics, and business unit effectiveness at strategy
implementation. Acad. Manage. J., 27(1): 25-41.
Gurbuz G, Aykol S (2009). Entrepreneurial management,
entrepreneurial orientation and Turkish small firm growth. Manage.
Res. News, 32(4): 321-336.
Habaradas RB (2008). SME development and technology upgrading in
Malaysia: lessons for the Philippines. J. Int. Bus. Res. 7(1): 89 - 116.
Hair JFJ, Anderson RE, Tatham RL, Black WC (1998). Multivariate data
analysis (5th ed.). New Jersey: Prentice Hall.
Hair JFJ, Babin B, Money AH, Samouel P (2003). Essentials of
business research methods. New York: John Wiley & Sons.
Hair JFJ, Black WC, Babin BJ, Anderson RE, Tatham RI (2006).
Multivariate data analysis (6th ed.). New Jersey: Prentice Hall.
Hamel G (2000). Leading the revolution. Boston: Harvard Business
School Press.
Hedman JJ, Kalling TT (2003). The business model concept: theoretical
underpinnings and empirical illustrations. Eur. J. Inform. Syst., 12(1):
49-59.
Hoque F (2002). The alignment effect: how to get real business value
out of technology. Upper Saddle River, NJ: Financial Times/Prentice
Hall.
Huck SW (2004). Reading statistics and research. Boston, MA:
Pearson.
Kara A, Spillan JE, DeShields Jr. OW (2005). The effect of a market
orientation on business performance: a study of small-sized service
retailers using MARKOR scale. J. Small Bus. Manage., 43(2): 105-
118.
Kim WC, Mauborgne Re (2000). Knowing a winning business idea
when you see one. Harv. Bus. Rev., 78(5): 129-138.
Kotey B, Meredith GG (1997). Relationship among owner/manager
personal values, business strategies, and enterprise performance. J.
Small Bus. Manage. 37(2): 37-62.
Ladzani WM, Van Vuuren JJ (2002). Entrepreneurship training for
emerging SMEs in South Africa. J. Small Bus. Manage., 40(2): 154 -
161.
Lumpkin GT, Dess GG (1996). Clarifying the entrepreneurial orientation
construct and linking it to performance. Acad. Manage. Rev., 21(1):
135 - 172.
Lyon DW, Lumpkin GT, Dess GG (2000). Enhancing entrepreneurial
orientation research: operationalizing and measuring a key strategic
decision making process. J. Manage., 26(5): 1055-1085.
Magretta J (2002). Why business models matter. Harvard Bus. Rev.,
80(5): 86-92.
Malhotra NK (1996). Marketing research: an applied orientation. New
Jersey: Simon and Schuster.
Malone TW, Weill P, Lai RK, D'Urso VT, Herman G, Apel TG et al.
(2006). Do some business models perform better than others? SSRN
eLibrary Retrieved 28 January 2007, fromhttp://ssrn.com/paper=920667.
Man MK, Wafa SA (2007). The relationship between distinctive
capabilities, innovativeness, strategy types and the performance of
small And medium-size enterprises (SMEs) of Malaysian
manufacturing sector. Paper presented at the 13th Asia Pacific
Management Conference, Melbourne, Australia.
McGrath JE (1982). Dilemmatics: the study of research choices and
dilemmas. In J. McGrath, J. Martin & R. Kulka (Eds.). Judgement
calls in research. London: Sage.
McGrath R, MacMillan I (2000). The entrepreneurial mindset. Boston,
MA: Harvard Business School Press.
Md Zabid AR (1992). Management practices, motivations and problems
of male and female entrepreneurs in Malaysia. Malays. J. SMEs. 3:
35-46.
Mohd KH, Syed AW (2002). Small & medium-sized enterprises in
Malaysia: development issues. Petaling Jaya, Selangor: Prentice
Hall.
Mohd AA (1997). Industri kecil dan sederhana di Malaysia: tinjauan
terhadap pembangunan program bantuan. Kuala Lumpur: Fajar
Bakti.
Aziz and Mahmood 8931

Mohd SD, Hee HC, Hashim N, Keat OY, Ahmad S, Bakar H (2005).
Asas Keusahawanan. Shenton Way, Singapore: Thomson Learning.
Morris M, Schindehutte M, Allen J (2005). The entrepreneur's business
model: toward a unified perspective. (Special Section: The Nonprofit
Marketing Landscape). J. Bus.Res., 58(6): 726-735.
Murphy GB, Trailer JW, Hill RC (1996). Measuring performance in
entrepreneurship research. J. Bus. Res., 36: 15-23.
Murphy KR, Davidshofer CO (2005). Psychological testing: principles
and applications. New Jersey, USA: Pearson Prentice Hall.
Nadler DA, Tushman ML (1997). Competing by design: the power of
organizational architecture. New York, NY: Oxford Business Press.
Nanthakumar L, Nawawi MN, Sukemi N, Harun M, Hasan ZRA (2004).
Small and Medium Enterprise (SME): a case study at East Coast
Peninsular Malaysia. Paper presented at The 4th International
Malaysian Studies Conference (MSC4).
Narver JC, Slater SF (1990). The effect of a market orientation on
business profitability. J. Mark., 54(4): 20.
Newby R, Watson J, Woodliff D (2003). SME survey methodology:
Response rates, data quality, and cost effectiveness. Entrep. Theory
Prac., 28(2): 163 - 172.
Norita D, Mohamad A, Ahmad S, Bakar H, Yusop M, Hashim MK
(2007). Keusahawanan. Shah Alam: McGraw Hill.
Normah MA (2007). SMEs: Building blocks for economic growth. J. Dpt.
Stat. Malays., 1: 1-13.
Nunnally JC, Bernstein IH (1994). Psychometric theory (3rd ed.). New
York: McGraw-Hill.
Pallant J (2007). SPSS survival manual. A step-by-step guide to data
analysis using SPSS for Windows (Version 15) (3rd ed.). Crows Nest,
NSW, Australia: Allen & Unwin.
Pearce JA, Robinson RB (2002). Strategic management. Boston: Mc-
Graw Hill.
Pelham AM (2000). Market orientation and other potential influences on
performance in small and medium-sized manufacturing firms. J.
Small Bus. Manage., 27(1): 48-66.
Portal KKTAK (2006). Keusahawanan: PUNB Perkenal Skim Usahawan
Pemborong [Electronic Version]. Retrieved 19 August 2008 fromhttp://www.idesa.net.my/modules/news/article.php?storyid=1255.
Prajogo DI (2006). The relationship between innovation and business
performance - a comparative study between manufacturing and
service firms. Knowl. Process Manage., 13(3): 218 - 225.
Rajala R, Westerlund M (2007). Business models - a new perspective
on firms' assets and capabilities: observations from the Finnish
software industry. Int. J. Entrep. Innov., 8(2): 115-125.
Reiss F (2007). Why small businesses failed [Electronic Version].
Retrieved 19 August 2008 fromhttp://www.publishinggame.com/art_whysmallbusinessesfail.htm.
Roscoe JT (1975). Fundamental research statistics for the behavioral
sciences. (2nd ed.). New York: Holt, Rinehart and Winston.
alavou H (2002). Profitability in market-oriented SMEs: does product
innovation matter?. Eur. J. Innov. Manage., 5(3): 164-171.
Salleh MI (1990). Small and medium scale industrialisation: Problems
and Prospects.Kuala Lumpur: Institute of Strategic and International
Studies (ISIS).
Sany SMM (2007). The relationship between market orientation and
quality orientation and its impacts on the performance of Malaysia
manufacturing firms. Unpublished PhD Thesis, Universiti Utara
Malaysia, Sintok, Kedah.
Sarasvathy SD (2001). Causation and effectuation: toward a theoretical
shift form economic inevitability to entrepreneurial contingency. Acad.
Manage. Rev., 26(2): 243.
Saunders M, Lewis P, Thornhill A (2007). Research methods for
business students. Harlow: Prentice Hall.
Secretariat to National SME Development Council (2005). Definitions
for Small and Medium Enterprises in Malaysia: Bank Negara
Malaysia.
Sekaran U (2003). Research methods for business: A skill-building
approach (4th ed.). New York: John Wiley & Sons, Inc.
Shafer SM, Smith HJ, Linder JC (2005). The power of business models.
Bus. Horiz., 48(3): 199-207.
Slater SF, Narver JC (2000). The positive effect of a market orientation
on business profitability: a balanced replication. J. Bus. Res., 48: 69-
73.
8932 Afr. J. Bus. Manage.

Smart DT, Conant JS (1994). Entrepreneurial orientation, distinctive
marketing competencies and organizational performance. J. App.
Bus. Res., 10(3): 28 - 38.
SMIDEC (2008). The Official Website of Small and Medium Industries
Development Corporation (SMIDEC). Retrieved 19 August, 2008,
fromhttp://www.smidec.gov.my/index.jsp?page=home.
Star Biz (2009). Ramon: SMEs in need of comprehensive plan - Nation
lacks strategy to help sector weather crisis. The Star, p. B3.
Subramanian A, Nilakanta S (1996). Organizational innovativeness:
exploring the relationship between organizational determinants of
innovation, types of innovations, and measures of organizational
performance. Omega, 24(6): 631-647.
Tabachnick BG, Fidell LS (2007). Using multivariate statistics. New
York: Allyn and Rose.
Tan KC, Lyman SB, Wisner JD (2002). Supply chain management: a
strategic perspective. Int. J. Oper. Prod. Man., 22(6): 614-631.
Timmers P (1998). Business models for electronic markets. Electron.
Mark, 8(2): 3-8.
Tosi HL, Slocum JWJ (1984). Contingency theory: some suggested
directions. J. Manage., 10(1): 9-26.
Tracey M, Lim J, Vonderembse MA (2005). The impact of supply-chain
management capabilities on business performance. Supply Chain
Manage., 10(3): 179-191.
United Nations (1986). Policies and strategies for small and medium
industry development in Asia and Pacific Region (Mac). Kuala
Lumpur.
Venkataraman N, Ramanujam V (1986). Measurement of business
performance in strategy research: a comparison of approaches.
Acad. Manage. Rev., 11(4): 801-814.

Vorst JGAJVd, Dongen SV, Nouguier S, Hilhorst R (2002). E-business
initiatives in food supply chains; definition and typology of electronic
business models. Int. J. Logist., 5(2): 119-138.
Walker OCJ, Ruekert RW (1987). Marketing's role in the implementation
of business strategies: a critical review and conceptual framework. J.
Mark., 51(3): 15-33.
Weisberg HF, Bowen BD (1977). An introduction to survey research
and data analysis. Madison Avenue, New York: W. H. Freeman.
Wiklund J, Shepherd DA (2005). Entrepreneurial orientation and small
business performance: a configurational approach. J. Bus. Venturing.
20(1): 71-91.
World Bank (1984). Malaysia: development issues and prospects of
small enterprises. Report No. 3851 - MA (June).
Yamin S, Mavondo F, Gunasekaran A, Sarros J (1997). A study of
competitive strategy, organizationl innovation and organizational
performance among Australian manufacturing companies. Int. J.
Prod. Econ., 52(1,2): 161-172.
Yusuf A (2002). Environmental uncertainty, the entrepreneurial
orientation of business ventures and performance. Int. J. Commer.
Manage., 12(3 & 4): 83-103.
Zott C, Amit R (2007). Business model design and the performance of
entrepreneurial firms. Organ. Sci., 18(2): 181 - 199.

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