The document discusses factors affecting ICT use among agro-based SMEs in Selangor, Malaysia. It notes that prior research has found factors like firm size, skills/training, and government policies influence ICT adoption. A study of agro SMEs in Selangor found their ICT adoption level is low, with key factors being system support/readiness and perceived benefits. The document outlines several research questions and objectives to determine the level of ICT use among agro SMEs and relationships between use and factors like performance/effort expectations, with moderation by age, gender, experience.

2. Introduction…1
• In the field of small & medium-scale enterprises (SMEs) ICT usage research, most
empirical work is conducted in large organisations and SMEs are often left on their
own. (Devos, van Landeghem & Deschoolmeeste, 2014). Therefore, to conduct a
study in factors affecting ICT use in agro-based SMEs would be a very good idea.
• Although it is very cumbersome to clearly define what constitutes ICT success in
SMEs, it was shown that success of bringing, for instance, e-transaction into SME
organisations supports the size, training, skilled manpower and government policy
hypotheses (Higon, 2011; Bernaert, Poels, Snoeck & De Barker, 2014).
• There is also the question of difference in defining what constitutes an SME. In
Europe SMEs are defined as companies with less than 250 employees, but in the US
SMEs are defined as companies with up to 500 employees (Devos, van Landeghem &
Deschoolmeeste, 2014), while in Malaysia SMEs are companies with employees
ranging from 5 full-time workers to 200, and total annual turnover ranging from
RM300,000 to RM50 million respectively (SMECORP, 2014; DOSM, 2014).

3. Statement of the Research Problem…1
• Small and Medium-scale Enterprises (SMEs) nowadays constitute a major
business sector all over the world, covering a wide spectrum of industries.
The number of SMEs far exceeds the number of large and very large
organisations. SMEs contribute strongly to the GDP and even more to the
growth in employment of most countries.
• The latest statistics from the Economic Census 2011 indicates that SMEs
constitute 97.3% of total business establishments in Malaysia (645,136) &
employs over 4,854,142, which is 57.4% of total SMEs employment figure,
8,460,971 in 2012(DOSM, 2014). Also, only 27% of the total of 645,136
SMEs in Malaysia use ICT even though as high as 67% of them use the
Internet (MCMC, 2014).
• However, many SMEs struggle to survive and grow and they display
limited productivity. In spite of being a key economic contributor in many
countries, SMEs suffer from various challenges, often inherent, and
induced by social, economic, geographical or cultural grounds, or other
reasons beyond their control (Kapurubandara & Lawson, 2006).

4. …Statement of the Research Problem 2
• Although there are quite some factors contributing to low SME survival
rates, one crucial factor that has been singled out in recent studies is the
(lack of) successful adoption and use of Information & Communication
Technologies (ICT) (Higón, 2012; Runevad & Olofsson, 2014).
• According to Kuan (2005), the management skills is another factor that is
encouraging involvement in small medium size enterprise (SME) sector in
Malaysia.
• SMEs often express a reluctant vision to ICT adoption which could be
based on a lack of managerial ICT capabilities. This may be due to
organisational immaturity and results in an asymmetric relationship with
ICT suppliers dominating the arena (Devos et al. 2012). SMEs are
vulnerable organisations with a shortage of expertise, resources and
managerial maturity (Welsh et al. 1981).
• Probably those factors could affect ICT use among agro-based
entrepreneurs in Selangor, Malaysia. This study wants to find that out .

5. …Statement of the Research Problem 3
• Knowledge Gaps :
1. Studies found that the ICT adoption level of agro-based SMEs in Selangor is fairly low. According to the
findings, less than half of the SMEs have achieved level 3 ICT adoption level, which denotes the usage of ICT as
information sharing tools across several department within the companies. The factors affecting the adoption and
use of ICT in agro-based SMEs in Selangor are system support and readiness and perceived benefits. (Nawi &
Luen, 2014).
2. Furthermore,, more research findings indicate that most SMEs workers do not have required skills and
knowledge to make ICT adoption and use a success (Dholakia & Kshetri, 2004; Taiwo & Downe, 2013; . Agro-
based SMEs are not ready to adopt advance ICT due to employee's limited ICT knowledge. Employees lack ICT
knowledge and skills to enable companies to further adopt advance ICT. However, most agro-based SMEs do
realize that ICT is capable of their business by easing up communication constraints with both trading partners
and between employees., reducing costs and time of job performance, etc (Ramli, Abu Samah, Hassan, Omar,
Bolong, & Shaffri ,2015; Nawi & Luen, 2014).
• Observation:
Ismail (2009) and Murthy & Mani (2013) found that in a knowledge-based economy like that of Malaysia,
information (ICT), creativity & skills are key factor for SMEs sustainability (survivability).
3. Since Nawi & Luen (2014) used an interview survey (descriptive) method, TAM model and a smaller sample
size (50 agro-based SMEs) in their study, the researcher will determine the reasons agro-based SMEs in Selangor
are lagging behind in the adoption and usage of ICT in their enterprise using a quantitative methodology and
UTAUT model. It is expected new empirical data with better results would be obtained.

6. …Statement of the Research Problem 4
• Knowledge Gaps :
4. The ICT “adoption ladder” as Martin & Matlay (2001) call it, comprises the following ICT
usage level measuring tools: e-mail, website, e-commerce, e-business and transformed
organisations may have been good enough to measure ICT usage level in SMEs to some
degree, however, both Dutta & Evrard (1999) and Martin & Matlay (2001) have not included
social networking sites (SNSs) such as Facebook, Twitter, LinkedIn, etc as a component of
online business channels just as they highlighted e-commerce and e-business as significant
components.
• Observations:
SNSs are a popular platform for customer communication, marketing and products
promotion among Malaysian SMEs (Kal-kauthar, Norhayati Rafida, Nurulhusna, Aliana & Siti
Mashito, 2013).), even though the credibility of SNSs as sources of information is still under
debate (Kal-kauthar, et al., 2013). SNSs have been identified as tools that can provide
improved communication and collaboration between SMEs and their stakeholders (Fosso-
Wamba & Carter, 2014).
• SNSs have also been described as an innovative way for SMEs to identify products with high
selling potential (Liang & Turban, 2011; Fosso-Wamba & Carter, 2014). SNSs are further seen
as better channels for attracting and retaining online customers (IBM, 2009; Fosso-Wamba &
Carter, 2014). The researcher will determine the role SNSs play in boosting agro-based
entrepreneurship.

7. …Statement of the Research Problem 4
• Knowledge Gaps :
5. Citing Malaysian International Report (2010),) Moghavvemi & Salleh (2014
posited that the Malaysian government started a policy that aims to convince
entrepreneurs to adopt and use IS products as a new, more efficient method of
performing work. According to the scholar, despite many programmes to
encourage entrepreneurs to use ICT, surveys showed that only 5% of
Malaysian SMEs have fully automated ICT and communication operations,
and only 30% have any form of enterprise-level ICT solutions.
• Observation:
Moghavvemi & Salleh (2014) used entrepreneurial event model (EEM) in their
study to determine ICT user’s intention as a factor that affects the user’s ICT
use in entrepreneurship, however, their actual sample size was relatively larger
(412). Rather than determine ICT user’s intention as a motivator for ICT use,
the researcher will determine the users’ actual ICT use using a more
comprehensive model, UTAUT. It is expected at the end of the study to obtain
improved results.

8. The Research Questions
The general research question shall be what are the factors that affect ICT use
among the agro-based SMEs and what is the relationship(s) between ICT use and
the factors that affect ICT use with the moderating effect of age, gender, experience
& voluntariness of use? While the specific research questions shall be as follows:
• 1. What is the level of ICT use among the agro-based SMEs?
• 2. What is the relationship between ICT use and factors that affect ICT use:
performance expectancy, effort expectancy, social influence, facilitating conditions,
SME (organisational size) and SME managerial creativity and innovativeness among
the agro-based SMEs?
• 3. What is the moderating effect of age, gender, experience and voluntariness of use
on the following factors that affect ICT use: effort expectancy, performance
expectancy, social influence and facilitating conditions among the agro-based SMEs?

9. The Research Objectives
The general research objective shall be to determine the factors that affect ICT
use among the agro-based SMEs and examine the relationships between ICT use
and the factors that affect ICT use, with the moderating effect of age, gender,
experience and voluntariness of use. While the specific objectives shall be as
follows:
• 1. To determine the level of ICT use among the agro-based SMEs.
• 2. To determine the relationship(s) between ICT use and factors that affect ICT
use: performance expectancy, effort expectancy, social influence, facilitating
conditions, SME (organisational) size and SME managerial creativity and
innovativeness among the agro-based SMEs.
• 3. To determine the moderating effects of age, gender, experience and
voluntariness of use on the following factors that affect ICT use: performance
expectancy, effort expectancy, social influence and facilitating conditions among
the agro-based SMEs.

10. Significance of the Study
• The study will provide new data from a research area that is still not well explored as
indicated by literature. It will also provide some useful insights; define policy
recommendations for the government, universities/research institutes and private
sector firms, business entrepreneurs managers.
• The study will contribute to the literature of SMEs support services, innovation and
entrepreneurship development and will enhance the knowledge and skills within the
industrial sector and entrepreneurial sub-sector.
• The study output will be used to create awareness to the policy makers and financiers,
researchers and the business community in Selangor in particular and Malaysia in
general. As SMEs grow in Malaysia and become burgeoning, the agro-based SMEs will
broaden which inevitably builds industrial competence and firms will be competitive.
• An agro-based SMEs ICT usage model for sustainable socio-economic and industrial
development of Malaysia.
• The study is also expected to augment the body of literature and increase the depth of
knowledge for the collective and individual benefits of society.

11. Scope of the Study
• Scope:
The scope of the study, by & large, covers information & communication
technologies (ICTs) & agro-based small and medium-scale entrepreneurships
(SMEs) in Malaysia. These are very large research fields, beyond the capacity of this
study. However, the researcher will only examine some limited portions of the
research purviews due to scarce resources, time-limit & type of study.
• Limitations:
In ICT the study shall consider only the use of mobile phone & its applications, fixed
telephone, fax, e-mail, website, computers, e-business (e-transaction) applications
& software, social networking sites (SNSs) such as Facebook, Twitter, Google+,
Pinterest, Flickr, Tumblr, Instagram & the Internet.
• In agro-based SMEs the study shall only cover crop-based, livestock-based, fishery-
based (marine and or aquaculture), forest/logging/lumbering-based, and agro-
based farming inputs like fertilizer-based, livestock feeds-based and
horticulture/floriculture-based SMEs. The above agro-based categorisation is based
on SMECORP (2014).
• Location:
The researcher will administer the survey questionnaire to agro-based SMEs that
are based in Selangor State only.

12. Definition of Key Terms
• 1. ICT: “...comprise all devices, systems & facilities that can be deployed to
collect, process, store & diffuse information...include...technologically
sophisticated tools such as computers & Internet,...&
conventional...media...such as radios, television... (Njoh, 2011:343).
• 2 (a) Agro-based entrepreneurship: “...include direct sale or processing of
agro products...” (Sharma, 2013:10).
• (b) “Entrepreneurship is...the practice of starting new business
organizations in response to perceived opportunities” (Sonawane,
2014:24).
• (c) Agro-based small & medium-scale enterprises (SME) are agro-based
business organisations whose sales turnover ranges from RM300,000 to
less than RM15 million & RM15 million to RM50 million or full-time
employees ranging from 5 to 74 & 75 to 200 respectively (SMECORP,
2014:168).

13. Literature Review…1
S/No Author(s) Date Finding(s) Obj.
1 (1) Bayo-Moriones,
Billo’n & Lera-
Lo’pez
(2) Rodney and
Renee
(3) Higon
(4) Bernaert, Poels,
Snoeck & De
Barker
(5) Murthy & Mani
(1) 2011
(2)2011
(3) 2011
(4) 2014
(5) 2013
Prior research has demonstrated that the level of ICT use by both
employees and managers, as well as the skills and abilities of
human capital, rather than ICT investment, strengthens the ICT
effect: the greater the use of these technologies among
employees, the higher the impact on labour productivity.(1).
Some of the positive factors that have significant influences on
entrepreneurial involvement in business are the improvement of
management commitment, customers’ focus, employees’
involvement, training and education, reward and recognition to
the workers (2), SME-friendly government ICT policies and firm
size ((3); (4)) and ability to survive and compete in the market (5)
which constantly require skills & creativity.
1
2 Nawi & Luen 2014 The ICT adoption level of agro-based SMEs in Selangor is fairly low. Less
than half of them have achieved level 3 ICT adoption level, which denotes
that ICT use as an information sharing tool across several department within
the SMEs. The factors affecting ICT adoption (and use) in agro-based SMEs
in Selangor are system support and readiness and perceived benefits. Most
agro-based SMEs do not have required skills and knowledge to make ICT
adoption a success. Agro-based SMEs are not ready to adopt advance ICT
due to employee's limited ICT knowledge. Employees lack ICT knowledge
and skills to enable the SMEs to further adopt advance ICT.
“

14. …Literature Review 2
S/No Author(s) Date Finding(s) Obj.
3 (1) Palmer
(2) Walczuch,
Braven &
Lundgren
(3) Martin & Matlay
2000
2000
2001
Internet (ICT) use was evaluated in two main
categories: Internet tools used and applications
used on the Internet (1).
Level f Internet usage based on percentage usage
was measured using e-mail, searching for
company websites and randomly looking for
information, receiving orders from customers,
voice/video conferencing and placing job
vacancies (2).
To determine the level of ICT use among SMEs, a
framework called ‘adoption ladder’ was provided.
The framework initially measures ICT use level in
two dimensions: business benefits & extent f
organisational change & sophistication. The
ladder starts at the basic level, which is e-mail
then proceeds to website, e-commerce, e-
business & transformed organisation (3).
1

15. …Literature Review 3
S/No Author(s) Date Findings Obj.
4 1. (a) Taiwo & Downe
(b) Venkatesh, et al.
2. Oshlyansky, et al
(a) 2013
(b) 2003
2007
Information technology pervades the international
community from programmable home appliances to
organization applications. As people, organizations and
governments moved towards the use of Information
Technology. Such move of change has increased the
human computer interaction, which is the sole aim of
performing a task (Card, Moran and Newell, 1983).
Interaction between humans and computers is affected by
quite a number of human factors and its characteristics
(Whitley, 1997), to which studies have come up with
theories and models to investigate factors that influences
humans to use computers and its applications. performance
expectancy, effort expectancy, and social influence predict
behavioral intention towards the acceptance of information
technology. Studies found that facilitating conditions
predict use behavior in the acceptance of information
technology. 1 (a & b)
* Technology acceptance, or ICT use is people’s attitude to
the uptake and use of different technologies (ICTs). 2
2

16. …Literature Review 4
• a
• s
S/No Author(s) Date Findings Obj.
5 (1) Oh & Yoon
(2) Devos, et al.
(3) Dholakia &
Kshetri
(1) 2014
(2) 2014
(3) 2002
The most pressing issue facing markers of information technology services is what
makes potential users accept and use Internet services. Understandably,
individuals’ beliefs and attitudes influence the use and acceptance of Internet
technology. In addition, this decision is, to some extent, influenced mainly by
individuals’ attitudes towards others’ opinions.
A number of studies have proposed various theories to explain what induces users’
to accept and use Internet technology. Most theories speculate that the acceptance
of a technology is determined more by the user’s attitude and behaviour than by
characteristics of the technology .... Furthermore, previous studies have suggested
that users’ perception of a technology influences their acceptance of the
technology (2). The underlying entrepreneurial attitudes and behaviours are three
key dimensions: Innovativeness, risk taking and proactiveness . Organisational size
has also been documented to affect ICT adoption/use by organisations and their
workers. 3
2
6 Venkatesh, et al. 2003 It should be noted that performance expectancy appears to be a determinant of
intention in most situations: the strength of the relationship varies with gender and
age such that it is more significant for men and younger workers. The effect of
effort expectancy on intention is also moderated by gender and age such that it is
more significant for women and older workers, and those effects decrease with
experience. The effect of social influence on intention is contingent on all four
moderators included here such that we found it to be non-significant when the data
were analyzed without the inclusion of moderators. Finally, the effect of
facilitating conditions on usage was only significant when examined in
conjunction with the moderating effects of age and experience-i.e., they only
matter for older workers in later stages of experience.
3

17. Related Theory
• The researcher will use the Unified Theory of Acceptance and Use of Technology
(UTAUT) developed by Venkatesh, et al (2003).
• The core constructs theorised to impact the intention to use technology are Performance
Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI), which impact
Behavioural Intention (BI) while Facilitating Conditions (FC) are known to directly
impact Use Behaviour (UB). Eventually, Behavioural Intention (BI) directly impacts Use
Behaviour (Oh & Yoon, 2014). The independent variables (PE, EE, SI & FC) impact the
dependent variable, Use Behaviour (UB) via the mediatory influence of gender, age,
voluntariness of use and experience (Anderson & Schwager, 2014).
• Venkatesh et al.’s (2003) UTAUT model consolidates eight previously established
theories related to technology acceptance and use: the theory of reasoned action (TRA)
(Fishbein and Ajzen 1975), the TAM (Davis 1989), the motivational model (Davis et al.
1992), the theory of planned behaviour (TPB) (Ajzen 1991), a combination of the TAM
and the TPB (Taylor and Todd 1995b), the model of PC utilisation (MPCU) (Thompson
et al. 1991), the innovation diffusion theory (Moore and Benbasat 1991, Rogers 1995),
and the social cognitive theory (Compeau and Higgins 1995).

18. UTAUT: Definition of Constructs
Source: Escobar-Rodriguez & Carvajal-Trujillo (2014: 73)
S/No Construct Definition
1 Performance
Expectancy
(PE)
“The degree to which an individual believes that using the
system will help him or her to attain gains in job
performance”
2 Effort
Expectancy
(EE)
“The degree of ease/effort associated with the use of the
system”
3 Social Influence
(SI)
“The degree to which an individual perceives that important
others believe that they should use the new system”
4 Facilitating
Conditions (FC)
“The degree to which an individual believes that an
organizational and technical infrastructure exists to support
use of the system”

19. Related Theory: UTAUT
Fig. 1: Theoretical Framework
Source: Venkatesh, Morris, Davis & Davis (2003)
a
• 1
Voluntariness
of Use
Social Influence
experience
Facilitating
Conditions
Performance
Expectancy
Age
ICT Usage
Effort Expectancy
gender
Behavioural
Intention

20. Fig. 2: Conceptual Framework
a
• 1
Voluntariness
of Use
Social Influence
experience
Managerial
Creativity &
Innovativeness
Facilitating
Conditions
SME
(Organisational) Size
Performance
Expectancy
Age
ICT Usage
Effort Expectancy
gender
H1
H2
H3
H4
H5
H6
H7 H8 H9 H10H11a
H11b
H12a
H12b
IVs Moderator Variables DV

21. Operationalisation of Variables…1
a
Operationalisation of Variables…
S/No Variable Definition Category Measurement
1 Level of Use of
ICT
Indicators for the actual use,
degree (frequency) of use,
preference use & purposes of
use of ICT in running the
SMEs (Acar, Kocak, Sey &
Arditi, 2005; Mutambi, 2011;
Gallego, Gutierrez & Lee,
2011).
Dependent
Variable (DV)
The researcher will ask
the respondents
questions about their
ICT preference, the
extent of their use of ICT,
the purposes to which
they put ICTs to use,
their use of Internet-
based & non-Internet-
based ICTs, quantity of
ICTs per employees &
percentage of employees
working with ICTs.
2 Creativity &
Innovativeness
in the Use of
ICT
Skills & expertise of ICT usage
(Duan, Mullins, Hamblin,
Stanek, Sroka, Machado &
Araujo, 2002; Acar, Kocak, Sey
& Arditi, 2005).
Independent
Variable (IV)
The researcher will ask
the respondents
questions about their
skills, knowledge &
expertise in the use of
ICT software &
applications.

22. …Operationalisation of Variables 2
• a
S/No Variable Definition Category Measurement
3 Performance
Expectancy
(PE)
The degree to which an
individual employee of the
SME believes that using ICT
will help him or her to attain
gains in job performance
(Venkatesh, et al 2003;
Escobar, et al 2014)
“ The researcher will ask
the respondents
questions about their
expectations about the
usefulness of ICT when
they use it.
4 Effort
Expectancy
(EE)
The degree of ease/effort
associated with the use of ICT
by an individual employee of
the SME (Venkatesh, et al
2003; Escobar, et al 2014.
“ The researcher will ask
the respondents
questions about their
expectations of the
ease or otherwise of
the use of ICT when
they use.

23. …Operationalisation of Variables 3
• a
S/No Variable Definition Category Measurement
5 Social
Influence (SI)
The degree to which an
individual employee of the
SME perceives that
important others believe
that he or she should use ICT
(Venkatesh, et al 2003;
Escobar, et al 2014.
Independent
Variable (IV)
The researcher will
ask the respondents
questions about their
perception of societal
factors that can affect
their use of ICT.
6 Facilitating
Conditions
(FC)
The degree to which an
individual employee of the
SME believes that an
organisational & technical
infrastructure exists to
support use of ICT in the
SME.
“ The researcher will
ask the respondents
questions about the
availability &
accessibility of
technical &
infrastructural
support toward the
efficient use of ICT in
the SME.

24. …Operationalisation of Variables 4
• aS/No Variable Definition Category Measurement
7 SME (organisational)
Size
Entrepreneurial capacity of
an agro-based SME
determinedby the
organisation’s number of
employees, the vastness of
its operations, market reach
and share (Horisch, Johnson
& Schaltegger, 2014; Gupta,
2010; Ramdani, Kawalek &
lorenzo, 2009).
Independent
Variable (IV)
The researcher
will ask the
respondents
questions about
the number of
employees of the
organisation, its
branches & annual
turnover/profit.

25. Hypotheses…1
The following hypotheses will be tested with the moderation of
age, gender, voluntariness of use & experience (Venkatesh, et al
2003; Anderson & Swagger, 2014).
• H1: There is positive and significant
relationship between SME’s
Performance Expectancy (PE) &
ICT use .
• H2: There is positive and significant
relationship between SME’s Effort
Expectancy (EE) & ICT use.
• H3: There is positive and significant
relationship between SME’s Social
Influence (SI) & ICT use.
• H4: There is positive and significant
relationship between SME’s
Facilitating Conditions & ICT use.
• H5: There is positive relationship
between SME (organisational) size
& ICT use.
• H6: There is positive relationship
between SME managerial creativity
& innovativeness & ICT use.

26. …Hypotheses 2
• H7: There is significant moderating
effect of age and gender on
performance expectancy, such that the
effect will be stronger for men and
particularly younger men.
• H8: There is significant moderating
effect of age, gender and experience
on effort expectancy, such that the
effect will be stronger for women,
particularly younger women, and
particularly at early stages of
experience.
• H9: There is significant moderating
effect of age, gender, voluntariness
of use and experience, such that the
effect will be stronger for women,
particularly older women,
particularly in mandatory settings in
the early stages of experience.
• H10: There is significant
moderating effect of age and
experience on facilitating
conditions, such that the effect will
be stronger for older workers,
particularly with increasing
experience.

27. …Hypotheses 3
• H11: There is moderating
effect of voluntariness of use
and experience on SMEs
(organisational) size.
• H12: There is moderation
effect of age, gender,
voluntariness of use and
experience on SMEs
managerial creativity and
innovativeness.

28. Methodology…1
• Research Instrument: A four-section questionnaire including a respondents’
demographic information section. Five-point Likert scale and other measurement
scales such as Extremely Low, Low, Moderate, High , Extremely High and options like
yes or no will be used in the questionnaire.
• Method of Data Collection: Quantitative data gathering with self –administered
questionnaire. The researcher will administer questionnaire to only 10 employees
(including both management staff & others) per SME organisation; & each
organisation shall be surveyed only once.
• Subjects: Population: The population of the study is 63,664 staff & employees of the
674 agro-based SMEs (Yellow Pages Malaysia, 2014).
• NB: The researcher obtained the location and contact addresses of only 674 agro-
based SMEs in Selangor from Yellow Pages Malaysia (2014) and determined the
population of their employees based on an approximate average population of 95
employees per SME (as provided by SMECORP SME Census, 2011 - 834 agro-based
SMEs in Selangor with a workforce of 78,777).
• Subject: Sample: The sample size is 381 employees (Krejcie & Morgan, 1960) and
381.7, which is approximately 382 employees (Cochran, 1977). Therefore, the sample
size is 382 employees of the agro-based SMEs.

29. …Methodology 2
• Sampling: Random and purposive sampling methods: The researcher will
determine the sampled SMEs to be surveyed based on random sampling method.
That is due to the geographical spread of the agro-based SMEs in Selangor State
(regarding their exact locations/addresses). While during questionnaire
administering to the respondents, the researcher will use purposive sampling
method to determine the particular respondents to administer the research
instrument to. The researcher will choose to use purposive sampling in order to
be able to distinguish between management & production staff and staff who use
ICT in their work and those who do not.
• The category of sample size per SME: The category of the 10 respondents per SME
that will be administered with questionnaire shall include (1) the SME’s chief
executive officer (CEO)/chairperson/manager, (2) marketing executive, (3) the
accountant, (4) procurement executive & (5) technical executive as the five
managerial staff. While the five non-managerial staff shall include any
employee/production staff that uses ICT to do his or her work in the SME.
• Thus, the researcher will survey 38 agro-based SMEs (382÷10=38.2; that is, 38
agro-based SMEs), as illustrated below using Cochran (1997) formula:

30. …Methodology 3
• = Where =
• ci = 95% confidence interval
• p = 50% = 0.5% assumption proportion
• d = 0.05α level
• = =
•
•
•
• =
Sample size =

31. …Methodology 3
• The researcher will survey those category of staff and employees because
an SME’s managerial staff constitute the real entrepreneurs and
administrators while the non-managerial employees can constitute the
actual ICT-user employees, whose jobs are crucial and can serve as an
auxiliary ‘management’ function in terms of running the SME from
production perspective (Anderson & Schwager,2014: Gallego, et al 2011).
• Location: Selangor State. The researcher decided to choose Selangor State
because the state has the highest percentage of all SMEs (19.5% of the
total of 645,136 SMEs); as well as ICT and ICT-related service firms
(49.2% of the total of 2379 ICT SMEs) in Malaysia (SMECORP, 2014).
Based on those facts, the researcher decided to choose Selangor State in
addition to limited resources at the researcher’s disposal, the calibre of
the study & for convenience reasons.

32. …Methodology 4
• Data Gathering, Analysis & Presentation: Computer data analysis
software (SPSS) will be used to run regression analysis, inferential
analysis (ANOVA and t-test) in addition to descriptive analysis to
interpret the data and determine the various relationships & or
differences between & among the variables. The data will be presented
using tables. In addition, SEM (AMOS) will also be used to determine the
relationships between and among the various variables.
• Validity & reliability of the research instrument: The researcher will
rely on SPSS & run Chrombach’s Alpha (of values between 0.7 & 0.9).
The researcher will also use scholars’ opinion & run a pilot test on 30
agro-based SMEs in Selangor, in March 2015.

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35. Thank You!
1